Energy Modeling Methodology

ENERGY MODELING METHODOLOGYL E V E R A G I N G T E C H N O L O G Y T O D E L I V E R S M A RT E R , M O R E S U S TA I N A B L E B U I L D I N G D E S I G N S

AUTHOR - CHRISTOPHER WINGATE

FACULTY ADVISOR - BLAINE BROWNELL

MS&R ADVISOR - THOMAS MEYER

DATE - AUGUST 2012

MADE POSSIBLE BY A PARTNERSHIP BETWEEN THE UNIVERSITY OF MINNESOTA

SCHOOL OF ARCHITECTURE AND MEYER, SCHERER & ROCKCASTLE, LTD

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS

A UNIQUE COLLABORATION

EQUEST AND IES VE COMPARISON

ABOUT THE STUDY

TOOLS OF DESIGN

ENERGY MODELING TIMELINE

ENERGY MODELING& CONCEPT DESIGN

INTEGRATED ENERGY DESIGN

WHY ENERGY MODEL?

CLIMATE CHANGE

DESIGN THINKING EVOLVED

VITRUVIUS REDEFINED

ENERGY MODELING INPUTS

PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE

CONCEPT MASSING STUDIESWIND ANALYSIS

OPTIMIZING R-VALUES

ENERGY MODELING& DESIGN DEVELOPMENT

OPTIMIZING DAYLIGHT

OPTIMIZING GLAZING %

CONCEPT MASSING STUDIES

SMARTER CONCEPTS

ITERATIVE DEVELOPMENT

1. University of Minnesota Master of Architecture program, www.arch.design.umn.edu.

2. Meyer Scherer & Rockcastle, ltd. www.msrltd.com.

3. Karges-Faulconbridge, Inc. www.kfiengineers.com.

Energy Modeling Methodology is the result of a unique col-

laboration between the academic and professional worlds

of architecture. Renee Cheng, Head of the University of

Minnesota School of Architecture, created a semester long

work/study program that pairs Master of Architecture stu-

dents with local design firms to conduct research projects.

This paper is a result of the pilot semester of the project.1

Students enrolled in the program split their time between

the classroom and the office, but their focus is always di-

rected by the research project. This structure harnesses the

strengths of the university and the private sector in con-

ducting mutually beneficial research. Architecture firms

benefit from the exploration of innovative processes, tools,

and techniques by university students and faculty, and the

university is able to vet its research in the real world, us-

ing experienced professionals to shape academic concepts

into adoptable methodologies. At the center of it all is an

invaluable opportunity for students; they gain experience

and make connections in the field while learning a unique

skill set that makes them attractive to future employers.

Energy Modeling Methodology was written and researched

by Christopher Wingate while paired with Meyer Scherer

& Rockcastle, ltd.2 The research is focused on develop-

ing an energy modeling methodology for small to medium

sized architecture firms that can be used to help inform ear-

ly concept, schematic, and design development decisions.


COLLABORATIVE RESEARCH BETWEEN THE UNIVERSITY AND THE PROFESSION

PROFESSIONAL PRACTICE

• Implement research on real projects and generate real world results

• Research reviewed by experienced professionals

• Research must fit within existing budgets, schedules, and work flows

ACADEMIC RESEARCH

• Explores the latest approaches, innovations, and technologies

• Encourages the technical and conceptual understanding of

tools and processes through extended investigation

Profession MS&R architecture

KFI engineering

Research ProjectENERGY MODELING

AcademicUNIVERSITY OF MINNESOTA

COLLEGE OF DESIGN

University of Minnesota School of ArchitectureProgram Coordinator - Renee Cheng, Head of School of Architecture

Faculty Advisor - Blaine Brownell, Assistant Professor

Student Researcher - Christopher Wingate, M.Arch Candidate

Meyer Scherer & Rockcastle, Ltd.Program Coordinator - Thomas Meyer, FAIA

Project Support - Allison Salzman, AIA

- Sam Edelstein

PROJECT TEAM

Karges-Faulconbridge, Inc.Energy Simulation Engineer - Katherine R. Edwards

OPTIMIZED ENERGY MODELING PROCESS

• Inform decisions throughout the design process

• Easy to use

• Communicates graphically

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


5 10 15 20 25 30 35 40 4540 35 30 25 20 15 10 545

110%

224%

36%4

36%

512%

612%

Chart Title

Wingate(U of M)

Brownell

MS&

R team

Edwards

Wingate(MS&R)

Wingate(TA)

1. NCARB Intern Development Program, www.ncarb.org

2. ARCH 5516 Thermal and Luminous Design, http://www.zeropluscampus.umn.edu/

Energy Modeling Methodology wouldn’t have been pos-

sible without the collaborative efforts of multiple organiza-

tions and individuals.

The program was structured to split the student research-

er’s time between the classroom and the office. Christo-

pher Wingate spent 10 hours per week conducting research

for academic credit under the guidance of faculty advi-

sor Blaine Brownell and an additional 15 hours per week

at Meyer Scherer & Rockcastle. Research completed at

MS&R was overseen by Thomas Meyer, founding princi-

pal, and counted for IDP credit.1 A team of MS&R profes-

sionals also provided weekly feedback on the progress of

the project. Katherine Edwards, an energy simulation en-

gineer from KFI, collaborated on portions of the research.

Energy Modeling Methodology was also informed by

Christopher Wingate’s position as a teaching assistant for

Thermal and Luminous Design, a graduate studio focused

on sustainable design through energy modeling.2 The

teaching position ran concurrently with the work/study

program.

Firms that participate in the work/study program receive

a strong return on their investment. During this study,

MS&R invested 301 hours of its time into the program. It

benefited from an additional 259 hours funded by the Uni-

versity of Minnesota. In a business climate that makes re-

search and development difficult, this work/study program

enables firms to push the profession forward by leveraging

the resources and expertise of the University of Minnesota.

PROJECT TIMELINE AND HOURS WORKED

PROJECT TIMELINE

JAN

UA

RYFEBRU

ARY

MA

RC

HA

PRIL

MAY

JUN

EJU

LY

ACADEMIC HOURSPROFESSIONAL HOURS

110%

224%

36%4

36%

512%

612%

Chart Title

ACADEMIC259 hours

MS&R301 HOURS

KFI74

HOURS WORKED BY INSTITUTION

Chris Wingate, U of M Student Researcher

Chris Wingate, U of M Teaching Assistant

Blaine Brownell, U of M Faculty Advisor

MS&R Energy Modeling Team

Katherine Edwards, KFI Engineer

Chris Wingate, MS&R Student Researcher

66

38

75

74

155

Combined Total Hours Spent on the Project 634

226

KEY RESEARCH HOURS

The horizontal lines of the graph split each month into four representative weeks. Each person’s

weekly hours are represented additively at these intersections. The height of the highest peak or

valley at each week represents the total hours worked by all people on the project. Individual

weekly hours are read by measuring the difference between the peak of the category and the

peak directly below it.

HOURS WORKED BY INDIVIDUAL

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


COMPARING ENERGY MODELING SOFTWARE : EQUEST AND IES VE

Energy Modeling Methodology development began by

choosing an energy modeling software. When the research

project started, MS&R had already narrowed its search

for an energy modeling program down to eQUEST by the

Department of Energy and IES VE by Integrated Environ-

mental Solutions.1,2 MS&R initially wanted to use energy

modeling at the beginning of the design process to help in-

form conceptual and schematic design decisions, so a set

of selection criteria was developed with that goal in mind.

The criteria was based around the steps necessary to cre-

ate, analyze, and compare energy models of early concep-

tual schemes. Please see the following three pages for the

full selection criteria matrix and score comparison between

eQUEST and IES VE.

Each category in the selection criteria matrix represents a

step necessary to create an energy model or to run an energy

modeling analysis. The categories are:

1. Climate Analysis - Use the software to analyze the site’s

specific climate and its ramifications on design.

2. Design Model - Create an energy model from a design

concept .

3. Base Model - Create a baseline energy model to com-

pare performance of design options against.

4. Solar Shading - Use the software to run a shadow study.

5. Daylighting - Use an energy model to test daylighting

performance.

6. Thermal Analysis - Use energy modeling to analyze

thermal performance.

7. Conceptual Model Comparisons - Compare the perfor-

mative characteristics of multiple concept models.

The subcategories are similar across each category, analyz-

ing characteristics such as the time required to complete a

task, ease of using the software, and the graphical quality

of its output. This structure allowed the research team to

compare software in a variety of ways. By averaging the

software’s scores in each subcategory, a metric emerged that

gave a quick overview of the energy modeling program.

For example, the average score of each category’s Time Re-

quired subcategory was calculated and given the title Speed.

This metric is a score out of 5 that illustrates the amount of

time it takes to complete a given task with the software. A

higher score is always related to better performance. The

other subcategories were scored and averaged in the same

manner. The results can be seen at the bottom of the selec-

tion criteria in the scoring boxes labeled Speed, Ease of Use,

Data Quality, Graphics, and Workflow.

The scores were also tallied for each category. The overall

scores for each software were calculated in the box labeled

Total Score.

IES VE received a higher total score than eQUEST. It also

outscored eQUEST in every subcategory, with the largest

margins in Graphics and Workflow. This is due to IES VE

being designed and marketed to architects as well as en-

gineers. Although both software platforms will accurately

model the energy performance of a building, IES VE is de-

signed with visual thinkers in mind, emphasizing the ability

to create spatially complex three dimensional energy mod-

els and run graphically rich analyses.

After scoring the software, the research team created an-

other matrix that highlighted the selection criteria that most

heavily impacted a software’s ability to influence early de-

sign decisions. We found that the most important aspect of

a successful energy model was its ability to match the three

dimensional qalities of the design concept. The process of

creating an energy model always involves simplifying a de-

sign model, but a successful energy model will still retain

the feel of the design intent, convincing the design team

that the architecture is actually shaping the energy model’s

performance. IES VE uses a Sketchup plugin to create its

energy models, giving architects the ability to easily capture

the volumetric intent of their designs. By contrast, eQUEST

creates an energy model by tracing over an AutoCAD draw-

ing, extruding floor plans, and controlling other geometric

elements with spreadsheet-based parameters. This severs

the connection between design intent and energy analysis,

inturrupting the feedback loop necessary to turn analytical

tests into generative project ideas.

1. eQUEST, doe2.com/equest

2. IES VE, www.iesve.com

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


0

20

22

27

1926

2511

1018

2528

25 24SPEED EASE OF USE DATA QUALITY GRAPHICS WORKFLOW TOTAL SCORE

2.32.34.53.74.0 117SPEED EASE OF USE DATA QUALITY GRAPHICS WORKFLOW TOTAL SCORE

3.74.24.74.04.1 161ENERGY MODELING SOFTWARE COMPARISON

Climate Analysis

Ease of Use

Time Required

Graphical Output

Quality of Data

Climate-Specific Design Strategies Included

File Import / Export Options

Base Model

Ease of Use

Time Required

Graphical Output

Quality of Data

Base Model Helps Understand Effects of Design Options


Concept Model Studies

Ease of Use

Time Required

Graphical Output

Quality of Data

Strength of Link Between Actual Design and Design Model


Daylighting

Ease of Use

Time Required

Graphical Output

Quality of Data

Ability to Test a Design’s Affect on Daylighting Levels


Design Model

Ease of Use

Time Required

Graphical Output

Quality of Data


Solar Shading

Ease of Use

Time Required

Graphical Output

Quality of Data

Integration of Solar Shading with Thermal Analysis


Thermal Analysis

Ease of Use

Time Required

Graphical Output

Quality of Data

Accuracy Compared to Other Accepted Modeling Programs


IES VEeQUEST

Category Averages and Total Score

Score Notes

0

0

0

0

0

0

5

5

5

3

3

5

5

4

3

3

3

2

3

1

3

1

1

1

3

5

3

1

1

5

3

4

4

3

3

5

5

4

3

3

5

5

3

5

2

4

3

Clear, concise results.

Five minutes.

Three simple graphs combine key information.

Included data gives great overview, but not enough for detailed analysis.

A few basic climate-specific design strategies are included, but other tools outperform it.

Graphics can only be exported as image files, not vectors.

4

2

4

0

0

1

4

5

4

5

4

5

3

5

4

3

5

5

5

5

5

4

4

5

3

5

3

5

4

5

5

3

3

4

3

After you have a fully defined design model, it automatically matches a base model to it.

Five minutes, after you have a fully defined design model.

None .

The only data included is kBTU / square foot.

Base model is automatically created, but its data is severely limited.

None.

Creating geometry is very easy. Geometry and building data can be defined in Sketchup.

One hour per massing study to model. Four additional hours to analyze.

Analysis results are graphically rich, but can only be exported as image files.

You can run the full suite of analyses on massing models once they are in IES.

Massing model geometry is imported from sketchup. Easy workflow.

You have to get the geometry into IES through Sketchup. Can’t import directly from Rhino.

10 minutes to 12 hours depending on quality settings.

Results can be viewed in a number of formants including contours, perspectives, etc.

Full suite of daylight analysis tools available including the very accurate Radiance engine.

Daylighting levels can be analyzed in plan, section, and perspective renderings.

Geometry must come into IES from Sketchup. Graphic output limited to image files.

Once shades are in, they can be accounted for in all daylight and thermal analyses.

Thirty minutes. Shading devices modeled in Sketchup, so creation is fast.


IES models the impact of shading accurately.

IES models the impact of shading on daylight and thermal analyses accurately.

Shading geometry imported from Sketchup. Graphic output limited to image files.

Geometry is imported from sketchup. Assigning model data can be overwhelming at first.

Two to four hours to create geometry. Four to eight hours to assign model data.


Full suite of analyses available once model is defined in IES.

Creating geometry in sketchup allows for strong 3D correlation between idea and model.

Design model geometry is imported from sketchup. Easy workflow.

Scheduling and HVAC systems input is complicated without help from M/E consultant.

Ten to sixty minutes depending on complexity of model.


Output a bevy of graphs and raw data. Highly accurate with correct HVAC systems.

IES with APACHE HVAC module is highly accurate. Without module it is inaccurate.

HVAC systems must be manipulated in IES.

Geometry must be traced from AutoCAD plans. Wizard for inputting model data.

One hour per massing study to model. Two additional hours to analyze.

Charts and graphs are easy to create but somewhat limited in scope.

Can quickly compare design options by looking at key energy use metrics. No daylighting.

Model is simplistic 3D extrusion of AutoCAD. Doesn’t feel like the design at all.

Must retrace AutoCAD drawings to create model. Graphical output is image file only.

No separate daylight analysis included, although daylighting does affect thermal analysis.


Must view daylight as a potential energy savings strategy (lower lighting load).

Daylighting levels can not be simulated, only how daylight affects energy performance.

No way to view daylighting levels.

None. Daylighting analysis is turned on via a check box.

Shading devices must be defined via text inputs for each opening.

Add an extra two hours to modeling process.

Must view effects of shading as a potential energy savings strategy (lowered cooling load).

eQUEST is considered an accurate modeling program.

eQUEST accurately simulates the effects of shading on energy use.

None. Shading is defined via text inputs for each opening.

Modeling is tedious. Inputting model data is made easier by wizard and smart presets.


Results displayed in simplistic charts and graphs. No plan overlays or 3D views available.

Energy use and ROI feedback is accurate. Daylighting studies not available.


Scheduling an HVAC systems input is helped by a wizard and smart default settings.

Five to thirty minutes depending on complexity of model.

Charts and graphs clearly illustrate impacts of design options, but aesthetically lacking.

eQUEST is an acceptable energy modeling software for a variety of certification programs.


HVAC systems must be manipulated in eQUEST.

Base model is created automatically.


Base model has same graphical output as the design model. Simplistic charts and graphs.

The automatically created base model has the same functionality as your design model.

Base and design models have same functionality. Can be seamlessly compared.

Created automatically, so same import/export problems as the design model.

Not available.

Not available.

Not available.

Not available.

Not available.

Not available.

Strength of Link Between Actual Design and Concept Model Creating geometry in sketchup allows for strong 3D correlation between idea and model.5

Score Notes

2 Model is simplistic 3D extrusion of AutoCAD. Doesn’t feel like the design at all.

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


0

20

22

27

1926

2511

1018

2528

25 24SPEED EASE OF USE DATA QUALITY GRAPHICS WORKFLOW TOTAL SCORE

2.32.34.53.74.0 117SPEED EASE OF USE DATA QUALITY GRAPHICS WORKFLOW TOTAL SCORE

3.74.24.74.04.1 161ENERGY MODELING SOFTWARE COMPARISON

Climate Analysis

Ease of Use

Time Required

Graphical Output

Quality of Data

Climate-Specific Design Strategies Included


Base Model

Ease of Use

Time Required

Graphical Output

Quality of Data

Base Model Helps Understand Effects of Design Options


Concept Model Studies

Ease of Use

Time Required

Graphical Output

Quality of Data

Strength of Link Between Actual Design and Design Model


Daylighting

Ease of Use

Time Required

Graphical Output

Quality of Data

Ability to Test a Design’s Affect on Daylighting Levels


Design Model

Ease of Use

Time Required

Graphical Output

Quality of Data


Solar Shading

Ease of Use

Time Required

Graphical Output

Quality of Data

Integration of Solar Shading with Thermal Analysis


Thermal Analysis

Ease of Use

Time Required

Graphical Output

Quality of Data

Accuracy Compared to Other Accepted Modeling Programs


IES VEeQUEST

Category Averages and Total Score

Score Notes

0

0

0

0

0

0

5

5

5

3

3

5

5

4

3

3

3

2

3

1

3

1

1

1

3

5

3

1

1

5

3

4

4

3

3

5

5

4

3

3

5

5

3

5

2

4

3

Clear, concise results.

Five minutes.

Three simple graphs combine key information.

Included data gives great overview, but not enough for detailed analysis.

A few basic climate-specific design strategies are included, but other tools outperform it.

Graphics can only be exported as image files, not vectors.

4

2

4

0

0

1

4

5

4

5

4

5

3

5

4

3

5

5

5

5

5

4

4

5

3

5

3

5

4

5

5

3

3

4

3

After you have a fully defined design model, it automatically matches a base model to it.

Five minutes, after you have a fully defined design model.

None .

The only data included is kBTU / square foot.

Base model is automatically created, but its data is severely limited.

None.

Creating geometry is very easy. Geometry and building data can be defined in Sketchup.

One hour per massing study to model. Four additional hours to analyze.


You can run the full suite of analyses on massing models once they are in IES.

Massing model geometry is imported from sketchup. Easy workflow.

You have to get the geometry into IES through Sketchup. Can’t import directly from Rhino.

10 minutes to 12 hours depending on quality settings.

Results can be viewed in a number of formants including contours, perspectives, etc.

Full suite of daylight analysis tools available including the very accurate Radiance engine.

Daylighting levels can be analyzed in plan, section, and perspective renderings.

Geometry must come into IES from Sketchup. Graphic output limited to image files.

Once shades are in, they can be accounted for in all daylight and thermal analyses.

Thirty minutes. Shading devices modeled in Sketchup, so creation is fast.


IES models the impact of shading accurately.

IES models the impact of shading on daylight and thermal analyses accurately.

Shading geometry imported from Sketchup. Graphic output limited to image files.

Geometry is imported from sketchup. Assigning model data can be overwhelming at first.



Full suite of analyses available once model is defined in IES.

Creating geometry in sketchup allows for strong 3D correlation between idea and model.

Design model geometry is imported from sketchup. Easy workflow.

Scheduling and HVAC systems input is complicated without help from M/E consultant.

Ten to sixty minutes depending on complexity of model.


Output a bevy of graphs and raw data. Highly accurate with correct HVAC systems.

IES with APACHE HVAC module is highly accurate. Without module it is inaccurate.

HVAC systems must be manipulated in IES.

Geometry must be traced from AutoCAD plans. Wizard for inputting model data.

One hour per massing study to model. Two additional hours to analyze.

Charts and graphs are easy to create but somewhat limited in scope.

Can quickly compare design options by looking at key energy use metrics. No daylighting.

Model is simplistic 3D extrusion of AutoCAD. Doesn’t feel like the design at all.




Must view daylight as a potential energy savings strategy (lower lighting load).

Daylighting levels can not be simulated, only how daylight affects energy performance.

No way to view daylighting levels.

None. Daylighting analysis is turned on via a check box.

Shading devices must be defined via text inputs for each opening.

Add an extra two hours to modeling process.

Must view effects of shading as a potential energy savings strategy (lowered cooling load).

eQUEST is considered an accurate modeling program.

eQUEST accurately simulates the effects of shading on energy use.

None. Shading is defined via text inputs for each opening.

Modeling is tedious. Inputting model data is made easier by wizard and smart presets.


Results displayed in simplistic charts and graphs. No plan overlays or 3D views available.

Energy use and ROI feedback is accurate. Daylighting studies not available.


Scheduling an HVAC systems input is helped by a wizard and smart default settings.

Five to thirty minutes depending on complexity of model.

Charts and graphs clearly illustrate impacts of design options, but aesthetically lacking.



HVAC systems must be manipulated in eQUEST.



Base model has same graphical output as the design model. Simplistic charts and graphs.

The automatically created base model has the same functionality as your design model.

Base and design models have same functionality. Can be seamlessly compared.

Created automatically, so same import/export problems as the design model.

Not available.

Not available.

Not available.

Not available.

Not available.

Not available.

Strength of Link Between Actual Design and Concept Model Creating geometry in sketchup allows for strong 3D correlation between idea and model.5

Score Notes

2 Model is simplistic 3D extrusion of AutoCAD. Doesn’t feel like the design at all.

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


IES VEeQUEST

While comparing eQuest and IES VE, the research team

concluded that one of the most important aspects of an en-

ergy modeling software is its ability to create a model that

matches the three dimensional intent of the design. The

images on the right show the considerable differences be-

tween the programs’ approach to modeling.

eQuest creates a model by tracing and extruding masses

from an autoCAD plan. Other geometric information, like

pitched rooves and glazing, is controlled by check boxes.

The final model resembles an extruded box, modified by

spreadsheet-like inputs. Complex sectional characteristics

are impossible to capture.

IES VE uses a Sketchup plugin to create its energy models.

This allows designers to accurately represent the design in-

tent in their energy models. The 3D model is able to cap-

ture complex geometry, important sectional characteristics,

and the intent of the design, building confidence that the

energy model actually responds to changes in the archi-

tecture. This is the number one reason why IES VE was

chosen over eQuest as MS&R’s energy modeling software.

EQUEST AND IES VE COMPARISON - CREATING AN ENERGY MODEL IN EQUEST AND IES VE

MODELING IN EQUEST AND IES VE

Source Drawing - AutoCAD Source Drawing - AutoCAD or Revit

Creating Rooms - Tracing Plans Creating Rooms - Extruding Plans

Modeling Roof - Check Box Modeling Roof - 3D Geometry

Final Model - Simple Box Final Model - Complex Geometry

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN



WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS



CLIMATE CHANGE AND THE IMPACT OF THE BUILT ENVIRONMENT

Climate change. Global warming. Extreme weather. These

themes seem to dominate news headlines as humanity’s im-

pact on the planet shifts from scientific theory to a force

that can be experienced first hand with increasing frequen-

cy. From the destruction of coral reefs to the shrinking of

the world’s glaciers, it is clear that our climate is changing.

The scientific community is in agreement that humanity is

causing the change, and carbon dioxide is our weapon of

choice. As we pump CO2 into the atmosphere by burning

fossil fuels, it acts as a “greenhouse” gas, trapping the sun’s

heat in our atmosphere and leading to a gradual increase

in the Earth’s temperature. Scientists predict this will have

dire consequences including rising sea levels, the increasing

frequency of severe weather, drought, and a massive destruc-

tion of ecosystems across the globe. It is time for humanity

to act, and the built environment is poised to play a pivotal

role in redefining our relationship with climate.

Architecture 2030 sums up the important role the built en-

vironment has to play in the fight against climate change on

its website:1

“Problem: The Building Sector

Solution: The Building Sector”

Architecture 2030 explains that the building sector con-

sumes nearly half of all energy produced in the United

States. It was also responsible for 46.7% of U.S. CO2 emis-

sions in 2010. To make matters worse, building sector en-

ergy consumption and CO2 emissions are projected to rise

faster than any other source between now and 2030.

The graph U.S. Energy Consumption by Subdivided Sector

shows that the vast majority of energy use attributed to the

building sector is used to operate buildings. This includes

all the energy needed to heat, cool, and light buildings over

their life spans. For an even clearer illustration on how op-

erating buildings impacts energy use, look at the graph U.S.

Electricity Consumption By Sector; a full 75% of the elec-

tricity used in the U.S. goes into operating buildings.

If architects design buildings that are more energy efficient,

we can drastically reduce the energy demands of the planet

and slow the pace of global warming. With enough down-

ward pressure, we can even reach carbon neutrality. So

what are these targets and what does it take to get there?

Architecture 2030 provides a guideline.

1. Architecture 2030. www.architecture2030.org U.S. ELECTRICITY CONSUMPTION BY SECTOR1

U.S. ENERGY CONSUMPTION BY SECTOR1

U.S. ENERGY CONSUMPTION BY SUBDIVIDED SECTOR1

“WE TEND TO RUSH TOWARD THE COMPLEX WHEN TRYING TO SOLVE A DAUNTING PROBLEM, BUT IN THIS CASE, SIM-

PLICITY WINS. BETTER BUILDINGS, RESPONSIBLE ENERGY USE AND RENEWABLE ENERGY CHOICES ARE ALL WE NEED TO

TACKLE BOTH ENERGY INDEPENDENCE AND CLIMATE CHANGE.”

- Edward Mazaria, Architect and founder of Architecture 2030

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. Architecture 2030. www.architecture2030.org

Architecture 2030 is optimistic about the positive impact

the built environment can have on reducing domestic energy

use over the next twenty years. It points to the projection

that by 2035, approximately 75% of the built environment

will be either new or renovated.1 Architecture 2030 calls

for architects to seize this opportunity, challenging them to

design each new or renovated building to meet ever increas-

ing energy targets, leading us to carbon neutrality by 2030.

Architecture 2030 developed its energy reduction targets

by working backward from the greenhouse gas emissions

reductions scientists predicted were necessary to reach by

2050 to avoid catastrophic climate change. In an interview

with BLDG BLOG, Ed Mazaria explains, “Working back-

wards from those reductions, and looking at, specifically,

the building sector – which is responsible for about half of

all emissions – you can see what we need to do today. We

need an immediate, 50% reduction in fossil fuel, greenhouse

gas-emitting energy in all new building construction. And

since we renovate about as much as we build new, we need

a 50% reduction in renovation, as well. If you then increase

that reduction by 10% every five years – so that by 2030 all

new buildings use no greenhouse gas-emitting fossil fuel en-

ergy to operate – then you reach a state that’s called carbon

neutral. And you get there by 2030. That way we meet the

targets that climate scientists have set out for us.”1

Meeting these targets requires the design of more energy

efficient buildings, the development of new building tech-

nologies and systems, and the implementation of renewable

energy sources. Of these categories, it is building design

that can have the greatest impact on energy reductions. It is

design that will create buildings that are in tune with their

natural environments and harvest the local climate to con-

dition their interiors, resulting in a more efficient, and more

appealing, built environment.

Environmentally sensitive designs require an environmen-

tally sensitive design approach, one that seeks to understand

the climate at the outset of the process, collaborates with the

entire design team on sustainable strategies, and adopts the

tools necessary to test and develop them into sustainable ar-

chitecture. Integrated Energy Design shows what this new

process might look like.

ARCHITECTURE 2030 - A ROAD MAP TO RECOVERY

MEETING THE 2030 CHALLENGE1

COMPOSITION OF THE BUILDING SECTOR BY 20351

ARCHITECTURE 2030 FOSSIL FUEL ENERGY REDUCTION TARGETS1

“THE MAJOR PART [OF A BUILDING’S ENERGY USE] - 40% - IS DESIGN. EVERY TIME WE DESIGN A BUILDING, WE SET UP ITS

ENERGY CONSUMPTION PATTERN AND ITS GREENHOUSE GAS EMISSIONS PATTERN FOR THE NEXT 50-100 YEARS. THAT’S

WHY THE BUILDING SECTOR AND THE ARCHITECTURE SECTOR IS SO CRITICAL. IT TAKES A LONG TIME TO TURN OVER.”

- Edward Mazaria, Architect and founder of Architecture 2030

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


“AN INTEGRATED DESIGN MIGHT BEGIN WITH THE REDUCTION OF HEAT LOADS IN THE OCCUPIED SPACE THROUGH

THE USE OF ENERGY-EFFICIENT LIGHTING FIXTURES AND DAY LIGHTING. THAT MAY MAKE IT POSSIBLE TO REDUCE SUP-

PLY-AIR FLOW RATES, LEADING TO LESS PRESSURE DROP IN THE AIR-DISTRIBUTION SYSTEM AND ALLOWING FOR SMALLER

FANS TO BE INSTALLED. FURTHER, AS A RESULT OF ALL OF THOSE DOWNSTREAM CHANGES, IT MAY ALSO BE POSSIBLE TO

SPECIFY A SMALLER COOLING PLANT.”

- Energy Design Resources

1. Integrated Energy Design, Energy Design Resources, www.energydesignresources.com

Meeting the Architecture 2030 challenge requires rethinking

how a project is delivered, bringing together owners, design-

ers, and consultants to work towards creating sustainable

and energy efficient buildings. Integrated Energy Design,

a process developed by Energy Design Resources, outlines

how to accomplish that.1 Of the process’s six steps, the first

three provide the strongest guidance for our Energy Model-

ing Methodology.

1. Plan for energy efficiency right from the beginning of

the design process.

The diagram on the right illustrates that the greatest po-

tential to affect the energy use of a building occurs at the

beginning of the design process. As the design continues,

decisions are locked into place, making changes difficult.

Therefore, it is imperative that planning for energy efficien-

cy is implemented from the start.

2. Identify integrated design strategies that will reduce life-

time costs while also improving occupant comfort.

Energy Design Resources gives an example of why integrat-

ed design strategies are so effective. “An integrated design

might begin with the reduction of heat loads in the occu-

pied space through the use of energy-efficient lighting fix-

tures and daylighting. That may make it possible to reduce

supply-air flow rates, leading to less pressure drop in the

air-distribution system and allowing for smaller fans to be

installed. Further, as a result of all of those downstream

changes, it may also be possible to specify a smaller cooling

plant.”2 This process can result in energy savings, cost sav-

ings, and increased occupant comfort.

3. Run whole-system analyses that treat a building as a

complete system, taking into account the interactions

among all of the building’s systems.

According to Energy Design Resources, “Whole-systems

analysis is an evaluative process that treats a building as

a series of interacting systems instead of looking at build-

ing systems as individual components that function in iso-

lation.” It takes a specialized tool to run a whole-systems

analysis, and that tool is energy modeling. In order to de-

liver more sustainable buildings, we need to redefine our de-

sign process, planning for energy efficiency from the start,

developing integrated sustainable design strategies, using

energy modeling to analyze building performance.


Prog

ram

min

g

Phase of design process

Sche

mat

icde

sign

Des

ign

deve

lopm

ent

Cons

truc

tion

Cons

truc

tion

docu

men

ts

Occ

upan

cy

Level ofdesign e�ort

Potentialcost-e�ective

energy savings

Source: ENSAR Group and E SOURCE

Energy-saving opportunities and the design sequenceFigure 1:

ENERGY SAVING OPPORTUNITIES AND THE DESIGN SEQUENCE1

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


In 27 BC, Vitruvius wrote a definition of architecture that

is still relevant. He wrote that architecture must exhibit

three qualities - firmness, commodity, and delight. Firm-

ness is concerned with structure and construction systems;

commodity is related to function, program, and budget; and

delight describes the beauty, aesthetics, and emotional im-

pact of a building.

A cornerstone of Energy Modeling Methodology is that

building performance is viewed as an integral part of archi-

tecture. Energy modeling doesn’t reside outside of the design

process, it is used to enhance architecture’s core qualities.

Designing for energy performance is a natural extension of

the Vitruvian Triangle. The emotional impact of a building

is enhanced by optimizing its use of natural daylight, archi-

tecture’s environmental impact should be considered just as

its function, program, and budget are, and energy perfor-

mance directly effects a building’s structure and materiality.

Integrated energy modeling into the design process enhances

a design team’s ability to understand the issues that affect a

project, fully explore the impact of their design on architec-

ture’s core qualities, and deliver a richer, more sustainable

final project.

VITRUVIUS REDEFINED

THE VITRUVIAN TRIANGLE REDEFINED - USING ENERGY MODELING TO ENHANCE DESIGN

Firmness

Com

modity D

eligh

t

Architecture

Beau

tyA

esth

etics

Emot

iona

l Im

pact

Construction Systems

Materiality

Structure

Function

Program

Budget

Firmness

Com

modity D

eligh

tBe

auty

Aes

thet

icsEm

otio

nal I

mpa

ctD

aylig

ht

Energy Performance

Construction Systems

Materiality

Structure

Function

Program

Budget

Environmental Im

pact

THE VITRUVIAN TRIANGLE

AN ANCIENT ROMAN ARCHITECT NAMED VITRUVIUS

WROTE THAT A BUILDING MUST BE CONSIDERED “WITH

REFERENCE TO FUNCTION, STRUCTURE, AND BEAUTY.”

...THINK OF THE VITRUVIAN FACTORS AS THE LEGS OF A

TRIPOD CALLED ARCHITECTURE. NONE CAN STAND

ALONE; EACH IS DEPENDENT UPON THE OTHER TWO TO

FORM THE WORK OF ARCHITECTURE.1

- James O’Gorman, from ABC of Architecture.

Architecture

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. Tom Fisher, Lecture, September 2010, University of Minnesota College of Design

Before we can push the design process forward, we must first

understand the thought process that powers it. Thomas Fisher,

Dean of the University of Minnesota’s College of Design, dia-

grammed how design thinking was distinct from problem solving

in a 2011 lecture to his Principles of Design Theory class.

Deductive and inductive reasoning are two types of problem

solving. Throughout their academic lives, students are taught

the value of linear thought processes, training them to search for

one correct solution to a given problem. Deductive reasoning

is more commonly known as the scientific method. It involves

making a hypothesis, running experiments to test the hypothesis,

and evaluating the resulting evidence to determine if it is correct.

Inductive reasoning works in reverse; a person makes an array of

observations, constructs generalizations that connect the obser-

vations, and arrives at a conclusion when a generalized statement

can be used to explain the entire set of observations. Although

these processes are useful, it is important to realize that they will

only lead to solutions that lay in the original field of inquiry.

These processes explain existing phenomena, they do not create

new phenomena.

Creativity is powered by design thinking, a decidedly non-linear

process. Design thinking involves addressing a problem by look-

ing at a multitude of issues that define it and using them to gener-

ate and explore new avenues of possibility. Some discoveries will

push the process forward while others will cause the designer to

take a step back, revisiting prior assumptions. Still others will

redefine the original problem all together, generating a unique

trajectory of their own. It is precisely design thinking’s chaotic,

non-linear nature that enables it to create in innovative discover-

ies. Architecture is very much a product of design thinking.

DESIGN THINKING1


INDUCTIVE REASONING1

CONCLUSIONS

GENERALIZATIONS

FACTS, EVIDENCE,

OBSERVATIONS

HYPOTHESIS

EXPERIMENTS

DATA COLLECTION,

EVIDENCE, OBSERVATIONS

DEDUCTIVE REASONING1

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


While non-linear design thinking powers creative innova-

tion, architects must also inhabit the linear world of the

design process to deliver a project. Energy modeling exists

in this overlap, acting as a catalyst to help architects make

informed decisions at each stage of development, leading

to projects that can meet the Architecture 2030 challenge.

The creative process by its very nature pulls inspiration

from a variety of sources, ensuring that the final result of

a design, as well as the criteria used to judge it, will be

unique. It is usually the architect’s own narrative that is

used to test the merit of early conceptual development.

As a project progresses, the design must meet a variety of

other demands, from structural loads to fire safety require-

ments. Energy performance should be thought of in the

same way; the conceptual intent of a design must be bal-

anced against given performance standards to improve the

quality of the project. Energy modeling should be used at

each stage of design to ensure energy performance and sus-

tainability are addressed throughout the process.

Over time, this enhanced design process will result in ac-

cumulated sustainable expertise within the office. Energy

modeling reacts to the specifics of a project, but the sustain-

able strategies it points to can be abstracted and digested

as new and improved rules of thumb. Future designs will

start from an ever-more informed position, improving

the sustainability and energy efficiency of each successive

building.

DESIGN PROCESS AND ENERGY MODELING

DESIGN PROCESS AND ACCUMULATED EXPERTISE FROM ENERGY MODELING

DESIGN PROCESS WITH ENERGY MODELING

DESIGN PROCESS

DESIGNDEVELOPMENT

SCHEMATICDESIGNCONCEPT

CONSTRUCTIONDOCUMENTS

ENER

GY

MO

DEL

ING

ENER

GY

MO

DEL

ING

ENER

GY

MO

DEL

ING

ENER

GY

MO

DEL

ING

ACCUMULATED EXPERTISE FROM ENERGY MODELING

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


REVITSKETCHUP

RHINO

RHINO

SKETCHUP

IES VE

INDESIGN

3D PRINTER

VRAY

PHOTOSHOP

PHYSICALMODEL

VRAY

PHOTOSHOP

INDESIGN

ILLUSTRATOR

PDF

PDF

AUTOCAD

TOOLS OF DESIGN

DESIGN STUDY TOOLS AND WORKFLOW

DO

CU

MEN

TAT

ION

VIS

UA

LIZ

ATIO

N

AN

ALY

SIS

DES

IGN

MO

DEL

DESIGN THINKING

DesignStudy

DesignStudy Design

Study

DesignStudy

REVIT

DESIGN STUDY - THE MOLECULE OF DESIGN THINKING

PRIM

ARY

MO

DEL

Architectural offices must accept that there is no single

piece of software that consolidates all of the functional-

ity necessary to create and execute a design. Rather, firms

must work with a collection of tools, developing a work-

flow that matches the character of the office.

The diagram on the right maps the software tools and

workflow patterns MS&R uses during design studies. The

studies themselves are the building block of the design pro-

cess. Each study uses the project’s current state as input,

explores the design, and creates output that can inform the

project and spark the next study.

MS&R uses Revit as its primary modeling software and

treats Rhino and Sketchup as design models. Design mod-

els can be thought of as digital sketches; the software en-

ables quick explorations of ideas. However, much like a

sketch can’t inform the project until it leaves the design-

er’s desk and is shared with the team, the results of design

models don’t become fully interwoven into the project until

they are deposited into Revit.

Energy modeling software enables MS&R to analyze the

performance of design studies. IES VE uses Sketchup to

create the 3D geometry for the energy model. It is not

possible to import Rhino geometry directly into IES VE,

however Sketchup can be used to translate Rhino geometry

and then export it to IES VE.

MS&R’s software and workflow fosters collaboration

within a design team while still allowing for individual cre-

ative freedom.

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


MS&R uses a variety of software throughout the design

process. Design Phases and Software Implementation il-

lustrates when and how each software is used. The dia-

gram also shows the weighted emphasis of the software at

each stage of design. Rhino, Grasshopper, and Sketchup

are used heavily in the beginning of the process, leveraging

the ability of the software to quickly model and explore

multiple concepts. Revit is integrated throughout, building

up the digital model as the design progresses. Once the

Construction Documents phase is reached, the majority of

digital modeling occurs within the detailed Revit model.

Energy modeling is used during every phase, but it has the

greatest impact on design at the beginning of the process.

It is used during Concept and Schematic Design to analyze

the climate and test the performance of early design stud-

ies, helping inform and improve design decisions.

Energy modeling has long been thought of as too compli-

cated and specialized to be utilized in the design process

effectively. Viewing it alongside other design software puts

it in perspective; it is simply another tool that helps address

a specific set of decisions that must be made during the

design process. Effective implementation of energy model-

ing allows design teams to address a wider scope of issues,

improving design decisions and ultimately the performance

of the building itself.

DESIGN PHASES AND TECHNOLOGY

DESIGN PHASES AND SOFTWARE IMPLEMENTATION

DESIGNDEVELOPMENT

SCHEMATICDESIGNCONCEPT

CONSTRUCTIONDOCUMENTS

CONSTRUCTIONADMINISTRATION

BUIL

DIN

G IN

FOR

MAT

ION

MO

DEL

ING

Zoning Analysis

Program Studies

Existing Conditions

Quantity Analysis

Test Fit Program

Program Refinement

Prelim. Systems Definition

Prelim. Systems Integration

Infrastructure Identification

Final Systems Definitions

System Integration

Typical Details

Door / Finish Schedules

Coordination

Quantity Analysis

Final Systems Integration

Final Design Development

Construction Sequencing

Atypical Details

Contract Documents

RFI’s

Supplemental Sketches

Construction Sequencing

Share Model with Engineer

Prelim. Daylight Analysis

Prelim. Thermal Analysis


Detailed Daylight Analysis

Detailed Thermal Analysis


Regulatory Compliance Model

Climate Analysis

Initial Daylight Analysis

Initial Shadow Studies

Massing and Energy Use

Glazing Percentage Studies

Concept Comparison

Multiple Schemes

Site Analysis

Existing Conditions

Massing Studies

Spatial Quality

3D Printed Models

Design Options

Model Complex Geometry

Visualization

Design Options


Visualization


3D Detailing

RH

INO

GR

ASS

HO

PPER

SKET

CH

UP

DIG

ITA

L SK

ETC

HIN

G

REV

ITM

AIN

MO

DEL

IES

VE

ENER

GY

MO

DEL

NEWFORMA

ADOBE CS5SUPP

LEM

ENTA

L CLIMATE CONSULTANT Climate Analysis

Communication Management

Presentation


Presentation, Rendering


Presentation, Rendering

Information Management

Presentation

RFI’s, Info Management

Weighted Emphasis of Software

Light heavy

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


The inputs that go into an energy model are common

across all software packages. The modeling software

combines climate data with information about the build-

ing form, construction types, occupancy types, occupancy

loads, building systems, and building system schedules to

analyze the energy use of the building.

These inputs can be broken into categories by looking at

whether the architect or engineer is responsible for them

during the design process. Climate is a given condition

directly related to the project’s site. Building form, con-

struction types, and occupancy types are controlled by the

architect’s programming and design. Occupancy loads,

building systems, and building systems schedules are in the

engineer’s domain.

An energy model can be represented as a stacked set of

inputs. When each input is defined with project specific in-

formation, the model will be at its most accurate, as shown

in Fully Defined Energy Model.

If you don’t input project specific information into a cat-

egory, the model will instead rely on pre loaded default

settings. In this state, an energy model will still perform

analyses, it just won’t be as accurate as a model that has

been fully defined by project specific information. As each

input becomes project-specific, the results become more ac-

curate.

ENERGY MODELING INPUTS Energy ModelingInput Category

Design TeamResponsibility

ENERGY MODELING INPUTS AND DESIGN TEAM RESPONSIBILITY

1

2

34, 5

6, 7

DEFINING ENERGY MODELING INPUTS

Input Defined by Engineers

Undefined Energy Model Input(Program Default)

Key

Energy ModelClimate Data

Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems

Building Systems Schedules

Fully Defined Energy Model


Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems


Partially Defined Energy Model

1) Climate Data

2) Building Form

3) Construction Types

4) Occupancy Types

5) Occupancy Loads

6) Building Systems

7) Building System Schedules

Architect

Engineer

Input Defined by Architects

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Analyze climate

Analyze site

Explore program

Identify energy budget

Identify construction budget

Identify design strategies

Create massing studies

Explore siting options

Explore design options

Initial investigation of materials

Analyze climate

Identify building systems budget

Identify systems design strategies

Develop building systems narrative

Explore building systems design options

DESIG

N D

EVELO

PMEN

TC

ON

CEPT

/ SCH

EMAT

IC D

ESIGN

COMBINE DESIGN

FINALIZE DESIGN

ARCHITECTSENGINEERS

Detailed exploration ofbuilding geometry

Detailed exploration ofconstruction systems

Detailed exploration of materials

Calculate heating, cooling, and lighting loads

Size building systems

CURRENT ENERGY MODELING TIMELINE

Currently, energy modeling, if it happens at all, occurs at

the end of design development. Engineering consultants

create an energy model by defining each input based on

the finalized design. Because the design is actually a com-

posite of decisions made during the duration of the design

process, the engineers in effect collapse a tree of decisions

made over time and turn them into energy modeling inputs.

The results of this type of energy model are an accurate

prediction of how the building will perform, but they are

an ineffective design tool. The current process places en-

ergy modeling too late in the design process, turning it into

more of an autopsy of performance rather than a genera-

tive tool to inform the design.

If we want energy modeling to be used to facilitate design

decisions, it must be implemented at the start of a proj-

ect and used throughout its duration. The following pages

diagram what this process looks like.

ENERGY MODELING TIMELINE - CURRENT PRACTICE


Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems


DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Analyze climate

Analyze site

Explore program








Analyze climate





DESIG

N D

EVELO

PMEN

TC

ON

CEPT

/ SCH

EMAT

IC D

ESIGN

COMBINE DESIGN

FINALIZE DESIGN

ARCHITECTSENGINEERS






Simulate energy use

ENERGY MODELING TIMELINE - PHASE I

Energy Modeling Timeline - Proposed Phase I shows how

to implement energy modeling at the earliest stages of de-

sign. At the beginning of a project, the design team starts

an energy model by defining Climate Data and Occupancy

Types with project-specific information. When the team

begins exploring massing and materials, they input infor-

mation about Building Form and Construction Types into

the model for different design options, running compara-

tive tests between them. At this stage, the software’s output

is accurate enough to evaluate the relative performance of

the options.

Think of relative performance testing like a concept sketch.

Concept sketches allow designers to evaluate how well dif-

ferent designs conform to the site and embody the concept,

but are understood to not initially tackle issues like ADA

accessibility and fire egress. Relative performance testing

in energy modeling is similar; it informs the designers how

different options perform against one another even though

the results are not 100% accurate.

If engineers and architects share an energy model, it can

be passed from architects to engineers as design develop-

ment begins. Energy Modeling Timeline - Proposed Phase

1 realigns the creation of an energy model more closely

with the way decisions are made during the design process.

Phase II explores the potential of sharing an energy model

during design development.

ENERGY MODELING TIMELINE - PHASE 1


Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems



Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems



Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems


DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Analyze climate

Analyze site

Explore program








Analyze climate










Official energy model for certification

DESIG

N D

EVELO

PMEN

TC

ON

CEPT

/ SCH

EMAT

IC D

ESIGN

COMBINE DESIGN

FINALIZE DESIGN

ARCHITECTSENGINEERS

Energy Modeling Timeline - Phase II illustrates the power

of sharing an energy model between architects and engi-

neers during design development. As the design progresses

and the model’s default settings are replaced by project-

specific information, the results become more accurate. In

Phase II, engineers and architects collaborate on the same

energy model, using their combined knowledge to fully de-

fine all of its inputs and ensure accurate results.

After schematic design, architects hand the model to the

engineers who fill in its inputs for occupancy loads, build-

ing systems, and building systems schedules. If the engi-

neers hand the model back to the architects, both parties

now have an energy model fully defined with project-spe-

cific information.

Equipped with a fully defined model, architects can now

fine tune a project during Design Development by using the

energy model to run iterative tests. Not only can the results

be used to test how different options for building form and

construction types perform against one another, the results

are now an accurate projection of the building’s energy use.

Both relative performance comparisons and accurate per-

formance projections are useful. By sharing an energy

model, architects and engineers can start with relative

comparisons early in the design process and work towards

accurate projections as the design is developed. This will

help the team integrate building performance into the en-

tire design process, keeping projects on track to reach Ar-

chitecture 2030’s performance goals.

ENERGY MODELING TIMELINE - PHASE II

ENERGY MODELING TIMELINE - PHASE II


Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems



Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems



Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems



Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems



Building Form

Construction Types

Occupancy Types

Occupancy Loads

Building Systems


DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Concept design provides an ideal opportunity for design

teams to set aggressive energy goals and leverage energy

modeling to steer projects towards them. During this

phase, designers have a great deal of flexibility in exploring

strategies to minimize energy use and maximize building

performance. At the same time, the project schedule pres-

sures the design team to be efficient in their explorations

and design recommendations. Integrating energy modeling

along with a clearly defined process will make the most out

of this opportunity by helping designers make informed

decisions.

The goal of the Energy Modeling Methodology during con-

cept design is to help inform design decisions. To achieve

this, it must be:

• Easy to use

• Able to efficiently compare design options

• Produce graphical output

A clearly defined process will help the design team utilize

energy modeling efficiently. The process should follow

these principles chronologically:

• Define energy goals

• Understand and diagram climate

• Identify possible passive and energy efficient design

strategies

• Use energy modeling to compare design options

• Interpret results holistically

SMARTER CONCEPTS

PROCESS GOAL

GUIDING PRINCIPLES

METHODOLOGY

Easy to use

Able to efficiently compare design options

Produce graphical output

Define energy goals

Understand and diagram climate

Identify passive and energy efficient design strategies

Use energy modeling to compare design options

Interpret results holistically

Help inform design decisions during concept design

CONCEPT DESIGN ENERGY MODELING METHODOLOGY

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. Lever House, photo by David Shankbone, Photobucket. media.photobucket.com/image/lever%20

house/HansPB/USA/Lever_House_by_David_Shankbone.jpg.

Sustainable and energy efficient buildings come in a variety

of shapes and sizes but they share one thing in common -

they respond to their local climates. Unfortunately, this is

the exception rather than the rule for today’s built environ-

ment. Beginning with the Lever House in 1952, buildings

became sealed boxes, separating themselves from climactic

considerations and instead relying on cheap energy from

fossil fuels to run HVAC systems that conditioned their in-

teriors.

Architects must reverse this trend using a design process

that embraces site sensitivity and uses passive strategies to

harness local climactic conditions. This process starts with

a thorough understanding of climate before design begins.

Two excellent tools that help a design team understand

their site’s climate and its impact on design are IES VE and

Climate Consultant. The following pages give an overview

of the tools.

CLIMATE ANALYSIS

PASSIVE DESIGN STRATEGIES FOR LAKE ITASCA BIOLOGICAL RESEARCH CENTER

LEVER HOUSE, 1952, 1ST SEALED CURTAIN WALL SKYSCRAPER 1

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


CLIMATE

Tulsa_bayStudy 00131/July/2012 at 12:46 PM INTEGRATED

ENVIRONMENTALSOLUTIONS LTD

Climate metrics

Copyright © 2012 IES Limited All rights reserved



Summer is potentially most dominant - the design must minimise cooling energy. Latitude is mid - solar radiation on south/east/west walls is significant. Solar radiation on roofs is significant. Summer is hot/warm. Summer also has a large diurnal range. Humidity is often greater than normal comfort limits. Winter is mild. There may be seasonal destructive storms (Hurricanes, Typhoons). Wind patterns: Typically westerly winds. Insects may be an issue.

Max annual temperature (Jul) 102.9 °FWarmest six months Jul Aug Jun May Sep Oct Coldest month JanMin annual temperature (Jan) -0.9 °FColdest six months Jan Dec Feb Nov Mar Apr Number of months warmer than 50.0°F mean = 8

Diurnal temperature swing3:0 months swing > 68 °F, of which 0 are in the warmest 6M0 months swing 59 to 68 °F, of which 0 are in the warmest 6M11 months swing 50 to 59 °F, of which 5 are in the warmest 6M1 months swing 41 to 50 °F, of which 1 are in the warmest 6M0 months swing < 41 °F

Max. moisture content 0.021 lb/lbMin. moisture content 0.000 lb/lbMean moisture content 0.009 lb/lbMean relative humidity 66.9 %

Annual mean speed 15.8 ft/sAnnual mean direction E of N 179.6°

Annual rainfall 40.591" inDriest month Jan with 1.539" in rainfallWettest month May with 5.598" in rainfallWettest summer month MayWettest winter month AprDriest summer month JulDriest winter month JanWettest six months May Sep Jun Apr Oct Mar

Annual hourly mean global radiation(a) 187.0 Btu/h•ft2

Mean daily global radiation(b) 1420.5 Btu/ft2

Annual solar resource(c) 519.3 Btu/ft2.yrAnnual mean cloud cover(d) 3.9 oktas

HDD(64.4) = 4094.3CDD(50.0) = 5114.8

Tulsa Intl Airport

ASHRAE 90.11 3A Warm humid Koeppen-Geiger1 Cfa Humid temperate (mild winters), Fully humid; no dry

season, Hot summer (sub-tropical), Mild winters, hot muggy summers with thunderstorms

Chosen weather file is TulsaTMY2.fwtRainfall location: Tulsa, USA

Temperature2:

Warmest month Jul

Moisture and humidity4:

Wind5:

Precipitation6:

Solar energy7:

Degree days8:

The climate report provides the headlines you need to know about the weather file you have selected

1. The Ashrae 90.1 climate classes are based around the Koeppen-Geiger classification system, but provide better definition in temperate and maritime zones. See also Koeppen Geiger and Kottek, Greiser,Beck, Rudolf and Rubel

2. Note the coincidence of wet or dry seasons and warm or cold seasons e.g. Wet summers, dry summers, wet winters etc

3. A good diurnal swing (monthly mean of the daily swing) during the warmest months indicates the potential for passive night time cooling and the use of thermal mass

4. Moisture content the nominal comfort range is 0.004-0.012 lb/lb If moisture content is 0.020 lb/lb or above either all year or in summertime it is an issue. High humidity high temp. cause comfort stress.

5. Wind speeds:less than 4.9 ft/s light and calm4.9-26 ft/s breeze26-45 ft/s strong breezegreater than 45 ft/s gale and above

6. Typically what does annual rainfall mean:Wet 67 inchesTemperate 20 to 59 inchesDry 12 inchesDesert 4 inches

7. Globally what is the range?a. 48 to 143b. 634 to 2061c. 254 to 697d. 1.5 to 8

8. Globally what is the range?HDD 32 to 11432CDD 32 to 11732

Page 1 of 1

7/31/2012file:///M:/Projects/2012001TUL/IES/Tulsa_bayStudy%20001/Toolkits/Climate/Report/Climate...

Climate Metrics, an automated report within the IES VE

energy modeling software, gives an excellent overview of

climactic conditions. The report consists of three columns,

one containing climate graphs, the second containing criti-

cal climate metrics, and the third serving as an explanation

of how to read and interpret the first two.

The center graph in the first column is a strong start-

ing point for analyzing climate. It quickly illustrates the

months that have cold stress (require cooling), heat stress

(require heating), or are comfortable (require little to no

conditioning). It also shows when peak temperatures and

rainfall occurs, and what months contain diurnal swings of

greater than 9 degrees. In a snapshot, designers can start

to understand the climate. If there are more heating stress

months than cooling, the design should place emphasis on

minimizing heating loads. If diurnal swings of greater than

9 degrees occur in the summer, there may be potential to

use night flushing as a passive cooling strategy. And if these

strategies didn’t immediately pop in your head, no worry;

the explanatory column on the right points them out for

you.

The information in the middle column has been paired

down to the most important climate metrics. Reading and

digesting it will give design teams a strong initial under-

standing of climate. For a more in depth study, turn to

Climate Consultant.

CLIMATE ANALYSIS - IES VE

GRAPHIC CLIMATE ANALYSIS FOR TULSA, OKLAHOMA

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. Climate Consultant, www.energy-design-tools.aud.ucla.edu/

Climate Consultant is a free tool developed by UCLA.1 It

is an excellent source for graphically representing climactic

information.

The tool is used by loading a climate file and clicking

through the various graphic representations of the data.

Everything from monthly temperature range to wind roses

are covered.

Walking through the Climate Consultant is an excellent

way to study certain aspects of climate in detail. During

the development of Energy Modeling Methodology, I was

asked to research the climate in Tulsa for a library MS&R

was working on. The design team was interested in how

to cool a garden space next to the library using passive

strategies. By looking at the graph Temperature Range,

we quickly saw that the average temperature in July was

85 degrees. We also learned from the Dry Bulb x Relative

Humidity graph that the relative humidity hovered around

66% in July. This combination of heat and humidity meant

that passive cooling strategies relying on evapotranspira-

tion wouldn’t be that effective. However, the wind patterns

in the area showed that the summer breezes came directly

from the south. This positioned them to flow right through

the project’s outdoor garden. After learning this, the design

team focused its initial passive cooling strategies around

shading and harnessing the wind to passively condition the

outdoor garden.

CLIMATE ANALYSIS - CLIMATE CONSULTANT

TEMPERATURE RANGE MONTHLY DIURNAL AVERAGES

DRY BULB AND RELATIVE HUMIDITY SKY COVER RANGE

WIND VELOCITY RANGE WIND ROSE

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. The Psychrometric Chart is part of the Climate Consultant software.

www.energy-design-tools.aud.ucla.edu/PSYCHROMETRIC CHART SHOWING NATURAL VENTILATION AND INTERNAL HEAT GAIN

After a design team becomes familiar with climate, the next

step is to determine how it might affect design. Luckily, a

tool has been developed that clearly illustrates the effec-

tiveness of a variety of passive design strategies in a given

climate - the psychrometric chart.1

Psychrometric charts work by setting up a system of axes

capable of graphing dry-bulb temperature, humidity ratio,

relative humidity, and wet-bulb temperature. Climate data

points are then graphed on the chart, usually in the form

of hourly data for the entire year. Once these points are

graphed, you can get a quick visual overview of the climate

by looking at the pattern of dots.

A comfort zone is then imposed on the chart. This shows

the ranges of temperature and humidity that people are

comfortable in. Dots that land inside this area don’t need

any heating, cooling, or humidity alteration to maintain

human comfort. Dots that sit outside of it show the hours

in the year where the climate does need conditioning to

reach comfort levels.

Finally, a series of passive design strategies can be selected

in the upper left hand corner. The user clicks on a strat-

egy and an associated area is graphed on the psychromet-

ric chart showing the climactic conditions it can effectively

temper. One a strategy is active, the chart also calculates

the percentage of yearly hours it effectively conditions.

Users can quickly cycle through the passive strategies, get-

ting visual feedback on how effective each strategy is in

their specific climate.

PSYCHROMETRIC CHART SHOWING HUMAN COMFORT ZONE

PSYCHROMETRIC CHART

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


36Meyer, Scherer & Rockcastle, ltd

context

WIN

TER WIN

DS

SUM

MER

WIN

DS

WIN

TER

WIN

DS

SITE

17:08

19:40 5:12

7:36

CLIMATE

At latitude 36 degrees, Tulsa is far enough north to escape the long

periods of heat in summer, yet far enough south to miss the extreme

cold of winter. The influence of warm moist air from the Gulf of

Mexico is often noted, due to the high humidity, but the climate is

essentially continental characterized by rapid changes in temperature.

Generally the winter months are mild. Temperatures occasionally fall

below zero but only last a very short time. Temperatures of 100

degrees or higher are often experienced from late July to early

September, but are usually accompanied by low relative humidity and

a good southerly breeze. The fall season is long with a great number

of pleasant, sunny days and cool, bracing nights.

Rainfall is ample for most agricultural pursuits and is distributed

favorably throughout the year. Spring is the wettest season, having an

abundance of rain in the form of showers and thunderstorms. The

steady rains of fall are a contrast to the spring and summer showers

and provide a good supply of moisture. The greatest amounts of

snow are received in January and early March. The snow is usually

light and only remains on the ground for brief periods.

Climate Overview

Max annual temperature (July) 102.9 F

Min annual temperature (Jan) 0.9 F

Mean relative humidity 66.9 %

Annual mean wind speed 15.8 ft/s

Annual rainfall 40.59 in

Mean daily global radiation 1420.5 Btu/sqft

Annual mean cloud cover 3.9 oktas

Heating Degree Days 4094.3

Cooling Degree Days 5114.8

By the Numbers

TULSA CLIMATE DIAGRAM

The power of diagrams lies in their ability to bring phe-

nomena into the visual realm, facilitating understanding

and communication. In architecture, where practitioners

are inherently visual people, diagraming a phenomena en-

ables it to be part of the design conversation. Climate is

not exempt from this rule; if climactic considerations are

to be interwoven into the design process, they must be dia-

grammed throughout a project’s development.

After researching climate, designers should immediately

begin diagramming its most important aspects alongside

a project’s other generative forces. The graphic on the

right was developed to facilitate MS&R’s understanding

of the Tulsa climate and how it affected the design of a

library they were working on. By simply overlaying climac-

tic information like wind direction and magnitude and the

sun path over an aerial view, they now become generative

forces for the design. Can the design harness the summer

winds and block the winter winds? Will the project be

shaded by nearby buildings?

Adding key climate metrics to the graphic helps the design

team gain a more nuanced understanding of how climate

might affect the design. Will the high daily global radiation

place an extreme cooling load on unshaded areas of the

site? Does the high relative humidity make natural ventila-

tion an ineffective strategy?

Finally, writing a short climate overview acts like a text-

based version of a diagram; it quickly brings together sa-

lient information into a format that facilitates understand-

ing and communication.

DIAGRAMMING CLIMATE

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


INVESTIGATED SUSTAINABLE STRATEGIES FOR THE TULSA GARDEN

A project’s diagrams should continue to address climate

throughout the design process. After completing the ini-

tial climate analysis for Tulsa, I explored passive and active

strategies for conditioning the project’s outdoor garden

space. First I created a graphic that combined the existing

spatial constraints of the site with the climactic conditions

that affected the design. Important climate metrics were

placed on the sheet, ensuring they would be referenced dur-

ing the process.

Wind flow and annual rainfall stood out as potential driv-

ers of passive design, and they were added to the diagram.

The resulting design proposal then looked at the ways wa-

ter could be passively collected, stored, cooled, and then

used to condition the garden and the interior of the library.

A combination of evapotranspiration and harnessing the

wind patterns might help further condition the air in the

garden, and this precooled air sould then be drawn through

an air / ground heat exchanger and used to condition the

library’s interior.

DIAGRAMMING CLIMATE

39Meyer, Scherer & Rockcastle, ltd

GARDEN STUDY

context

1

22

33

45

467

567

10

88

1111

12

1

9

Max annual temperature (July) 102.9 F

Min annual temperature (Jan) 0.9 F

Mean relative humidity 66.9 %

Annual mean wind speed 15.8 ft/s

Annual rainfall 40.59 in

Mean daily global radiation 1420.5 Btu/sqft

Annual mean cloud cover 3.9 oktas

Climate Metrics

1. Capture rainfall on roof and in garden

2. Store rainfall in underground cisterns

3. Potential to cool rainfall through a ground

heat exchanger

4. Explore cooling library interior through

indirect evaporative cooling by running water

over roof

5. PV panels produce electricity and shade roof

6. Study integrating irrigation system for garden

and green wall with canopy structure

7. Use tensile fabric to shade garden

8. Verify if garden and greenwall can condition

outdoor areas through evapotranspiration

9. Explore using summer breezes from the south

to help condition garden

10. Investigate collecting air at northern end of

garden and funneling it into an air ground heat

exchanger

11. Test viability of using an air ground heat

exchanger to precondition ventilation air for

the library

12. Consider using preconditioned air for library

ventilation

Investigated Strategies

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. IES VE MicroFLO User Guide. www.iesve.com/content/downloadasset_2287 TULSA GARDEN WIND FLOW ANALYSIS - DESIGN OPTION

IES VE was used to conduct a wind flow analysis for

MS&R’s Tulsa Central Library project. After earlier dia-

grams identified the possibility of using the site’s wind flow

patterns to passively cool the project’s garden space, the

design team wanted to explore the issue in more detail us-

ing energy modeling.

MicroFlo is a computational fluid dynamics application

that is a part of IES VE.1 It can be used to study internal

or external air flow. For this study, the design team was

interested in how a design option would affect wind flow

through the garden area between the library and parking

ramp. The project’s garden, library, parking ramp, and sur-

rounding buildings were modeled as simple masses. The

team then referenced the initial climate studies to deter-

mine the average summer wind speed and direction. The

values, 16 feet per second blowing from South to North,

were input in MicroFlo. The software then computed wind

flow patterns through the site.

The images show the results of the analysis. They each

depict a sectional slice of the modeled wind field that cuts

through the garden. As the scale shows, red areas represent

wind speeds of 16 feet per second and dark blue areas rep-

resent zones with speeds near 0 feet per second.

The design option explored in the lower image interrupts

wind flow at the garden’s surface but still allows air to cir-

culate above. The design team used this information to

inform the next round of design explorations.

WIND ANALYSIS

TULSA GARDEN WIND FLOW ANALYSIS - INITIAL CONDITION

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Massing studies are a cornerstone of concept design. Dia-

grams, hand sketches, and digital and physical models help

architects visualize, test, and refine early massing concepts.

Energy modeling can add another layer of analysis to the

mix, allowing the design team to consider a massing op-

tion’s impact on energy performance as well.

Using energy modeling to test massing concepts ensures

that issue of energy efficiency and sustainability will shape

the design from its earliest stages. Because the design teams

have so much creative freedom at the start of a project,

feedback from early energy modeling can put a design on

track to meet aggressive performance goals. Unfortunate-

ly, this inherent strength is also the process’s greatest chal-

lenge; because there are so many initial variables, it can

be difficult to compare and analyze the performance of di-

vergent concepts against one another. However, if design

teams adopt a process that starts by clearly defining goals

and ends with a wholistic comparison of design options

across a wide range of selection criteria, the methodology

can overcome this challenge and help inform those crucial

initial design decisions.

CONCEPT MASSING STUDIESDEFINE THE GOAL• What questions are you trying to answer?

• What variables are you testing?

1

CREATE SELECTION CRITERIA• Design decisions are complicated with a multitude of influences. Clear selection criteria

facilitates decision making

• Use existing standards as selection criteria when possible.

2

3 BUILD AN ENERGY MODEL• Simplify the model.

• Model only the detail necessary to facilitate decision making.

5

RUN ANALYSES• What analyses are necessary to shape your decision?

• What output is required to match your selection criteria?

• Are there additional analyses that can give you a more holistic view of performance?

4

INTERPRET RESULTS HOLISTICALLY• Always think holistically. Sustainability is not an end goal, it is part of good design.

• Balance energy modeling results with other important design aspects when making

design decisions.

CONCEPTUAL MASSING STUDIES COMPARISON

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Lake Itasca Biological Research Station, a MS&R project

targeting net-zero energy use, was used as the platform

to develop much of the Energy Modeling Methodology.

When research began, the project had already completed

Schematic Design and was awaiting the start of Design

Development. This allowed the research team freedom to

focus on process development rather than project deliver-

ables because the work was conducted outside of the stan-

dard fee and scheduling pressures of a project. This spe-

cific portion of the methodology, Concept Massing Studies,

revisited early concept studies as the basis of comparison.

Although these studies were conducted well after initial

design decisions had been made, the process that emerged

will be implemented on future MS&R projects to steer

concept design.

An early challenge for the design team was to choose a

massing option that not only responded to the project’s de-

sign drivers but also put it on track to achieve its net-zero

energy goal. In response, I created a process that combined

energy modeling with other selection criteria in compre-

hensively evaluating three different massing schemes. The

first step in the comparison was defining its goal. The goal

was defined as:

“Comprehensively compare massing options across selec-

tion criteria that integrating the project’s main design driv-

ers with energy performance.”

CONCEPTUAL MASSING OPTIONS FOR ITASCA BIOLOGICAL RESEARCH STATION

DEFINE THE GOAL

DEFINE THE GOAL 1

Comprehensively compare massing options across selection

criteria that integrating the project’s main design drivers with

energy performance.

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Using energy modeling to help in the comparison of con-

ceptual massing options is a powerful tool that is inher-

ently difficult to use; because there are so many initial vari-

ables at play, it is a challenge to compare analysis results

between massing options. However, by developing clear

selection criteria, the design team can facilitate massing op-

tion comparisons that will help steer the project in a suc-

cessful direction.

MS&R always strives to work with the client to clearly

define a project’s goals at the outset of design. These goals

become the benchmark of the project, acting as both a gen-

erative force and a set of criteria to judge design decisions

against.

When creating selection criteria to facilitate the compari-

son of concept massing options, the research team began

with the project’s goals. They were split into categories,

Economic, Social, Cultural, and Environmental. The last

category, Environmental, already contained aggressive per-

formance standards that could be analyzed by energy mod-

eling. The first three, while outside the domain of energy

modeling, are integral to the project’s success. Including

the entire lists ensures that massing options are compared

in a holistic manner.

DESIGN PERFORMANCE SELECTION CRITERIA FOR THE ITASCA BIOLOGICAL RESEARCH STATION

CREATE SELECTION CRITERIAECONOMIC

• Efficient to operate

• On budget

• Functional

SOCIAL

• Sensitive to historic fabric

• Building will be the visitor arrival point, meeting place, and social center

• Interior and exterior public spaces

CULTURAL

• Contemporary building that will not be confused with original historic buildings of the field station

• Embody the “field station” experience by enhancing outdoor activities and nature appreciation

• Posses a compelling identity

ENVIRONMENTAL

• Approach “zero net energy” within the limits of the budget

• Use natural light to illuminate interior during operating hours

• Utilize passive design strategies and make them an experiential and educational part of the building

CREATE SELECTION CRITERIA 2 Balance the Economic, Social, and Environmental impacts of

various massing options

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. IESNA Illumination guidelines are published by IESNA. Pacific Northwest National Laboratory repub-

lished them on their website. www.wbdg.org/pdfs/usace_lightinglevels.pdf

While outlining selection criteria for the Itasca concept

massing comparisons, the research team searched for exist-

ing standards that could be used to augment the list. The

environmental category called for the design to use natu-

ral light to illuminate the interior during operating hours.

IESNA standards exist that govern the lighting levels in

various programmatic spaces.1 The research team adapted

them to the project’s program and used them as a bench-

mark to test natural lighting performance when comparing

massing options.

IESNA lists nine categories that cover a variety of pro-

grams in its lighting standards. Attached to each are a

range of illuminance values required by the categories. The

research team listed the various programs the Itasca proj-

ect contained and, consulting the IESNA standards, chose

the illuminance levels that matched. The selection criteria

called for the design to use natural light to illuminate the

interiors during operating hours; this chart contained the

lighting levels required to meet this goal. And energy mod-

eling analyses were later used to test if the concept massing

options could hit these targets.

ECONOMIC

SOCIAL

CULTURAL

ENVIRONMENTAL

• Approach “zero net energy” within the limits of the budget

• Usenaturallighttoilluminateinteriorduringoperatinghours

• Utilize passive design strategies and make them an experiential and educational part of the building

CREATE SELECTION CRITERIA 2 Balance the Economic, Social, and Environmental impacts of various massing options

DESIGN PERFORMANCE SELECTION CRITERIA FOR THE ITASCA BIOLOGICAL RESEARCH STATION

ILLUMINANCE CATEGORIES AND ILLUMINANCE VALUES FOR GENERIC TYPES OF ACTIVITIES IN INTERIORS

TypeofActivity

Simple orientation for short temporary visits

Public spaces with dark surroundings

Performance of visual tasks of high contrast or large size

Working spaces where visual tasks are only occasionally performed

Lux

Performance of visual tasks of medium contrast or small size

Performance of visual tasks of low contrast or very small size

Performance of visual tasks of low contrast or very small size over a prolonged period

Performance of very prolonged and exacting visual tasks

Performance of very special visual tasks of extremely low contrast and small size

A

B

C

D

E

F

G

H

I

IlluminanceCategory

20-30-50

50-75-100

100-150-200

200-300-500

500-750-1000

1000-1500-2000

2000-3000-5000

10000-15000-20000

5000-7500-10000

2-3-5

5-7.5-10

10-15-20

20-30-50

50-75-100

100-150-200

200-300-500

1000-1500-2000

500-750-1000

General lighting throughout spaces

Illuminance on task

Illuminance on task, obtained by a combina-

tion of general and local lighting

RangesofIlluminance ReferenceWork-Plane

Foot Candles

ITASCA DAYLIGHTING TARGETS

ItascaProgrammaticSpaces

Office Area

Lab Area

Mechanical

Auditorium

Lux

Lobby

Rest Rooms

Circulation

E

D

D

D

B

B

B

IlluminanceCategory

General lighting throughout spaces

Illuminance on task

RangesofIlluminance ReferenceWork-Plane

Foot Candles

500-750-1000 50-75-100

200-300-500 20-30-50

200-300-500 20-30-50

50-75-100 5-7.5-10

50-75-100 5-7.5-10

50-75-100 5-7.5-10

200-300-500 20-30-50

USE EXISTING STANDARDS FOR SELECTION CRITERIA

• Modify existing standards for your project to create selection criteria

• Using existing standards as selection criteria when possible

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. IES VE Sketchup Plugin User Guide. http://www.iesve.com/content/downloadasset_2867

Energy modeling is used to analyze and compare the per-

formative aspects of massing options. When creating the

energy model, it is important to simplify it as much as pos-

sible. At this early stage of design, it is important for an

energy model to be quick to make and to be able to provide

enough information to facilitate a relative comparison.

These energy models don’t have to accurately predict the

building’s energy use down to the nearest kBtu/sf. Instead

they need to contain only the detail necessary to differen-

tiate them from one another and capture each concept’s

unique features that may affect energy use.

The building’s geometry should be simplified. Any rooms

that are similar should be grouped together into a single

zone. The images on the right show an early concept plan

for Itasca. The second image illustrates how the energy

model combines multiple offices into a single zone as well

as combining the lab spaces and their support areas. This

speeds up the modeling process considerably while still

keeping enough definition to provide results accurate

enough to facilitate a relative comparison.

COMBINE SIMILAR ROOMS INTO SINGLE ZONES WHEN BUILDING AN ENERGY MODEL1

BUILDING AN ENERGY MODEL

LAB SPACESOFFICE OFFICE

AUDITORIUM

CIRCULATION

LOBBY

REST ROOMS

BUILD AN ENERGY MODEL 3 Simplify, simplify, simplify. Model only the level of detail

necessary to facilitate decision making.

ITASCA CONCEPT SKETCH WITH DETAILED ROOM DIVISIONS

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. IES VE Sketchup Plugin User Guide. http://www.iesve.com/content/downloadasset_2867

Because IES VE uses a Sketchup plugin to create its energy

models, going from concept sketch to three dimensional en-

ergy model is quick and easy. The images on the right start

by showing a concept drawing that has been imported into

Sketchup. Because the most important differences were the

sectional characteristics and glazing placement between the

massing options, these were captured in detail. Again, us-

ing Sketchup makes modeling this detail very easy.

When creating an energy model in Sketchup, do not model

wall thickness. Energy models deal in zones, looking at the

space between defining elements, not at the elements them-

selves. Define the geometry with simple planes.1

After the sketchup model is complete, the IES Plugin au-

tomates the process that converts it into an energy model.

The plugin searches the model for enclosed areas and turns

them into zones that can be read by IES VE. Finally, it ex-

ports the converted model into IES VE where the full suite

of analyses can be run on it.

BUILDING AN ENERGY MODEL

A) CONCEPT SKETCH B) SKETCHUP MODEL

C) SKETCHUP IES ENERGY MODELING PLUG IN D) IES ENERGY MODEL (DAYLIGHT ANALYSIS SHOWN)

1) CONCEPT DRAWING

2) SKETCHUP MODEL

3) SKETCHUP IES ENERGY MODELING PLUG IN

4) IES ENERGY MODEL

A

B

C

D

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. IES VE ApacheSim User Guide. www.iesve.com/content/downloadasset_2883

2. IES VE FlucsDL User Guide. http://www.iesve.com/content/downloadasset_2307

Once an energy model is created, design teams need to

choose analyses that will provide them with the infor-

mation necessary to make an informed decision. For the

Itasca project, our selection criteria was broken into four

categories: economic, social, cultural, and environmental.

Energy modeling analyses can help test the performance of

the concept massing options in the environmental category.

The environmental category of the selection criteria called

for a building that approaches zero net energy, uses natural

light, and utilizes passive design strategies. The first two

criteria, energy use and natural lighting, can be easily ana-

lyzed by an energy model. It is much more difficult and

time consuming to analyze passive design strategies with

an energy model, so the design team instead relied on cli-

mate research and the psychrometric chart to determine

what passive strategies might be effective.

A massing concept’s energy use can be determined by run-

ning a thermal analysis with IES VE ApacheSim.1 Remem-

ber that the performance comparisons between massing

options will be relative; define the building geometry and

make quick assumptions about the rest of the energy mod-

eling inputs. When running a thermal analysis, focus on

heating and cooling loads instead of energy use, as building

systems, an unknown at this point in the process, have little

effect on them.

Daylight analyses use IES VE Flucs DL. Run tests for the

winter and summer solstice. Then measure and graph

lighting levels in foot candles to enable comparisons with

the lighting selection criteria.

RUNNING ANALYSES

CONCEPT 1

CONCEPT SKETCH ENERGY MODEL DAYLIGHTING ANALYSIS

CONCEPT 2

CONCEPT 3

CONCEPT 3

KBTU/SF

7070

71

74

79

RUN ANALYSES4 Chose analyses that will help inform decision making in a holistic manner

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Thermal Loads - 70 kBtu/sf

Total Floor Area - 13295 sf

Exterior Wall Area - 10262 sf

Glazing to Floor Area Ratio - 9.82%

Thermal Loads - 70 kBtu / SF












Concept 1

Concept 2

Concept 3

Concept 4

SOCIA

L

CONCEPTS THERMAL ANALYSIS Sens

itive t

o Hist

oric

Fabr

ic

DAYLIGHTING ANALYSIS Build

ing w

ill be

the v

isitor

arriv

al po

int an

d soc

ial ce

nter

Inter

ior an

d Exte

rior P

ublic

Spac

es

Contem

porar

y buil

ding w

ith un

ique c

harac

ter

Contem

porar

y buil

ding w

ith un

ique c

harac

ter

Embo

dy th

e “Fie

ld Sta

tion”

expe

rienc

e

CULTURAL

Appro

ach n

et ze

ro en

ergy

Use na

tural

light

Use pa

ssive

desig

n tha

t are

expe

rienti

al

ENVIRO

NMENTA

L

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

COMPARING CONCEPT MASSING OPTIONS

The final steps in comparing conceptual massing options is

compiling the analyses, interpreting the results, and mak-

ing a decision. The most important thing to remember is

to think holistically.

The graphic on the right brings together the four massing

options, the energy modeling results, and the original selec-

tion criteria. Architecture must respond to a wide range of

factors; combining all of this information helps ensure that

each concept is evaluated against the full range of selection

criteria.

To facilitate the decision making process, the concepts can

be scored for each selection criteria. Design teams can

also weight the scores if certain aspects of the project are

deemed more critical than others.

After scoring the concept options, the design team elected

to continue in the direction of Concept 4. Although it had

the highest energy use with 79 kBtu/sf, it also contained a

much higher glazing percentage than the rest of the models.

The concept outperformed the rest in daylighting and was

the only one to achieve the IESNA lighning benchmarks.

And the unique section, with skylights on the south stream-

ing into a sun corridor and then through a translucent pan-

el and into the lab, received high marks for using passive

design strategies as experiential elements.

If the concept massing comparison wasn’t done holistically,

this option may have been tossed out for its higher energy

use. But, after looking at the full range of design drivers, it

was decided to be the best direction for the project.

INTERPRETING RESULTS

INTERPRET RESULTS HOLISTICALLY5 Balance energy modeling results with other important

design aspects when making design decisionsDESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Energy modeling is a perfect match for the design devel-

opment phase. During design development, large-scale

decisions have been made, a concept has been locked in,

and the project team spends the majority of their time fine

tuning the design. Energy modeling thrives in this environ-

ment, leveraging its strength as an analytical tool that is

most effective when studying isolated variables. Designers

can use energy modeling to help dial in a range of design

development decisions using iterative analyses.

An iterative analysis takes one variable, be it the R value of

a wall, the building’s glazing percentage, or the geometry or

a room, testing baseline performance against a series of op-

tions that all slightly modify it. By using iterative analyses,

the design team can optimize conditions. In practice, this

usually involves using energy modeling to find a range of

optimized conditions and setting them as bracketed targets

for the design to hit.

ITERATIVE ANALYSIS

PROCESS GOAL

GUIDING PRINCIPLES

METHODOLOGY

Easy to use

Able to efficiently compare design options

Produce graphical output

Create a baseline energy model of the schematic design

Identify key aspects of the design to fine tune

Use iterative analysis to bracket optimized conditions

Interpret results holistically

Aid designers in fine tuning a design

DESIGN DEVELOPMENT ENERGY MODELING METHODOLOGY

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS

ITERATIVE ANALYSIS

1 1/2" = 1'-0"1 Section - Double Stud Wall

BACKFILL

12” COMPACTED GRAVEL FILL

UNDISTURBED SOIL

11” COMPACTED GRAVEL FILL

1 1/2” FLOWABLE FILL

TOTAL R VALUE OF ASSEMBLY 57.47

WALL ASSEMBLY

5/8” Hardy Panel

5/8” OSB Sheathing

3 1/2” Cellulose Blown Insulation

1” Rigid Insulation - Extruded Polystyrene


5/8” OSB

1” Rigid Insulation - Extruded Polystyrene

5/8” Gypsum Board

.08

5

0.63

13.65

9.75

21.45

.63


5

.56

Material R Value

WALL SECTION AND R-VALUES

As buildings strive to reach higher levels of energy efficien-

cy, the quality of their envelopes becomes very important.

Having a well insulated, well designed, and well construct-

ed envelope is critical to the performance of a design. So

just how much insulation is necessary? Energy modeling

can help answer this perennial question.

R-value is a measurement of thermal resistance used to

describe the performance of building materials. It is ex-

pressed as the thickness of the material divided by its ther-

mal conductivity. Materials with higher insulating capaci-

ties have a higher R-value. The R-value for an assembly is

calculated by adding the R-values of its component parts

together. U-value, used to describe the thermal resistance

of windows, is simply the reciprocal of R-value.

Energy modeling and iterative analysis can help design

teams dial in optimized target R-values for a building’s en-

velope.

As a target, the values help guide the design while still al-

lowing for the flexibility necessary to address design de-

cisions holistically. While iterative analysis will provide a

range of optimized R-values, it is still up to the design team

to factor in the cost, durability, constructability, sustain-

ability, and aesthetic and conceptual impact of designing

the envelope to achieve the recommended values.

OPTIMIZING R-VALUES

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


1. IES VE ApacheSim User Guide, http://www.iesve.com/content/downloadasset_2883

OPTIMIZING R-VALUES

The design team for MS&R’s Itasca Biological Research

Center wanted to determine target values for effective lev-

els of insulation in the project’s envelope. The process be-

gan by creating a base energy model, setting the envelope’s

R-values to code-minimum levels. The performance of this

base condition was analyzed using IES VE ApacheSim and

graphed as the design’s total annual heating and cooling

load.1

Each assembly was then studied independently using itera-

tive analysis. With the rest of the building remaining at

code-minimum levels, each successive iteration would raise

the R-value of the assembly being tested by 5 and model

its impact on heating and cooling loads. Eleven iterations

were completed for each assembly.

The results all show that heating and cooling loads are re-

duced when the assembly’s R-value is increased. However,

by studying the slope of each graph, the design team could

see where the performance benefits of additional R value

began to plane out. When the cost of increasing an as-

sembly’s R-value is factored in, it became clear that these

changes in slope signaled the point where increased insula-

tion no longer carried a strong return on investment. These

target values were highlighted in yellow. The lighter shade

of yellow indicated increased R-values that, while not re-

turning a large performance benefit, might still be neces-

sary to achieve the project’s net-zero energy targets. The

orange line marks where the R-values were previously set

during schematic design.

The top row of graphs also illustrates the relative perfor-

mance benefits of addressing one assembly against anoth-

er. The graphs show that increasing the window R-value

ITASCA ITERATIVE ANALYSIS OF R-VALUES

ITASCA ENERGY MODELING Design Model

Wall R Value Roof R Value Slab R Value Window R ValueWall R Value Heating Loads Cooling Loads Total Loads Roof R Value Heating Loads Cooling Loads Total Loads Slab R Value Heating Loads Cooling Loads Total Loads Window R Value Heating Loads Cooling Loads Total Loads

13 619827 133190 753017 30 619827 133190 753017 10 619827 133190 753017 1.5 619827 133190 75301715 606219 134041 740260 35 610011 132955 742966 15 578573 139255 717828 2 542684 135236 67792020 585561 136064 721625 40 602558 133113 735671 20 556004 142875 698879 3 466900 145821 61272125 572214 137022 709236 45 596704 133215 729919 25 540864 145434 686298 4 428415 152660 58107530 563177 137661 700838 50 591980 133288 725268 30 530198 147311 677509 5 405152 157421 56257335 556650 138115 694765 55 588089 133352 721441 35 522290 148740 671030 6 376684 178931 55561540 551702 138445 690147 60 584833 133421 718254 40 516184 149870 666054 7 365494 182487 54798145 547822 138699 686521 65 582076 133503 715579 45 511331 150786 662117 8 357087 185288 54237550 544698 138904 683602 70 579720 133601 713321 50 507375 151544 658919 9 350540 187547 53808755 542131 139080 681211 75 577687 133715 711402 55 504103 152174 656277 10 345291 189409 53470060 539987 139237 679224 80 575913 133820 709733 60 501334 152719 654053 11 340991 190969 53196065 538173 139384 677557 85 574368 133953 708321 65 499110 153159 652269 12 337402 192294 529696

Wall R Value Roof R Value Slab R Value Window R Value

650000

700000

750000

650000

700000

750000

650000

700000

750000

650000

700000

750000

500000

550000

600000

30 35 40 45 50 55 60 65 70 75 80 85500000

550000

600000

10 15 20 25 30 35 40 45 50 55 60 65500000

550000

600000

1 2 3 4 5 6 7 8 9 10 11 12500000

550000

600000

13 15 20 25 30 35 40 45 50 55 60 65

Model DataFloor Area 11740Volume 215865Ext. Wall Area 10434Ext. Opening Area 3300Ext. Roof Area 13223

30 35 40 45 50 55 60 65 70 75 80 85 10 15 20 25 30 35 40 45 50 55 60 65 1 2 3 4 5 6 7 8 9 10 11 1213 15 20 25 30 35 40 45 50 55 60 65

Current: R63 Current: R178 Current: R93 Current: R4.3

Wall R-Value Roof R-Value Slab R-Value Window R-Value

Ann

ual h

eatin

g an

d co

olin

g lo

ad (

kBtu

/sf)

Scal

e co

nsist

ent

acro

ss a

ssem

blie

s

ITASCA ENERGY MODELING Design Model

Wall R Value Roof R Value Slab R Value Window R ValueWall R Value Heating Loads Cooling Loads Total Loads Roof R Value Heating Loads Cooling Loads Total Loads Slab R Value Heating Loads Cooling Loads Total Loads Window R Value Heating Loads Cooling Loads Total Loads

13 619827 133190 753017 30 619827 133190 753017 10 619827 133190 753017 1.5 619827 133190 75301715 606219 134041 740260 35 610011 132955 742966 15 578573 139255 717828 2 542684 135236 67792020 585561 136064 721625 40 602558 133113 735671 20 556004 142875 698879 3 466900 145821 61272125 572214 137022 709236 45 596704 133215 729919 25 540864 145434 686298 4 428415 152660 58107530 563177 137661 700838 50 591980 133288 725268 30 530198 147311 677509 5 405152 157421 56257335 556650 138115 694765 55 588089 133352 721441 35 522290 148740 671030 6 376684 178931 55561540 551702 138445 690147 60 584833 133421 718254 40 516184 149870 666054 7 365494 182487 54798145 547822 138699 686521 65 582076 133503 715579 45 511331 150786 662117 8 357087 185288 54237550 544698 138904 683602 70 579720 133601 713321 50 507375 151544 658919 9 350540 187547 53808755 542131 139080 681211 75 577687 133715 711402 55 504103 152174 656277 10 345291 189409 53470060 539987 139237 679224 80 575913 133820 709733 60 501334 152719 654053 11 340991 190969 53196065 538173 139384 677557 85 574368 133953 708321 65 499110 153159 652269 12 337402 192294 529696

Wall R Value Roof R Value Slab R Value Window R Value

733321

738321

743321

748321

712269

732269

752269

679696

729696

717557

727557

737557

747557

708321

713321

718321

723321

728321

733321

30 35 40 45 50 55 60 65 70 75 80 85652269

672269

692269

10 15 20 25 30 35 40 45 50 55 60 65529696

579696

629696

1 2 3 4 5 6 7 8 9 10 11 12677557

687557

697557

707557

717557

13 15 20 25 30 35 40 45 50 55 60 65

Model DataFloor Area 11740Volume 215865Ext. Wall Area 10434Ext. Opening Area 3300Ext. Roof Area 13223

30 35 40 45 50 55 60 65 70 75 80 85 10 15 20 25 30 35 40 45 50 55 60 65 1 2 3 4 5 6 7 8 9 10 11 1213 15 20 25 30 35 40 45 50 55 60 65

Current: R63 Current: R178 Current: R93 Current: R4.3

Ann

ual h

eatin

g an

d co

olin

g lo

ad (

kBtu

/sf)

Scal

e to

fit

data

per

ass

embl

y

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


ITASCA BIOLOGICAL FIELD STATION - Design Development Daylight Optimization08.21.2012

Target Standard - LEED 2009 Credit 8.1: Daylight

LEED Credit 8.1 - 10 foot candle minimum daylight in 75% of

occupied space at 9:00 am and 3:00 pm on September 21st.

LEED Innovation in Design Credit - 25 foot candle minimum

daylight in 95% of occupied space at 9:00 am and 3:00 pm on

September 21st.

Standard Used - LEED Innovation in Design Credit

Model - IES VE FlucsDL with sky set to Clear Sky

Results File - 120820 Sun Co LEEED Daylight Study

SUN CORRIDOR DAYLIGHT STUDY

Average Daylight FC - 37.5

Meet LEED 8.1 Daylight Target - NO

Meet LEED IDC Daylight Target - NO


Meet LEED 8.1 Daylight Target - YES




Meet LEED IDC Daylight Target - YES

Option 3

Remove every other window

17% Glazing

Option 2

Remove every fourth window

29% Glazing

Option 1

Starting condition

46% Glazing







September 21st.



Results File - 120820 Sun Co LEEED Daylight Study 4










SUN CORRIDOR DAYLIGHT STUDY

Option 6

Remove every 4th window. Decrease size of all windows.

13% Glazing

Option 5


16% Glazing

Option 4


20% Glazing

ITASCA GLAZING PERCENTAGE OPTIMIZATION

Glazing percentage has a strong impact on a project’s ener-

gy use and daylighting potential. It is important to balance

these effects when using energy modeling to optimize them.

The study on the right was used to optimize the glazing

percentage on Itasca’s south facing sun corridor. Daylight-

ing targets were developed before beginning the analysis.

Because the project is pursuing LEED certification, the

design team used LEED Credit 8.1 - Daylighting and an

associated Innovation in Design credit to serve as the tar-

get. The standard called for 95% of a design’s regularly

occupied spaces to achieve daylighting levels between 25

and 500 foot candles measured at 9:00 am and 3:00 pm on

September 21st.

IES VE includes a LEED Credit 8.1 navigator that analzes

the design for credit compliance. I simply modeled the sun

corridor with a variety of glazing percentages in IES VE,

ran the navigator, and interpreted the results. The top im-

age shows the graphical output from the IES VE analysis.

It marks areas of the design that comply with the standard

in green. It also reports the percentage of the design that

complies. This allowed me to quickly hone in on glazing

percentages and patterns that achieved the standard.

After running a series of iterative analyses, I found the min-

imum glazing percentage that still achieved the daylighting

targets. Thermal analysis was carried out by engineering

consultants, revealing that the minimum condition actually

didn’t out perform the original heavily glazed design due

to a balance between passive heating gains and lowered

heat losses. Because of this, the design team felt free to

maximize the glazing to capture the unique site views of

Lake Itasca.

OPTIMIZING GLAZING PERCENTAGE

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Option 1

Starting Condition

Option 2

Raised Skylight

Option 3

Lowered North glazing to view height




Average Daylight FC - 31












September 21st.


Model - IES VE FlucsDL with sky set to Clear Sky.

Results File - 120820 Lab LEED Daylight Study

LAB DAYLIGHT STUDY







September 21st.



Results File - 120820 Lab LEED Daylight Study 4










Option 6

One large skylight in center

32% Roof Glazing. 21% North Facade Glazing.

Option 5

Two skylights at edges of room


Option 4

Thin and wide skylight


LAB DAYLIGHT STUDY

Daylighting can be optimized by analyzing glazing percent-

age as well as glazing design. Intelligent sizing and place-

ment of glazing will facilitate daylighting. The studies

shown on this page were completed to optimize glazing in

the Itasca Biological Research Center’s lab spaces. Once

again, an iterative approach to energy modeling was used.

Because the study was focused solely on the labs, I created

a new energy model of a single lab space and an adjacent

section of sun corridor. The sun corridor was included be-

cause the labs are designed to pull daylight from the sun

corridor. Like the glazing percentage optimizations shown

on the previous page, these studies used LEED Credit 8.1 -

Daylighting as the target and the IES VE navigator to test

for compliance.

What is unique about the challenge of studying the place-

ment of glazing is that there are unlimited possibilities; it

would be impossible to methodically test all of the pos-

sible permutations in search of an optimal design. Instead,

designers must analyze results for trends, leading them to-

wards designs that meet the criteria.

The first set of analyses studies the effect of moving a

north-facing skylight up. The results indicated that this

brought more daylight into the interior. The second set of

studies builds off this and shows the minimum glazing size

and placement of three design options that all achieve the

target daylighting levels.

OPTIMIZING DAYLIGHT

ITASCA DAYLIGHTING ANALYSIS

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES




SMARTER CONCEPTS


OPTIMIZING DAYLIGHT


LAB SECTION 1

Daylight Performance -

Thermal Performance -

Achieves LEED 2009 Credit 8.1: Daylight

Achieves LEED 2009 IDC Credit for Optimal Daylighting Performance

Average Daylight = 43.6FC


LAB SECTION 3

Daylight Performance -

Thermal Performance -

Achieves LEED 2009 Credit 8.1: Daylight

Achieves LEED 2009 IDC Credit for Optimal Daylighting Performance

Average Daylight = 41.4 FC

The final step in the daylight optimization studies was to

test the resulting geometries holistically. After finding two

glazing options for the lab space that achieved the daylight-

ing targets, they were diagrammed to test their ability to fa-

cilitate the project’s other goals. In a sense, this brought the

process full circle, combining a detailed daylighting analy-

sis with the original climate diagrams to help te team make

an informed design decision. Both options lent themselves

well to harnessing the site’s wind flow patterns, bringing

in the summer breezes through low windows in the south

facade and allowing them to vent out of the operable sky-

light. However, Lab Section 3 provided additional shading

for the skylights from the summer sun, added more south

facing roof surface area for mounting PV panels, and fur-

thered some of the project’s original aesthetic intentions.

By using a combination of analysis techniques and always

striving to present results graphically and in a holistic man-

ner, the design team was able to make well informed de-

cisions throughout the process. This kept the project on

track to be successful in not only meeting energy perfor-

mance goals, but also in achieving excellence in the other

areas of architecture described by Vitruvius - firmness,

commodity, and ultimately, delight.

OPTIMIZING DAYLIGHT

ITASCA DAYLIGHT ANALYSIS AND SECTIONAL STUDIES

DESIGN PROCESS 2.0

PROJECT TIMELINE

ARCHITECTURE 2030

CLIMATE ANALYSIS



ABOUT THE STUDY

TOOLS OF DESIGN




WHY ENERGY MODEL?

CLIMATE CHANGE


VITRUVIUS REDEFINED


PSYCHROMETRIC CHART

DIAGRAMMING CLIMATE


OPTIMIZING R-VALUES


OPTIMIZING DAYLIGHT



SMARTER CONCEPTS


Date post:	10-Feb-2016
Category:	Documents
Upload:	university-of-minnesota-college-of-design
View:	216 times
Download:	0 times