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Predictive Capability Maturity Model for Computational Modeling and Simulation

Predictive Capability Maturity Model for Computational Modeling and Simulation PDF Author: William L. Oberkampf
Publisher:
ISBN:
Category :
Languages : en
Pages : 70

Book Description


Predictive Capability Maturity Model for Computational Modeling and Simulation

Predictive Capability Maturity Model for Computational Modeling and Simulation PDF Author: William L. Oberkampf
Publisher:
ISBN:
Category :
Languages : en
Pages : 70

Book Description


Predictive Capability Maturity Model for Computational Modeling and Simulation

Predictive Capability Maturity Model for Computational Modeling and Simulation PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 71

Book Description
The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M & S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M & S effort. The PCMM addresses six contributing elements to M & S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M & S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M & S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

Uncertainty Quantification's Role in Modeling and Simulation Planning, and Credibility Assessment Through the Predictive Capability Maturity Model

Uncertainty Quantification's Role in Modeling and Simulation Planning, and Credibility Assessment Through the Predictive Capability Maturity Model PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 23

Book Description
The importance of credible, trustworthy numerical simulations is obvious especially when using the results for making high-consequence decisions. Determining the credibility of such numerical predictions is much more difficult and requires a systematic approach to assessing predictive capability, associated uncertainties and overall confidence in the computational simulation process for the intended use of the model. This process begins with an evaluation of the computational modeling of the identified, important physics of the simulation for its intended use. This is commonly done through a Phenomena Identification Ranking Table (PIRT). Then an assessment of the evidence basis supporting the ability to computationally simulate these physics can be performed using various frameworks such as the Predictive Capability Maturity Model (PCMM). There were several critical activities that follow in the areas of code and solution verification, validation and uncertainty quantification, which will be described in detail in the following sections. Here, we introduce the subject matter for general applications but specifics are given for the failure prediction project. In addition, the first task that must be completed in the verification & validation procedure is to perform a credibility assessment to fully understand the requirements and limitations of the current computational simulation capability for the specific application intended use. The PIRT and PCMM are tools used at Sandia National Laboratories (SNL) to provide a consistent manner to perform such an assessment. Ideally, all stakeholders should be represented and contribute to perform an accurate credibility assessment. PIRTs and PCMMs are both described in brief detail below and the resulting assessments for an example project are given.

Development of a Fourth Generation Predictive Capability Maturity Model

Development of a Fourth Generation Predictive Capability Maturity Model PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 76

Book Description
The Predictive Capability Maturity Model (PCMM) is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated for an intended application. The primary application of this tool at Sandia National Laboratories (SNL) has been for physics-based computational simulations in support of nuclear weapons applications. The two main goals of a PCMM evaluation are 1) the communication of computational simulation capability, accurately and transparently, and 2) the development of input for effective planning. As a result of the increasing importance of computational simulation to SNL's mission, the PCMM has evolved through multiple generations with the goal to provide more clarity, rigor, and completeness in its application. This report describes the approach used to develop the fourth generation of the PCMM.

Model Validation and Uncertainty Quantification, Volume 3

Model Validation and Uncertainty Quantification, Volume 3 PDF Author: Robert Barthorpe
Publisher: Springer
ISBN: 3319747932
Category : Technology & Engineering
Languages : en
Pages : 303

Book Description
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty

Methods and Applications for Modeling and Simulation of Complex Systems

Methods and Applications for Modeling and Simulation of Complex Systems PDF Author: Gary Tan
Publisher: Springer Nature
ISBN: 9811510784
Category : Computers
Languages : en
Pages : 276

Book Description
This volume constitutes the proceedings of the 19th Asia Simulation Conference, AsiaSim 2019, held in Singapore, Singapore, in October 2019. The 19 revised full papers and 5 short papers presented in this volume were carefully reviewed and selected from 36 submissions. The papers are organized in topical sections on simulation and modeling methodology; numerical and Monte Carlo simulation; simulation applications: blockchain, deep learning and cloud; simulation and visualization; simulation applications; short papers.

Verification and Validation in Scientific Computing

Verification and Validation in Scientific Computing PDF Author: William L. Oberkampf
Publisher: Cambridge University Press
ISBN: 1139491768
Category : Computers
Languages : en
Pages : 782

Book Description
Advances in scientific computing have made modelling and simulation an important part of the decision-making process in engineering, science, and public policy. This book provides a comprehensive and systematic development of the basic concepts, principles, and procedures for verification and validation of models and simulations. The emphasis is placed on models that are described by partial differential and integral equations and the simulations that result from their numerical solution. The methods described can be applied to a wide range of technical fields, from the physical sciences, engineering and technology and industry, through to environmental regulations and safety, product and plant safety, financial investing, and governmental regulations. This book will be genuinely welcomed by researchers, practitioners, and decision makers in a broad range of fields, who seek to improve the credibility and reliability of simulation results. It will also be appropriate either for university courses or for independent study.

Coarse Grained Simulation and Turbulent Mixing

Coarse Grained Simulation and Turbulent Mixing PDF Author: Fenando F. Grinstein
Publisher: Cambridge University Press
ISBN: 1107137047
Category : Science
Languages : en
Pages : 481

Book Description
Reviews our current understanding of the subject. For graduate students and researchers in computational fluid dynamics and turbulence.

Model Validation and Uncertainty Quantification, Volume 3

Model Validation and Uncertainty Quantification, Volume 3 PDF Author: H. Sezer Atamturktur
Publisher: Springer
ISBN: 3319152246
Category : Technology & Engineering
Languages : en
Pages : 361

Book Description
Model Validation and Uncertainty Quantification, Volume 3. Proceedings of the 33rd IMAC, A Conference and Exposition on Balancing Simulation and Testing, 2015, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Uncertainty Quantification & Model Validation Uncertainty Propagation in Structural Dynamics Bayesian & Markov Chain Monte Carlo Methods Practical Applications of MVUQ Advances in MVUQ & Model Updating

Model Validation and Uncertainty Quantification, Volume 3

Model Validation and Uncertainty Quantification, Volume 3 PDF Author: Roland Platz
Publisher: Springer Nature
ISBN: 3031370031
Category : Technology & Engineering
Languages : en
Pages : 208

Book Description
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Introduction of Uncertainty Quantification Uncertainty Quantification in Dynamics Model Form Uncertainty and Selection incl. Round Robin Challenge Sensor and Information Fusion Virtual Sensing, Certification, and Real-Time Monitoring Surrogate Modeling