Design and Construction of Relational Database for Structural Modeling Verification and Validation. Weiju Ren, Ph. D.

Transcription

1 Design and Construction of Relational Database for Structural Modeling Verification and Validation Weiju Ren, Ph. D. Oak Ridge National Laboratory ASME Verification and Validation Symposium 2012 Las Vegas, Nevada, May 2-4, 2012

2 DOE-NE is promoting modeling and simulation for nuclear reactor design, analysis and licensing. Conventional demonstration and testing of nuclear energy components/systems face great challenges. Often cost- or time-prohibitive. Extensive/exhaustive testing often impossible. Modeling and simulation (M&S) provides the basis for: R&D planning Program decision making Physical experiment minimizing 2 ASME Verification and Validation Symposium 2012

3 Before important M&S results can be trusted, challenging questions must be answered. Predictive? Courtesy of ANL V & V 3 ASME Verification and Validation Symposium 2012

4 Verification & Validation establish credibility of a model and confidence in its simulation results. What is V&V? At present, definitions and procedures for V&V vary across the M&S community. Generally speaking, V&V can be considered as: Systematic accumulation of evidence that given M&S is adequate for the intended application. 4 ASME Verification and Validation Symposium 2012

5 How can we systematically accumulate, manage, and track, and retrieve the evidence? The V&V activities should be well planned along with the M&S tasks. It is ideal that an evidence collection and management plan (V&V plan) is put in place before the M&S is started. The V&V workflow may be mapped to the M&S workflow. Every important M&S step should have corresponding evidence collection and management mechanisms. Specific information management system and tools should be provided. Facilitate systematic evidence accumulation and use. 5 ASME Verification and Validation Symposium 2012

6 It is imperative that practical methodologies and procedures be developed for V&V. Currently, most V&V approaches fall short of being consistent, practical, implementable, or reliable. An advanced information management framework may provide a solid basis for V&V activities. Construct customized relational database that visualizes specific V&V workflow. Offer tangible software tools for V&V activity planning and implementation. Provide effective documentation and data management. 6 ASME Verification and Validation Symposium 2012

7 M&S consists of five major steps, each involving chances for error. Verification becomes crucial. Reality of Interest Component, Subsystem, System Computational Model Computer Code Property parameters Initial parameters Boundary parameters Calculation Simulation Results Calculation Output Abstraction Important features Negligible characteristics Assumptions PIRT Numerical Implementation Discretizations Algorithms Convergence criteria Uncertainty Qualification Error limits Accuracy requirements 7 ASME Verification and Validation Symposium 2012 Conceptual Model Idealization of Physical Reality Mathematical Modeling Mechanics principles Material behavior Loads & interface Boundary conditions Mathematical Model Math Equations and Parameters Simulation Outcomes Final Results with Known Uncertainty Is the simulation prediction correct and satisfactory?

8 Special experimental data are needed for validation of the M&S for its predictability. Reality of Interest Component, Subsystem, System Abstraction Important features Negligible characteristics Assumptions PIRT Conceptual Model Idealization of Physical Reality Physical Modeling Assumptions Expectations Experiment Model Testing and Specimen Designs Raw data collection Data reduction Quality assessment Experimentation Experimental Results Testing Result Data Experimental Implementation Test definition Output identification Equipment calibration Uncertainty Qualification Data scatter Error limits Design tolerance 8 ASME Verification and Validation Symposium 2012 Physical Model Simplified Physical Representation Experimental Outcomes Final Results with Known Uncertainty Now we can answer the validation question.

9 All important levels in M&S hierarchy require V&V to build up credibility of the results. Mathematical Model Conceptual Model Revise model or experiment Physical Model Code Verification Computational Model Calculation Verification Simulation Results Simulation Outcomes Preliminary Calculations Validation Quantitative Comparison Experimental Model Experimental Results Experimental Outcomes Acceptable agreement? Yes Move to the next higher level in a bottom-up V&V process 9 ASME Verification and Validation Symposium 2012 No Is the simulation prediction correct and satisfactory?

10 Documentation & data management for a large model system can quickly become challenging. The Yes answer leads to extension of the process. The No answer leads to iteration of the process. To ensure traceability for efficient V&V, all documents and data should be managed in a schema that matches the specific M&S workflow. 10 ASME Verification and Validation Symposium 2012

11 V&V database structure can be customizable to catch required details for complicated M&S process. 11 ASME Verification and Validation Symposium 2012

12 Flexible version control can be used to capture and manage data modifications in the M&S iteration. The No answer leads to iteration of the M&S process. Revised M&S is linked to its version of V&V data for convenient traceability. 12 ASME Verification and Validation Symposium 2012

13 Ideal structural flexibility for V&V database can be achieved by a modularized database system. Individual Database C# Table Subset Folder.NET Class Libraries Record Attribute Data MSIL Modular Database Kit Microsoft Intermediate Language/Java Byte Code Construction elements and modules Custom design Relational V&V database CRL Common Language Runtime /JVM Native Processor Machine Language 13 ASME Verification and Validation Symposium 2012

14 A modular database infrastructure has been established at ORNL for various projects. Nuclear Energy Knowledge Base for Advanced Modeling and Simulation Gen IV Materials Handbook for international collaboration in nuclear structural materials ASME Materials Database for Code and Standard Development Mechanical testing projects and ASME Codification data management 14 ASME Verification and Validation Symposium 2012

15 The NE-KAMS is being developed to achieve several goals that are crucial for Advanced M&S. Provide V&V and Uncertainty Quantification (UQ) resources. Establish confidence in the use of M&S for nuclear reactor design, analysis and licensing. Develop and implement standards, requirements and best practices for V&V and UQ. Enable scientists and engineers to assess the quality of their M&S applications. Serve as important resource for technical exchange and collaboration. Enabling credible computational models and simulations for nuclear energy applications. 15 ASME Verification and Validation Symposium 2012

16 Summary It is imperative that consistent, practical, reliable and implementable V&V approaches be established. A relational database can provide a visualized framework for V&V planning and implementation. Desired features for developing an effective V&V database include but not limited to: Structural modularization Version control Various data type management Data quality categorization Data traceability Automated data transfer The modular database system at ORNL provides effective infrastructure for V&V and UQ database development. 16 ASME Verification and Validation Symposium 2012

17 Acknowledgments This work is sponsored by the U.S. Department of Energy, Office of Nuclear Energy Science and Technology under contract DE-AC05-00OR22725 with Oak Ridge National Laboratory, managed by UT-Battelle, LLC. The Author would like to thank Hyung Lee of Bettis, Kim Mousseau of INL, and Greg Weirs of SNL for collaboration in NE-KAMS development. 17 ASME Verification and Validation Symposium 2012