A framework for an integrated nuclear digital environment

Abstract A conceptual framework is proposed for a digital environment extending from the prototype design of nuclear plants through operations and decommissioning to storage and waste disposal. The environment consists of a series of interconnected multi-scale, multi-physics computational models linked to the real-world by data acquired during validation of prototypes, in-service monitoring and inspections of plant, post-shut-down inspections of plant and in-situ monitoring of stored waste. The technology gaps for the implementation of the integrated nuclear digital environment (INDE) are identified and discussed together with the advantages to be gained from its implementation. Implementation of INDE will be dependent on future advances in High Performance Computing systems approaching the exascale and parallel advances in the development of algorithms for processing large amounts of data. The data itself will be acquired through innovations in measurement, analysis and uncertainty and will be applied through projects relating to lifetime extension, decommissioning and resurgent national science programmes. It is postulated that the existence of this type of framework might be inevitable given both nuclear-specific and non-nuclear drivers and may be essential for the nuclear industry to deliver current and future challenges from the clean-up of legacy waste sites to time and budget, future generation nuclear reactors and small-scale mass-production of modular nuclear power plants. It is proposed that implementation of INDE will lead to shorten development times, reduced costs and increased credibility, operability, reliability and safety.

[1]  Richard S. Rudner.  The Scientist Qua Scientist Makes Value Judgments , 1953, Philosophy of Science.

[2]  Adam M. Grant,et al.  In the company of givers and takers. , 2013, Harvard business review.

[3]  R. Audi.  Epistemology: A Contemporary Introduction to the Theory of Knowledge , 1997 .

[4]  John E. Mottershead,et al.  Shape features and finite element model updating from full-field strain data , 2011 .

[5]  Hubert W. Schreier,et al.  Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts,Theory and Applications , 2009 .

[6]  Eann A. Patterson,et al.  On the integration of validation, quality assurance and non-destructive evaluation , 2013 .

[7]  Lee W. Schruben,et al.  Establishing the credibility of simulations , 1980 .

[8]  Eann A. Patterson,et al.  Decomposing Strain Maps Using Fourier-Zernike Shape Descriptors , 2011, Experimental Mechanics.

[9]  Brian L. Steward,et al.  Modeling and real-time simulation architectures for virtual prototyping of off-road vehicles , 2009, Virtual Reality.

[10]  D. Apelian,et al.  Aluminum nanocomposites for elevated temperature applications , 2011 .

[11]  Erwin Hack,et al.  An approach to the validation of computational solid mechanics models for strain analysis , 2013 .

[12]  Marius Stan,et al.  MULTI-SCALE MODELS AND SIMULATIONS OF NUCLEAR FUELS , 2009 .

[13]  David Andrs,et al.  An Object-Oriented Finite Element Framework for Multiphysics Phase Field Simulations , 2012 .

[14]  Eric Winsberg,et al.  Value judgements and the estimation of uncertainty in climate modeling , 2010 .

[15]  KwanSeong Jeong,et al.  The digital mock-up system to simulate and evaluate the dismantling scenarios for decommissioning of a NPP , 2014 .

[16]  Farhang Mozaffar,et al.  Smart-BIM virtual prototype implementation , 2014 .

[17]  Alex F. Sisti,et al.  Air Force hierarchy of models: a look inside the great pyramid , 2000, Defense, Security, and Sensing.

[18]  Eric J. Tuegel,et al.  The Airframe Digital Twin: Some Challenges to Realization , 2012 .

[19]  Benjamin W. Spencer,et al.  Verification of the BISON fuel performance code , 2014 .

[20]  Seung-Eock Kim,et al.  Effects of reinforcement ratio and arrangement on the structural behavior of a nuclear building under aircraft impact , 2014 .

[21]  Leonard E. Schwer,et al.  An overview of the PTC 60/V&V 10: guide for verification and validation in computational solid mechanics , 2007, Engineering with Computers.

[22]  Zeses E. Karoutas,et al.  CASL virtual reactor predictive simulation: Grid-to-Rod Fretting wear , 2011 .

[23]  Eann A. Patterson,et al.  On the credibility of engineering models and meta-models , 2015 .

[24]  Frank Schultmann,et al.  Building Information Modeling (BIM) for existing buildings — Literature review and future needs , 2014 .

[25]  Veena Tikare,et al.  Modeling and simulation of nuclear fuel materials , 2010 .

[26]  Rudy J. M. Konings,et al.  Basic research in support of innovative fuels design for the GEn IV systems: The F-Bridge project. , 2011 .

[27]  Norman Swindells.  Communicating and conserving digital data from nuclear science and engineering , 2014 .

[28]  Mikko Siuko,et al.  An interactive design approach for nuclear fusion purposes: remote handling system for FAST divertor , 2014 .

[29]  Ying Wang,et al.  Integrating Augmented Reality with Building Information Modeling: Onsite construction process controlling for liquefied natural gas industry , 2014 .

[30]  Joe Cecil,et al.  VREM: An advanced virtual environment for micro assembly , 2014 .

[31]  M. R. Wheatley,et al.  Long term preservation of scientific data: Lessons from jet and other domains , 2012 .

[32]  Michael N Louka,et al.  Comprehensive support for nuclear decommissioning based on 3D simulation and advanced user interface technologies , 2015 .