Annals of Nuclear Energy最新文献_第2页

Transient thermal diffusion analysis and failure prediction in heat-pipe-cooled reactors 热管冷却堆瞬态热扩散分析及失效预测

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-09 DOI: 10.1016/j.anucene.2026.112120

Jiaqing Zhang, Xiao Zhang, Wenxiao Chu, Qiuwang Wang

Heat pipe cooled reactors (HPCRs) rely on thermal conduction to transfer heat from the reactor core, where the thermal reliability becomes a critical concern. Studies on the temperature dynamic response due to random heat pipe (HP) failures and the prediction of specific heat pipes through temperature distribution analysis are the key challenges. This study investigates the spatial thermal diffusion mechanism and temperature dynamic response characteristics in the HPCR core during random HP failure processes using experimental and numerical methods. Moreover, the Random Forest algorithm method is introduced to predict HP failure locations. Results indicate that boundary HP failure (HP-A) exhibits a broader critical failure diffusion radius of 65.1 mm and diffusion angle of 190°, while central HP failure (HP-D) causes minimal disturbance and results in more uniform temperature gradient distributions. Correspondingly, the dynamic response time constant and response delay time are employed to quantitatively feature the temperature field evolution during HP failure. For HP-A, the time constant and response delay time are 5040 s and 170 s, respectively, compared to 10,950 and 550 s for HP-D. Additionally, two patterns with single and dual HP failures and four HP failure orientations are predicted by the Random Forest algorithm method. Results demonstrate the prediction accuracy of 97.1 %, with a failure time prediction error ranging from −0.7 % to 1.6 %.

热管冷却堆依靠热传导从堆芯传递热量，其热可靠性成为一个关键问题。研究随机热管（HP）失效时的温度动态响应以及通过温度分布分析预测比热管是关键挑战。采用实验和数值方法研究了高压随机失效过程中HPCR芯内的空间热扩散机制和温度动态响应特征。在此基础上，引入随机森林算法对HP故障位置进行预测。结果表明，边界HP失效（HP- a）的临界失效扩散半径为65.1 mm，扩散角为190°，而中心HP失效（HP- d）的扰动最小，温度梯度分布更均匀。相应的，采用动态响应时间常数和响应延迟时间来定量表征高温高压失效时温度场的演变。HP-A的时间常数和响应延迟时间分别为5040 s和170 s， HP-D的时间常数和响应延迟时间分别为10950 s和550 s。此外，利用随机森林算法预测了单HP故障和双HP故障的两种模式以及四种HP故障方向。结果表明，预测精度为97.1%，故障时间预测误差为- 0.7% ~ 1.6%。

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引用次数: 0

Evaluation of ENDF/B-VIII.0 nuclear data for criticality calculations using machine learning and the SHAP interpretability method ENDF/B-VIII的评价。使用机器学习和SHAP可解释性方法进行临界计算的0核数据

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-08 DOI: 10.1016/j.anucene.2026.112126

M. Hadouachi , K. Laazouzi , O. Belhaj , H. El Yaakoubi , A. Arectout , Abdelhamid Nouayti , H. Boukhal , E. Chakir , T. El Bardouni

In nuclear reactor criticality and stability studies, nuclear data uncertainties can significantly influence integral parameters such as the effective multiplication factor and neutron flux, which are directly linked to reactor safety margins and operational performance. It is therefore essential to quantify the impact of nuclear data uncertainties on reactor calculations. In this work, machine learning techniques were applied to identify the nuclear data that have the greatest impact on criticality calculations. For this purpose, sensitivity profiles, combined with other benchmark characteristics, were used as input features for various machine learning algorithms to predict the bias

Δ k_{eff}

. In order to interpret the model’s predictions, a SHAP (SHapley Additive exPlanations) analysis was applied to determine which reactions had the greatest influence on (k

_{eff}

) bias. The results highlight that nuclear data for nuclides such as ²³⁹Pu, ²³⁵U, ²³³U, ²³⁸U, ¹²C, and ¹H are the most important parameters related to a high

Δ k_{eff}

.

在核反应堆临界和稳定性研究中，核数据的不确定性会显著影响有效乘法系数和中子通量等积分参数，这些参数直接关系到反应堆的安全裕度和运行性能。因此，必须量化核数据不确定性对反应堆计算的影响。在这项工作中，机器学习技术被应用于识别对临界计算影响最大的核数据。为此，灵敏度曲线结合其他基准特征作为各种机器学习算法的输入特征来预测偏差Δkeff。为了解释模型的预测，应用SHAP （SHapley Additive explanation）分析来确定哪些反应对（keff）偏差的影响最大。结果表明，239Pu、235U、233U、238U、12C和1H等核素的核数据是与高Δkeff相关的最重要参数。

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引用次数: 0

Design and performance analysis of high-power lead-bismuth cooled micro reactor 大功率铅铋冷却微堆设计与性能分析

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-08 DOI: 10.1016/j.anucene.2026.112115

Yiming Xiong, Ren Li, Jilin Sun, Yuandong Zhang, Genglei Xia, Minjun Peng

With the wide range of sea applications of reactors, it is necessary to develop a high-power LBE reactor with a small volume and high-power output. A process of core design is proposed in this paper for conducting rapid iterations. With this process and a series of design criteria and guidelines, the concept of the High-Power Lead-Bismuth Cooled Micro Reactor (HLCMR) is designed. This design adopts low-enriched fuel and two sets of independent shut-down control systems, which are arranged in a triangular pattern to achieve higher power density and lower power peak. After iterative design, the design power is 12 MW, and the lifetime is at least 5 years with the core power density of 76.72 MW/m³. The power distribution shows that the highest power peak is 1.444 in the operating state. The temperature field and reactivity are also calculated to evaluate the safety and reliability of this design. The results show that all parameters of the HLCMR meet the thermal–hydraulic and control design requirements.

随着反应器在海上的广泛应用，研制体积小、输出功率大的大功率LBE反应器势在必行。提出了一种快速迭代的核心设计流程。根据这一过程和一系列设计准则和指导方针，设计了大功率铅铋冷却微堆（HLCMR）的概念。本设计采用低浓度燃料和两套独立的停机控制系统，以三角形的形式布置，以达到更高的功率密度和更低的功率峰值。经迭代设计，设计功率为12 MW，寿命至少5年，堆芯功率密度为76.72 MW/m3。由功率分布可知，在运行状态下，最高功率峰值为1.444。计算了温度场和反应性，评价了设计的安全性和可靠性。结果表明，HLCMR的各项参数均满足热液和控制设计要求。

引用次数: 0

Preliminary design and front-end fuel cycle assessment of 200 MWt marine molten chloride fast reactor 200mwt船用氯熔快堆初步设计及前端燃料循环评价

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-08 DOI: 10.1016/j.anucene.2026.112124

Andika Putra Dwijayanto , Kenji Nishihara , Tomohiro Okamura , Masahiko Nakase

The molten Chloride Fast Reactor (MCFR) emerges as one of the advanced nuclear reactor designs for use in a nuclear marine propulsion. This paper delineates the preliminary design of a 200 MWt Marine MCFR (MMCFR) intended as a propulsion for zero-carbon large container ship, focusing on the neutronic analysis and fuel cycle assessment. The MMCFR employs eutectic 66NaCl-34UCl₃ as the fuel with 19.55 wt% enriched uranium as the initial fuel contained in a BeO-reflected core, operated as a long-lived core and batchwise refuelling to simplify reactivity control and refuelling mechanism in a constrained space. As the MMCFR is designed with a compact core and large initial reactivity, the innovative Partial Fuel Change scheme is proposed to optimise fuel consumption and reduce the strain in the front-end fuel cycle, with Constant Mol or Constant Replacement scenario. Initial reactivity is suppressed using burnable absorber (BA) rods and control drums are used to control the reactivity and core shutdown. Neutronic and depletion calculations for the MMCFR design were performed using Serpent-2 code and ENDF/B-VII.0 library. The optimum front-end fuel cycle was obtained to be Constant Replacement scenario with lowest uranium consumption. Meanwhile, excess reactivity can be maintained below 5% throughout operational time by using BA and control drum, whilst temperature coefficient of reactivity (TCR) is sufficiently negative, ensuring the MMCFR fulfils the safety criteria.

熔融氯化物快堆（MCFR）是用于核动力船舶推进的先进核反应堆设计之一。本文描述了用于零碳大型集装箱船推进的200 MMCFR （MMCFR）的初步设计，重点介绍了中子分析和燃料循环评估。MMCFR采用共晶66NaCl-34UCl3作为燃料，初始燃料为19.55 wt%的浓缩铀，包含在beo反射堆芯中，作为长寿命堆芯运行，批量换料以简化反应性控制和在有限空间内换料机制。由于MMCFR设计具有紧凑的核心和大的初始反应性，因此提出了创新的部分燃料更换方案，以优化燃料消耗并减少前端燃料循环中的应变，采用恒定摩尔或恒定更换方案。使用可燃吸收棒抑制初始反应性，使用控制鼓来控制反应性和堆芯停机。使用Serpent-2代码和ENDF/B-VII进行了MMCFR设计的中子和耗尽计算。0图书馆。得到了最优的前端燃料循环是铀消耗量最低的持续替换方案。同时，通过使用BA和控制鼓，可以在整个运行时间内将过量反应性保持在5%以下，同时反应性温度系数（TCR）足够负，确保MMCFR符合安全标准。

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引用次数: 0

Analysis of the blowdown of supercritical carbon dioxide from simple vessel 简单容器中超临界二氧化碳排放的分析

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.anucene.2025.112110

Fengyuan Tian , Minyun Liu , Yanping Huang , Ruohan Zheng , Yangle Wang , Houjun Gong , Yu Tang , Tianzeng Liu , Jinghan Hu , Haohan Yuan , Yuan Zhou

The depressurization accident is one of the key problems during the transport and utilization of S-CO₂. In this paper, an analysis model was developed to analyze the blowdown of S-CO₂ from a simple vessel. The critical mass flow rate agreed well with experiment results, and the maximum error is less than 10%. As for the depressurization model, the homogeneous model could predict pressure and temperature, and the phase separation model and bubble rise model could predict the mass flow rate. Depressurization under different initial parameters, back pressures, breaks were analyzed. Results indicated that when the initial temperature exceeds a certain temperature, the pressure and mass flow rate would change smoothly. When the initial temperature is lower, the depressurization process could be divided into rapid depressurization, flash vaporization, and slow depressurization. The model developed may reflect the characteristics of depressurization and provide a reference for depressurization accidents of the S-CO₂ system.

减压事故是S-CO2输送和利用过程中的关键问题之一。本文建立了一个简单容器S-CO2排放分析模型。临界质量流量与实验结果吻合较好，最大误差小于10%。减压模型中均相模型可以预测压力和温度，相分离模型和气泡上升模型可以预测质量流量。分析了不同初始参数、背压、破断条件下的减压效果。结果表明，当初始温度超过一定温度时，压力和质量流量变化平缓。当初始温度较低时，减压过程可分为快速减压、闪蒸和慢速减压。所建立的模型可以反映出S-CO2系统的降压特性，为S-CO2系统的降压事故提供参考。

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引用次数: 0

Calculation and analysis of self-shielded cross sections for the high-fidelity neutronics calculation of fast reactors 快堆高保真中子计算中自屏蔽截面的计算与分析

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.anucene.2025.112103

Xiang Li, Zhouyu Liu, Wenjie Chen, Liangzhi Cao, Hongchun Wu

A new high-fidelity neutronics analysis tool for fast reactor calculations is built by coupling the lattice code TULIP, the SN code HYDRA and the high-fidelity neutron transport code NECP-X. TULIP is employed to generate multigroup effective cross sections for assemblies based on the 0-D or 1-D cylindrical model. HYDRA utilizes a reactor core-reflector model to perform group condensation for reflector. The cross sections are passed to NECP-X to conduct a whole-core simulation with explicit geometry description. Verifications were conducted based on the Superphénix 2-D, MET-1000 2-D and JOYO MK-I 3-D core problems. The reference solutions were obtained through Monte Carlo calculations with NECP-MCX. The difference of k_eff was at most 298 pcm for 2-D problems and did not exceed 55 pcm for 3-D problem. The root mean square error of assembly power was a maximum of only 1 %. These results prove the capability of this method in fast reactor calculations.

将晶格码TULIP、SN码HYDRA和高保真中子输运码NECP-X耦合在一起，建立了一个用于快堆计算的高保真中子分析工具。基于0-D或1-D圆柱模型，采用TULIP生成组件的多组有效截面。HYDRA利用反应堆堆芯-反射器模型对反射器进行群凝结。将截面传递给NECP-X进行具有显式几何描述的全核模拟。基于superphacimnix二维、MET-1000二维和JOYO MK-I三维岩心问题进行了验证。利用NECP-MCX进行蒙特卡罗计算得到参考解。二维问题的keff差异最多为298 pcm，三维问题的keff差异不超过55 pcm。装配功率的均方根误差最大仅为1%。这些结果证明了该方法在快堆计算中的能力。

引用次数: 0

Free convective condensation in the presence of noncondensable gases − A review with heat transfer studies 不可冷凝气体存在下的自由对流冷凝-传热研究综述

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.anucene.2025.112099

NK Maheshwari, Divij Kishal

Steam condensation plays a key role in removing heat from the containment in case of a postulated accident in water-cooled nuclear reactors. Steam released into the containment mixes with air present in that environment and condenses in the presence of noncondensable gases (air, helium, etc.) on the containment wall and other structures present in the containment. Advanced reactors design adopts passive containment cooling systems for long term containment cooling during the design basis and severe accident conditions. In this article, the research performed on free convective condensation in the presence of noncondensable gases on the tube outer surface has been reviewed. In the first part of the article, experimental studies have been covered. It is revealed that both the thermal hydraulic and geometrical parameters affect the condensation heat transfer in the presence of noncondensable gases. In the second part, various correlations developed by researchers are discussed accounting for thermal hydraulic, geometric parameters and nondimensional numbers; an assessment of these correlations is performed. In the third part, the theoretical model developed, results obtained and CFD studies performed by previous authors have been discussed. The effects of various parameters are discussed on the basis of experimental work and theoretical model developed. Finally, based on the review and studies performed, a summary is provided.

在水冷核反应堆发生假想事故的情况下，蒸汽冷凝在从安全壳中除去热量方面起着关键作用。释放到安全壳中的蒸汽与该环境中的空气混合，并在安全壳壁和安全壳中存在的其他结构上存在不可冷凝气体（空气，氦气等）的情况下凝结。先进反应堆设计采用被动式安全壳冷却系统，在设计基础和严重事故条件下进行长期安全壳冷却。本文综述了管内外表面存在不凝性气体时自由对流冷凝的研究进展。在文章的第一部分，已经涵盖了实验研究。结果表明，在不凝性气体存在的情况下，热工参数和几何参数对冷凝换热都有影响。在第二部分，讨论了研究人员开发的各种关联，考虑了热水力、几何参数和无因次数；对这些相关性进行评估。在第三部分，理论模型的建立，得到的结果和CFD研究进行了讨论。在实验工作和建立理论模型的基础上，讨论了各种参数的影响。最后，在回顾和研究的基础上，对本文进行了总结。

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引用次数: 0

Unsteady hydrodynamics of an RCP impeller across clearances and hot conditions pressure pulsation, spectral shift, and radial force RCP叶轮在间隙和高温条件下的非定常流体动力学研究压力脉动、谱移和径向力

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.anucene.2026.112113

Yuan Xu , Yun Long , Long Cai , Zhe Jiao

We investigate unsteady hydrodynamics of a shaft-sealed reactor coolant pump (RCP) across cold/hot states (25 °C/292 °C; 1/15.9 MPa) and tip-clearance variations from the design tip clearance of 0.8 mm (0.5 mm smaller and 1.0 mm and 2.0 mm larger than the design value). Using SST k–ω CFD with rotor–stator coupling, we quantify performance, pressure-pulsation spectra, and radial forces. Dominant components occur at the shaft frequency (1fn≈24.75 Hz) and diffuser blade-passing (5fn≈123.75 Hz), with a leading-peak shift to 5fn near the impeller outlet. Hot conditions intensify pulsations and radial loading and smooth the performance curve; at ∼ 1.2Q the hot-state head is ∼ 5 % higher. The radial force shows periodic modulation (≈3.22–3.42 kN) and a five-lobe pattern. Clearance changes alter head and spectra: +2 mm reduces head and elevates 5fn, whereas − 0.5 mm improves uniformity and still lowers head. These results provide a spectral-shift–load-coupled basis for clearance tolerance and operating-window selection to enhance RCP stability and safety.

我们研究了轴封式反应堆冷却剂泵（RCP）在冷/热状态（25°C/292°C; 1/15.9 MPa）下的非定常流体动力学，以及从设计尖端间隙0.8 mm（比设计值小0.5 mm，比设计值大1.0 mm和2.0 mm）开始的尖端间隙变化。使用SST k -ω CFD与转子-定子耦合，我们量化性能，压力脉动谱和径向力。主导分量出现在轴频（1fn≈24.75 Hz）和扩散器叶片通过（5fn≈123.75 Hz）处，在叶轮出口附近的导峰移至5fn。高温条件加剧了脉动和径向载荷，使性能曲线变得平滑；在~ 1.2Q时，热态水头高~ 5%。径向力表现为周期调制（≈3.22-3.42 kN）和五瓣模式。间隙改变了水头和光谱：+ 2mm降低了水头，提高了5fn，而- 0.5 mm提高了均匀性，但仍降低了水头。这些结果为间隙公差和操作窗口选择提供了光谱位移-负载耦合基础，以提高RCP的稳定性和安全性。

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引用次数: 0

Uncertainty analysis method for the multi-scale coupling program based on preCICE 基于preCICE的多尺度耦合方案的不确定性分析方法

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-06 DOI: 10.1016/j.anucene.2025.112112

Shihao Dong , Junjie Deng , Pengcheng Zhao , Zijing Liu , Wei Li

Current research on the multi-scale coupling of reactors primarily focuses on the development of coupled simulation programs, which suffer from numerous uncertainties. This work establishes an uncertainty quantification (UQ) framework for multi-scale thermal–hydraulic (TH) coupling, which leverages the preCICE open-source platform to integrate the high-fidelity CFD code FLUENT, subchannel code SUBCHANFLOW, and UQ code DAKOTA. A 3 × 3 rod bundle configuration is used as a benchmark to validate the coupled framework under steady-state and transient conditions. Under steady-state conditions, the coupled model consistently predict axial temperature distributions when benchmarked against solvers (FLUENT and SUBCHANFLOW), validating the computational accuracy of multi-scale TH coupling. Under transient conditions with sinusoidal inlet flow variations, the outlet flow response synchronizes the period and phase with input perturbations, confirming the dynamic simulation capability of coupled system. Uncertainty quantification suggests that key parameters, including coolant temperature and peak cladding temperature, exhibit a normal distribution approximately. Sensitivity analysis reveals that inlet mass flow rate, outlet pressure, inlet temperature, and fuel rod heat flux are the dominant parameters influencing the system response. Overall, the proposed system exhibits reliable response characteristics under dynamic conditions.

目前对反应器多尺度耦合的研究主要集中在耦合模拟程序的开发上，这些程序存在着许多不确定性。本文建立了多尺度热液耦合的不确定性量化（UQ）框架，该框架利用preCICE开源平台集成了高保真CFD代码FLUENT、子通道代码SUBCHANFLOW和UQ代码DAKOTA。采用3 × 3杆束结构作为基准，在稳态和瞬态条件下验证了耦合框架。在稳态条件下，耦合模型与求解器（FLUENT和SUBCHANFLOW）进行基准测试时，能够一致地预测轴向温度分布，验证了多尺度TH耦合的计算精度。在进口流量呈正弦变化的瞬态条件下，出口流量响应与输入扰动同步周期和相位，验证了耦合系统的动态仿真能力。不确定度量化表明，包括冷却剂温度和包层峰值温度在内的关键参数近似呈正态分布。灵敏度分析表明，进口质量流量、出口压力、进口温度和燃料棒热流密度是影响系统响应的主要参数。总体而言，该系统在动态条件下具有可靠的响应特性。

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引用次数: 0

Prediction of homogenized few-group constants for pressurized water reactor assembly using a Deep Neural Network with Gaussian Process Residual Correction 基于高斯过程残差校正的深度神经网络预测压水堆组件均质化少群常数

IF 2.3 3区工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY

Annals of Nuclear Energy

Pub Date : 2026-01-06 DOI: 10.1016/j.anucene.2026.112118

Wenming Yi , Feng Shen , GuoPing Quan , Xubo Ma , Guang Zhao

Accurate and efficient parameterization of assembly homogenized few-group constants is a critical challenge in reactor physics. Traditional methods are either too computationally expensive, like Monte Carlo codes, or struggle with the high-dimensional, non-linear relationships found in reactor data, like interpolation methods, especially when sample sizes are small. To address this, we propose a novel machine learning ensemble method, the Deep Neural Network with Gaussian Process Residual Correction (DNN-GPRC). This hybrid model uses a DNN to capture the primary data trends and a GPR to model and correct the DNN’s prediction residuals, leveraging GPR’s robustness on small datasets. Furthermore, we employ a Yeo–Johnson transformation in feature engineering to effectively mitigate the long-tail data distribution inherent in burnup calculations, significantly enhancing model performance. Tested on a small dataset of 2874 samples, the DNN-GPRC model consistently outperforms both standalone DNN and traditional linear interpolation methods. Crucially, on the test set, our model achieves a Root Mean Square Error of just 128 pcm for the infinite multiplication factor (

k_{i n f}

), a result markedly superior to linear interpolation. This work demonstrates that the DNN-GPRC framework provides a high-accuracy, computationally efficient, and robust tool for few-group constant parameterization. It moves the field forward by enabling rapid and accurate analysis even in low-sample scenarios, which is vital for accelerating new reactor design cycles and improving simulation fidelity.

准确、高效地参数化组件均质少群常数是反应堆物理学中的一个关键挑战。传统方法要么计算成本太高，比如蒙特卡罗代码，要么难以处理反应器数据中的高维非线性关系，比如插值方法，尤其是在样本量很小的情况下。为了解决这个问题，我们提出了一种新的机器学习集成方法，即高斯过程残差校正深度神经网络（DNN-GPRC）。该混合模型使用深度神经网络捕获主要数据趋势，并使用GPR建模和纠正深度神经网络的预测残差，利用GPR在小数据集上的鲁棒性。此外，我们在特征工程中采用了杨-约翰逊变换，有效地缓解了燃耗计算中固有的长尾数据分布，显著提高了模型性能。在2874个样本的小数据集上测试，DNN- gprc模型始终优于独立DNN和传统线性插值方法。至关重要的是，在测试集上，我们的模型对于无限乘法因子（kinf）的均方根误差仅为128 pcm，结果明显优于线性插值。这项工作表明，DNN-GPRC框架为少组常数参数化提供了高精度，计算效率高，鲁棒的工具。它通过在低样本情况下实现快速准确的分析，推动了该领域的发展，这对于加快新反应堆设计周期和提高模拟保真度至关重要。

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引用次数: 0