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Digital Twin for Multi-criteria Decision-Making Framework to Accelerate Fuel Qualification for Accident Tolerant Fuel Concepts

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Handbook of Smart Energy Systems

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Abstract

Accident-tolerant fuels and their licensing are one of the top priority strategic areas under “US Nuclear Regulation Committee (NRC) Systems Analysis Research Activities.” In addition, United States Department of Energy (DOE) has given significant attention for the advanced novel fuel, which can increase the burnup while exhibiting superior accident tolerance under “DOE Accident Tolerant Fuel Program” (under Fuel Cycle Research R&D). Therefore, this chapter focuses on the advanced composite accident-tolerant fuel systems. This chapter explains the integration of experiments with computational research efforts and data availability for the challenging qualification effort for accident-tolerant fuel concepts leveraging existing US DOE Accident-Tolerant Fuel Program’s industrial information. An overview of conventional empirical modeling reliance and its limitations in nuclear fuel development is also explained. The explanation of composite accident-tolerant fuel concepts leads to the concept development of digital twin and material twin technologies as a means to accelerate fuel qualification method, which can be leveraged in develo** and evaluating accident-tolerant fuel system. Most importantly, digital twin will pave the way for multi-criteria decision-making and risk-informed framework for both US DOE and US NRC for the new generation of accident-tolerant fuel concepts.

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References

  • S.B. Alam, C.S. Goodwin, G.T. Parks, Assembly-level analyses of accident-tolerant cladding concepts for a long-life civil marine SMR core using microheterogeneous duplex fuel. Prog. Nucl. Energy 111(September 2018), 24–41 (2019a)

    Article  Google Scholar 

  • S.B. Alam, R.G.G. de Oliveira, C.S. Goodwin, G.T. Parks, Coupled neutronic/thermal-hydraulic hot channel analysis of high power density civil marine SMR cores. Ann. Nucl. Energy 127, 400–411 (2019b)

    Article  Google Scholar 

  • B. Almutairi, S. Jaradat, D. Kumar, C.S. Goodwin, S. Usman, A. Alajo, S.B. Alam, Weight loss and burst testing investigations of sintered silicon carbide under oxidizing environments for next generation accident tolerant fuels for SMR applications. Mater. Today Commun. 30, 102958 (2022)

    Article  Google Scholar 

  • Ansys Software company. Ansys twin builder: Simulation-based hybrid analytic (datasheet), url: https://www.ansys.com/content/dam/product/digital-twin/twin-builder/ansys-twin-builder-technical-datasheet.pdf, (2022a)

  • Ansys Software company. Ansys twin builder (webpage), url: https://www.ansys.com/products/digital-twin/ansys-twin-builder, (2022b)

  • Ansys Software company. Build, validate and deploy simulation-based digital twins (video in the webpage), video url: https://share.vidyard.com/watch/myee78pdtm2c9xzybftsqv, page url: https://www.ansys.com/products/digital-twin/ansys-twin-builder, (2022c)

  • J. Bischoff, C. Delafoy, C. Vauglin, P. Barberis, C. Roubeyrie, D. Perche, D. Duthoo, F. Schuster, J.C. Brachet, E.W. Schweitzer, K. Nimishakavi, AREVA NP’s enhanced accident-tolerant fuel developments: Focus on Cr-coated M5 cladding. Nucl. Eng. Technol. 50(2), 223–228 (2018)

    Article  Google Scholar 

  • S. Chakraborty, S. Adhikari, R. Ganguli, The role of surrogate models in the development of digital twins of dynamic systems. ar**v:2001.09292 [cs, stat], Jun 2020. ar**v: 2001.09292

    Google Scholar 

  • Framatome. PROtect: The leading Enhanced Accident Tolerant Fuel Program, (n.d.)

    Google Scholar 

  • George Jacobsen and General Atomics Electromagnetic. On the Path to a Nuclear Fuel Digital Twin : Modeling and Simulation of Silicon Carbide Cladding for Accelerated Fuel Qualification, (n.d.)

    Google Scholar 

  • R. Ghanem, C. Soize, L. Mehrez, V. Aitharaju, Probabilistic learning and updating of a digital twin for composite material systems. Int. J. Num. Methods Eng., On line:1, (2020)

    Google Scholar 

  • B. Gong, T. Yao, P. Lei, C. Lu, K.E. Metzger, E.J. Lahoda, F.A. Boylan, A. Mohamad, J. Harp, A.T. Nelson, J. Lian, U3Si2 and UO2 composites densified by spark plasma sintering for accident-tolerant fuels. J. Nucl. Mater. 534, 152147 (2020a)

    Article  Google Scholar 

  • B. Gong, T. Yao, P. Lei, J. Harp, A.T. Nelson, J. Lian, Spark plasma sintering (SPS) densified U3Si2 pellets: Microstructure control and enhanced mechanical and oxidation properties. J. Alloys Compd. 825, 154022 (2020b)

    Article  Google Scholar 

  • M. Große, M. Steinbrück, J. Stuckert, Steam and air oxidation behavior of nuclear fuel claddings at severe accident conditions. Mater. Res. Soc. Sympos. Proc. 1264, 215–220 (2010)

    Article  Google Scholar 

  • S.L. Hayes, J.K. Thomas, K.L. Peddicord, Material property correlations for uranium mononitride. IV. Thermodynamic properties. J. Nucl. Mater. 171(2–3), 300–318 (1990)

    Article  Google Scholar 

  • S. He, J. Cai, Thermal hydraulic analysis of the PWR with high uranium density accident tolerant fuels under accident transients with and without reactivity. Nucl. Eng. Des. 355(July), 110358 (2019)

    Article  Google Scholar 

  • S.M. Homam, S.A. Sheikh, Fiber-reinforced polymers exposed to nuclear power plant environment. J. Comp. Construct. 17(6), 04013007 (2013)

    Article  Google Scholar 

  • W. Huang, X. Rui, J. Yang, Q. Huang, H. Heng, Data-driven multiscale simulation of frp based on material twins. Compos. Struct. 256, 113013 (2021)

    Article  Google Scholar 

  • M. Jolkkonen, P. Malkki, K. Johnson, J. Wallenius, Uranium nitride fuels in superheated steam. J. Nucl. Sci. Technol. 54(5), 513–519 (2017)

    Article  Google Scholar 

  • C.A. Junior, J. Villanueva, I. Medeiros, R. Almeida, Digital twin design for thermal power plant cooling system using fuzzy system, in 2021 14th IEEE International Conference on Industry Applications (INDUSCON), (INDUSCON, 2021), pp. 661–666

    Chapter  Google Scholar 

  • B. Kochunas, X. Huan, Digital twin concepts with uncertainty for nuclear power applications. Energies 14(1414), 4235 (2021)

    Article  Google Scholar 

  • T. Koyanagi, Y. Katoh, G. Singh, M. Snead, SiC/SiC Cladding Materials Properties Handbook (Number August in M3-FT17OR020202104. U.S. Department of Energy, 2017)

    Google Scholar 

  • D. Kumar, S.B. Alam, D. Vučinić, C. Lacor, Uncertainty quantification and robust optimization in engineering. Lect. Notes Mech. Eng., 63–93 (2020)

    Google Scholar 

  • D. Kumar, S. Alam, T. Ridwan, C.S. Goodwin, Quantitative risk assessment of a high power density small modular reactor (SMR) core using uncertainty and sensitivity analyses. Energy 227, 120400 (2021)

    Article  Google Scholar 

  • D. Kumar, M. Marchi, S.B. Alam, C. Kavka, Y. Koutsawa, G. Rauchs, S. Belouettar, Multi-criteria decision making under uncertainties in composite materials selection and design. Compos. Struct. 279(February 2021), 114680 (2022)

    Article  Google Scholar 

  • L. Lin, H. Bao, N. Dinh, Uncertainty quantification and software risk analysis for digital twins in the nearly autonomous management and control systems: A review. Ann. Nucl. Energy 160, 108362 (2021)

    Article  Google Scholar 

  • J.P. Moore, D.L. Mcelroy, Thermal conductivity o f nearly stoic h iomet ric single-C rystal and polycrystalline UO. J. Am. Ceram. Soc. 54(1), 40–46 (1970)

    Article  Google Scholar 

  • A.T. Nelson, Stability of U3Si2 under H2O/PWR Coolant Conditions, LA-UR-17-30041 (Technical report, Los Alamos Natinal Laboratory (INL), 2017)

    Google Scholar 

  • S. Nichenko, D. Staicu, Thermal conductivity of porous uo2: Molecular dynamics study. J. Nucl. Mater. 454(1), 315–322 (2014)

    Article  Google Scholar 

  • L.H. Ortega, B.J. Blamer, J.A. Evans, S.M. McDeavitt, Development of an accident-tolerant fuel composite from uranium mononitride (UN) and uranium sesquisilicide (U3 Si2) with increased uranium loading. J. Nucl. Mater. 471, 116–121 (2016)

    Article  Google Scholar 

  • L.J. Ott, K.R. Robb, D. Wang, Preliminary assessment of accident-tolerant fuels on LWR performance during normal operation and under DB and BDB accident conditions. J. Nucl. Mater. 448(1–3), 520–533 (2014)

    Article  Google Scholar 

  • D. Ribeiro, M. Hedberg, S.C. Middleburgh, J. Wallenius, P. Olsson, D. Adorno, Oxidation of UN / U 2 N 3 -UO 2 composites : An evaluation of UO 2 as an oxidation barrier for the nitride phases. J. Nucl. Mater. 544, 152700 (2021)

    Article  Google Scholar 

  • Q. Shao, A. Makradi, D. Fiorelli, A. Mikdam, W. Huang, H. Hu, S. Belouettar, Material twin for composite material microstructure generation and reconstruction. Comp. Part C: Open Access 7, 100216 (2022)

    Google Scholar 

  • B. Szpunar, J.A. Szpunar, Thermal conductivity of uranium nitride and carbide. Int. J. Nucl. Energy 2014, 1–7 (2014)

    Article  Google Scholar 

  • F. Tao, Q. Qi, L. Wang, A.Y.C. Nee, Digital twins and cyber–physical systems toward smart manufacturing and Industry 4.0: Correlation and comparison. Engineering 5(4), 653–661 (2019)

    Article  Google Scholar 

  • M.R. Tonks, D. Andersson, S.R. Phillpot, Y. Zhang, R. Williamson, C.R. Stanek, B.P. Uberuaga, S.L. Hayes, Mechanistic materials modeling for nuclear fuel performance. Ann. Nucl. Energy 105, 11–24 (2017)

    Article  Google Scholar 

  • M. Uno, T. Nishi, M. Takano, Thermodynamic and Thermophysical Properties of the Actinide Nitrides, Volume 2 (Elsevier Inc, 2012)

    Google Scholar 

  • Westinghouse, EnCore Fuel (Westinghouse Electric Company, Pennsylvania, 2019), p. 16066

    Google Scholar 

  • J.T. White, A.T. Nelson, Thermal conductivity of UO2+x and U4O9-y. J. Nucl. Mater. 443(1–3), 342–350 (2013)

    Article  Google Scholar 

  • J.T. White, A.T. Nelson, J.T. Dunwoody, D.D. Byler, D.J. Safarik, K.J. Mcclellan, Thermophysical properties of U3Si2 to 1773 K. J. Nucl. Mater. 464, 275–280 (2015)

    Article  Google Scholar 

  • J.H. Yang, D.J. Kim, K.S. Kim, Y.H. Koo, UO2-UN composites with enhanced uranium density and thermal conductivity. J. Nucl. Mater. 465, 509–515 (2015)

    Article  Google Scholar 

  • K. Yang, E. Kardoulaki, D. Zhao, A. Broussard, K. Metzger, J.T. White, M.R. Sivack, K.J. Mcclellan, E.J. Lahoda, J. Lian, Uranium nitride (UN) pellets with controllable microstructure and phase – Fabrication by spark plasma sintering and their thermal-mechanical and oxidation properties. J. Nucl. Mater. 557, 153272 (2021)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Nuclear Engineering and Radiation Science, Missouri University of Science and Technology, Rolla, MO, USA

    Kazuma Kobayashi, Brandon Bloss, Alexander Foutch, Brenden Kelly, Ayodeji Alajo, Carlos H. C. Giraldo & Syed Alam

  2. Department of Mechanical Engineering, University of Bristol, Bristol, UK

    Dinesh Kumar

Authors
  1. Kazuma Kobayashi
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  2. Brandon Bloss
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  3. Alexander Foutch
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  4. Brenden Kelly
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  5. Ayodeji Alajo
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  6. Carlos H. C. Giraldo
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  7. Dinesh Kumar
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  8. Syed Alam
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Corresponding author

Correspondence to Syed Alam .

Editor information

Editors and Affiliations

  1. Information Technology and Decision Sciences, University of North Texas, Denton, TX, USA

    Michel Fathi

  2. Centre for research on Risks and Crises (CRC), Mines Paris-PSL University, Sophia Antipolis, France

    Enrico Zio

  3. Industrial & Systems Engineering, University of Florida, GAINESVILLE, FL, USA

    Panos M. Pardalos

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Kobayashi, K. et al. (2023). Digital Twin for Multi-criteria Decision-Making Framework to Accelerate Fuel Qualification for Accident Tolerant Fuel Concepts. In: Fathi, M., Zio, E., Pardalos, P.M. (eds) Handbook of Smart Energy Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-97940-9_160

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