Inverse optimization design of heat transfer performance for the reactor pressure vessel insulation structure based on reduced-order model

ZHAO Jie; DAI Yanjun; WANG Yungang; GUO Zhenyuan; BAI Fan

doi:10.3724/j.0253-3219.2026.hjs.49.240552

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Inverse optimization design of heat transfer performance for the reactor pressure vessel insulation structure based on reduced-order model

NUCLEAR ENERGY SCIENCE AND ENGINEERING | 更新时间：2026-01-19

- Inverse optimization design of heat transfer performance for the reactor pressure vessel insulation structure based on reduced-order model
- NUCLEAR TECHNIQUES Vol. 49, Issue 1, Article number: 010608(2026)
- 作者机构：
  
  西安交通大学能源与动力工程学院西安 710049
- 作者简介：
  
  ZHAO Jie, male, born in 1998, graduated from Xi'an Jiaotong University with a master's degree, doctoral student, focusing on flow and heat transfer in reactor pressure vessels
  DAI Yanjun, E-mail: daiyanjun2015@xjtu.edu.cn
- 基金信息：
  
  National Natural Science Foundation of China General Program(52276085)
- DOI：10.3724/j.0253-3219.2026.hjs.49.240552
  CLC： TL35
- Received：29 December 2024，
  
  Revised：2025-02-22，
  
  Published：15 January 2026
- 稿件说明：
移动端阅览
赵杰,戴艳俊,王云刚等.基于降阶模型的反应堆压力容器保温结构传热性能逆优化设计[J].核技术,2026,49(01):010608.

ZHAO Jie,DAI Yanjun,WANG Yungang,et al.Inverse optimization design of heat transfer performance for the reactor pressure vessel insulation structure based on reduced-order model[J].NUCLEAR TECHNIQUES,2026,49(01):010608.
赵杰,戴艳俊,王云刚等.基于降阶模型的反应堆压力容器保温结构传热性能逆优化设计[J].核技术,2026,49(01):010608. DOI： 10.3724/j.0253-3219.2026.hjs.49.240552. CSTR： 32193.14.hjs.CN31-1342/TL.2026.49.240552.

ZHAO Jie,DAI Yanjun,WANG Yungang,et al.Inverse optimization design of heat transfer performance for the reactor pressure vessel insulation structure based on reduced-order model[J].NUCLEAR TECHNIQUES,2026,49(01):010608. DOI： 10.3724/j.0253-3219.2026.hjs.49.240552. CSTR： 32193.14.hjs.CN31-1342/TL.2026.49.240552.

摘要

为了改善反应堆压力容器（Reactor Pressure Vessel，RPV）保温结构在正常运行条件下的热泄漏现象，合理的参数设计对其安全运行至关重要。然而，传统的试错法设计低效，且难以从众多的变量中识别出最佳的参数组合。本文提出了一种基于本征正交分解（Proper Orthogonal Decomposition，POD）的逆设计方法，旨在提高RPV保温结构传热性能。首先，将保温层外壁平均热流（

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524442&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524454&type=

4.14866638

3.89466691

）、平均温度（

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524469&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524468&type=

4.40266657

3.21733332

）以及混凝土局部最高温度（

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524471&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524470&type=

4.99533367

3.21733332

）作为优化目标，利用计算流体动力学（Computational Fluid Dynamics，CFD）方法生成24组工况作为POD快照。其次，利用验证后的POD方法重构了275组工况以反映设计变量与优化目标间的映射关系。最后，定义了一个百分制无量纲参数（

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524486&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524460&type=

5.67266655

3.21733332

）来评价其综合传热性能。研究结果表明：POD重构结果有效地保留了原始物理场信息，其预测的平均决定系数（

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524474&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524487&type=

2.96333337

2.53999996

）超过0.95，平均相对偏差（Mean Relative Deviation，MRD）低于2.87%。同时，相比于CFD方法能够节省约99%的CPU时间。结果表明：综合分数

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524464&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=98524463&type=

5.67266655

3.21733332

为97.4的变量组合（2 mm-16 ℃-309.5 ℃）性能最佳，与RPV保温结构原型设计相比综合传热性能提高了59.2%。

Abstract

Background

Thermal leakage in reactor pressure vessel (RPV) insulation structure poses safety risks

and traditional trial-and-error parameter optimization methods are inefficient for handling complex variables.

Purpose

This study aims to develop a proper orthogonal decomposition (POD)-based inverse design methodology to enhance the thermal performance of RPV insulation structure.

Methods

Firstly

three design variables (air supply temperature

RPV outer wall temperature

and installation gap) and their corresponding level numbers were systematically determined

and three optimization objectives were defined as average heat flux (

ave

)

average temperature (

ave

) on the RPV insulation's outer wall

and maximum local temperature (

max

) of the concrete. Then

a comprehensive dataset comprising 24 computational fluid dynamics (CFD) simulations was generated through full factorial design method

with these computational results employed as POD snapshots. Finally

the validated POD method was employed to reconstruct 275 working condition cases

and a dimensionless comprehensive score (FPOD) on a percentage scale was established to evaluate the overall heat transfer performance based on the three optimization objectives.

Results

Calculation results show the POD reconstruction achieved high fidelity is achieved by the POD reconstruction

with an average determination coefficient (

) exceeding 0.95 and mean relative deviation (MRD) below 2.87%

while reducing CPU time is reduced by 99% compared to CFD. The optimal variable combination (2 mm-16 ℃-309.5 ℃) yieldeds a comprehensive score (

POD

) of 97.4

improving overall heat transfer performance by 59.2% over the original design.

Conclusions

Results of this study demonstrate that the POD-based inverse design methodology provides an efficient and accurate approach for RPV insulation structure optimization. The optimal parameter combination achieves significant improvements in thermal performance

with

ave

reduced to 84.89 W·m

-2

ave

to 35.21 ℃

and

max

to 72.86 ℃

which significantly enhances the safety and operational efficiency of RPV insulation structure.

关键词

Keywords

references

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