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Identification algorithm of low-count energy spectra under short-duration measurement based on heterogeneous sample transfer

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nuclear science and Techniques 2025年第3期36卷 12-26页

作者： Hao-Lin Liu Hai-Bo Ji Jiang-Mei Zhang Jing Lu School of Information Engineering Southwest University of Science and TechnologyMianyang 621010China Department of Automation University of Science and Technology of ChinaHefei 230026China Fundamental Science on Nuclear Wastes and Environment Safety Laboratory Southwest University of Science and TechnologyMianyang 621010China School of Automation and Information Engineering Sichuan University of Science and EngineeringZigong 643000China

In scenarios such as vehicle radiation monitoring and unmanned aerial vehicle radiation detection,rapid measurements using a NaI(Tl)detector often result in low photon counts,weak characteristic peaks,and significant statistical *** issues can lead to potential failures in peak-searching-based identification *** address the low precision associated with short-duration measurements of radionuclides,this paper proposes an identification algorithm that leverages heterogeneous spectral transfer to develop a low-count energy spectral identification *** experiments demonstrated that transferring samples from 26 classes of simulated heterogeneous gamma spectra aids in creating a reliable model for measured gamma *** only 10%of target domain samples used for training,the accuracy on real low-count spectral samples was 95.56%.This performance shows a significant improvement over widely employed full-spectrum analysis methods trained on target domain *** proposed method also exhibits strong generalization capabilities,effectively mitigating overfitting issues in low-count energy spectral classification under short-duration measurements.

关键词： Radionuclide identification Low-count Gamma energy spectral analysis Heterogeneous Transfer learning

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Early fault detection method for nuclear power plants based on sparse denoising autoencoder and kernel principal component analysis

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Annals of nuclear Energy 2025年 220卷

作者： Yin, Wenzhe Xia, Hong Huang, Xueying Shan, Longfei Ran, Wenhao Jia, Zhujun Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin150001 China

Effective fault detection technology is of great significance to the safety and economy of nuclear power plants (NPPs). To accurately identify early faults in NPPs, this study proposes a novel fault detection method based on sparse denoising autoencoder (SDAE) and kernel principal component analysis (KPCA). First, the operating data of NPPs is collected by numerous sensors, and the operating parameters are grouped according to physical properties. Then, the corresponding fault detection model is established according to each parameter group, and each detection model consists of the SDAE and KPCA. The case study evaluated four accident scenarios (LOCA, SLBIC, FHAIC, FHAIAB) across two development degrees (0–1 % and 0–0.1 %). The proposed method achieved fault detection rates of 99.07 %, 95.20 %, 99.73 %, and 99.60 % for the 0–1 % degree with zero false alarms. Even for the subtler 0–0.1 % degree, it maintained a 94.84 % average detection rate and no false alarms. Compared to traditional methods, its average fault detection rate was higher than that of PCA and KPCA by 62.9 % and 32.4 % (0–1 % degree), and by 89.5 % and 88 % (0–0.1% degree), demonstrating its potential application value in NPPs. © 2025 Elsevier Ltd

关键词： nuclear power plants

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Radiation and ergonomic-aware A-star algorithm for nuclear decommissioning path planning

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nuclear Engineering and Design 2025年 439卷

作者： Adibeli, Justina Onyinyechukwu Liu, Yong-Kuo Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin150001 China Man-Power Training and Capacity Development Directorate Nigeria Atomic Energy Commission Abuja Nigeria

This study presents a novel modification of the A* path planning algorithm that integrates ergonomic and radiological constraints to enhance worker safety in nuclear decommissioning environments. The algorithm optimizes paths by incorporating ergonomic scores derived from biomechanical data alongside radiation exposure estimates from simulations. To assess the impact of load carriage, worker performance is analyzed under normal and weighted walking conditions, with a focus on joint biomechanics, including moment, power, angle, and velocity. Results indicate that while cumulative radiation exposure remains relatively stable, weighted walking significantly increases biomechanical strain, elevating the risk of musculoskeletal disorders (MSDs). The proposed dual-cost optimization approach provides a comprehensive framework for balancing radiation exposure and ergonomic stress, offering practical improvements for worker safety and efficiency in hazardous environments. © 2025

关键词： Decommissioning (nuclear reactors)

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Cross-domain fault diagnosis method for nuclear power plant bearings based on deep transfer learning under small sample conditions

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Progress in nuclear Energy 2025年 186卷

作者： Yin, Wenzhe Xia, Hong Zio, Enrico Huang, Xueying Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin150001 China MINES Paris PSL University CRC Sophia Antipolis France Energy Department Politecnico di Milano Milan20156 Italy

In recent years, methods based on deep learning have attracted attention in the fault diagnosis of rotating machinery in nuclear power plants (NPPs). However, these methods are typically developed under the assumption that sufficient fault samples are available. In practice, rotating machinery in NPPs operate in healthy state most of the time and faults occur rarely and last a relatively short period of time. This work proposes a fault diagnosis method based on deep transfer learning to overcome the issue of small sample conditions in the bearing fault diagnosis task of NPPs. The bearing vibration signals collected by the sensor are converted into a time-frequency map by synchrosqueezed wavelet transforms, they are used as input of the deep convolutional neural network. In the learning phase, the deep learning model first learns domain-related knowledge from real devices, then the model parameters are transferred to the target task, and the model is fine-tuned based on the target domain knowledge. The proposed method was applied to two case studies: bearing fault localization and fault severity assessment. Experimental results demonstrated that, for the fault localization case, the method achieved average accuracy, precision, and F1 score of 95.21 %, 95.35 %, and 95.17 %, respectively, under four small sample conditions (with 10, 20, 30, and 40 samples per category in the training dataset). For the fault severity assessment case, the method attained average accuracy, precision, and F1 score of 95.03 %, 95.45 %, and 94.94 %, respectively, under three small sample conditions (with 3, 5, and 8 samples per category in the training dataset), demonstrating its potential value for NPPs bearing fault diagnosis. © 2025

关键词： Bearings (machine parts)

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The effect of multi-orifice plate configuration on bubble detachment volume

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Chinese Journal of Chemical Engineering 2019年第1期27卷 72-84页

作者： Jiming Wen Qiunan Sun Zhongning Sun Haifeng Gu Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University

The multi-orifice plate gas sparger, mainly composed of a multi-orifice plate and a gas chamber, is one of the most common sparger *** aeration performance of multi-orifice plate has a close relation with the multiorifice plate *** addition, the weeping phenomenon has a considerable influence on the gas chamber condition which affects the bubble detachment volume *** paper conducts a set of visual experiments to study the influence of multi-orifice configuration and gas chamber condition on the aeration performance of gas *** multi-orifice plate, an improved theoretical model is proposed which considers the wave effect of the previous bubbles generated from adjacent orifices and the variance of the number of active bubbling orifice.A parameter is proposed to evaluate the aeration performance in order to overcome the difficulty caused by the randomness of bubble formation *** experimental results suggest that the gas chamber filled with water is in favor of large bubble *** influence of the pitch of orifice on aeration performance can only be observed in high-restricted *** to the theoretical model and experimental results, the influences of gas flow rate and the number of open orifices on the aeration performance are analyzed and a design criterion for the number of open orifice is proposed.

关键词： Multi-orifice plate Aeration performance Bubble detachment volume The number of open orifices

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Bubble coalescence efficiency near multi-orifice plate

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Chinese Journal of Chemical Engineering 2019年第8期27卷 1765-1776页

作者： Jiming Wen Qiunan Sun Zhongning Sun Haifeng Gu Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University

Bubble coalescence reduces specific area and weakens the work performance of bubble column. The bubble coalescence near gas sparger which is caused mainly by bubble growing is different from the ones occurring in major liquid. Bubble coalescence efficiency near gas sparger is influenced by many factors including sparger configuration, gas flow rate, bubble deformation, solution composition, etc. This work has conducted a set of visual experiments to study the coalescence characteristics near multi-orifice plate. The experiment parameters cover a wide range of conditions including large scope of gas flow rate,different kinds of solution and orifice configurations. The experimental results suggest that coalescence time is applicable to reflect the influence of the pitch of orifices and gas flow rate on bubble coalescence efficiency. As the number of orifices increases, bubble coalescence efficiency is reduced by the disturbance from the bubbles at adjacent orifices. A hindering coefficient is used to consider the hindering effect of additives on bubble coalescence efficiency. Finally a new calculation expression is established to predict bubble coalescence efficiency near multi-orifice plate whose fundamental form is based on the logistic curve of binary response. The calculated values that refer to this calculation expression are well consistent with the experimental results.

关键词： Bubble column Bubble coalescence efficiency Multi-orifice plate Coalescence time

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Integrating spatial prediction and Bayesian optimization for dynamic event tree optimization branch search

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nuclear Engineering and Design 2025年 440卷

作者： Chen, Haoyin Wang, He Wang, Longcong Zhao, Qiang Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin China

The dynamic event tree (DET) method has been extensively utilized in safety analyses of nuclear power plant accidents. However, due to the complex nature of accident response processes, ensuring a comprehensive simulation of accident outcomes and calculating precise failure probability values requires an enormous number of discrete branches generated by DET, which incurs a prohibitive computational cost. This paper proposes a DET branch search method that integrates spatial prediction and Bayesian optimization. This method uses a limited number of DET branch calculation results as prior data and employs Bayesian optimization to automatically search for the optimal branch step size. By integrating Dynamic Time Warping (DTW) classification with data stability testing, the status of unknown spaces is preliminarily determined, gradually reducing the scope of spaces with potential failure risks. Through the selection of critical yet minimal DET branches for a comprehensive simulation of accident outcomes, computational efficiency is enhanced, and accurate failure probability results are achieved. Using the operation time of the turbine-driven auxiliary feedwater system and the main pump shaft seal leakage time in a station blackout (SBO) accident of a CPR1000 nuclear power plant as an example, a DET model is constructed. Ultimately, the computational time and failure probability of the DET branching optimization search method are compared with those of the equally spaced variable values method. The relative error of the failure probability is within 1.96%, while computational efficiency is improved by a factor of 4.82. This approach not only ensures computational accuracy but also enhances the efficiency of DET calculations, offering substantial methodological support for the practical application of DET. © 2025

关键词： nuclear reactor accidents

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A Common Optical Potential for ~4He+^(12)C at Intermediate Energies

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Chinese Physics Letters 2016年第7期33卷 46-49页

作者：胡力元宋玉收侯英伟刘辉兰 Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University

A common optical potential for 4He＋12C at intermediate bombarding energies, which is essential in analyzing exotic nuclei with 4He clusters, is obtained based on the Sao Paulo potential. Among systematic optical potentials for 4He＋12 C, this potential has the merit of using a fixed imaginary part of the Woods Saxon form. By optical- model calculations, this potential reproduces the experimental elastic scattering angular distributions of a He＋12 C well within the energy range of 26A 60A MeV. It is also applied successfully in calculations of the breakup reactions of 6Li＋12 C and 6He＋12 C with a three-body continuum discretized coupled-channel method.

关键词： A Common Optical Potential for on of C at Intermediate Energies CDCC is COP in

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Research on fault sensor detection and localization method based on autoencoder

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Annals of nuclear Energy 2025年 220卷

作者： Shan, Longfei Liu, Yongkuo Ai, Xin Gao, Jiarong Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin150001 China

Some sensors in nuclear power plants are exposed to extreme conditions, including high temperatures, high pressures, and intense radiation. As a result, the sensors may experience varying degrees of aging or malfunction. In this paper. we investigate the problem of detecting failures and locating faults in nuclear power plant sensors and proposes a sensor failure detection and localization method based on autoencoders. This method primarily consists of three parts: anomaly detection, fault diagnosis, and faulty sensor localization. Among these, the autoencoder method is used for anomaly detection and faulty sensor localization;feature extraction methods and the random forest algorithm are employed for fault diagnosis. This study used the Fuqing nuclear Power Plant simulator as the data source to verify the effectiveness of the proposed algorithm. The experimental results show that the autoencoder method can identify faults and normal states with 99.6 % accuracy. The feature extraction-Random Forest method used to distinguish between sensor faults and system faults can identify system faults and sensor faults with 100 % accuracy, and the feature extraction method proposed in this paper is generally applicable, improving accuracy by 2.65 %-14 %. The autoencoder method for fault sensor localization demonstrates good diagnostic accuracy in both single-sensor and multi-sensor fault localization with a low false alarm rate. The autoencoder-based sensor fault detection and localization method demonstrates good diagnostic capability, providing a universal and direct sensor fault diagnosis framework for various types of sensor fault diagnosis. © 2025 Elsevier Ltd

关键词： nuclear power plants

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Dynamic exergy optimization of feedwater heater start-up process in nuclear power plant using optimal control method

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nuclear Engineering and Design 2025年 441卷

作者： Zhijiang Zhang Zhaofei Tian Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin 150001 China

The operational optimization of energy systems is of great significance for the sustainable development of energy, as well as for achieving carbon peaking and carbon neutrality. This research took the feedwater heater in a nuclear power unit as the research object, developed a thermo-hydraulic model applicable to the optimization. The optimal control algorithm, which is widely used in chemical and energy systems, has been innovatively applied to nuclear power units and combined with the dynamic exergy analysis method to optimize the start-up process. The results show that although the time optimal control shortens the startup time by 19.69%, the cumulative exergy loss increases by 1 time. The optimal control with the highest exergy efficiency as the goal reduced the start-up time by 19.23%, and the accumulated exergy destruction decreased by 25.14%. This study greatly reduced the startup time of feedwater heater and improved the process exergy efficiency. This study provided important guidance for the dynamic exergy optimization of energy system start-up processes and addressed the long-standing limitation of exergy analysis being confined to steady-state conditions.

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