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Lumped-Parameter Thermal Network Model and Experimental Research of Interior PMSM for Electric Vehicle 被引量:3
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作者 Qixu Chen Zhongyue Zou Binggang Cao 《CES Transactions on Electrical Machines and Systems》 2017年第4期367-374,共8页
A 25kW interior permanent magnet synchronous machine(IPMSM)applied to the electric vehicle is introduced in the paper.A lumped-parameter thermal network model is presented for IPMSM temperature rise calculation.Furthe... A 25kW interior permanent magnet synchronous machine(IPMSM)applied to the electric vehicle is introduced in the paper.A lumped-parameter thermal network model is presented for IPMSM temperature rise calculation.Furthermore,a 3D liquid-solid coupling model considering the assembly clearance is compared with the 2D lumped-parameter thermal network model.Finally,a dynamometer platform for temperature rise measurement is established to verify the above-mentioned methods,which obtains the measured efficiency map at rated load case and overload case.At the same time,the measured no-load back electromotive Force(EMF),load line input voltage and load current are gathered.Thermocouple PTC100 is used to measure the temperature of the stator winding and iron core,and the FLUKE infrared thermal imager is applied to measure the surface temperature of PMSM and controller.Testing result shows that the lumped-parameter thermal network have a high accuracy to predict each part temperature. 展开更多
关键词 Interior permanent magnet synchronous machine lumped-parameter thermal network liquid-solid coupling thermal resistance thermal conductance.
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Analysis of the Temperature Characteristics of High-speed Train Bearings Based on a Dynamics Model and Thermal Network Method 被引量:5
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作者 Baosen Wang Yongqiang Liu +1 位作者 Bin Zhang Wenqing Huai 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2022年第5期351-363,共13页
High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in... High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors.In this study,a dynamics model of the axle box bearing of high-speed trains is established.The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring,inner-ring,and rolling-element faults.Based on the model,a thermal network method is introduced to study the temperature field distribution of the axle box bearings of high-speed trains.In this model,the heat generation,conduction,and dispersion of the isothermal nodes can be solved.The results show that the temperature of the contact point between the outer-ring raceway and rolling-elements is the highest.The relationships between the node temperature and the speed,fault type,and fault size are analyzed,finding that the higher the speed,the higher the node temperature.Under different fault types,the node temperature first increases and then decreases as the fault size increases.The effectiveness of the model is demonstrated using the actual temperature data of a high-speed train.This study proposes a thermal network model that can predict the temperature of each component of the bearings on a high-speed train under various speed and fault conditions. 展开更多
关键词 High-speed train Axle box bearing Temperature characteristics thermal network method
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Development of a Methodology for Determination and Analysis of Thermal Displacements of Machine Tools Using Finite Elements Method and Artificial Neural Network
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作者 Romualdo Figueiredo de Sousa Fracisco Augusto Vieira da Silva Joao Bosco Aquino Silva Jose Carlos de Lima Junior 《Journal of Mechanics Engineering and Automation》 2014年第6期488-498,共11页
In the processes of manufacturing, MT (machine tools) plays an important role in the manufacture of work pieces with complex and high dimensional and geometric accuracy. Much of the errors of a machine tool are thos... In the processes of manufacturing, MT (machine tools) plays an important role in the manufacture of work pieces with complex and high dimensional and geometric accuracy. Much of the errors of a machine tool are those which are thermally induced which are from internal and external heat sources acting on the machine. In this paper, a methodology for determining and analyzing the thermal deformation of machine tools using FEM (finite element method) and ANN (artificial neural networks) is presented. After modeling the machine using FEM is defined the location of the heat sources, it is possible to obtain the temperature gradient and the corresponding thermal deformation at predetermined periods. Results obtained with simulations using the software NX.7.5 showed that this methodology is an effective tool in determining the thermal deformation of the machine, correlating the temperature reading at strategic points with volumetric deformation at the tool tip. Therefore, the thermal analysis of the errors in the pair tool part can be established. After training and validation process, the network will be able to make the prediction of thermal errors just stating the temperature values of specific points of each heat source, providing a way for compensation of thermally induced errors. 展开更多
关键词 thermal displacement machine tool finite element method artificial neural network.
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Analysis of temperature field for a surface-mounted and interior permanent magnet synchronous motor adopting magnetic-thermal coupling method 被引量:7
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作者 Jikai Si Suzhen Zhao +2 位作者 Haichao Feng Yihua Hu Wenping Cao 《CES Transactions on Electrical Machines and Systems》 2018年第1期166-174,共9页
Aiming at obtaining high power density of surface-mounted and interior permanent magnet synchronous motor(SIPMSM),it is important to accurately calculate the temperature field distribution of SIPMSM,and a magnetic-the... Aiming at obtaining high power density of surface-mounted and interior permanent magnet synchronous motor(SIPMSM),it is important to accurately calculate the temperature field distribution of SIPMSM,and a magnetic-thermal coupling method is proposed.The magnetic-thermal coupling mechanism is analyzed.The thermal network model and finite element model are built by this method,respectively.The effects of power frequency on iron losses and temperature fields are analyzed by the magnetic-thermal coupling finite element model under the condition of rated load,and the relationship between the load and temperature field is researched under the condition of the synchronous speed.In addition,the equivalent thermal network model is used to verify the magnetic-thermal coupling method.Then the temperatures of various nodes are obtained.The results show that there are advantages in both computational efficiency and accuracy for the proposed coupling method,which can be applied to other permanent magnet motors with complex structures. 展开更多
关键词 Equivalent thermal network method magnetic-thermal coupling method power frequency iron loss surface-mounted and interior permanent magnet synchronous motor(SIPMSM) temperature field
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Magneto-Thermal Finite Element Analysis and Optimization by Neural Network of Induction Cooking 被引量:1
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作者 Allaoui Fethi Kansab Abdelkader +2 位作者 Matallah Mohamed Zaoui Abdelhalim 3 and Feliachi Mouloud 《材料科学与工程(中英文A版)》 2013年第9期653-658,共6页
关键词 神经网络 有限元分析 优化 电磁炉 温度均匀 感应加热 不均匀分布 几何形状
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基于深度随机对偶动态规划的水-火-新能源协同调度方法
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作者 高立乾 崔世常 +5 位作者 方家琨 艾小猛 文劲宇 邢栋 徐尧宇 张君 《电力系统自动化》 北大核心 2026年第5期184-196,共13页
随着新能源大规模接入,水-火-新能源电力系统中水电的快速调节能力和火电的稳定支撑能力,在新能源高渗透的场景下依然是保障电网安全经济运行的核心资源。然而,新能源的不确定性与时序耦合约束导致水-火-新能源协同调度的复杂度显著增加... 随着新能源大规模接入,水-火-新能源电力系统中水电的快速调节能力和火电的稳定支撑能力,在新能源高渗透的场景下依然是保障电网安全经济运行的核心资源。然而,新能源的不确定性与时序耦合约束导致水-火-新能源协同调度的复杂度显著增加,传统优化调度方法难以兼顾求解效率与最优性。为解决上述问题,提出了一种基于Benders分解法的深度随机对偶动态规划求解算法。首先,将水-火-新能源协同调度问题建模为多阶段随机规划模型来刻画随机变量逐时段揭示的特性,并利用Benders分解法实现整数变量与连续变量的分离以降低求解难度。其次,引入全输入凸神经网络高效逼近值函数,在保证收敛性的同时提升了拟合能力与计算效率。最后,在不同规模系统上进行算例验证,结果表明所提算法具有可行性与可扩展性,并显著提升了近似精度、求解效率及质量。 展开更多
关键词 协同调度 水电 火电 新能源 多阶段随机规划 随机对偶动态规划 BENDERS分解法 神经网络
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考虑温度影响的圆柱滚子轴承接触特性分析
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作者 于浩 《河南科技》 2026年第2期46-50,共5页
【目的】圆柱滚子轴承通常用于承担较大的工作载荷,运转过程中温度会有所升高,温度变化将对轴承参数产生影响,有必要对考虑温度影响的圆柱滚子轴承接触特性进行分析。【方法】基于轴承拟静力学分析,利用热网络法建立温度分布计算模型,... 【目的】圆柱滚子轴承通常用于承担较大的工作载荷,运转过程中温度会有所升高,温度变化将对轴承参数产生影响,有必要对考虑温度影响的圆柱滚子轴承接触特性进行分析。【方法】基于轴承拟静力学分析,利用热网络法建立温度分布计算模型,将温度升高导致的结构参数变化考虑在内,建立一种考虑温度影响的圆柱滚子轴承接触力学计算模型。【结果】结果表明,考虑温度影响后,轴承内部承载滚子个数增多,各滚动体与滚道间的接触应力均增大;随外载荷及工作转速的提升,轴承内部各位置角处的接触应力值均增大。【结论】研究结果可为重载工况下圆柱滚子轴承的接触力学分析提供理论依据,对提升轴承运转可靠性具有重要工程意义。 展开更多
关键词 圆柱滚子轴承 结构参数 热网络法 温度分布计算模型 接触应力
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Numerical modeling of thermal breakthrough induced by geothermal production in fractured granite 被引量:6
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作者 Hejuan Liu Hongwei Wang +3 位作者 Hongwu Lei Liwei Zhang Mingxing Bai Lei Zhou 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2020年第4期900-916,共17页
It is well known that the complicated channeling of fluid flow and heat transfer is strongly related with the intricate natural fracture system.However,it is still challenging to set up the fracture network model whic... It is well known that the complicated channeling of fluid flow and heat transfer is strongly related with the intricate natural fracture system.However,it is still challenging to set up the fracture network model which is strong heterogeneous.Compared with other methods(e.g.equivalent continuum model(ECM),discrete fracture model(DFM),and ECM-DFM),the fracture flow module in the COMSOL Multiphysics simulator is powerful in definition of fractures as the inner flow boundary existing in the porous media.Thus it is selected to simulate the fluid flow and heat transfer in the geothermal-developed fractured granite of Sanguliu area located at Liaodong Peninsula,Eastern China.The natural faults/fractures based on field investigation combined with the discrete fracture network(DFN)generated by the MATLAB are used to represent the two-dimensional geological model.Numerical results show that early thermal breakthrough occurs at the production well caused by quick flow of cold water along the highly connected fractures.Suitable hydraulic fracturing treatments with proper injection rates,locations,etc.can efficiently hinder the thermal breakthrough time in the natural fracture system.Large well spacing helps the long-term operation of geothermal production,but it is highly dependent on the geometrical morphology of the fracture network.The enhancement of reservoir properties at the near-well regions can also increase the geothermal production efficiency.The results in this study can provide references to achieve a sustainable geothermal exploitation in fractured granitic geothermal reservoirs or hot dry rocks at depth. 展开更多
关键词 thermal breakthrough Discrete fracture network(DFN) Monte Carlo method Fracture aperture GRANITE
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Characteristic analysis of mechanical thermal coupling model for bearing rotor system of high-speed train 被引量:3
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作者 Yongqiang LIU Baosen WANG +2 位作者 Shaopu YANG Yingying LIAO Tao GUO 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2022年第9期1381-1398,共18页
Based on Newton’s second law and the thermal network method,a mechanical thermal coupling model of the bearing rotor system of high-speed trains is established to study the interaction between the bearing vibration a... Based on Newton’s second law and the thermal network method,a mechanical thermal coupling model of the bearing rotor system of high-speed trains is established to study the interaction between the bearing vibration and temperature.The influence of lubrication on the vibration and temperature characteristics of the system is considered in the model,and the real-time relationship between them is built up by using the transient temperature field model.After considering the lubrication,the bearing outer ring vibration acceleration and node temperature considering grease are lower,which shows the necessity of adding the lubrication model.The corresponding experiments for characteristics of vibration and temperature of the model are respectively conducted.In the envelope spectrum obtained from the simulation signal and the experimental signal,the frequency values corresponding to the peaks are close to the theoretical calculation results,and the error is very small.In the three stages of the temperature characteristic experiment,the node temperature change of the simulation model is consistent with the experiment.The good agreement between simulation and experiments proves the effectiveness of the model.By studying the influence of the bearing angular and fault size on the system node temperature,as well as the change law of bearing lubrication characteristics and temperature,it is found that the worse the working condition is,the higher the temperature is.When the ambient temperature is low,the viscosity of grease increases,and the oil film becomes thicker,which increases the sliding probability of the rolling element,thus affecting the normal operation of the bearing,which explains the phenomenon of frequent bearing faults of high-speed trains in the low-temperature area of Northeast China.Further analysis shows that faults often occur in the early stage of train operation in the low-temperature environment. 展开更多
关键词 high-speed train coupling dynamic model thermal network method track irregularity(TI) low temperature
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Thermogram-based estimation of foot arterial blood flow using neural networks 被引量:2
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作者 Yueping WANG Lizhong MU Ying HE 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2023年第2期325-344,共20页
The altered blood flow in the foot is an important indicator of early diabetic foot complications.However,it is challenging to measure the blood flow at the whole foot scale.This study presents an approach for estimat... The altered blood flow in the foot is an important indicator of early diabetic foot complications.However,it is challenging to measure the blood flow at the whole foot scale.This study presents an approach for estimating the foot arterial blood flow using the temperature distribution and an artificial neural network.To quantify the relationship between the blood flow and the temperature distribution,a bioheat transfer model of a voxel-meshed foot tissue with discrete blood vessels is established based on the computed tomography(CT)sequential images and the anatomical information of the vascular structure.In our model,the heat transfer from blood vessels and tissue and the inter-domain heat exchange between them are considered thoroughly,and the computed temperatures are consistent with the experimental results.Analytical data are then used to train a neural network to determine the foot arterial blood flow.The trained network is able to estimate the objective blood flow for various degrees of stenosis in multiple blood vessels with an accuracy rate of more than 90%.Compared with the Pennes bioheat transfer equation,this model fully describes intra-and inter-domain heat transfer in blood vessels and tissue,closely approximating physiological conditions.By introducing a vascular component to an inverse model,the blood flow itself,rather than blood perfusion,can be estimated,directly informing vascular health. 展开更多
关键词 diabetic foot thermal analysis blood flow inverse method neural network
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Numerical Investigation of Thermal Behavior of CNC Machine Tool and Its Effects on Dimensional Accuracy of Machined Parts 被引量:1
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作者 Erick Matezo-Ngoma Abderrazak El Ouafi Ahmed Chebak 《Journal of Software Engineering and Applications》 2024年第8期617-637,共21页
The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally in... The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally induced positioning error compensation remains the most effective and practical method in this context. However, the efficiency of the compensation process depends on the quality of the model used to predict the thermal errors. The model should consistently reflect the relationships between temperature distribution in the MT structure and thermally induced positioning errors. A judicious choice of the number and location of temperature sensitive points to represent heat distribution is a key factor for robust thermal error modeling. Therefore, in this paper, the temperature sensitive points are selected following a structured thermomechanical analysis carried out to evaluate the effects of various temperature gradients on MT structure deformation intensity. The MT thermal behavior is first modeled using finite element method and validated by various experimentally measured temperature fields using temperature sensors and thermal imaging. MT Thermal behavior validation shows a maximum error of less than 10% when comparing the numerical estimations with the experimental results even under changing operation conditions. The numerical model is used through several series of simulations carried out using varied working condition to explore possible relationships between temperature distribution and thermal deformation characteristics to select the most appropriate temperature sensitive points that will be considered for building an empirical prediction model for thermal errors as function of MT thermal state. Validation tests achieved using an artificial neural network based simplified model confirmed the efficiency of the proposed temperature sensitive points allowing the prediction of the thermally induced errors with an accuracy greater than 90%. 展开更多
关键词 CNC Machine Tool Dimensional Accuracy thermal Errors Error Modelling Numerical Simulation Finite Element method Artificial Neural network Error Compensation
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形状记忆合金驱动的智能点阵精确变形设计及实时控制方法
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作者 朱继宏 徐博 +4 位作者 张亚辉 侯杰 王骏 谷小军 张卫红 《航空制造技术》 北大核心 2025年第22期14-33,共20页
智能变体结构作为未来先进无人飞行器等装备研制的关键技术,其分布式主动变形结构可实现光滑连续与多自由度变形,是显著提升结构性能与任务适应性的有效手段。针对这一需求,提出了一种基于形状记忆合金驱动的智能点阵结构的创新设计与... 智能变体结构作为未来先进无人飞行器等装备研制的关键技术,其分布式主动变形结构可实现光滑连续与多自由度变形,是显著提升结构性能与任务适应性的有效手段。针对这一需求,提出了一种基于形状记忆合金驱动的智能点阵结构的创新设计与控制方案。首先,提出的拟热变形法可用于高效评估SMA驱动器的变形性能,通过仿真与试验验证该方法对智能点阵结构的变形性能分析具有5%以内的误差精度,并成功实现了其结构的多模式可控变形。进一步构建了以能耗优化为目标、变形精度为约束的分布式驱动设计模型,在翼型结构应用中仅需16.67%的全局能量即可实现8个控制点400 mm的高精度变形(误差<1%)。针对大规模结构的实时控制难题,采用BP神经网络实现了多自由度变形的精确预测与控制,该方法具有突出的普适性,可拓展至多种形式的SMA驱动形式及复合翼面等智能结构设计,为兼具力学性能与智能变形的新一代智能变体结构系统提供了新的解决方案。 展开更多
关键词 智能点阵结构 形状记忆合金 分布式驱动 拟热变形法 神经网络模型
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基于城市规划布局的绿地系统“冷岛网络”建构及应用——以重庆市高新区绿地专项规划为例
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作者 王立 邬铃莉 +2 位作者 王怀 韩贵锋 李平 《西部人居环境学刊》 北大核心 2025年第3期85-93,共9页
绿地“冷岛效应”对于改善城市热环境具有重要意义。为通过优化绿地布局提升绿地系统冷岛效应,文章以高新区绿地系统规划为例,在规划语境下以“规模”为核心变量建立冷岛范围预测模型,结果表明两者呈反正切函数关系;结合复杂网络方法,... 绿地“冷岛效应”对于改善城市热环境具有重要意义。为通过优化绿地布局提升绿地系统冷岛效应,文章以高新区绿地系统规划为例,在规划语境下以“规模”为核心变量建立冷岛范围预测模型,结果表明两者呈反正切函数关系;结合复杂网络方法,探索形成以绿地斑块为“节点”、以斑块间冷岛范围在空间上的重叠关系为“边”的冷岛网络建构路径;从系统、子群、个体三个维度分析高新区冷岛网络特征发现,其冷岛网络整体集聚性差、3大子群的节点连通效率差异显著、系统内除寨山坪节点外缺少高中心度节点;将“冷岛网络”与研究区现状热环境叠加识别出降温“盲区”,并以强化系统整体冷岛效应为导向,提出打造区域结构绿网、织补绿网降温盲区、调控绿地空间形态的绿地系统布局优化策略。研究结果可为城市绿地系统规划以及相关标准制定提供参考依据。 展开更多
关键词 绿地系统 冷岛网络 复杂网络分析 热环境 布局优化策略。
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基于WOA-BP神经网络的热式流量测量技术研究
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作者 刘升虎 刘太逸 +3 位作者 冉建立 郭会强 邢亚敏 梁钊睿 《仪表技术与传感器》 北大核心 2025年第4期50-54,共5页
针对热式流量测量方法易受环境因素影响的问题,构建了一种WOA-BP神经网络流量预测模型,以热式传感器采样电压值及含水率测量信号作为模型输入量,以预测流量值作为输出值,进行温度补偿,利用鲸鱼群算法进行网络初值参数优化,得到优化后的... 针对热式流量测量方法易受环境因素影响的问题,构建了一种WOA-BP神经网络流量预测模型,以热式传感器采样电压值及含水率测量信号作为模型输入量,以预测流量值作为输出值,进行温度补偿,利用鲸鱼群算法进行网络初值参数优化,得到优化后的补偿模型,提高了算法的收敛速度。实验结果表明:优化后的神经网络模型在热式流量测量方法中具有较好的流量预测效果,WOA-BP网络模型R~2达到0.989,比传统BP模型的预测精确性和鲁棒性更高,在对油井产液量预测方面具有实用价值。 展开更多
关键词 鲸鱼优化算法(WOA) BP神经网络 热式流量测量方法 温度补偿
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月球表面热管熔盐堆概念设计 被引量:1
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作者 刘坤 林铭 +3 位作者 李锐 左献迪 程懋松 戴志敏 《核技术》 北大核心 2025年第6期129-140,共12页
在月球建立基地是人类探索太空的第一步,而为基地提供稳定可靠的能源是最重要的方面之一。与太阳能相比,核能具有高功率、比质量低、使用寿命长、可全天候供电等优点,是月球表面基地能源供给的理想选择。基于100 kWe的供电需求,设计了... 在月球建立基地是人类探索太空的第一步,而为基地提供稳定可靠的能源是最重要的方面之一。与太阳能相比,核能具有高功率、比质量低、使用寿命长、可全天候供电等优点,是月球表面基地能源供给的理想选择。基于100 kWe的供电需求,设计了月球表面热管熔盐堆。使用SCALE 6.1开展了中子物理与屏蔽分析。基于热管的黏性极限、声速极限、携带极限、沸腾极限和毛细极限,采用热阻网络法模拟热管传热,并耦合计算流体力学方法进行了正常工况下全堆芯热工流体分析。分析结果表明:通过三分区堆芯布置可以展平功率;在不需要额外屏蔽和换料的情况下,反应堆可以满功率运行20年;热管传热功率低于传热极限,热管工作在温度限值之内,符合设计要求。整体设计满足月球基地初步建设工作的需求,也可为星球表面熔盐堆设计提供参考。 展开更多
关键词 月球表面 热管 熔盐堆 热阻网络法 分区布置
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基于组合神经网络模型的快堆堆芯瞬态热工水力参数预测方法研究
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作者 赵梓炎 赵鹏程 +2 位作者 刘紫静 李卫 于涛 《核技术》 北大核心 2025年第4期99-111,共13页
对于反应堆热工水力参数的预测,现有的研究多使用单一神经网络的预测方法,但在噪声较大的情况下,单一神经网络不能很好地剔除噪声的影响。本文使用基于经验模态分解法(Empirical Mode Decomposition,EMD)与奇异谱分析法(Singular Spectr... 对于反应堆热工水力参数的预测,现有的研究多使用单一神经网络的预测方法,但在噪声较大的情况下,单一神经网络不能很好地剔除噪声的影响。本文使用基于经验模态分解法(Empirical Mode Decomposition,EMD)与奇异谱分析法(Singular Spectrum Analysis,SSA)结合自适应径向基神经网络(Radial Basis Function Neural Network,RBF)的组合模型提高堆芯热工参数瞬态预测的精度。采用1/2中国实验快堆(China Experimental Fast Reactor,CEFR)为研究对象,使用快堆子通道程序SUBCHANFLOW生成瞬态堆芯热工水力参数的时间序列,并利用组合神经网络模型对堆芯质量流量和包壳表面最高温度时间序列进行单步预测和连续预测。结果表明:相对于单一RBF神经网络,EMD-RBF组合神经网络和EMD-SSA-RBF组合神经网络对质量流量的单步预测误差分别下降41.2%和86.7%,对包壳表面最高温度的单步预测误差分别下降44.7%和60.5%,明显地降低了连续预测误差,且计算时间较短。该方法相比于深度神经网络有一定的优势,对于提高反应堆在工程应用中的安全性有一定的参考价值。 展开更多
关键词 经验模态分解 奇异谱分析 径向基神经网络 热工参数预测 快堆
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基于场路结合的专用车辆机-电-液系统暂态温升预测研究
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作者 何智翔 高剑 +2 位作者 刘锟 赵玉峰 程自然 《微电机》 2025年第8期1-8,共8页
现代专用车辆机电液系统的快速、精准与高可靠热设计,对于保障专用车辆系统可靠性至关重要。本文提出了一种面向现代专用车辆机电液系统的暂态温度场快速计算方法。该方法结合有限元暂态热计算与集总参数热网络理论,通过建立系统的暂态... 现代专用车辆机电液系统的快速、精准与高可靠热设计,对于保障专用车辆系统可靠性至关重要。本文提出了一种面向现代专用车辆机电液系统的暂态温度场快速计算方法。该方法结合有限元暂态热计算与集总参数热网络理论,通过建立系统的暂态集总参数热网络模型,在显著缩短计算时长的基础上保障了温度预测的准确性。首先,通过损耗分析,确定了机电液系统的热源空间分布,基于热阻网络以及有限元理论,构建了机电液系统的暂态温度计算模型。接下来,为验证该模型的准确性和适用性,搭建了机电液系统本体、驱动与控制以及温度测试系统等组成的样机实验平台。最后开展了样机温度测试实验,基于有限元仿真与实验结果,验证了机电液系统暂态集总参数热网络模型的有效性和准确性。实验结果表明,本文中提出的热网络模型与传统有限元计算方法相比,能够保持良好准确性的同时降低80%计算时间,实现了系统暂态温度快速准确预测。此外,本文中提出的暂态集总参数热网络计算方法可以为其他机电液系统的温升预测提供理论参考和依据。 展开更多
关键词 暂态温度场 集总参数热网络法 有限元 机电液系统
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高导热性复合材料三维制备方法的综述
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作者 王悦 侯佳乐 +3 位作者 唐波 王沁 何腾锋 吴新锋 《塑料》 北大核心 2025年第6期143-149,共7页
分析了高导热性复合材料在众多现代科技领域的核心地位及其不可替代的作用,这些领域包括但不限于微电子、光电子、能源转换与存储以及航空航天等。然后,详细介绍了数种先进的三维制备技术,分别为牺牲盐模板法、静电纺丝法、多场耦合法... 分析了高导热性复合材料在众多现代科技领域的核心地位及其不可替代的作用,这些领域包括但不限于微电子、光电子、能源转换与存储以及航空航天等。然后,详细介绍了数种先进的三维制备技术,分别为牺牲盐模板法、静电纺丝法、多场耦合法、原位生长法和碳化骨架法。描述了每种方法独特的制备过程、原理及热导率。通过对这些方法导热性能的总结,发现,构筑三维导热网络结构对于提升复合材料的热导率具有决定性作用。制备过程和对比分析结果均表明,三维导热网络能够有效地提高热传导效率,显著提高了材料的整体导热性能。最后,对高导热复合材料未来的发展前景进行了展望,并提出了对高导热复合材料三维制备方法的完善建议。 展开更多
关键词 三维导热网络 导热复合材料 热导率 制备方法 展望
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基于神经网络方法的布雷顿循环定量分析及多目标优化
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作者 顾新壮 李青芯 +7 位作者 石明 杨瑞睿 殷岳 杨航 马文明 魏务卿 周朔晨 陈昊芃 《热力发电》 北大核心 2025年第11期42-48,共7页
布雷顿循环被公认为第三代太阳能热发电技术的动力循环,得益于神经网络方法具有重要度评估和定量分析等优势。首先,采用控制变量法从多个运行参数中筛选出透平机进口温度和压缩比等重要参数,控制变量法中重要度随着R^(2)值的降低而增加... 布雷顿循环被公认为第三代太阳能热发电技术的动力循环,得益于神经网络方法具有重要度评估和定量分析等优势。首先,采用控制变量法从多个运行参数中筛选出透平机进口温度和压缩比等重要参数,控制变量法中重要度随着R^(2)值的降低而增加,当不含上述重要参数时,其对应的R^(2)值分别降低到0.57和0.64,均低于其余运行参数;然后,采用布雷顿循环中的输出功定量分析结果,其R^(2)值大于0.999,其中热效率和输入热量的R^(2)值分别为0.992和0.988;最后,通过多目标优化结果所推荐的透平机进口温度和压缩比值分别为500℃和2.19,相对应的热效率、输出功和输入热量分别为46.58%、100.97 k J/kg和–176.5 kJ/kg。该研究可作为光热电站布雷顿循环的实际运行和性能研究的参考。 展开更多
关键词 布雷顿循环 神经网络方法 热效率 定量分析 多目标优化
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基于PI-DeepONet模型的IGBT模块结温估算方法
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作者 项江鑫 霍思佳 +2 位作者 乐应波 杨程 崔昊杨 《半导体技术》 北大核心 2025年第7期746-755,共10页
时变高功率工况下,IGBT模块结温的实时准确估算是高效实施热管理策略的基础。但现有方法中,有限元分析(FEA)法难以实时响应,热网络模型法估算准确率低,两者均无法满足结温估算实时性和准确率的均衡性需求。针对这些问题,提出了一种基于... 时变高功率工况下,IGBT模块结温的实时准确估算是高效实施热管理策略的基础。但现有方法中,有限元分析(FEA)法难以实时响应,热网络模型法估算准确率低,两者均无法满足结温估算实时性和准确率的均衡性需求。针对这些问题,提出了一种基于物理约束深度算子网络(PI-DeepONet)模型的IGBT模块结温实时准确估算方法。首先,在算子网络的损失函数中引入物理约束,设计了具有物理约束的PI-DeepONet模型;随后,将FEA计算的IGBT模块热特性参数与时空位置信息作为输入对模型进行训练;最后,利用训练所得的最优算子估算模块结温。仿真结果表明,该模型兼顾了结温估算的准确率和实时性,能够适应复杂工况,为IGBT模块热管理策略的高效实施提供了可靠的理论支持与技术保障。 展开更多
关键词 IGBT 结温估算 物理约束深度算子网络(PI-DeepONet)模型 有限元分析(FEA)法 热网络模型 热管理策略
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