[American Institute of Aeronautics and Astronautics 10th AIAA Aviation Technology, Integration, and...

American Institute of Aeronautics and Astronautics

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Rapid Air System Concept Exploration – A Parametric

Physics Based System Engineering Design Model

Armand J. Chaput,

Aerospace Engineering and Engineering Mechanics

University of Texas at Austin, Austin, Texas, 78712

Rapid Air System Concept Exploration (RASCE) is a physics-based, unmanned air

system (UAS) conceptual level design and analysis system. Originally developed as an

educational tool to support undergraduate student exploration of a wide range of UAS

design and operational concepts during a 15 week semester, it has been applied to a number

of system level studies for both government and industry. It runs quickly and in real time on

a standard laptop and does not require laborious input data preparation and/or calculations.

It is designed to provide physics-based feedback on conceptual designs, "what-if"

operational requirement, design and technology decisions, to support evaluation of

configuration options and/or to perform trade studies, all in real time. RASCE is a mature

design and analysis system, having been used on 100s of UAS concept design projects since

its introduction in 2003. Predicted performance has been correlated with flight test data

with good results.

Nomenclature

AR = Wing aspect ratio = b2/Sref (dimensionless)

Awet = Wetted aspect ratio = b2/Swet (dimensionless)

BPR = Engine bypass ratio (dimensionless)

BHp = Brake horse power

BHp0 = Design maximum uninstalled engine power at SLS conditions (BHp)

CD = Drag coefficient (dimensionless)

CL = Lift coefficient (dimensionless)

CLto = Takeoff lift coefficient (dimensionless)

CL3/2

/CD = Parameter used to determine minimum power required (dimensionless)

Dfe = Fuselage equivalent diameter = (WfHf)0.5

e = Oswald wing efficiency (dimensionless)

Es = Specific energy (ft-lbf/lbm)

FOV = Sensor field of view (deg)

ff = Fuel fraction (Wf/W0 )

Hf = Fuselage maximum height (ft)

IFOV = Sensor pixel instantaneous field of view (micro radians)

L/D = Lift-to-drag ratio at a given speed and altitude (dimensionless)

(L/D)max = Maximum lift-to-drag ratio (dimensionless)

Ps = Specific excess power (ft/sec)

SFC = Specific fuel consumption (lbm/hr-BHp

Sht = Horizontal tail exposed reference area (ft2)

Sref = Wing planform reference area (ft2)

Svt = Vertical tail exposed reference area (ft2)

Swet = Air vehicle wetted area (ft2)

T0 = Design maximum uninstalled engine thrust at SLS conditions (lbf)

TOP = Takeoff parameter for prop aircraft = (W0/Sref)/[σ CLto(BHp0/W0)]

for jet aircraft = (W0/Sref)/[σ CLto(T0/W0)]

TSFC = Thrust specific fuel consumption (lbm/hr-lbf)

10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference 13 - 15 September 2010, Fort Worth, Texas

AIAA 2010-9301

Copyright © 2010 by Armand J. Chaput. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.


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Vavail = Total volume available of the sum of all body components intended for installation of all fuel, payload

and systems (ft3)

Vreq'd = Total volume required for installation of fuel, payload and systems (ft3)

W0 = Design maximum gross weight (lbm)

Waf = Air vehicle airframe weight (lbm)

We = Air vehicle empty weight (lbm)

Wf = Air vehicle fuel weight (lbm)

Wf = Fuselage maximum width (ft)

Wpay = Air vehicle payload weight (lbm)

ηp = Installed overall propulsion efficiency (dimensionless)

σ = atmospheric air density ratio relative to sea level (dimensionless

Acronyms

CAD = Computer Aided Design

CER = Cost Estimating Relationship

COTS = Commercial Off The Shelf

EAS = Equivalent Air Speed (knots)

IC = Internal Combustion

IFR = Instrument Flight Rules

RASCE = Rapid Air System Concept Exploration

SLS = Sea Level Static

UA = Unmanned Aircraft (i.e. the air vehicles)

UAS = Unmanned Aircraft System (i.e. the entire system)

I. Introduction

Aircraft and air system design has a long history and uses many design tools and techniques to explore, develop

and analyze conceptual designs. Among the many text books written on the subject, Nicolai1, Roskam

2 and

Raymer3 are generally recognized as being among the best. Although there are some differences in their

approaches, at a basic level they have fundamental similarities. All three use parametric methods for initial concept

sizing and then follow up with more detailed evaluation of candidate point-designs. Each point design is developed

to a sufficient level of detail to gain insight into its quantitative characteristics and capabilities. The process

typically starts with a concept drawing or sketch, followed by aerodynamic, mass property, propulsion, structures,

performance and other evaluations. Next are trade studies to improve and/or optimize performance. In industry and

government mission, effectiveness evaluations are typically performed by an Operations Research group, using

generic vehicle concepts with simple models of sensors and weapons until more definitive concepts are available.

As the studies progress and preferred concepts start to emerge, the design, analysis and mission effectiveness

processes comes together to focus on the most promising of the starting concepts.

A wide range of design tools are used ranging from simple in-house parametric sizing codes to sophisticated

point-design commercial off the shelf (COTS) programs. Parametric codes are typically used for concept

exploration. Most parametric codes are relatively simple with minimal physics-based modeling beyond the Breguet

range or endurance equation. Historically based design parametrics and weight-based fractions feed the process.

Simplifying assumptions and estimates are required to keep the process from bogging down in too much detail.

Unfortunately, some of the simplifications and assumptions can drive the outcome especially when new design

spaces are being explored. Sensors, communications, Concepts of Operation, cost, logistics and support are often

addressed as separate subjects and careful coordination is required to keep the entire process connected.

Concept design and analysis codes are typically point design focused and require a fairly complete definition of

the mission, payload, propulsion system and air vehicles. Considerable time and effort can be involved in

generating data of sufficient quality and fidelity to feed the process. COTS codes can be complex and results can be

driven by subtle assumptions, and/or limitations, some of which are not clear until later in the process.


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Satisfying propulsion data requirements can be a problem, particularly for students. Air vehicle performance

codes typically require tabular inputs of installed thrust and fuel flow. Generating the installed data can be time

consuming and/or involve use of proprietary engine company codes. Students, therefore, have been known to use

uninstalled engine data from text books or websites without realizing that differences between installed and

uninstalled data can be significant. Even more difficult (particularly for students) are fundamental propulsion trades

of basic propulsion issues (turboprop vs. turbofan, bypass ratio vs. vehicle performance, installation concepts, etc.).

Typically, the design process focuses on meeting in-flight air vehicle performance requirements. More subtle

performance requirements such as sensor and communication payload secondary power and cooling demands are

typically estimated parametrically and may not be recognized as serious point design issues until late in the process.

Important multi-discipline design issues including volume, c.g. and control requirements also may not discovered

until after a concept has been more fully defined. In fact the amount of effort required to develop a viable baseline

often discourages exploration of alternate concepts. Teams can start to fall in love with their starting concepts and

don't aggressively explore the available design space. Once again, the process is particularly challenging for

students. They can spend so much time feeding the design process that they don't have time to think about what

they are designing and why.

One solution to the problem is to use an integrated multi-discipline parametric design system that has the fidelity

of a conceptual point design and analysis system and the flexibility of a parametric sizing code4. This would allow

design teams to go straight from brainstorm type concepts to fully converged point design solutions in a single step.

With the proper design interface, designers would be encouraged to explore design options by using slider bars

instead of discrete numerical inputs. Included would be parametric propulsion models with enough fidelity to

properly capture physics and operational limits across a range of propulsion types. Even though the individual

models of the system might be simple, when integrated at the system level to include sensors, communication and

other key elements, an overall physics-based system model of a complete air system suitable for projecting cost and

effectiveness can result. In addition to the physics, however, the models need to include calibration factors that are

always necessary to adjust air vehicle and/or system element models to represent realistic or observed performance.

II. Rapid Air System Concept Exploration (RASCE) Model Based Design

RASCE is an integrated set of air system design and analysis models originally developed for educational

purposes. It was originally intended to teach students how to approach the design of systems from a physics and

requirements perspective. Most system design methodologies focus on requirements only - physics based issues are

often not addressed and/or discovered until later. RASCE has also been applied to wide range of design projects

ranging from top-level system concept evaluations to exploration of existing hardware options for performance

enhancement.

Figure 1 - RASCE User Interface Worksheet


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Although the original focus was on unmanned air systems, RASCE is equally applicable to manned air systems.

In its current form RASCE operates as an integrated set of EXCEL air vehicle spreadsheets with linked physics

based sensor and parametric communication and cost model spreadsheets as shown in Figure 1. A trained user can

go from an initial concept idea to an air vehicle sized against full mission rules in about an hour. Sensor sizing and

communications payload definition can take more or less time depending on system complexity.

A unique feature of the RASCE air vehicle model (what makes it different from traditional sizing programs) is

its parametric geometry basis. A parametric geometry model emulates the function of a CAD model traditionally

used to physically integrate aero-propulsion, stability and control, mass property, volume, mission performance and

other requirements. RASCE iterates the parametric design and converges to a point solution that uniquely meets

input requirements. Output includes a sized air vehicle conceptual level “drawing” in addition to traditional

configuration description data, and detailed performance by mission segment. The output “drawing” is used to

visualize the concept and identify disconnects and areas for improvement.

System Design Approach. The objective of a typical RASCE based design and analysis is to determine the

overall size and capability of a UAS concept to meet system requirements. Typically system level requirements

involve a geographic coverage area, a top-level mission objective (e.g. detect, identify and prosecute targets of a

specified size), a performance objective (e.g. detect and prosecute 95% of the targets) and timeline requirements

(e.g. 24 hour coverage and 5 minutes from ID to attack). Options for meeting the requirements are evaluated in

individual design and analysis sessions and solutions are output in terms of size and numbers of air vehicle and

payload combinations required to achieve the objective. Simple size, number and weight based cost estimating

relationships (CERs) are used to estimate development and procurement costs. Operations and support costs are

based on flight hours and estimated manpower required to maintain flight operations and to service and maintain the

system. Output solutions are saved and cross plotted to identify optimums from an overall system design

perspective.

Mission definition. Mission descriptions are included in an overall air vehicle design interface module and

include multiple mission segments including outbound and inbound cruise, operational loiter, ingress and egress,

and combat. Specific methods are described in the sections that follow. For example, engine start and taxi times

are defined and takeoff is modeled as a requirement using Raymer's takeoff parameter2. Energy based climb/descent

and acceleration/deceleration segments are included between the individual mission segments. Landing includes

defined loiter, fuel reserve and taxi back requirements. Flight speeds are currently limited to high subsonic

conditions (onset of drag rise). Performance calculations assume typical benign UAS profiles (flight path climb

angles of 15 degrees or less).

Figure 2 - RASCE Mission Definition

Two types of missions can be specified. One is a design mission used to size the overall air vehicle. The other is a

fallout mission used to calculate the performance of the sized air vehicle to meet another set mission objectives. The

fallout mission feature is included to give students an appreciation of the impact of conflicting design requirements

on the system design. Otherwise the fallout mission is used to build a matrix of point-design performance estimates

over a range of candidate missions.

Design margins. Mission performance, empty weight and internal volume margins are specified by

requirement and included as mission sizing criteria. All solutions are required to be feasible and unique so that

constraint analysis is not required to identify viable areas of the design space. If a user attempts to define a non-

viable concept, feedback is provided in the form of a solution that either won't compute or one that simply diverges.

Launch and recoveryMission control

Operating Distance

Ingress/egress

Photos from


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Either way, there is no confusion about when a configuration concept and mission capability limit has been pushed

beyond feasible limits.

Payload definition. Physics based sensor models are currently developed for Electro-Optical (EO) and Infra

Red (IR) systems. EO/IR inputs include resolution requirements and criteria, focal plane array size, pixel pitch,

image overlap criteria and other key sensor parameters. Single and multi-frame scanning capabilities are modeled.

Linear optics models size sensors against requirements and produce field of view and area coverage estimates.

Uninstalled sensor size, weight, volume, power and stabilization requirements are parametrically derived.

Installation effects are estimated using parametric weight, density, power and drag factors.

Figure 3 - RASCE EO/IR Parametric Sensor Models

Communications payload size, weight and power (SWaP) is estimated parametrically based on type (e.g., line

of sight vs. SatCom), range and frequency. Line of sight (LOS) calculations are physics based and driven by input

mission requirements. Communications payload requirements are assumed to be sensor payload driven. A separate

vehicle-specific communication system is assumed to be included in air vehicle mission avionics

Weapons payloads are defined by weight, density and drag area. Internal and/or external carriage can be

specified and weapons can be expended over the target or carried throughout the mission. External fuel tanks can be

specified by number, shape (fineness ratio) and installation drag area.

Retained payload and expendable internal payload locations are specified relative to air vehicle fuselage length.

Expendable external payloads and external fuel tanks are assumed to be located on the air vehicle center of gravity

at maximum weight.

Air vehicle configuration definition. A wide variety of air vehicle types can be modeled using simple

geometric shapes to represent individual bodies or integrated shapes. Discrete body types include fuselage(s),

nacelle(s), pod(s), wings, horizontal and vertical tails and winglets consistent with traditional CAD model

definitions or advanced parametric CAD systems such as Vehicle Sketch Pad (VSP)11

. Fuselage(s) are defined as a

body or bodies to which tails are attached and nacelles are assumed to contain engines as shown in Figure 4.

Fuselages, nacelles and pods have defined forebody, center body and aftbody sections and defined installation

factors for fuel, payload and systems (including landing gear). Center bodies are defined as constant area sections

with generic elliptical cross sections (defined by height-to-width ratio). Forebodies and aftbodies are modeled as

ellipsoids of revolution having defined body length fraction. Fuselage and pod volumes are usable for fuel, payload

or systems with installation density being controlled by input packing factor criteria (ranging from zero up to some

reasonable upper limit packing factor). Propulsion systems are assumed to be installed in nacelles and user inputs

h = altitude

Slant range (SLR) - min

Slant range (SLR) - max

hreq’d = RmaxTan(θθθθmin)

Swath width (w)

Max range = Rmax

θminθmax

Field of View (FOV)

Min range = Rmin

h = altitude

Slant range (SLR) - min

Slant range (SLR) - max

hreq’d = RmaxTan(θθθθmin)

Swath width (w)

Max range = Rmax

θminθmax

Field of View (FOV)

Min range = Rmin

FOVh IFOVhIFOVh

Nph = number of

horizontal pixels Vehicle speed (V)

Equiv focal

length (EFL)Target distance (d)

Swath width (Ws)

Swath length (Ls)

Image overlap

fraction (OLF)

IFOVh(horizontal)

(µrad/pixel)

Basic equations (far field) - stabilized

• FOVh = IFOVh∗Nph

• Rph = IFOVh∗SLR

• Ls = SLR∗FOVh

• Imaging frame rate (FR) ≥ V/[Ls(1-KOLF)]• Imaging data rate = FR*Nph*Npv*BPP/CR

Typical EO/IR Performance - Narrow FOV

0

50

100

150

0 1 2

FOV (degrees))

IFO

V (

mic

ro-r

ad

) EOIR

EO Optics - Narrow FOV

0.1

1

10

5 10 15 20

Turrent Diameter (in)

FO

V (

deg

)

HorizontalVerticalvertical

EO/IR Weight

0

50

100

150

200

250

5 10 15 20 25

Turret diameter (in)

Weig

ht

(lb

)


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define where the installation occurs (i.e. in a forebody, aft body, center body or over a complete nacelle).

Propulsion installation volume is specified by not allowing volume to be used fuel, systems or payload. The

primary function of geometry models is calculate (1) volume available for equipment and subsystem installation, (2)

wetted area (for body weight and drag calculations) and (3) body reference lengths and diameters (to determine

component locations and Reynolds number effects).

Figure 4 - RASCE Air Vehicle Geometry Model Approach

Wing geometry is defined by standard input wing planform parametrics including taper ratio, thickness to chord

ratio, Aspect ratio, wing sweep and wing loading at design maximum gross weight (W0). A single wing can be

represented by up to 3 wing panel segments, all of which are assumed to be trapezoidal. Wings also have

parametrically defined compartments for fuel, payload and systems with installation density being control by

packing factors. Wing position on the air vehicle is determined analytically based on input static margin

requirements, estimated air vehicle neutral point location and calculated center of gravity (c.g.). Wings are assumed

to be integrated with fuselages and exposed wing reference area is estimated based on fuselage geometry. Wing

wetted area is estimated using a simple algorithm based on wing thickness and exposed planform area.

Horizontal and vertical tail surfaces are sized based in input horizontal and vertical tail volume coefficients and

defined locations relative to either the fuselage(s) or wing mean aerodynamic chord. Tail geometry is determined

based on input leading edge sweep, taper ratio and aspect ratio. Winglets are sized based on and input wing

reference area fraction. Winglet geometry is defined by the input vertical tail geometry and winglet location relative

to the wing tip chord. Winglets are assumed to contribute to meeting vertical tail volume criteria. An option is

provided to let swept outer wing panels to contribute to horizontal tail volume.

Input wetted area and hidden area factors are used to integrate individual body models into viable overall

configuration concepts. For example, an engine nacelle integrated into a fuselage might be modeled by specifying

that the nacelle forebody is 100% exposed while the center and aft bodies are 0% exposed (meaning it doesn't exist

for purposes of the weight, volume and drag calculation). The fuselage on the other hand would be defined as

having no forebody (0% exposed) and center and aft bodies that are 100% exposed. A similar approach would used

to allocate volume for fuel, systems and payload. In the above example, no nacelle volume would be allocated to

fuel, systems and payload because it is intended for engine installation. The fuselage forebody would also receive

no volume allocation because it has been replaced by the nacelle. That leaves only the fuselage center and aft bodies

- Sized by mission requirements

- Weight and volume from power-to-weight and density

- Performance from parametric cycle deck (V, h, %throttle)

Fuselage model

- Ellipsoid forebody

- Elliptical cylinder centerbody

- Ellipsoid aftbody

- Diameter sized to meet volume requirements less

wing and nacelle

- Weight and balance based

on wetted areaWing model

- Multi-panel planform,

constant taper (λ) & thickness-to-chord (t/c)

- Partial span and chord trapezoidal volume, constant

λ & t/c- Area sized by wing loading

(W0/Sref)- Location based on balance

- Volume calculated

- Weight and balance based

on exposed planform areaPropulsion model

5 10 15 20Fuselage Station - FS (ft)

Payload model


- Location input parametrically

Nacelle model

- Ellipsoid forebody

- Elliptical cylinder centerbody

- Ellipsoid aftbody

- Inlet and exhaust sized by frontal area ratios

- Diameter sized by engine

requirements

- Weight and balance based on wetted area

Empennage models

- Single panel planform, constant

taper (λ) & thickness-to-chord (t/c)- Exposed areas sized by tail volume

coefficients

- Weight and balance based on

exposed planform area

Landing gear and systems- Volumes from density

- Weights from fractions

- Locations input parametrically

Fuel



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available for fuel, payload and systems and the availability would be input accordingly using industry standard

packing factors for each installation type.

Summary level geometry by component is output for user reference. Outputs include overall lengths, diameters

and planform and wetted areas plus additional data on fore and aft body components. Typical geometric efficiency

parameters are also output for user reference. Volume available by input body is used to determine cross sectional

area as a function of body length fraction for output to allow resolution of volume available vs. volume required

location issues.

Propulsion model definition. Four basic propulsion types are provided (electric, internal combustion,

turboprop and non-afterburning turbojet-turbofan). The models are based on previously unpublished, physics-based

conceptual level parametric “cycle decks” designed to generate installed thrust available and fuel flow as functions

of speed, altitude and throttle setting12

.

IC power available is modeled using the well-known air density-maximum power relationship originally

published by NACA where the ratio of power available at altitude to SLS power available is given by:

BHp/BHp0 = [8.55σ-1]/7.55

Fuel flow is calculated based on an assumption of constant specific fuel consumption by mission segment (e.g.,

climb, cruise and high speed dash). Thrust available is calculated using a single assumed propulsion efficiency

factor (ηp) by mission segment that combines both propeller and installation effects. Typical values used are in the

range 0.6<ηp<0.85 and capture a range of issues from induction system losses to propeller efficiency. Electric

motor thrust available is calculated in a similar fashion except that that maximum power available does not vary

with altitude and "fuel" consumption is weight invariant.

Turbofan thrust available and fuel flow is calculated based on four simplifying assumptions: Fan Bypass Ratio,

core engine corrected Specific Thrust and fuel-to-air ratio are constant and corrected Fan Specific Thrust varies

linearly with respect to an assumed takeoff reference speed. Turboprop performance is simply modeled as a

turbofan of very high bypass ratio.

All four propulsion models are programmed with similar input and output structures so they can function as

generic conceptual level "cycle decks" across a design space. Primary power or thrust is decremented by secondary

power required to meet subsystem and payload requirements to a simple input duty cycle. Simple physical

integration concepts are assumed with inlet and nozzle losses captured using overall ηp efficiency inputs to adjust

uninstalled cycle deck calculations for installation effects. More complicated concepts can be accommodated by

discrete adjustments to parametric inputs.

Propulsion model parametric inputs can also be used for trade study purposes. For example a recent study for

the US Air Force Research Laboratory Propulsion Directorate evaluated propulsion design features of a range of

advanced technology internal combustion cycle types to determine which features showed the most benefit at the

overall air system level. The results of the RASCE study were unambiguous and not only identified which of the

characteristics were most significant, but also for which vehicle sizes the benefits were most significant and vice

versa7.

Aerodynamics, stability and control. Lift (CL) and drag (CD) coefficient calculations are based on standard

Mach adjusted lift curve and Reynolds number corrected component drag build-up methods based on Raymer2.

Friction drag is estimated for each air vehicle component based on wetted area and a user defined laminar vs.

turbulent flow fraction. Standard Reynolds number adjustments are applied to the turbulent and laminar

calculations. A variety of published and unpublished component form factor algorithms are used depending on

component type. Component interference factors are user defined. A simple parabolic drag polar is assumed using

Oswald's wing efficiency factor (e). Climb and loiter aerodynamics are estimated using either lift coefficient (CL) for

maximum lift-to-drag ratio (L/D)max or for minimum power required (CL3/2

/CD). Non-component body such as

fixed external landing gear drag is calculated used drag factors from Raymer2. Sensor and external payload drags

are also estimated using simple drag factors plus interference factors.

Lift is calculated as a requirement based on a input stall lift coefficient, air vehicle maximum weight wing

loading and mission speeds and altitudes by mission segment. Required angle of attack is calculated using a

standard Mach and exposed wing area corrected equation for lift curve slope. All input speeds are checked against a


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user input maximum allowable Mach and minimum allowable speed as defined by input stall margin by mission

segment. Input speeds are adjusted automatically to stay within specified constraints.

Static stability is satisfied by definition of overall air vehicle neutral point, required static margin and calculated

vehicle c.g. at maximum design gross weight (W0). The wing is simply positioned to meet static margin

requirements at maximum weight W0. Input horizontal and vertical tail volume coefficients ensure that tail sizing is

consistent with historical trends. In addition, a minimum horizontal tail area required at a user input maximum tail

lift coefficient and tail dynamic pressure ratio vs. free stream is calculated and compared to the size required to meet

tail volume criteria.

Calculated aerodynamic coefficients are used by the air vehicle performance module to calculate performance.

Summary data is output for user information in the form of component drags as percentage of total drag and a design

mission drag polar. Calculated static margins at empty weight (We) and empty weight plus retained payload (Wpay)

are output and are intended to be used to identify typical off-design static margin issues.

Air vehicle mass properties. Sensor and communication payload mass and volume estimates are based on

parametrics developed from publically available supplier information. EO/IR sensors are assumed to be turret

mounted and use pixel instantaneous field of view (IFOV) as the driving design parametric. IFOV (the arc length

subtended by a single pixel) is calculated from slant range, target size, required resolution and required probability

of detection or identification based on Johnson imaging criteria9. Sensor field of view (FOV) required can be

calculated from sensor swath length or swath width requirements or determined from focal plane array geometry.

For turreted systems, FOV has been parametrically correlated with turret diameter and sensor power and uninstalled

weight as shown previously in Figure 3. Parametric installation effects are estimated using weight and clearance

factors to account for rack, wiring and connector weight and volume.

Other parametric correlations are used to estimate communication system size, weight and power.

Communication RF power is correlated with range and bandwidth requirements. RF power is correlated with input

power, and electronic hardware uninstalled size and weight. Antenna uninstalled size and weight is estimated

separately based on communication system type (line of sight or SatCom), frequency and bandwidth. Parametric

factors account for installation weight and volume penalties.

Expendable payload uninstalled size and weight estimates are based on publically available data. Installation

factors are based on unpublished data and summarized in thus far unpublished class notes10

.

Initial air vehicle mass property estimates are based on body surface areas, and weight based fractions.

Airframe weight is calculated using airframe unit weights and calculated body areas. Fuselage, nacelle and pod

weights are based on wetted areas and wings and tails are based on exposed planform areas. Airframe unit weights

can be based on nominal values by configuration types such as shown in Raymer Table 15.22. To encourage

students to think about weight from a physical perspective, they are required to make an initial weight estimate

which is used a seed value for iteration. Similarly they are required to estimate airframe weight at their design wing

loading using a parametric based on the ratio of airframe weight (Waf) to wing reference area (Sref) as shown in

Figure 5. Subsystem weight estimates are currently calculated based on simple gross weight based factors although

higher fidelity methods are currently in development. Statistically derived regression equations can also be

programmed and used to calculate unit weights and weight fractions.


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Figure 5 - RASCE Airframe Weight Parametric

Air vehicle volume. Throughout the mass property convergence process, calculations are made to ensure that

volume available meets volume required. This is done through the use of input component densities and packing

factors. Volume required is calculated at the end of each of the weight iteration and compared to volume available

from the geometry model. If volume available exceeds volume required, geometry model size is reduced. If volume

available (Vavail) is less than volume required (Vreq'd), geometry model size is increased. The geometry model is

structured such that a single geometry parameter, fuselage equivalent diameter (Dfe) controls overall vehicle volume

available. Convergence is based on linear extrapolation/interpolation of Dfe vs. Vavail/Vreq'd. Convergence is assumed

to occur within 75 pre-programmed iterations. Overall air vehicle convergence is shown when a plot of overall air

vehicle W0 converges and (Vavail/Vreq'd) = 1.00. Body volume and wing area required, however, are decoupled so

that volume and wing loading effects can converge to separate criteria. Wing volume available is included in the

calculation with priority given to fuel carriage within user defined areas of the wing.

A similar iterative calculation is done to ensure that input tail volume coefficient requirements are met. This is

done by iterating relative horizontal and vertical tail areas times their calculated relative moment arm body length

fractions to converge tail size to meet input criteria.

Included in the convergence loop is volume required to meet propulsion requirements but the computational

approach is different. Propulsion physical installation requirements are defined by a required nacelle height ratio

relative to engine diameter and installation length. Throughout the convergence process, engine weight required to

meet input thrust or power-to-weight ratio is calculated (based on input uninstalled engine power or thrust-to-engine

weight) as is engine volume required (based on input uninstalled engine density). Engine parametric geometry

inputs (length-to-diameter ratio and width to height ratio) convert the volume requirement to a required engine

height. Nacelle height required is estimated using a input requirement for engine-to-nacelle height ratio (e.g. nacelle

height might be defined as 130% of engine height). Nacelle diameter required for installation, therefore, is satisfied

by definition. Satisfaction of engine position within the nacelle, however, is a user responsibility. This is done

using a slider bar to move the engine around within the nacelle and/or by changing the relative volume allocated to

propulsion installation. This is aided visually by overlaying the engine geometry on an output graphical depiction of

the overall air vehicle as shown in Figure 4.

Although Vavail vs. Vreq'd is satisfied as a part the convergence loop, user input is currently required to resolve

associated cross sectional area disconnects. It is one thing to have enough volume available somewhere and it is

another to have the volume where it needs to be for installation and balance. To aid resolution of these issues,

RASCE outputs a plot of cross sectional area available and cross sectional area required to contain fuel, payload and

systems as a function of fuselage station. Disconnects have to be resolved (just as they do in the physical world) by

moving things around and/or by modifying the geometry (e.g. by physically changing a component parametric

geometry parameter). Automated methods for doing this are under investigation but for now, user interaction is

required for resolution.

Airframe Weight Comparisons(UA extrapolation)

0

5

10

15

0 10 20 30 40 50W0/Sref (psf)

Wa

f/S

ref

(psf)

Biz JetSE Piston PropME Piston PropReg TurboJet TransJet fightersMil TrainManned RecceUAV (est)Mil PBCHALE pred.UCA pred.BWB 6/27


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Figure 6 - User Input Currently Required to Adjust Cross Sectional Area Req'd vs. Available

Air vehicle performance. Air vehicle performance is calculated by individual mission segment which are

linked mathematically to represent the overall mission. The mission segments are categorized by performance

calculation type required as discussed below. Some mission segment types are almost trivial (but necessary) to

calculate while others are more complex and involve iteration and convergence.

Takeoff power or thrust required to meet mission performance objectives is defined by a requirement to meet a

specified ground roll distance using Raymer's Figure 5.4 Takeoff Parameter (TOP)2. All vehicles are required to

have enough power or thrust to meet takeoff ground roll requirements and/or to meet a minimum specific excess

power (Ps) requirement at every point in the mission. Engine size is defined by a user input uninstalled power or

thrust-to-air vehicle weight ratio (BHp0/W0 or T0/W0). Although the value required should be calculated by the

user, the initial estimates are often wrong and adjustments are required to ensure mission performance requirements

are satisfied as discussed under air vehicle convergence below.

One simplifying assumption used for all RASCE performance calculations is that air vehicle weight is equal to

lift. The assumption is made to simplify calculations in a spreadsheet environment and has been found to be a

reasonable approximation for conceptual level assessments of UA that fly relatively benign flight profiles.

When air vehicles using liquid fuels are assessed, fuel weight is subtracted from air vehicle weight at the end of

each mission segment. When battery powered vehicles are analyzed, energy consumed is subtracted from the

battery but weight is assumed to remain constant. Otherwise, electric and liquid fuel vehicle performance is

calculated identically.

Starting with the simplest computational approaches, the mission segment types and performance methods

employed are categorized as follows:

1. Time at a defined throttle setting (e.g. engine start, taxi, combat time and post-landing taxi). The

primary function of the calculation is to determine fuel used for a defined time period and throttle setting

(from idle to max power). For such segments, cycle deck fuel flow at the prescribed speed and altitude

(e.g. field elevation at taxi speed) are simply multiplied by fractional throttle setting and time period. Fuel

required for combat over the target can be calculated based on time at max power and defined combat

speed and altitude and/or estimated based on number of combat turns as addressed below.

2. Time at defined throttle setting and calculated speed (e.g. takeoff and combat turns). The objectives

of this type calculation are to determine fuel usage and some other performance parameter. For example,

takeoff fuel required is calculated based on input time to takeoff at maximum power at field elevation but

takeoff speed is calculated from wing loading and takeoff lift coefficient. A combat segment can be

defined by time at max power as described above or by the number of 360 degree turns over the target at

some input normal load factor and combat altitude. In the latter case, time to turn is estimated based on an

input roll rate and calculated turn rate and speed for best sustained turn rate (minimum power required for

propeller aircraft or L/Dmax for jets).

3. Breguet range or endurance segment. The well known Breguet range equation is solved for fuel

required to meet a defined distance requirement at an input speed and altitude. The Breguet endurance

© 2009 Armand J. Chaput

Design

Component FS

Locations (Lf fraction)

Ret'd payload #1 0.79Ret'd payload #2 0.00

Ret'd payload #3 0.00

Expend. payload 0.40

Fuel (exc. wing) 0.44

Sys.+Avionics 0.23

Engine(s) c.g. 0.380

Engine nacelle(s) -0.0002Fuselage(s)

Pod(s) 0.00

Wing

FSht(ac)/Lf 0.950

FSvt(ac)/Lf 0.950

Landing Gear Location

Nose gear FS/Lf 0.2

Main gear BL/(b/2)

Installed Include wing sweep in HT TVC? (Y = 1)

length

(Lf fraction) Y axis shift

0.43 0.430.00 0.00 Neng

0.00 0.00

0.00 0.00

0.24 0.24

0.15 0.15 0

0.15 0.15 2.6

0.54 0.54 2.6

Design

Component FS

Locations (Lf fraction)

Ret'd payload #1 0.79Ret'd payload #2 0.00

Ret'd payload #3 0.00

Expend. payload 0.40

Fuel (exc. wing) 0.44

Sys.+Avionics 0.23

Engine(s) c.g. 0.380

Engine nacelle(s) -0.0002Fuselage(s)

Pod(s) 0.00

Wing

FSht(ac)/Lf 0.950

FSvt(ac)/Lf 0.950

Landing Gear Location

Nose gear FS/Lf 0.2

Main gear BL/(b/2)

Installed Include wing sweep in HT TVC? (Y = 1)

length

(Lf fraction) Y axis shift

0.43 0.430.00 0.00 Neng

0.00 0.00

0.00 0.00

0.24 0.24

0.15 0.15 0

0.15 0.15 2.6

0.54 0.54 2.6

Non-wing XC Area Avail vs. Req'd

0.0

1.0

2.0

3.0

4.0

5.0

0 5 10 15 20 25 30

FS (ft)

Are

a (

sqft

)

FuselageNacellePodRet'd payloadNon-wing fuelSys+avExp'd payloadNose LGMain LG

Volume req’d axis can be shifted

up to ensure stacked areas fit


11

equation can either be solved for fuel required to meet a defined loiter requirement and altitude (e.g.

standard 45 minute IFR endurance reserves at field elevation) or to calculate available loiter time at a given

altitude and fuel state (e.g. operational endurance remaining after other mission segment fuel requirements

have been satisfied). Since the Breguet equation assumes constant lift-to-drag ratio (L/D) and engine SFC

or TSFC, simple iteration is required to compute a mission segment average. RASCE uses a single

iteration to compute a mission segment average which has been found to be a reasonable approximation for

all but very long mission segments.

4. Climb and acceleration segment. A simplified form of the standard energy method is used to

calculate time-to-climb and accelerate and associated fuel consumption and performance. Climbs are

assumed to be flown at a speed for (L/D)max for jets or minimum drag for props or at an input target climb

Mach number, whichever is less. As currently programmed, for reasons of program simplification, climbs

and accelerations are combined into a single computational segment. Using speeds and altitudes from the

previous mission segment, initial specific energy (Es) is calculated and compared to the desired specific

energy state of the following segment. The difference between the two provides an initial estimate of the

specific energy surplus or deficit that is computationally associated with the climb and acceleration

segment. If excess specific energy from the prior segment exists, the available energy excess can be

converted to an instantaneous altitude change based on a target climb speed. Specific excess power (Ps) is

calculated for that speed and altitude combination and used to make a rough estimate of time required to

achieve the final energy state. This estimate is used to make another estimate of fuel consumed and final

Ps available at the end state. Initial and final Ps are then averaged and used to make a final estimate of the

average Ps for the climb and/or acceleration segment and time to climb and/or accelerate is calculated.

Weight and Ps at the end of the segment is recalculated and is assumed to be close enough to the previous

estimate for convergence. Spot checks have shown the approximation is good enough for conceptual

design purposes, particularly when applied to the relatively benign flight profiles associated with UA.

5. Repeated mission segments. Because of their long endurance nature, UA missions can involve

repetition of combinations of mission segments. For example, multiple ingress/combat/egress segments

from a single defined loiter location (a.k.a. "orbit") are possible. Rather than run the mission repeatedly in

sequence, for computational simplicity RASCE combines all like segments together and computes

performance accordingly. For example, if a mission involves one 10 nm ingress/combat/egress cycle per

hour for 12 hours, the performance will be calculated as if there were 12 sequential ingress segments

combined (total = 120 nm) followed by 12 combat segments, followed by 12 egress sequential egress

segments. Climb and acceleration segments from loiter-to-ingress and egress-to-loiter are calculated based

on a nominal mid-mission weight condition and summed.

Air vehicle convergence. RASCE air vehicle convergence occurs in two discrete steps, physical convergence

and mission convergence. The physical convergence step is automatic and is designed to ensure that the vehicle is

physically converged. Included in the first convergence step are weight, volume and tail sizing. All three design

parameters are iterated simultaneously during the 75 internal program iterations described above. The iteration

process requires seed values for W0, Waf/Sref, BHp0 and tail area ratios (Sht/Sref and Svt/Sref). Doing hand

calculations and/or making parametric estimates for these seed values is a good exercise for students but in reality

the convergence algorithms are sufficiently robust that almost any seed value can be used and the solution will still

converge.

The output of the physical convergence step is a physics-based, conceptual-level estimate of an air vehicle sized

to meet physical requirements to include weight and volume margins. The estimate, however, may or may not meet

mission requirements since the estimate is based on a user defined value of design fuel fraction (ff = Wf/W0) and

takeoff power-to-weight (BHp0/W0) or thrust-to-weight (T0/W0) ratio and one or both could be off. For example, the

engine may too small to meet in-flight Ps requirements. And the fuel fraction may be too high and result in excess

operational loiter capability. Therefore, a second user-controlled convergence step is required to precisely size the

vehicle to meet mission requirements.

During mission convergence, two fundamental design variables are adjusted to meet three mission performance

objectives - fuel fraction (ff) and uninstalled power or thrust-to-weight (BHp0/W0 or T0/W0). The mission


12

performance objective functions are operational endurance, takeoff ground roll and minimum allowable Ps (for any

mission segment). Other design parameters to can be included but these are the minimum required.

Fuel fraction required is relatively straight forward to estimate using RASCE. Design mission ff is entered

using a slider bar and the input can be adjusted up or down until the desired operational loiter estimate is displayed.

Similarly, BHp0/W0 or T0/W0 to meet takeoff ground roll and/or minimum in-flight Ps requirements can be handled

in a similar fashion, the takeoff power or thrust-to-weight slider bar is adjusted until the requirements are satisfied.

The problem, of course, is that the input variables impact each other. When engine size is "dialed" up or down, ff

required to achieve a desired level of operational endurance changes. And BHp0/W0 or T0/W0 required to meet TOP

requirements may "oversize" the engine from a minimum in-flight Ps perspective. Although these outcomes are

intuitively obvious to an experienced designer, for students it can be a revelation and manually adjusting the

parameters does have educational value. But for serious design work, hand iteration can be time consuming.

Therefore, it is more convenient, to use a standard spreadsheet macro, Solver, to converge the solution in one step.

The methodology involves defining target values for Ps, TOP and operational endurance and specifying the variables

to be adjusted to meet the design objectives. This is a one step process and takes only a few seconds to execute as

will be shown later in Figure 7.

At the end of the second step, the air vehicle should be fully converged to meet both physical and mission

performance requirements. However, as in all good design processes, users need to carefully review results to

ensure they make engineering sense. Too often students (and unfortunately graduate engineers) take computer

program outputs as a given and don't subject them to rigorous technical scrutiny. RASCE encourages this kind of

user involvement by plotting selected solution results on parametric plots. For example, (L/D)max is plotted vs.

wetted Aspect Ratio (Awet) and compared to other air vehicles. Similar plots are presented for uninstalled engine

thrust or power-to-engine weight, airframe weight parameter (Waf/Sref) vs. wing loading (W0/Sref), max equivalent

air speed (EAS) vs. Aspect ratio (AR) and a number of other design parametrics that can help students and/or other

users judge the validity of their configurations and analysis results.

Mission capability. Overall mission models are used to determine air system capabilities to meet defined

target coverage requirements. Mission capability typically is determined by a combination of air vehicle and

payload capability. For example, for a side looking sensor equipped UA as shown in Figure 3, mission area

coverage rate is determined by the product of air vehicle speed and sensor swath width. For a given geographic area

and target revisit rate, therefore, the number of air vehicles required over the operations area at any given time can

be calculated as follows:

Air vehicles on target = [(target area)/(revisit time)]/[(air vehicle speed)(sensor swath width)]

The calculation, however, needs to also include a fudge factor to account for turns, image overlap and other

operational realities including threat avoidance. These considerations can easily add 10-30% to air vehicle range or

endurance requirements.

Assuming operational requirements are for continuous surveillance, the number of missions required can be

calculated from the number of air vehicles required in the operational area, air vehicle time on station capability and

required operational period (e.g. 24/7 coverage for 30 days). The number of missions that can be flown by a single

air vehicle is determined by total mission time from engine start to shutdown plus ground turn around and

maintenance time. The total number of air vehicles and payloads required (excluding spares) is simply the number

of missions required divided by the number of missions a single air vehicle can fly during the operational period.

Mission cost. Cost to perform a defined mission is the sum of the procurement cost of the air vehicles, the

payloads, control stations, communications and ground support equipment plus the operations and support costs

associated with these system elements. If the UAS are new, development costs must also be included. RASCE uses

simple cost estimating relationships (CERs) such as used by RAND's DAPCA process to calculate air vehicle costs

and other unpublished methods to estimate the cost of sensors, communications and other equipment5. Parametric

methods are also used to estimate the numbers operators, maintenance, support and infrastructure personnel required

and their associated costs.


13

III. Applications

Although developed for educational purposes, RASCE has been used in support of a number of conceptual

design and other studies to include developing baseline concepts and conducting technology trades for a USAF

Scientific Advisory Board (SAB) Summer Study6. Six system concepts were developed and traded in less than a

week. They were given a sanity check by the major primes and the Air Force Research Lab with no issues

identified. It has also been used for design studies in support of government and industry including the Propulsion

Directorate of the USAF Research Laboratories7 and Raytheon Missile Systems

8 as well having been used in

support of student design projects.

A recent example of RASCE application to a student project was its use for modeling and simulation of the UT

student designed Vespertilio UA. Named after the bat species resident under the Congress Street Bridge in Austin,

Vesper is a relatively large UA (40 lbm gross weight class) used to support student projects and experiments, the

most recent involving flight testing and performance analysis. In this example, Vesper was first modeled using

NASA's innovative new Vehicle Sketch Pad (VSP) parametric CAD system to generate a model of the actual

geometry. Using VSP generated geometric parameters (e.g. fineness and Aspect ratios) as inputs, a parametric

RASCE model was created and used to model the air vehicle and predict flight test performance. Even though the

VSP and RASCE geometries differ somewhat at a detail level as shown in Fig 7 below, from a weight, wetted area

and overall configuration perspective, the models correlate closely. RASCE generated performance also correlated

well with flight test data as shown.

Figure 7 - RASCE Geometry, Weight and Flight Test Correlation

0 1 2 3 4 5 6 7Butt line (ft)

Plan view

RASCE model

(output)

Vehicle Sketch Pad

(VSP) model 0 1 2 3 4 5 6 7 8 9Fuselage Station - FS (f t)

Side view

Wetted Area Comparisons

y = 1.0163x - 0.0254

0

5

10

15

20

25

30

35

40

45

50

0 10 20 30 40 50

VSP (sqft)

RA

SC

E (

sq

ft)

Wetted area - allWing only

Weight Comparisons

y = 0.999x - 0.012

0

5

10

15

20

25

30

35

40

0 10 20 30 40

Vesper Actuals

RA

SC

E (

sq

ft)

Power Curve Comparfison (Flights 2,3, and 6)

0

20

40

60

80

100

120

140

0.0 0.5 1.0 1.5 2.0 2.5

Power (BHP)

Av

era

ge

Tru

e A

irsp

ee

d (

ft/

sec)

Fl ight Test 2,3,6

RASCE

Vesper Rate of Climb as a Function of Power Setting

(up wind and down wind averages)

0

200

400

600

800

1000

1200

1400

20 30 40 50 60 70

Average True Airspeed (ft/sec)

Cli

mb

Ra

te (

ft/

min

)

Fl ight test 2,3,6

RASCE


14

Other application examples include design studies to evaluate the effects of requirements on vehicle size and

cost. For example, a quick study was done to demonstrate the effects of endurance requirements on vehicle size. A

nominal Predator type configuration (conventional wing-body-tail, pusher prop) was sized to identical requirements

except for operational endurance. The trade study was performed in a few minutes using Solver to converge the

solutions. To ensure the vehicle met requirements at the smallest size, minimum empty weight was defined as an

objective function. Fuel fraction (ff) and takeoff power-to-weight (BHp0/W0) ratio were defined as trade study

variables. Solution constraints included operational endurance, takeoff ground roll and minimum allowable in-flight

Ps. As shown in Figure 8, vehicle size vs. endurance was reasonably linear up to about 60 hours time on station.

Above 60 hours vehicle size required went non-linear. Interestingly, divergence was not driven by fuel volume

required to meet the endurance requirement but by tail area required to meet tail volume criteria. Conventional wing

body tail configurations with aft mounted internal combustion engines work reasonably well when the required

BHp0/W0 is relatively low which typically translates into a low wing loading for IC powered aircraft. As vehicle

size required increases in response to increased demands for operational endurance, wing area increases but at a

faster rate than the required fuselage size required to meet volume requirements. This in turn drives the tail vs. wing

area ratio to increase and the configuration starts to diverge. These types of trends are well known to experienced

designers but for students and less experienced designers, the physical the interactions can be difficult to

comprehend. With a parametric model based design system like RASCE, however, the interactions and drivers are

evident and learning is enhanced. When these types of trends are understood by students they intuitively start to

understand, for example, why a turbo-prop with a higher SFC can achieve longer endurance than an internal

combustion (IC) engine powered concept with a lower SFC.

Figure 8 - System Requirement Impact - Predator A Type Concept

A similar but more complex application would be to compare a range of configuration types against the same

requirements; i.e. to demonstrate to students why certain configuration concepts out perform on one application and

under-perform on others. Again, the rationale may be intuitively obvious for experienced designers, but for others

(including non-technical program management and customers) it may not. Figure 9 shows three typical small UA

concepts with aft mounted IC engines, a conventional wing-body-tail, a nacelle-boom- tail and a blended wing body,

that were evaluated for concept demonstration purposes. The design variable of interest for demonstration purposes

is minimum in-flight Ps required. Not shown in the Figure are three other concepts, a conventional wing-body-tail

with a forward mounted engine (i.e. tractor installation), a canard-wing body with an aft mounted engine and a very

high aspect ratio blended wing body.

© 2009 Armand J. Chaput

Solution approach – Same as previous

example except wing loading constant

and operational loiter input varied

a. Run multiple loiter solutions

a. Copy results into worksheet

b. Plot results

c. Copy and paste selected graphics

Solution approach – Same as previous

example except wing loading constant

and operational loiter input varied

a. Run multiple loiter solutions

a. Copy results into worksheet

b. Plot results

c. Copy and paste selected graphics

Constraints- Op loiter (B96) = 6 ⇒⇒⇒⇒ 120 hours

- BHp0/W0 ≥≥≥≥ BHp0/W0 to meet TOP (B97)- B99 (Minimum in flight Ps) ≥≥≥≥ 5 fps

Variables- Wf/W0 (B95)

- BHp0/W0 (B96)

Objective – minimize empty weight

Constraints- Op loiter (B96) = 6 ⇒⇒⇒⇒ 120 hours

- BHp0/W0 ≥≥≥≥ BHp0/W0 to meet TOP (B97)- B99 (Minimum in flight Ps) ≥≥≥≥ 5 fps

Variables- Wf/W0 (B95)

- BHp0/W0 (B96)

Objective – minimize empty weight

Operational Loiter Sensitivity

0

10000

20000

30000

40000

50000

0 30 60 90 120 150

Operational loiter (hrs)

Weig

ht

(lb

m)

W0WePoly. (We)

be a

dju

ste

d a

ccord

ingly

Sizing for Operational Loiter- Nominal Predator type)


0

10000

20000

30000

40000

50000

0 30 60 90 120 150


Weig

ht

(lb

m)

W0WePoly. (We)

be a

dju

ste

d a

ccord

ingly


0

10000

20000

30000

40000

50000

0 30 60 90 120 150


Weig

ht

(lb

m)

W0WePoly. (We)

be a

dju

ste

d a

ccord

ingly

be a

dju

ste

d a

ccord

ingly

be a

dju

ste

d a

ccord

ingly

Sizing for Operational Loiter- Nominal Predator type)

Note physical changes as geometry

model adjusts to meet requirements

Note physical changes as geometry

model adjusts to meet requirements


15

Figure 9 - Candidate Trade Study Configuration Concepts

For the purposes of illustration, the figure of merit used for the demonstration is vehicle empty weight. The

concepts are referred to using the following nomenclature:

Pusher WBT - Notional Wing Body Tail (WBT) with pusher (aft) engine installation

Pusher NBT - Notional Nacelle Boom Tail (NBT) with pusher engine installation

Pusher CWB - Notional Canard-Wing-Body (CWB) with pusher engine installation

Pusher BWB - Notional Blended Wing-Body (BWB) with pusher engine installation

Tractor WBT - Notional WBT type with tractor (forward) engine installation

High AR BWB - High Aspect Ratio (AR) BWB with pusher engine installation

In this simple example, nominal Predator A type requirements were assumed. Takeoff requirements are

relatively benign, operational endurance is 24 hours at 400 nm and the sensor payload is 450 lbm. For the baseline

vehicles, the engine is sized by takeoff and fallout in-flight Ps is in the range of 5-10 ft/sec. For the purposes of the

study, the baseline concepts were assumed to have moderately high AR ≈ 20 wing planforms, except for the BWB

which had AR = 10. An excursion was done to look at the benefit of a AR = 20 BWB which is not only high but

perhaps unachievable. RASCE, however, does not know that the concept is a control challenge and projected the

lowest empty weight of the five for the AR = 20 BWB at about 850 lbm as shown in Figure 10. The next lightest

was the AR = 10 BWB at a little over 1000 lbm followed by the tractor WBT at around 1100 lbm and the NBT at

1200 lbm. The pusher WBT came in fifth at 1250 lbm while the CWB finished last at a little over 1300 lbm. When

the in-flight Ps requirement was increased, engine size required also increased. As shown the figure, the weight

ranking generally held except for the pusher CWB and AR = 10 BWB which increased in weight faster than the

other concepts. At an in-flight Ps requirement of 30 ft/sec, the AR = 20 BWB empty weight approached1500 lbm

while the tractor CWB and pusher NBT grew to about 2000 lbm. The AR = 10 BWB came in fourth at 2300 lbm

and the CWB came in fifth. At this level of Ps required, the pusher WBT essentially became non-viable. The

bottom line of the study was that if a very high AR BWB really can be developed, it will have significant advantage

for a Predator A type mission….as will be discussed in my next research grant proposal!

Wing-body-tail Boom tail Blended wing body


16

Empty Weight vs. Specific Excess Power

500

1000

1500

2000

2500

3000

3500

5 10 15 20 25 30

Minimum In Flight Ps (fps)

We

igh

t (l

bm

)

Tractor WBTPusher WBTPusher NBTPusher CWBPusher BWBHigh AR BWB

Figure 10 - Effects of Ps Requirements on Candidate Configuration Concepts

IV. Conclusions

Physics-based, parametric modeling and simulation has significant advantages when applied to rapid conceptual

air system concept evaluation. Fundamentally, it allows conceptual system designers to integrate two steps of

traditional concept development into a one. Specifically, the traditional first step of parametric sizing is combined

with the initial concept development and analysis phase and executed without having to physically generate baseline

concept drawings. RASCE allows system concept designers to explore a wide range of concepts and generate

quantitative design metrics that can be used to support configuration selection. RASCE has also been applied to a

number of system level studies for both government and industry. It runs quickly and in real time on a standard

laptop and does not require laborious input data preparation and/or calculations. It provide physics-based feedback

on operational requirement effects, design and technology options and supports in-depth, conceptual level trade

studies, all in real time. RASCE is a mature design and analysis system, having been used on 100s of UAS concept

design projects since its introduction in 2003.

References 1 Nicolai, L., Carichner, G, Fundamentals of Aircraft and Airship Design, Volume 1, AIAA Education Series, 2010 2 Raymer, D, Aircraft Design - A Conceptual Approach, 4th Edition, AIAA Education Series, 2009 3 Roskam, J, Airplane Design, Parts I - VIII, DAR Corporation, 1990-2003 4 Chaput, A., “Physics Based Parametric Modeling and Simulation Applications to Unmanned Air Systems“, International

Conference on Autonomous Unmanned Vehicles, Bangalore, India, 2009 5 Boren,H,, "Development and Production Costs for Aircraft (DAPCA)", Memorandum RM-5221-PR, RAND Corporation, 1967 6 Johnson et al, Aerial Vehicles in Perspective: Effects, Capabilities, and Technologies”, US Air Force Scientific Advisory Board,

SAB-TR-03-01, 2003 7 Chaput, A. "Physics Based Parametric Modeling and Simulation (M&S) Support of Small Unmanned Air System (SUAS) Engine

Concept Exploration ", University of Texas at Austin, Air System Laboratory Unfunded Study, Presented to USAF Propulsion

Directorate, 2008 8 Chaput, Dziuk, Escamilla, Gilbreath, Stewart, "Extended Range Blended Wing Body Design and Technology Trades", University

of Texas at Austin, Air System Laboratory Final Report, PO 4200135961, Proprietary - Raytheon Missile Systems, 2009 9 J. Johnson, "Analysis of Image Forming Systems," Proc. Image Intensifier Symposium, US Army Engineer Research and

Development Laboratories, Fort Belvoir, Va., 1958. 10 Chaput, A. "Conceptual Design of Unmanned Air System", Chapter 11 - Sensors, University of Texas at Austin, 2010 11 W. Fredericks, K. Antcliff, G. Costa, G , N. Deshpande, M. Moore, E. San Miguel, A. Snyder, "Aircraft Conceptual Design

Using Vehicle Sketch Pad", AIAA 2010-657, 48th AIAA Aerospace Sciences Meeting, Orlando, 2010 12 Chaput, A. "Conceptual Design of Unmanned Air System", Chapter 18 - Propulsion, University of Texas at Austin, 2010

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