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NSDL MatDL: Supporting Transformational Materials E-research & E-education
Laura M. Bartolo, Cathy S. Lowe Materials Informatics Lab, Kent State University
036 Science Research Building, Kent, OH USA 44242-0001 ABSTRACT The NSF supported National Science Digital Library Materials Digital Library Pathway has implemented an information infrastructure to disseminate government funded research results and to provide content as well as services to support the integration of research and education in materials. This paper describes how we are integrating a digital repository into open-source collaborative tools, such as wikis and collaborative source code control systems, to support users in materials research and education as well as interactions between the two areas. Keywords: Materials Science, digital libraries, wiki, collaborative program source code management Contact: [email protected]
NSDL MatDL: Supporting Transformational
Materials E-research & E-education
Laura M. Bartolo & Cathy S. Lowe
Materials Informatics Lab ,
Kent State University
International Symposium of Materials Database, MITS 2007Friday March 16, 2007
National Institute for Materials Science, Sengen Site (Tsukuba science city)
2007 MITS Meeting
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OutlineCyberinfrastructure for e-Science
Transformational Research & Education
NSF NSDL MatDL Pathway
Background
Collaborative tools for MS community
Soft Matter Wiki
MatForge
2007 MITS Meeting
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Vision of Cyberinfrastructure (CI)
Blue Ribbon Advisory Panel, Revolutionizing
Science & Engineering Through Cyberinfrastructure
http://www.nsf.gov/od/oci/reports/toc.jsp
“The vision …”
ubiquitous, comprehensive digital environments
interactive and functionally complete in terms of people,
data, information, tools, and instruments
unprecedented levels of computational, storage, and data
transfer capacity
2007 MITS Meeting
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Support for Transformational Research & Education
Virtual research and
education communities
complementary needs and
expertise
Trusted information
reuse across research and
education
Structured Data
domain & cross domain
metadata, markup
languages and vocabulary(Tim Berners-Lee, Scientific American, May 2001)
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Deliverables & Benefits
Individuals, teams, & organizations:
revolutionize what they do, how they do it, & who
participates
over time, geographic, organizational, & disciplinary
distance
access to more, better information & facilities for
discovery and learning (Blue Ribbon Panel, 2003)
2007 MITS Meeting
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DLI 2 - NSF, et al., initiated in FY98, continuing
in UG Education FY 98-99
DLI 2 Special Emphasis
DLs & UG Earth Systems Educationinitiated FY99, continuing
Digital Libraries Initiative (DLI 1) - NSF/NASA/ARPA, FY 94-97
NSDL Launch
Fall 2002
NSF, Cyberinfrastructure & Digital LibrariesNSF, Cyberinfrastructure & Digital Libraries
NSF NSDL Program
2000
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What is NSDL?An NSF-funded $20 million/year program in Science,
Technology, Engineering and Mathematics (STEM)
education
A digital library describing nearly two million carefully
selected online STEM resources (at http://nsdl.org)
A core integration team (Columbia, Cornell, UCAR)
working with 10 pathways and services projects
A community of endusers: experts and novices
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NSF NSDL Materials Digital Library Pathway
Domain - Materials Science
Study of materials structure & processing-property relations to
improve products
Audience – MS research & education community
Undergraduate and above
Goals
Implement an information infrastructure
Disseminate information generated by government-funded
efforts in materials
Provide content and services to support the integration of
research and education in materials
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NSF NSDL MatDL Pathway
Supporting…
Virtual Labs•Intro to Solid State Chemistry
Collaborative Code
Development•MatForge
-FiPy
Teaching Resource
Development•MS Teaching Archive
NSF MS Initiatives•Nanoscale Interdisciplinary Research Teams
•Materials Research Science & Engineering Centers
•International Materials Institutes
-Soft Matter Wiki
IOWA STATE UNIVERSITY
2007 MITS Meeting
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Two examples of Collaborative MS Tools
Soft Matter Wiki
Authoritative information of expert community
MatForge
computational methods enabling new/improved
predictions of materials behavior
2007 MITS Meeting
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Soft Matter
What is it?
Organic materials -- polymers, biomolecules,
liquid crystals, surfactants, and proteins
Multidisciplinary & evolving
Why is it important?
Next generation molecular electronic, photonic,
drug delivery, and sensing materials and
instruments
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MatDL Soft Matter Wiki:
Development & Objectives
Vocabulary on assembly
of nanosystems
Expert community-driven
Wiki-based bottom-up
approach
Gather vocabulary,
definitions, & relationships
Collaborate with domain
experts
Low barrier threshold for
contributions/working
together
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What is Soft Matter Wiki?
Website for use by the Soft Matter Community
MediaWiki Installation
Collaborative information exchange
Expert community authored
Low-barrier
Multiple purposes
Access: Authoritative scientific information
Reference: graduate education
Introduction: undergraduate research experience
2007 MITS Meeting
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Metadata Capture<dc:title>Brownian Dynamics simulation of a nanoparticle
aggregating tethered nanosphere</dc:title>
<dc:creator>Chris Iacovella</dc:creator>
<dc:subject>Tethered Building Block</dc:subject>
<dc:subject>Lennard-Jones</dc:subject>
<dc:subject>Brownian Dynamics</dc:subject>
<dc:subject>NVT</dc:subject>
<dc:subject>FENE</dc:subject>
<dc:description>
Number of tethered building blocks = 800;
Number of beads = 7200;
Length of tether = 8;
Diameter of the nanopshere = 2.0;
System temperature = 0.2667;
System volume fraction = 0.25;
Integration scheme to use = Brownian Dynamics, NVT;
Number of Dimensions = 3;
United Atom Bead Spring with Lennard-Jones and FENE;
Phase: Hexagonally packed cylindrical micelles</dc:description>
<dc:publisher>Glotzer group. Depts of Chemical Engineering, Materials Science &
Engineering, Macromolecular Science, and Physics,University of
Michigan</dc:publisher>
<dc:date>2006-9-19</dc:date>
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MatDL Soft Matter Wiki: Results
Public view – launched September 2006
Number & range of terms
Currently 71 terms under 12 different categories
Approximately 70% of the terms have definitions
Format of entries
Vary from very brief to considerable detail
Adding context
Images, references
Related items in (e.g., preprints, images)
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Interaction Potentials:
The Lennard-Jones Potential
Weeks-Chandler-Andersen Potential
Hard Sphere Potential
Dzugutov Potential
Yukawa Potential
Harmonic Spring
FENE Spring
Simulation Methods:
Brownian Dynamics Simulation (BD)
…
System Classifications:
Polymer
Block Copolymer
Liquid Crystal
Surfactant
Colloid
Tethered Building Block
2007 MITS Meeting
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C.R. Iacovella, A.S. Keys, M.A. Horsch, S.C. Glotzer Icosahedral
packing of polymer-tethered nanospheres and stabilization of the
gyroid phase Submitted, (2006)
Record on MATDL Repository
2007 MITS Meeting
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Attached Files
Name Description MIMEType
n2006TNSGyroid.pdf n2006TNSGyroid.pdf application/pdf
Related Links
Link Description
http://testmatdl.lci.kent.edu/fez/view.php?pid=matdl:152 hexagonally packed cylinders
http://testmatdl.lci.kent.edu/fez/view.php?pid=matdl:153 double gyroid
http://testmatdl.lci.kent.edu/fez/view.php?pid=matdl:155 perforated lamellae
http://testmatdl.lci.kent.edu/fez/view.php?pid=matdl:154 lamellar bilayers
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What is MatForge? SourceForge for MS
Workspace for collaborative code development
Subversion software repository with Trac web
interface
Manage changes to program source code
Enable teams to work on the same files in a
distributed environment
Keep track of who has done what and when
2007 MITS Meeting
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SubversionSource code version control system
Remembers every change to files and directories
Allows multiple people to access, manage, and
modify same data across networks
Improves on CVS (e.g., versioning directories)
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TracWiki engine plus project management
Web-based interface to a Subversion source
code repository
Basic scheduling features
Job/bug ticketing system
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Projects hosted on MatForge
FiPy - an extensible object oriented, partial differential
equation (PDE) solver: MSEL/NIST
Lab for Computational Nanoscience and Soft Matter Simulation: University of Michigan
Rollett Research Group: Carnegie Mellon University
Powell Research Group: Veryst Engineering
ChemPhys 74495 Computational Materials Science:Chemical Physics Program and Liquid Crystal
Institute, Kent State University
2007 MITS Meeting
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NIST & Collaborative Code Development
Focus:
Computational modeling of materials
Issues:
Extensive security inhibits external
collaborations
Branded, trusted, & neutral site for open
source MS code
New approaches:
train student to use its tools
promote development of its tools
develop a pool of next generation users in
academe, industry
Using FiPy to model superconformal
electrodeposition (superfill) in
semiconductors.
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Summary
Beginning with soft matter simulation
Expand to: electronic materials, glasses, polymer
thin films
Make public domain software widely available
Support connections between MatDL
resources like Soft Matter Wiki and MatForge
2007 MITS Meeting
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Thank you & questions?
The NSDL Materials Digital Library Pathway is supported by the National
Science Foundation DUE-0532831. Any opinions, findings, and conclusions
or recommendations expressed in this material are those of the authors and
do not necessarily reflect the views of NSF.
MatDL http://matdl.org
Soft Matter Wiki http://matdl.org/matdlwiki
MatForge http://matforge.org
Databases of Baikov Institute on properties of inorganic materials and substances
Nadezhda N.Kiselyova
A.A.Baikov Institute of Metallurgy and Materials Science of Russian Academy of Sciences
P.O.Box: 119991 GSP-1, 49, Leninskii Prospect, Moscow, Russia
ABSTRACT
The principles of organization of the databases (DBs) on properties of inorganic substances and materials of A.A.Baikov Institute of Metallurgy and Materials Science (IMET): the DB on the properties of inorganic compounds “Phases”, the DB on phase diagrams of systems with semiconducting phases “Diagram”, the DB on properties of acousto-optical, electro-optical and nonlinear-optical substances “Crystal”, the DB on band gaps of inorganic compounds “Bandgap” and the DB on properties of chemical elements “Elements” are considered. The peculiarities of these DBs are: Internet-access to the information, supplement of DBs by means of the analysis of the information based on artificial intelligence methods, the use of different DBMS and operational systems, the use of servers of different types, and integration of DBs.
Three approaches to DB integration: Data Warehouse with ETL (Extract, Transform, Load)-technology, EII (Enterprise Information Integration)-technology and EAI (Enterprise Application Integration)-technology are discussed. The limitations of these approaches in the solution of problem of integration of DBs on properties of inorganic substances and materials are noted. The combined way that applies both EII and EAI technologies is proposed. This approach is based on an application of metabase. It is a special database that stores metadata on contents of integrated DBs, namely, about chemical systems and substances, which are identified, firstly, by set of chemical elements – components of systems, and by their content, and, secondly, by data on crystal structure of phases. Metabase contains also information about properties stored in different DBs, and other data. This information has enough to make search for relevant systems, data about properties and substances. The possibilities of expansion of integrated system of DBs on properties of inorganic substances and materials are discussed.
The integrated system of DBs is assessed for registered users: www.imet-db.ru.
Keywords: database on properties of inorganic substances and materials, DB integration, Internet, metabase, Enterprise Application Integration, Enterprise Information Integration.
Contact: e-mail address of the author [email protected]
1
Databases of Baikov Institute on Properties of Inorganic Materials and Substances
Nadezhda N.Kiselyova
A.A.Baikov Institute of Metallurgy and Materials Science
of Russian Academy of Sciences,
Laboratory of Semiconducting Materials
International Symposium of Materials Database, MITS 2007Friday March 16, 2007
National Institute for Materials Science, Sengen Site (Tsukuba science city)
2
Databases of Baikov Institute on Properties of Inorganic Materials and
Substances• 1. Tendencies of development of modern DBs on properties of inorganic
substances and materials.
• 2. Principles of construction of DBs on inorganic compounds’ and
substances’ properties developed by Baikov Institute.
• 3. DB on the properties of inorganic compounds “PHASES”.
• 4. DB of phase diagrams of systems with intermediate semiconducting
phases "DIAGRAM".
• 5. DB on width of the forbidden zone of semiconductors “BANDGAP”.
• 6. DB of substances with significant acousto-, electro- and nonlinear-optical
properties "CRYSTAL".
• 7. DB on the properties of chemical elements “ELEMENTS”.
• 8. Integration of DBs.
3
0
5
10
15
20
25
30thermodynamic andthermochemicalproperties
physical (electrical,magnetic, optical, etc)properties
crystallographic andcrystal chemicalpropertiesengineeringproperties
chemical andphysical-chemicalproperties
Number of DBs
Distribution of Databases on Properties of Inorganic Substances
and Materials over Subject Scope
4
Tendencies of Development of Modern DBs on Properties of Inorganic
Substances and Materials
1. Internet-access to the information.
2. The use of powerful DBMS: Oracle, MS SQL
Server, Sybase, etc.
3. The most attention has been concentrated on
the quality of the stored information.
4. Supplement of DBs by means of the analysis
of the information.
5. Integration of DBs on substances and
materials.
5
Principles of Design of the Distributed System of DBs on Properties of Substances
and Materials of Baikov Institute
DBs containing information
about the most widespread
properties of compounds DB5
DB6
DB7
DB1 DB2 DB4DB3 MDB1
Information systems containing detailed data
about substances promising for practical
applications
6
Structure of DBs on Compounds’and Materials’ Properties
E1 El2 … Elm Compo-
sition
Crystal
structure
Property Reference
Number
Number Reference
El1 El2 … Elm Compo-
sition
Crystal
structure
Property Reference
Number
7www.phases.imet-db.ru
DB volume is more than 4.5 GB
DB on the Properties of Inorganic Compounds “Phases”
8
Structure of DB “Phases”
System (Atomic Numbers of Chemical Elements)
Number of the Compounds
Designations of Known Quasibi-nary Sections
Temperature of the Studied Iso-
thermic Sec-tions
ReferenceNumbers
Compounds
Type of Melt-ing and Melt-ing Point at
1 atm
Decomposition Temperature in the Solid or/and Gaseous State
at 1 atm Homogeneity Range of the Compound
Experts Notes
Types of the Crystal Structures
Temperature and Pres-sure to be Exceeded to Insure the Formation of
the Particular Crystal Modification
Crystal System
Space Group
Z (Number of Formula Units
in Unit Cell)
Experts Notes
Boiling Point at 1 atm
9
Structure of DB with Internet-remote
minimal requirements imposed on hardware-
software of the remote DB-users;
opportunity of the separate control of DBMS
and Web-server;
simplicity of program realization;
use of modern technologies on a basis of ASP
and ISAPI.
WEB-SERVERUSERS DB-SERVER
10
Software-Hardware Realization of Servers of DB “Phases”
Web-server DB-server
MS Internet Information Server 5.0
DBMSMicrosoft SQL
Server 2000
S Windows 2003 Server
S Windows 2003 Server
Server Pentium 4 Dual Xeon
Server Pentium 4 Dual Xeon
11
Software-Hardware Realization of Servers of DB “Diagram”
Web-server DB-server
MS Internet Information Server 5.0
DBMSOracle-8
S Windows 2003 Server
S Solaris 9
Server Pentium 4 Dual Xeon
Server SunFire 240
12
Example of Results of the Search in DB “Phases”
13
Example of Results of the Search in DB “Phases”
14
www.diag.imet-db.ru
DB volume is
more than
200 MB
DB on Phase Diagrams of Semiconducting
Systems “Diagram”
15
Conceptual Structure of Subsystem onBinary Semiconducting Systems
Information on Binary
Systems
T-x, P-T, P-x Projections. Experimental and Optimized
Data
Solid Solution Range of Doped Impurity in
Semiconducting Phase. Experimental and Optimized Data
Homogeneity Range of the Semiconducting
Phases. Experimental and Optimized Data
Coefficients of Equation
lgP = -A/T + B for Compounds
Co-ordinates of Invariant and Particular
Points
Diagrams of T-x, P-T, P-x Projections
Quality Level of System Elements Data
References
Subsystem
on
References
Analytical Review
Crystal Structures of Phases
Thermodynamic Properties.Models for Calculations
16
Conceptual Structure of Subsystem onTernary Semiconducting Systems
Crystal Structures of Phases
Subsystem on
References
Diagrams of Projections of Liquidus (Solidus, Solvus)
Surfaces, P-T-x, P-T-y, P-x-y Projections, Quasibinary,
Isothermal and PolythermalSections
Information on
Ternary Systems
Analytical Review
Projections of Liquidus(Solidus, Solvus)
Surfaces (Experimental and Optimized Data)
Isothermal and PolythermalSections (Experimental and
Optimized Data)
Quasibinary Sections (Experimental and Optimized Data)Co-ordinates of
Invariant and Particular Points
Reaction Scheme
Quality Level of System Elements Data References
Information on BinarySystems
Subsystem on
Binary
SystemsThermodynamic Properties.Models for Calculations
17
Conceptual Structure of References Subsystem
Reference Number
Authors: Surname and
Initials
Title of Journal (Collection of
Papers)
Year of Publication
Number
References
Volume
Initial and Last Page Numbers
Title of Paper/Book
Organization Where Work Was
Accomplished
Country Keywords
Full Text of Paper/Book
18
Example of Results of the Search for Full Texts of Papers in DB “Diagram”
19
Example of Results of the Search in DB “Diagram”
20
Example of Results of the Search for Graphical Information in DB “Diagram”
21
www.bg.imet-db.ru
DB volume is 60 MB
DB on Band Gaps of Inorganic
Compounds “Bandgap”
22
Conceptual Structure of DB on Bandgaps
Band Gap
Crystal Modification
Space groupTemperature References
Crystal System
Direction
Structure type
Experts Notes
Subsystem on References
Composition
23
Example of Results of the Search in DB “Bandgap”
24
DB volume
is more
than 500
MB
DB on Properties of Acousto-Optical, Electro-Optical and Nonlinear-Optical Substances
“Crystal”
www.crystal.imet-db.ru
25
Conceptual Structure of DB on
Crystals with Acousto, Electro- and Nonlinear Optical Properties “Crystal”
Substance
Analytical Review
Solubility
Type of Melting and Melting Point
Curie Point
Density
Hardness
Elastic Wave Velocity and Attenuation
Thermal Expansionand Conductivity,
Heat Capacity
Crystal System, Space and Point Group, Z, Lattice Parameters
Refractive Indices, Transparency Band,
SellmeierCoefficients
PiezoelectricConstants
Dielectric Constantsand Losses
ElasticCoefficients
Elasto-Optical Coefficients
Acousto-OpticalCoefficients
Electro-OpticalCoefficients
Nonlinear OpticalProperties
References
26
Example of Results of the Search in DB “Crystal”
27
DB on Properties of Chemical Elements
“Elements”
www.phases.imet-db.ru/elements
DB volume is more than 4 MB
28
Modern Approaches to DBs Integration
EII
EAI
ETLBatch
mode
Real time
processdata
29
Full Merging of DBs - ETLData MegabaseExtract
Transform
Load
30
Full Merging of DBs -Megabase
Advantages:
Database exploitation costs reduction.
Information duplication reduction.
Shortcomings:
High complexity of development of single
information system.
Change of the procedures and techniques
of work with existing DBs.
31
Integrated System
EII – Enterprise Information Integration
Directory of DBs being integrated - metabase
Directory of DBs
DB1
DB2
DBn
…
Mediator
32
Message Bus
EAI – Enterprise Application Intergration
…
DB1
DB2
DBn
33
EII & EAI
Advantages:
Reduction of expenses for creation of integrated
system.
Preservation of an infrastructure of DBs which are
integrated.
Independence in evolution of subsystems.
Opportunity of expansion of the integrated system.
Access to “live” data.
Shortcomings:
Complexity of integration of heterogeneous DBs.
34
Hierarchy of Chemical Concepts
Chemical System
Solution Chemical Compound Heterogeneous Mixture
Crystal Modification Crystal Modification
35
Structure of Metabase (EAI)
Users and their
permissions
Relevance
classes and
its
description
Integrated resources
contents description
36
Structure of Integrated DBs System of Baikov Institute
Metabase - special database storing
data on contents of integrated DBs
DB “Diagram” DB “Crystal”
DB “Phases”
DB “Elements”
Mediator
DB “Bandgap”
www. imet-db.ru
37
Results of a Search for Relevant Information in Integrated System of
DBs on Materials for Electronics
http://www.imet-db.ru
38
DBs ofIMET of
RAS
DBs of Institutes of Russian Academy of
Sciences
DBs of Russian Universities
Foreign DBs
Future
39
Features of DBs of Baikov Institute
1. The information of DBs on materials for electron-ics is captured and estimated from the point of view ofreliability by the experts in subject domains. I.e., theuser receives not only "row" information but also rec-ommended values.
2. Internet-remote to DBs. 3. DBs are integrated and there is an opportunity of
the further expansion of the distributed heterogeneous information system. It allows to give to user the maxi-mal complete information about certain substance.
4. DBs are supplied with the subsystems for the data analysis and the search for regularities in the in-formation based on the various programs of artificialintelligence.
DEVELOPMENT OF ONLINE STRUCTURAL MATERIALS HANDBOOK FOR GEN IV NUCLEAR REACTOR SYSTEMS
Weiju Ren
Oak Ridge National Laboratory
No. 1 Bethel Valley Rd. MS-6155, Bldg. 4500-S Oak Ridge, TN 37831
United States
ABSTRACT
The development of an interactive and web-accessible structural materials database dubbed “Gen IV Materials Handbook” at the Oak Ridge National Laboratory is described. The Handbook is developed for materials selection, component design, and information management for Gen IV nuclear reactor and related programs, with potentials for international data sharing and collaboration.
A brief introduction of Oak Ridge National Laboratory and Gen IV Program is followed by a presentation of U. S. efforts in developing nuclear structural materials databases. Three aspects in the Handbook development – database content, database container, and database development support, are discussed in details. Database development strategies and access controls are also discussed with a brief on-line demonstration of the Handbook data management structure.
Keywords: structural, materials, database, nuclear, Gen IV
Contact: [email protected]
Weiju Ren
Oak Ridge National LaboratoryUnited States
International Symposium of Materials Database, MITS 2007National Institute for Materials Science
Sengen Site, Tsukuba Science CityMarch 16, 2007
DEVELOPMENT OF ONLINE STRUCTURAL MATERIALS DEVELOPMENT OF ONLINE STRUCTURAL MATERIALS
HANDBOOK FOR GEN IV NUCLEAR REACTOR SYSTEMSHANDBOOK FOR GEN IV NUCLEAR REACTOR SYSTEMS
1
2
Oak Ridge National Lab (ORNL) is the home of the Oak Ridge National Lab (ORNL) is the home of the worldworld’’s first continuously operated nuclear reactor.s first continuously operated nuclear reactor.
The Graphite ReactorThe Graphite Reactor
3
Today, ORNL is the largest multipurpose science Today, ORNL is the largest multipurpose science
laboratory of the U.S. Department of Energy.laboratory of the U.S. Department of Energy.
• U.S. largest concentration of open source materials research
• US largest energy R&D laboratory
• $900 million budget; 90% from Department of Energy
• 16 research divisions, 4000 staff
• 3000 guest scientists and engineers annually
4
DOE is leading the U. S. participation in the Gen IV DOE is leading the U. S. participation in the Gen IV
initiative to develop advanced commercial reactors.initiative to develop advanced commercial reactors.
• Currently eight international partners focusing on six different advanced reactor concepts
• Gas, liquid-metal, molten salt, and supercritical water coolants
• Gen IV reactors will be efficient, economical, safe, sustainable, and proliferation resistant.
5
6
• Nuclear structural materials testing and qualification
• Development of improved high temperature design methodology
• Environmental testing and thermal aging of high temperature metals
• Support of ASME code and ASTM standards
• Reactor pressure vessel materials irradiation
• Nuclear applications of composites, graphites, and ceramics
• Development of Gen IV Materials Handbook
ORNL plays a crucial role in the U. S. Gen IV ORNL plays a crucial role in the U. S. Gen IV
Nuclear Reactor Materials Program.Nuclear Reactor Materials Program.
7
• Development of the Gen IV Nuclear Reactor Systems require many material types and various activities.
–Metals, ceramics, graphites, composites
–Material selection, component design, stress analysis
• A high-quality materials database is highly desired for the success of the program.
–Authoritative single data source
– Internally consistent, validated, and highly qualified data
–Complement ASME and ASTM codes and standards
• A platform for sharing data among participants under the umbrella of Gen IV International Forum (GIF)
Gen IV Materials HandbookGen IV Materials Handbook is a specifically is a specifically
developed structural materials database.developed structural materials database.
8
Nuclear System Materials Handbook (NSMH) proved Nuclear System Materials Handbook (NSMH) proved
a success for previous U.S. DOE reactor programs.a success for previous U.S. DOE reactor programs.
9
• Developed from the mid 1970’s to late 1980’s led by ORNL.
• Covered liquid and metal breeder, gas-cooled, and fusion reactors.
• Overlapping requirements and data needs of various participants were met by a single source.
• Various R&D reports and documents were substantially reduced to a single reference.
• Deficiencies in materials data were readily identified and corrected.
Gen IV Materials HandbookGen IV Materials Handbook is a highis a high--tech, new tech, new
generation Nuclear System Materials Handbook.generation Nuclear System Materials Handbook.
10
• Covers all the candidate structural materials for Gen IV reactors.
• Provides powerful data managing tools and a durable data storage.
• Shares data in agreement with international participants.
• Facilitates identifying data gaps, needs, and requirements.
• Assists in developing constitutive equations and design rules.
• July 2004: The First Gen IV Materials Handbook Workshop was held in La Jolla, California.
• October 2004: Collection and evaluation of existing data for Handbook population were initiated.
• March 2005: “Gen IV Materials Handbook Implementation Plan”
was completed.
• April 2005: Search was initiated for software developers as well as customizable software products to support the Handbook.
• May 2005: “Gen IV Nuclear Reactor Materials Handbook
Product Requirements Template” was developed.
• June 2005: “Assessment of Existing Alloy 617 Data for Gen IV
Materials Handbook” was completed.
HandbookHandbook development history review (1)development history review (1)
11
• August 2005: Decision was reached that using Granta MI System software as the base software for Handbook development can satisfy Gen IV needs, as well as significantly save time and cost.
• September 2005: “Initial Development of the Gen IV Materials
Handbook” was completed.
• October 2005: “Gen IV Materials Handbook Advisory Committee Charter” was developed.
• October 2005: Handbook task joined the Materials Data Management Consortium (MDMC).
• October 2005: Handbook hardware and base software system was assembled for initial evaluation.
• February 2006: “Gen IV Materials Handbook Architecture and System Design” was completed.
HandbookHandbook development history review (2) development history review (2)
12
• February 2006: Inaugural Gen IV Materials Handbook AdvisoryCommittee Meeting was held in Santa Fe, NM.
• May 2006: Handbook task leader visited JRC to discuss collaboration with European Mat-DB.
• July 2006: Gen IV database panel sessions were held with EU, Japanese, and Korean database leaders and an audience of ASME, academia, and industry Gen IV participants.
• September 2006: Gen IV Materials Handbook beta version was released for structural and functional evaluation.
• February 2007: Gen IV Materials Handbook was demonstrated and reviewed at U.S. DOE headquarters in Washington DC.
HandbookHandbook development history review (3)development history review (3)
13
A series of documents were written to guide A series of documents were written to guide
the rapid development of the the rapid development of the HandbookHandbook..
14
• Database content
– Applicable data identification
– Existing data collection and evaluation
– International data collaboration and sharing
– New data generation
• Database container
– Software for interactive, web-accessible Handbook operation
– Hardware for Handbook servers and data storage
• Database development support
– Gen IV Materials Handbook Organization
– Handbook Advisory Committee
– Material Data Management Consortium
TheThe HandbookHandbook development includes development includes three major aspects three major aspects
15
DATABASE CONTENTDATABASE CONTENT
16
• Candidate metallic materials under the VHTR Testing Plan
– For T 760ºC: 617, CCA 617, 230, X, XR, 740, 263
– For T = 650 ~ 760ºC: 800H, 120
– For T = 600 ~ 650ºC: 316FR SS, 316H SS, 316LN SS
– For T < 600ºC: Grade 91; Grade 92; Grade 122, SAVE 12
– Special and advanced alloys: 214, ODS alloys, Abe alloys
• Candidate metallic materials under the VHTR HTDM GIF Collaboration Plan
– For T >950°C: 617, 230, Single crystal Ni alloy
– For T = 650 ~ 950ºC: X, XR, 800H, 617, 230, 718, 720, Directionally solidified Ni alloys, 792, CM247, 738, 316, 304, 347, 321, 20/20
– For T < 650ºC: A508/533B, 9Cr 1Mo, T91, T92, 2 ¼ Cr 1Mo/F22V, Advanced low Cr alloys, 316, 304, 347, 321, 20/20
Metallic materials are identified for Metallic materials are identified for Gen IV Gen IV
Materials HandbookMaterials Handbook evaluation and collection.evaluation and collection.
17
Nonmetallic materials are being confirmed for the Nonmetallic materials are being confirmed for the HandbookHandbook in collaboration with GIF members.in collaboration with GIF members.
18
Hot DuctFloor BlockStructural Liner & InsulationControl Rods and Guides
C-C and/orSi-Si Composites
Reflector StructureCore Support Pedestals & BlocksFuel Element & Replaceable Reflector
Toyo Tanso IG-110
Large Permanent ReflectorSGL Carbon HLM
Large Permanent ReflectorGraftek PGX
Insulation BlocksReflector Structure Floor Blocks & Insulation BlocksCore Support Pedestals & BlocksFuel Element & Replaceable Reflector
Graftek PCEASGL Carbon NBG-10,17,18
Core Support Pedestals & Blocks Carbone USA 2020
76 mm
Data sources for theData sources for the HandbookHandbook include existing include existing
databases and Gen IV materials testing programs.databases and Gen IV materials testing programs.
19
MIL-HDBK-5
ASMH
NASA NASGRO
ASM MIL-HDBK-7
4m
DATABASE CONTAINERDATABASE CONTAINER
20
• Desire for long database service life versus dynamic changes of information technologies
• Rapid growth of database labyrinthine links versus needs for future modifications and changes
• Intensive competitions in information industry and stability of database software developers
• Prevention of unethical use of database information
• Assurance of uninterrupted operation
Database container development faces Database container development faces many technical and managerial challenges.many technical and managerial challenges.
21
database
reporting client/server
Various Front/End Tools
PresentationTier
ApplicationTier
DataTier
relatedapplications
internet
application servers application servers application servers application servers application servers
relatedapplications
relatedapplications
application servers application servers
relatedapplications
The 3The 3--Tier structure is selected for database Tier structure is selected for database
stability and adaptability to new technologies.stability and adaptability to new technologies.
22
Hardware is also selected to facilitate future Hardware is also selected to facilitate future
expansion and technology development.expansion and technology development.
23
• Rack optimized
general purpose
servers expandable
for future database
growth
• Separation of servers
for the Data Tier and
the other two Tiers
• Minimized loss in
future changes for
drastic hardware
technology
advancements
• “Piecewise” development is adopted to avoid large scale modifications and changes.
• Source code escrow mechanism is considered for the worst scenario in intensive IT competition.
• Legal agreement with users will be mandatoryto discourage database information abuse.
• A “mirror” version is planned for a separate safe location to ensure smooth operation during disasters such as fire, flood, attack etc.
Specific strategies and contingency plans are Specific strategies and contingency plans are made to ensure a successful development.made to ensure a successful development.
24
• R - Required Feature, for features that must be included to be a usable product.
• H - High Priority, for features that are important.
• M - Medium Priority, for features that are desired.
• L - Low Priority, for features that are nice to have if possible.
• F - Future Enhancements, for features that may be developed in future for enhanced performance.
Database development and construction are Database development and construction are
guided by prioritized Product Requirements.guided by prioritized Product Requirements.
25
Micrographs of the specimen material are provided for test data.
MMCT1040
Test data are traceable for test specimen pictures.
LMCT1030
Test data are identified with the program and organization by which the data were generated.
HMCT1020
Test data are traceable for material pedigree including heat, composition, heat treatment, product form , provider etc.
RMCT1010
Test data record name includes test environment, temperature, stress, and record number.
RMCT1000
NotesDescriptionPriorityID
Metal Creep Test Data (MCT) Requirements
DATABASE DEVELOPMENT SUPPORTDATABASE DEVELOPMENT SUPPORT
26
Industry, academia, & government experts are Industry, academia, & government experts are
organized to support organized to support HandbookHandbook development.development.
27
Each kind of data will be provided via a network Each kind of data will be provided via a network
of designated managers and task leaders.of designated managers and task leaders.
28
Gen IV MaterialsGen IV Materials HandbookHandbook is divided into is divided into ten interconnected parts/chaptersten interconnected parts/chapters
29
Part CTest & Data
Management
Part DStatisticalTest Data
Part FDesign Data
Part BPedigree
Part GApplications
Part IReports
Part EMicrostructures
Part JReference
Part AMaterials
HDBKSchemaB060209
Architecture
ORNL / W. Ren
Part HComments& Analyses
• VIEWER Read Mode for Handbook users
–Search
–Browse
–Select
–Comparison Table
–X-Y Chart
–Export
Users can efficiently use and manage Users can efficiently use and manage HandbookHandbook
data through the basic VIEWER component.data through the basic VIEWER component.
30
• VIEWER Edit Mode for Handbook datamanagers
–Edit existing data
–Add new data
–Add records and folders
–Change access control settings on data holders.
• ADMIN – Handbook data management system construction and management
• API – a data flow channel to and from external software such as ANSYS, ABAQUAS for stress analysis
• LAB – various tools for data processing and analysis
–Data importer and exporter ports
–Test analysis modules (Tension for ASTM E8, E111, E132, D3552, C1275, D3039, ISO EN 61, Compression, Creep, Stress Relaxation, LCF/Cyclic Deformation, Fatigue Crack Growth)
–Fracture analysis modules (E399 Fracture Toughness, E561 Fracture Toughness, E1820 Fracture)
–Statistical analysis modules (Tension, Cyclic Deformation, Creep, Fatigue)
31
Advanced components are also developed Advanced components are also developed
for sophisticated data activities.for sophisticated data activities.
HandbookHandbook Access ControlAccess Control
32
• Application Access Control defines what a user can do in the database.
• Database Access Control defines which portion of the database can be accessed by a given user.
• Combination of the two Access Controls determines a user’s privilege in the Handbook.
–Different users see different authorized Handbook
contents.
–Different users conduct different authorized Handbook
activities.
Access Control System is developed to meet the strict Access Control System is developed to meet the strict
requirements of MDMC aerospace & military members.requirements of MDMC aerospace & military members.
33
• READ privilege
–VIEWER Read Mode
–Excel Exporter
–LAB Analysis
• WRITE privilege
–VIEWER Read and Edit Modes
–Excel Exporter
–LAB Analysis
–Can not change Access Control settings
One of the four One of the four Application AccessApplication Access privilegesprivileges
can be granted to a particular user.can be granted to a particular user.
34
• GRANT privilege
–VIEVER Read and Edit Modes
–View all data
–Excel Exporter
–LAB Analysis
–Can change Access Control settings on data
• ADMIN privilege
–Can use all components
–Can view and edit all data
–Can develop Handbook structures
A Database Access setting can be assigned A Database Access setting can be assigned
to any Data Holder in the Holder hierarchy.to any Data Holder in the Holder hierarchy.
35
Individual Database
Table
Subset
Folder
Record
Attribute
Data
U S C o m p an y A
R ead W rite
U S C o m p an y B
U K C om pa ny A
C o m p any
M a teria l
R e ad W rite
D es ign
S a le s
D iv is io n
A cc essD iv is io nC o m p an yR e ad & W riteM a teria lsU S C o m p an y A
R e ad on lyD es ig nU S C o m p an y A
R e ad on lyM a teria lsU S C o m p nay B
W rite on ly !M a teria lsU K C om pa ny A
N o Ac cessD es ig nU K C om pa ny A
N o acc essS a lesAny
N o acc essM a teria lsN o ne
Combination of the Application and Database Access Controls Combination of the Application and Database Access Controls
ensures protection of proprietary data and facilitates collaboraensures protection of proprietary data and facilitates collaborations.tions.
Application Access ControlApplication Access Control Database Access ControlDatabase Access Control
• User applies for access to Gen IV Materials Handbook in writing to Manager of Operations.
• Manager of Operations reports to National Technical Director on Application and Database Access privileges for the applicant.
• Manager of Operations approves and documents the applicant’s access privilege setting.
• The approved access privilege setting is executed only by computer support personnel at the request in writing from Manager of Operations.
• Status of active users and their access privileges are regularlyaudited.
• Periodic password expiration and initiation of new password are required for all users.
Procedures are developed to ensure Procedures are developed to ensure HandbookHandbook
access privileges are securely managed. access privileges are securely managed.
36
A Jaunt to A Jaunt to HandbookHandbook Construction SiteConstruction Site
http://gen4www.ornl.govhttp://gen4www.ornl.gov
37
THANK YOU FOR YOUR ATTENTION!THANK YOU FOR YOUR ATTENTION!
38
!!
Best Practice Materials Data Management For Aerospace And Energy
Dr. Will Marsden*, Dr. David Cebon** and Dr, P Coulter*
Granta Design
*Rustat House, 62 Clifton Road, Cambridge CB1 7EG, UK
**Cambridge University Engineering Department, Trumpington St, Cambridge, CB2 PZ, UK
ABSTRACT
In aerospace, energy and defense engineering, quality is paramount. All design and production decisions must be carefully modeled using accurate materials property data. Often, this data must be certifed by internal experts or external regulators. So using the right reference sources is vital. Excellence in managing and analyzing test data is also important in order to guarantee the reliability of internal design data and the quality of your production materials. Such data consists of a huge range of parameters — materials, properties of interest, components, operating conditions, tests, analyses, and more — posing a formidable information management challenge. Best practice also demands that your design decisions are fully traceable and that problems can be quickly diagnosed. Ideally, all relevant data and analyses should be retained, along with the connections between them.
Organizations in these sectors also need to deploy approved materials information effectively across their networks — for example, making it easy to access and use for your stress engineers and analysts as they perform CAE simulations. In an environment where information can be highly sensitive, security is essential in this deployment process. Data must get to those authorized to use it, when and where they need it — and to no-one else.
Yet the best organizations want to do more than just cope with overwhelming materials data. They aim to turn it to their advantage. They may wish, for example, to continuously assess data on the performance of materials in use, in order to improve design allowable values. Or they may wish to use materials information to support key decisions as they optimize their materials strategies.
GRANTA MI is the leading system for materials information management. Its development is guided by the Material Data Management Consortium (MDMC), a collaboration of top organizations such as NASA, GE - Aviation, Rolls-Royce, Honeywell, and Oak Ridge National Labs.
Keywords: Materials data management, MDMC,
Contact: [email protected]
www.grantadesign.com
Best practice for materials information management for aerospace and energy
International Symposium of Materials Database
MITS 2007Dr. Will Marsden, Granta Design
Product Manager: Aerospace and Energy
Introducing Granta
We are the materials information technology experts
Granta provides software and related services that help you to manage, analyze, and apply essential
materials data in engineering enterprises and education
Introducing Granta
The materials information technology experts
• Software and related services tomanage, analyze, and apply essentialmaterials data
• GRANTA MI – the leading system formaterials information management in engineering enterprises
• CES EduPack – the teaching toolkit for materials and process education
Our history
• 1994: founded, education product
Professor Mike Ashby,University of Cambridge
• 2000: ASM International
• 2002: Material Data Management Consortium (MDMC)
• 2005: Launch of GRANTA MI
• 2006: Materials Strategy Forum
Our customers
• Enterprise – aerospace, automotive, energy, defense, medical devices, materials production, industrial / domestic equipment…
• Education – 550 universities, colleges & lycées worldwide
Our partners
• Data – ASME, MMPDS (Battelle), MMDH (ESDU), MIL-HDBK-17, CAMPUS plastics, IDES plastics…
• Software – UGS, ANSYS, Moldflow, …
• Cambridge University, ASM, MaterialsData Management Consortium,Materials Strategy Forum
Our customer-centric approach
Alcan Aerospace
ASM International
AWE
Concurrent Technologies Corporation
GE - Aviation
Honeywell Aerospace
Los Alamos National Labs MST6
Los Alamos National Labs ESA
NASA GRC
NASA MSFC
Oak Ridge National Labs
Rolls-Royce
US Navy (NSWC)
Williams International
Development is guided by our customers, including theMaterial Data Management Consortium
A collaborative project that formalizes input to GRANTA MI development via:
• Regular meetings & networking
• Identification & prioritization of requirements
• Product review & feedback
The Goal of the MDMC
To continue development and guidance of a highly effective,
powerful and flexible, enterprise-wide software systems for
managing mission-critical materials information…
MDMC Objectives
• Increase the efficiency of materials test data collection, parameterization and storage.. Save time and money;
• Increase the quality, traceability and consistency of materials tests data;
• Flexible tools for improving the management and control ofmaterials testing programs;
• All materials test data is stored automatically with the necessary pedigree information: re-use and re-analyze in future;
• Single source of qualified in-house materials information to the engineering functions of member organizations, appropriate access controls;
• Promote best practice for materials testing, analysis and storage within the aerospace, defense and energy industries;
• Networking between partners/government/commercial aerospace/defense industry
Examples of Major Member Contributions
1. Development prioritization
2. Lab test database schema
3. Lab data reduction and summary procedures
4. Software specifications
• Meta data requirements
• Access control system
• Version control system
• Database merger/synchronization capabilities
• Referential Integrity
• Mathematical data storage and manipulation
• Graphical data storage and manipulation
• …
Some representative customers
High-tech Equipment
Applied Materials Inc
Ballard Power Systems
Intel
Philips Electronics
Domestic/Industrial
Bosch
Emerson Electric
Hilti AG
Moen Incorporated
Pella Corp.
Whirlpool
Materials
Alcan-Pechiney
Dow Chemical
Huntsman TPU
Johnson Matthey
Aerospace & DefenseBAE Systems
Boeing F22
DSTL
EADS Astrium Satellites
Lockheed Martin
Los Alamos NL
GE - Aviation
Goodrich Controls
Honeywell
IHI Aero Engines
NASA GRC, MSFC
Naval Surface Warfare Center
Navy Research Labs
Rolls-Royce
Transport & AutomotiveBombardier Transportation
Eaton Corporation
Ferrari F1
Fiat Research
Renault F1
Siemens Transportation
Other Sectors
Adidas
BAM
Fraunhofer-Institut
GE Corporate R&D
Westmoreland Testing
Information Publishers
ASM International
National Physical Labs
NIST
UK Steel Association
Universities
Cambridge
École des Mines de Paris
MIT
…and 550 others
The importance of materials IT
Strategy
Best use of materials
(cost, environmental,
manufacturing…)
InformationManagement
Testing,
analysis…
Design
CAD, CAE,
Simulation…
Materials
Granta focuses on the materials
domain…
‘The materials informationtechnology experts’
GrantaGranta
…and on meeting customers’ needs
A customer-centric approach
Example customer issues (customise accordingly)
Increasing efficiency
• “I waste a lot of time finding, handling, and manipulating data”
• “We work with many fragmented systems”
• “The knowledge that we develop is not used to its full potential”
• “We need to demonstrate a return on investment from our systems”
Improving quality
• “We want better control so that everyone uses up-to-date & accurate data”
• “Our engineers are often unsure which number to use”
• “We’re using data with variable pedigree”
• “We’re not using all available information to make the best decisions”
Best practice: reducing risk and managing liability
• “Certification is too much time and effort”
• “We can’t trace a design back to the fundamental data”
• “I need to minimize risk in our process”
• “I need to respond to change in regulation and the business environment”
A complete solution: test lab to design
Test lab
Design
The materials data lifecycle
CAPTURE ANALYZE DEPLOY
MAINTAIN
GRANTA MI – what does it do?
Reference data
MIL-Handbook-17, MMPDS,ESDU MMDH, medical devices, plastics, ASME…
Test data
Name, pedigree, materials & process details, test definitionand information, results: tensile, LCF/HCF, FCG, creep…
Legacy data
Numerical, text,graph, image data from spreadsheets, datasheets, filing systems…
Import materials dataStore
Browse & searchEdit
Statistical analysesExport & report
Applications
Design, R&D, Maintenance.etc.
Materials data management examples
Materials data management examples
MATERIALS PEDIGREE
What is the material
Where did it come from
What were the conditions user to create it
Links to ALL information we have measured from specimens cut from it
Materials data management examples
RAW TEST DATA
Every test result from every test performed
Stored in areas specifically design for each test type
Links from each raw records to reduced records, all batches of materials used and all statistical data derived from this raw data
Materials data management examples
DERIVED DATA
Initial location for internal design curves
Model fit coefficients
Limits for fit
Conditions: eg temp, R ratio, freq…
Links to all data used in derivation of model
GRANTA MI: capture
All materials information in one placeInternal testing/QA, external data
Integrate access to key external referencesMMPDS (MIL-5), MIL-17, ASM Handbook, ESDU,CAMPUS, IDES…
Ensure ease of import Bulk or single records from testing, QA, analysis, external….
Handle the specifics of materials informationVaried materials types & properties, curves…
GRANTA MI: capture (reference data)
Universe seriesMaterials Universe, Process Universe
Polymer Universe, EcoSelector
AerospaceMMPDS-02
MIL-HDBK-17
ESDU MMDH
PlasticsCAMPUS, IDES
ChemRes
MoldFlow
Fast, easy, cost-effective, integrated access
for users across the enterprise
(Read-only or data management options)
Medical devicesMaterials for Medical
Devices Database
Special projectsLead-free solders
Metal foams
GRANTA MI: analyze
Flexible analysis
Single curves, multiple curves, multiple points…
Simple access to powerful methods
Provide an easy-to-use GUI to a comprehensive range ofanalysis tools
Traceability
Records all data, analyses,and their connections –information has pedigree
Example materials analyses
Test Modules
• Tensile
• Compression
• Creep
• Stress Relaxation
• LCF / Cyclic Deformation
• Fatigue Crack Growth
• E399 Fracture Toughness
• E561 Fracture Toughness
• E1820 Fracture Toughness
Quasi- Static:
• Stress v Strain Curves (for stress andstrain controlled tests): Ramberg-Osgood Model
Creep models
• To fit test load as a function of time to failure and other % creep strains at various constant temperatures): Larson Miller model (for creep and creep rupture)
• Hyperbolic tangent modent (for creep rupture, MDMC only)
Fatigue:
• Stress v Life Curves (for Stress Controlled Tests): Basquin, Life Power, Equivalent Stress (as in MIL-HDBK-5), Ramberg-Osgood…
• Strain v Life Curve (for Strain ControlledTests): Coffin-Manson, Combined Basquin and Coffin-Manson, Life Power, Equivalent Strain (as in MIL-HDBK-5)
+ easy to add in-house and third-party analyses
GRANTA MI: deploy
Secure & controlledManage access; deliver current, accurate data
Ease of accessWeb-based search and browse for engineers
Fit to engineers’ workflowEasy to get data into Excel, ANSYS, Abaqus, NASTRAN, UGX…
Scalable & robustDesigned for enterprise deploymentto 1,000s of engineers
GRANTA MI: maintain
The system helps you to cope with changes in…
Data
• GRANTA MI enables continual update of dynamic in-house data
• Regularly-updated external references
People
• Preserve knowledge by capturing the full context of materials information
The IT / business environment
• Regular updates respond to changing standards, operating systems, user requirements etc.
• You can share the cost of essential development & maintenance
GRANTA MI – the system
GRANTA MI – summary
GRANTA MI is the leading system for materials information management in engineering enterprises
• Tailored to the specifics of materials information
• Supports the complete ‘materials data lifecycle’
• Controls data: accuracy, consistency, audit, traceability, security
• Commercial software: robust, scalable, maintained
• Developed in collaboration with the MDMC
GRANTA MI helps you to innovate, save time, ensure quality, and reduce risk in the engineering process
SciDex - An Integrated Materials Database Management System
Volkmar Vill, Gaja Peters
University of Hamburg, Department of Chemistry
Martin-Luther-King-Plz. 6, 20146 Hamburg, Germany
ABSTRACT
A knowlegde system is not a list of floating point numbers and text but a computer system with validated data and applied rules and data specific functionality. SciDex, is a tool for new types of knowledge systems and has generalized object definitions to serve chemistry, physics and biology. It has methods to store, normalize, validate, analyse, compare and predict data. It is currently used for example for LiqCryst (LCD, liquid crystals), Landolt-Börnstein, natural products (AntiBase), NMR (29Si-NMR, 17O-NMR) and multi-user online inventory systems (CLAKS), e.g. see:
http://liqcryst.chemie.uni-hamburg.de
http://lb.chemie.uni-hamburg.de/
The aim of SciDex is not to develope highly specific computer systems for single applications, but to cover all areas of materials study in just one system.
The data generalized data model and the analysis methods of SciDex will be described.
Keywords: Material Database, object oriented knowledge systems, structure analysis, QSPR
Contact: [email protected]
1
International Symposium of Materials Database, MITS 2007Friday March 16, 2007
National Institute for Materials Science, Sengen Site (Tsukuba science city)
SciDex – An Integrated
Materials Database Management System
Volkmar Vill, Gaja Peters
Department of Chemistry,
University of Hamburg (Germany)
2
Content
• General remarks
• SciDex - Basics
• Applications
– LiqCryst
– Landolt-Börnstein Index
– Natural Products
– Chemistry Laws
3
Database Knowledge
System• Store data
• Find
• Search =Find known data
• Know, what is in
• Integrate validated dataand rules
• Find / Analyse / Predict
• Search = Create Answers– Find
– Interpolate/Extrapolate
– Calculate
– Associate
• Know, what is in and what is not in
4
Adapt Science to Common Databases
• Reduce Information
– Data types cannot cover data fully
• e.g. fixed length strings, numbers without errors
• Create new data and rules
– Registration numbers
– cryptic data definitions
• The user has to support the needs of the
computer
5
Create Databases for Science
• Object oriented system (not SQL)
• Common drawbacks
– no standardisation
– highly specific solution, isolated solutions
6
motto
• Create a natural environment for data
• The solution should have the same
symmetry as the problem
• Don't use more variables as independ
logical features exist
7
SciDex
• Object-oriented database management
• Client/Server, embedded web-server
• Validation methods– Structures, names, CAS-RN
• Substructure comparision
• Object data types– 2D/3D structures, assigned spectra, numerical tables,
amount
– Taxonomy (biology)
• no limits (109 Comps, 32000 Atoms, 32000 Subproperties in a property, ..)
8
SciDex: Types of Data
• Compounds
– incl. mixtures, copolymers, reaction schemes
• Structures
– entries for atoms, bond, e.g. NMR data, 3D
• Properties
– complex records incl. graphics, spread sheets
• References
– citations, locations, url
– ca. 30 predefined fields
9
Conception: SciDex
Properties ReferencesCompounds
& Mixtures
Properties References
extract
extract
List of
Compounds
extract
extract
List of List of
searchsearchsearch
Relations:
Windows:
List of Pairs
compare
Statistics (QSAR)
Diagrams (Graphs)
Single Compound Single Reference
Predictions
mathematical methods
10
Applications of SciDex
• LiqCryst - Database of Liquid Crystals
• Landolt Börnstein Index
• 29Si-NMR / 17O-NMR
• AntiBase - natural compounds
• International Chemistry Laws
• CLAKS - hazard information / inventory
11
LiqCryst: data
• 90000 compounds– LCD, NLO, lipids, bio-polymers
– Metallomesogens, nano-particles, virus
– Ferroelectrics, antiferroelectrics
• 90000 references– Journals, patents, PhD, conference proc.
• 280000 properties– Transition temperatures
– Thermodynamic data
– Electro-optical data
– Everything reported
12
LiqCryst: methods
• Validated data
• Substructure comparision, QSPR
• Prediction by
– Similarity
– Neural networks
– Increments
13
LiqCryst: single compound
14
LiqCryst - Data prediction
15
Prediction of Transition Temperatures
5°C 10°C 15°C > 15°C
N 60% 82% 93% 7%
SmA 57% 78% 88% 12%
SmC 54% 78% 88% 12%
Tm 35% 60% 75% 25%
16
LiqCryst: usage
• 12 Versions since 1995
• 150 inhouse installations
• 2000 online users
• ? users of book versions
– (LB IV/7 and XIII/5a)
17
Landolt-Börnstein Index
Numerical Data and Functional Relationships in Scienceand Technology”, Springer-Verlag, since 1883
341 volumes of New Series15 volumes new every year
lb.chemie.uni-hamburg.de/ Search Enginelb.chemie.uni-hamburg.de/static/ organic html indexlb.chemie.uni-hamburg.de/inorg/ inorganic html indexhttp://lb.chemie.uni-hamburg.de/mix/ mixtures
18
19
CLAKS-DB: Chemistry Laws
• 127000 Compounds incl. biomaterials
• 230 International Laws and Regulation
– 'expanded' to all related compounds
– Kyoto, Doping (WADA), Trade, DualUse
• Hazard information, Products
• Chemical substitutes
20
Natural Products
21
Taxonomy
22
Demonstrations
• Compound-Def-DB
– substructure search, substructure comparison
• NAPIS- Natural Products
– taxonomy, NMR-Data search
• GC - gel chromatography
– data analysis, data linking
• CLAKS - Chemistry Laws
• LiqCryst
– tables, data analysis, data prediction
23
Links
• liqcryst.chemie.uni-hamburg.de/scidex.php
• www.lci-publisher.com
• lb.chemie.uni-hamburg.de/static
• lb.chemie.uni-hamburg.de/
Development of a Network Database for Thermophysical Property Data
Tetsuya Baba
National Institute of Advanced Industrial Science and Technology
AIST Tsukuba Central 3, 1-1-1, Umezono, Tsukuba, Ibaraki 305-8563, JAPAN
ABSTRACT
A network database for thermophysical property data has been developed and opened to the Internet by collaboration of scientists, researchers, and engineers who produce data by measurement or evaluation in Japan. This database accumulates thermophysical property data such as thermal conductivity, specific heat capacity, thermal expansion coefficient, surface tension, viscosity and density etc. for variety of materials including solids, high temperature melts and fluids. At present, thermophysical property data of, 1) standard and basic data, 2) functional materials, 3) reference data of fluids and high temperature melts, 4) thin films and boundary thermal resistances, 5) materials for use at high temperatures, 6) materials for use at low temperatures, 7) organic materials and inorganic materials, are stored.
This database uses hierarchy structure for material classification to which thermophysical property data is assigned. Scope and overall coverage of the database can be viewed by an explorer like user interface. The target material can be searched following the hierarchy structure from higher class to lower class. A powerful and flexible search engine has been developed with two modes of search, "material search" and "property search". The material search can find target materials from information such as material name, chemical formula, material code, etc. The property search can find materials which have physical properties within the specified range. A user friendly graphical user interface has been developed to access thermophysical property data via internet efficiently.
This database can be accessed at the url “http://www.aist.go.jp/RIODB/TPDB/DBGVsupport/English/”. Keywords: thermophysical property, database, network, internet, graphical user interface
Contact: [email protected]
Development of a network database for
thermophysical property data
Tetsuya Baba
National Metrology Institute of Japan (NMIJ) ,
National Institute of
Advanced Industrial Science and Technology (AIST)
International Symposium of Materials Database, MITS 2007Friday March 16, 2007
National Institute for Materials Science, Sengen Site (Tsukuba science city)
Simulation for design of optical disk
Principle of the laser flash method
to measure thermal diffusivity of materials
0.0 0.2 0.4 0.6 0.8 1.0
0
2
4
6
8
10
T/T
dx
1
2
3
4
6
5
1:
2:
3:
4:
5:
6:
0001.0t
0003.0t
003.0t001.0t
03.0t01.0t
0.0 0.2 0.4 0.6 0.8 1.0
0
2
4
6
8
10
T/T
dx
1
2
3
4
6
5
1:
2:
3:
4:
5:
6:
0001.0t
0003.0t
003.0t001.0t
03.0t01.0t
0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.5
1.0
0.1388
t1/2
T/T
0t0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.5
1.0
0.1388
t1/2
T/T
0t 21
2
0
2
1388.0t
dd
Light Pulse
heatingRadiation
detectorSpecimen
Observation of rear
face temperature
Time
Tem
pera
ture
Thermal
diffusivity
Tem
pera
ture
Time
Distance from the surface
Thermal diffusivity measurement of bulk
glass like carbon by the laser flash method
Evolution of the laser flash method
Faster observations can measure thinner specimens
Picosecond TR method
Thin films, 30nm 10ps-10ns
Specimen
Light
Pulse
Laser flash method
Bulk materials 1mm10ms-10s
2dThickness
Thermal
diffusivity
Heat diffusion time
Observation of radiation
Nanosecond TR method
Thin films, 1 m10ns-10 s
Temperature detector ?
Picosecond thermoreflectance method
Similar configuration to the laser flash method for bulk material
2
f
f
dT
t
d[m] thickness of the film
Heat diffusion time
across thin film
Small thermal diffusivity
Large thermal diffusivity
100 m
~100nm
50 m
Time / ps
0 100 200 300 400 500 600
Th
erm
ore
fle
cta
nce
sig
na
l /
a.u
.
0
5
10
15
20
70 nm
100 nm
200 nm
Temperature response curve of Mo thin films
Thermal diffusivity of molybdenum thin films measured
with the picosecond thermoreflectance method
Synthesized by magnetron DC sputtering
Substrate Corning 7740 glass
Thermal diffusivity of molybdenum thin films measured
with the picosecond thermoreflectance method
Synthesized by magnetron DC sputtering
Substrate Corning 7740 glass
-125 sm10
Heat diffusion time / s
100 10-210-1210-4 10-6
10-8 10-10
Thermal diffusivity,
Conventional Laser flash method
Nanosecond laser flash method
Picosecond laser flash method
(Electrical delay)
Picosecond laser flash method
(Optical delay)
Heat diffusion length / m
10-2 10-410-3 10-5 10-6
10-7 10-8
Bulk materials Thin plates Thin films
)(
)(l
2125 ,sm101 l
Light pulse heating methods can cover thermal
diffusivity measurements from plates to thin films
Thermophysical property database and measurement standard
Manufacturing process
Character of material
Reliable thermophysical property data
with uncertainty
Material science
Practical measurement instruments
Data for simulation
Correlation between
thermophysical property
and character of material
Thermophysical
property database
Development of measurement
standard and traceability
Heat transfer simulation
Advancement of thermal design
Sta
nd
ard
da
ta
Development of
materials
Utilization of
materials
Metal / alloy
Ceramics
Glass
Semiconductor
Energy
Electronics
Process control
Environment /
building / life
Food / medical
care / bio
Ph
ysic
al P
rop
ert
y d
ata
ba
se
Polymer
Physical property database as a bridge between
development and utilization of materials
• Centralized database
A single group is responsible for the
database server, the database
management system, and collection,
register, update, and evaluation of data.
• Network database
Constructed on the Internet by
collaboration of scientists, researchers,
and engineers who produce data by
measurement or evaluation.
Data production,
collection d evaluation
Data production,
collection, and evaluation
Data user
Data user
Steering committee
Key station
Data user
Data production,
collection, and evaluation
Standardization of data
format and data evaluation
Material databases
Database server
Data production,
collection, and evaluation
Data user
Independent data stationsExchange data via the Internet
Standard format
of XML
AIST, JSTP
NIMS etc.
Display of thermal conductivity of thin films
Data numberProperty Property Data number
Statistics of stored data in the thermophysical property database
Web interface of the thermophysical property database
Graph of thermophysical property data
Summary
A network database system of thermophysical property data is
under operation in Japan.
The database is accessible via the Internet.
http://www.aist.go.jp/RIODB/TPDB/DBGVsupport/English/
http://www.aist.go.jp/RIODB/TPDB/TPDS-web/en/
Database management system with graphical user interface
Graph of thermophysical property data can be displayed
and handled interactively on the computer display.
Application of Materials Databases to Composite Materials Design
Yibin Xu Materials Database Station, National Institute for Materials Science, Tokyo, Japan
CompoTherm, a thermophysical property prediction system for composite materials has been developed by National Institute for Materials Science (NIMS) and opened to the Internet access (http://composite.nims.go.jp/) since April 1st, 2005. This system offers users a platform to design a new composite material using the materials stored in multiple NIMS Materials Databases (http://mits.nims.go.jp/db_top_eng.htm), and predict the thermophysical properties such as density, specific heat, thermal conductivity and thermal diffusivity of the designed material, basing on the property data of the component materials and the composite structure. Tow simulation methods, analytical method and finite element method are provided to calculate the thermal conductivity of composite materials. And a knowledge base is available to help the users to understand the theoretical foundation of composite material design and property prediction. The system have been used to calculate the interfacial thermal conductance of SiC-particles-reinforced aluminum alloy matrix composites, the thermal conductivities of SiC-whisker-reinforced aluminum alloy matrix composites and thermal-sprayed Zr2O thermal barrier coatings. The calculated values are in good agreement with the experimental ones. Acknowledgement A part of this work was financially supported by The Budget for Nuclear Research of The Ministry of Education, Culture, Sports, Science, and Technology based on the screening and counseling by The Atomic Energy Commission.
Application of Materials Databases to
Composite Materials Design
Yibin Xu
National Institute for Materials Science
Tokyo, Japan
Why composite material?
• Multi-requirements on material property
•
• Difficult to be satisfied by single phased material
• Improve material performance by mixing two or three phases
• Infinite combination of materials and structures
• Constitutional and structural design and optimization by computer simulation
Nuclear power plants
Electronicpackaging
Brake disc of cars Thermal barrier coating
Non-radioactive, high thermal conductivity, thermal shock resistance, strength
high thermal conductivity, low thermal expansion, strength
high thermal conductivity, wear resistance, strength
Low thermal conductivity, low thermal expansion
Thermophysical property of composite
Nuclear fusion plant
CompositeComposite
•Thermal stress•Thermal shock resistance
•Energy transfer
•Thermal stress•Thermal shock resistance
•Energy transfer
Thermophysical property thermal conductivity, thermal expansion, heat capacity, etc.
Objective
• Develop a platform for design composites with
required thermophysical property, basing on the
material property data we known.
• Apply the system to material research and
evaluate the accuracy of calculation by
experiments.
System architecture of CompoTherm
Internet
Web server
Composite
design
iM ac
Property evaluation
Knowledge
base
KnowledgeKnowledgeKnowledge
base
Knowledge
baseMaterial
database
MaterialMaterial
databasedatabase
Material
database
FEM
simulation
FEMFEM
simulationsimulationsimulation
FEM
simulation
Analytical
simulation
AnalyticalAnalytical
simulationsimulation
Analytical
simulation
Materials database
• Thermophysical property database
– Density, specific heat and thermal conductivity data
extracted from NIMS Materials Database.
– Data number: 990 (polymers, alloys, ceramics, etc.)
Simulation systems
• Two simulation methods available
– Analytical method
– Numerical method (finite element method)
• Fit for different requirements on computational
efficiency and accuracy.
Analytical simulation method
• Analytical solutions used for different composite structures
• Features
– Simple model
– Quick calculation
– Suitable to study the dependence of thermal property on structure
Structure model
Structuretype
Dispersionshape
Dispersiondistribution
Interface
-- -- No-- -- Yes
SphereEllipsoidCylinder
1D, 2D, and 3D
No Equivalent inclusion method
Sphere
Ellipsoid
Cylinder
1D Yes Effective medium theory
Dispersioncomposite
Wiener expression(Law of mixture)
Laminatecomposite
Analytical solutions
Demonstration
Finite element simulation method
• Features
– Precise material arrangement
– Composites containing dispersions with different shapes, sizes, materials, etc.
– Material with anisotropy
– Thermal conductivity dependence on temperature
T0
T1
a
b
Qx
Qx
Qy
Qy
x
y t
Geometry FEM Mesh Heat transfer
simulation
zzzyzx
yzyyyx
xzxyxx
Thermal
conductivity
Demonstration
Example of Application (1)
• Prediction of thermal conductivity of SiCw/Al composite
• Samples
10 m
Specimen SiCw0.5-10% SiCw0.5-20% SiCw1.0-10% SiCw1.0-20%
Matrix Al alloy A2024
SiC whisker diameter ( m)
0.5 0.5 1.0 1.0
SiC volume fraction
10% 20% 10% 20%
Example of Application (1)
Thermal conductivity of SiCw/Al perpendicular (a) and parallel (b) to the whisker.
(a) (b)
• ZrO2thermal barrier coating
Inter-splat crack (<1 m)
Pore
(1-10 m)
Branch crack
(>10 m)
Segment crack
(>10 m)
ima
ge
sF
EM
mo
de
ls
(A ) (B)
Example of Application (2)
Example of Application (2)
• Samples
Segment cracks Branch cracks PoresInter-splat
cracks
C2 2.25% 0.36% 4.07% 4.20%
C1 1.85% 0.68 % 4.67 % 5.36%
C3 1.83 %3.78% 0.29 % 1.89%
Plasma power (KW) Spray distance (mm) Substrate temp. ( )
C1 25.6 100 500
C2 34.2 80 650
C3 37.8 60 800
Coating condition
Volume fraction of pores
• Multi-scaled simulation
Segment cracksZrO2 Matrix PoresInter-splat cracks Branch cracks
Comparison of the calculated and measured transverse thermal conductivity T W/mK)
Step 0 Step 1 Step 2 Step 3 Step 4
Step0
(matrix)
Step1
(inter-splat
crack)
Step2
(pore)
Step3
(branch
crack)
Step4
(segment
crack)
Exp. Dev.
0.93 0.98
C2 2.30 1.27 1.20 1.16 1.14 1.12 1.8%
1.68
4.1%
3.0%1.63
C1 2.30 1.10 1.03 0.95
C3 2.30 1.78 1.73 1.71
Example of Application (2)
Work in Progress
Internet
Web server
Composite
design
iM ac
Property evaluation
Knowledge
base
KnowledgeKnowledgeKnowledge
base
Knowledge
baseMaterial
database
MaterialMaterial
databasedatabase
Material
database
FEM
simulation
FEMFEM
simulationsimulationsimulation
FEM
simulation
Analytical
simulation
AnalyticalAnalytical
simulation
Analytical
simulation
AIST
Thermophysical
property DB
XML
Data file
Conclusion
• An Internet platform for designing composites
with required thermophysical property with
connection to materials database has been
developed.
• The accuracy and reliability of the system has
been proved by experiments.
• In order to use external data resources,
standard format of materials data exchange is
expected.
