Development of a fourth generation predictive capability maturity model.
Author(s) -
R. E. Hills,
Walter R. Witkowski,
Angel Urbina,
William J. Rider,
T.G. Trucano
Publication year - 2013
Language(s) - English
Resource type - Reports
DOI - 10.2172/1096515
Subject(s) - computer science , clarity , completeness (order theory) , capability maturity model , maturity (psychological) , computational model , systems engineering , software engineering , artificial intelligence , machine learning , engineering , programming language , software , mathematics , psychology , mathematical analysis , developmental psychology , biochemistry , chemistry
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.
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