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Uncertainty analysis framework of MPS and implementation in the simulation of MCCI phenomenon.

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Title: Uncertainty analysis framework of MPS and implementation in the simulation of MCCI phenomenon.
Authors: Xiao, Xinkun1 (AUTHOR), Cai, Qinghang2 (AUTHOR), Li, Tianrui1 (AUTHOR), Chen, Ronghua1 (AUTHOR) rhchen@mail.xjtu.edu.cn, Su, Guanghui1 (AUTHOR)
Source: Computers & Mathematics with Applications. Apr2026, Vol. 207, p116-136. 21p.
Subjects: Particle methods (Numerical analysis), Sensitivity analysis, Reduced-order models, Nuclear reactor safety measures, Long short-term memory, Risk assessment
Abstract: This study establishes the Moving Particle Semi-implicit Plus Uncertainty (MPSPU) framework to enable rigorous uncertainty quantification (UQ) for particle-based simulations in nuclear reactor safety analysis. Designed to extend the Best Estimate Plus Uncertainty (BEPU) methodology, MPSPU addresses the specific challenges of Lagrangian particle methods while maintaining compatibility with existing regulatory assessment protocols. The framework is validated using the SURC-4 experiment, which simulates the Molten Core–Concrete Interaction (MCCI) phenomenon. A critical advancement is the formulation of a time-dependent sensitivity analysis, which reveals that melt temperature is the dominant driver governing early-stage MCCI behavior. Furthermore, a comparative evaluation of surrogate models for MPS time-series data identifies Long Short-Term Memory (LSTM) networks as the optimal architecture, outperforming conventional polynomial and neural network approaches. To demonstrate the framework's practical utility, an end-to-end calculation example is presented, illustrating the complete workflow from raw simulation data to regulatory-grade risk metrics. This example explicitly quantifies the conditional failure probability of concrete ablation depth against safety limits, showcasing the framework's ability to support risk-informed decision-making. Ultimately, this work provides a systematic pathway for integrating particle methods into safety analysis. [ABSTRACT FROM AUTHOR]
Copyright of Computers & Mathematics with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 192228290
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Uncertainty analysis framework of MPS and implementation in the simulation of MCCI phenomenon.
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  Data: <searchLink fieldCode="AR" term="%22Xiao%2C+Xinkun%22">Xiao, Xinkun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cai%2C+Qinghang%22">Cai, Qinghang</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Tianrui%22">Li, Tianrui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Ronghua%22">Chen, Ronghua</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> rhchen@mail.xjtu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Su%2C+Guanghui%22">Su, Guanghui</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Computers+%26+Mathematics+with+Applications%22">Computers & Mathematics with Applications</searchLink>. Apr2026, Vol. 207, p116-136. 21p.
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  Data: <searchLink fieldCode="DE" term="%22Particle+methods+%28Numerical+analysis%29%22">Particle methods (Numerical analysis)</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Reduced-order+models%22">Reduced-order models</searchLink><br /><searchLink fieldCode="DE" term="%22Nuclear+reactor+safety+measures%22">Nuclear reactor safety measures</searchLink><br /><searchLink fieldCode="DE" term="%22Long+short-term+memory%22">Long short-term memory</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study establishes the Moving Particle Semi-implicit Plus Uncertainty (MPSPU) framework to enable rigorous uncertainty quantification (UQ) for particle-based simulations in nuclear reactor safety analysis. Designed to extend the Best Estimate Plus Uncertainty (BEPU) methodology, MPSPU addresses the specific challenges of Lagrangian particle methods while maintaining compatibility with existing regulatory assessment protocols. The framework is validated using the SURC-4 experiment, which simulates the Molten Core–Concrete Interaction (MCCI) phenomenon. A critical advancement is the formulation of a time-dependent sensitivity analysis, which reveals that melt temperature is the dominant driver governing early-stage MCCI behavior. Furthermore, a comparative evaluation of surrogate models for MPS time-series data identifies Long Short-Term Memory (LSTM) networks as the optimal architecture, outperforming conventional polynomial and neural network approaches. To demonstrate the framework's practical utility, an end-to-end calculation example is presented, illustrating the complete workflow from raw simulation data to regulatory-grade risk metrics. This example explicitly quantifies the conditional failure probability of concrete ablation depth against safety limits, showcasing the framework's ability to support risk-informed decision-making. Ultimately, this work provides a systematic pathway for integrating particle methods into safety analysis. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Computers & Mathematics with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.camwa.2026.01.031
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      – Code: eng
        Text: English
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        PageCount: 21
        StartPage: 116
    Subjects:
      – SubjectFull: Particle methods (Numerical analysis)
        Type: general
      – SubjectFull: Sensitivity analysis
        Type: general
      – SubjectFull: Reduced-order models
        Type: general
      – SubjectFull: Nuclear reactor safety measures
        Type: general
      – SubjectFull: Long short-term memory
        Type: general
      – SubjectFull: Risk assessment
        Type: general
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      – TitleFull: Uncertainty analysis framework of MPS and implementation in the simulation of MCCI phenomenon.
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            NameFull: Xiao, Xinkun
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            NameFull: Cai, Qinghang
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            NameFull: Li, Tianrui
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            NameFull: Chen, Ronghua
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            NameFull: Su, Guanghui
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            – D: 01
              M: 04
              Text: Apr2026
              Type: published
              Y: 2026
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              Value: 207
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