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
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
The press-pack power module with multi-chip layout has drawn increasing attention from industry and academia with its thermal analysis becoming an essential issue.However,the pressure-dependent thermal variables,such ...The press-pack power module with multi-chip layout has drawn increasing attention from industry and academia with its thermal analysis becoming an essential issue.However,the pressure-dependent thermal variables,such as thermal contact resistance and thermal coupling resistance,are often neglected.In this paper,a pressure-dependent thermal network model is developed to characterize the thermal performance and mechanical status of press-pack power modules.By including the thermal contact resistance and thermal coupling resistance as the function of pressure,the proposed model ensures a more precise thermo-mechanical evaluation inside the press-pack power module.The influence of pressure on self-heating effects and thermal coupling effects of power modules is studied using the knowledge of elastic mechanics.A press-pack prototype with variable pressure loads is assembled.Then,thermal experiments under different pressures on chips are conducted and the pressure-variable temperature responses of the thermal network are measured.Consequently,the feasibility of the proposed thermal network model is validated.A cost-effective prognostic method on the mechanical status of press-pack power module is also achieved.展开更多
Realizing effective enhancement in the thermally conductive performance of polymer bonded explosives(PBXs) is vital for improving the resultant environmental adaptabilities of the PBXs composites. Herein, a kind of pr...Realizing effective enhancement in the thermally conductive performance of polymer bonded explosives(PBXs) is vital for improving the resultant environmental adaptabilities of the PBXs composites. Herein, a kind of primary-secondary thermally conductive network was designed by water-suspension granulation, surface coating, and hot-pressing procedures in the graphene-based PBXs composites to greatly increase the thermal conductive performance of the composites. The primary network with a threedimensional structure provided the heat-conducting skeleton, while the secondary network in the polymer matrix bridged the primary network to increase the network density. The enhancement efficiency in the thermally conductive performance of the composites reached the highest value of 59.70% at a primary-secondary network ratio of 3:1. Finite element analysis confirmed the synergistic enhancement effect of the primary and secondary thermally conductive networks. This study introduces an innovative approach to designing network structures for PBX composites, significantly enhancing their thermal conductivity.展开更多
Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required fo...Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations.A unique three-dimensional(3D)lumped parameter thermal network(LPTN)is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator(OR-HPMFSG)for direct-drive applications.First,the losses of the OR-HPMFSG are calculated using 3D finite element analysis(FEA).Subsequently,all machine components considering the thermal contact resistance,anisotropic thermal conductivity of materials,and various heat flow paths are comprehensively modeled based on the thermal resistances.In the proposed 3-D LPTN,internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components.Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN.A comparison of the results at various operating points between the developed 3-D LPTN,experimental test,and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.展开更多
Constructing controllable thermal conduction networks is the key to efficiently improve thermal conductivities of polymer composites.In this work,graphite oxide(GO)and functionalized carbon nanotubes(f-CNTs)are combin...Constructing controllable thermal conduction networks is the key to efficiently improve thermal conductivities of polymer composites.In this work,graphite oxide(GO)and functionalized carbon nanotubes(f-CNTs)are combined to prepare“Line-Plane”-like hetero-structured thermally conductive GO@f-CNTs fillers,which are then performed to construct controllable 3D GO@f-CNTs thermal conduction networks via selfsacrificing template method based on oxalic acid.Subsequently,thermally conductive GO@f-CNTs/polydimethylsiloxane(PDMS)composites are fabricated via casting method.When the size of oxalic acid is 0.24 mm and the volume fraction of GO@f-CNTs is 60 vol%,GO@f-CNTs/PDMS composites present the optimal thermal conductivity coefficient(λ,4.00 W·m^(-1)·K^(-1)),about 20 times that of theλof neat PDMS(0.20 W·m^(-1)·K^(-1)),also much higher than theλ(2.44 W·m^(-1)·K^(-1))of GO/f-CNTs/PDMS composites with the same amount of randomly dispersed fillers.Meanwhile,the obtained GO@f-CNTs/PDMS composites have excellent thermal stability,whoseλdeviation is only about 3%after 500 thermal cycles(20-200℃).展开更多
As one of the core components of a magnetic refrigerator,magnetic refrigeration materials are expected to have not only a considerable magnetocaloric effect but also excellent thermal conductivity.The poor thermal con...As one of the core components of a magnetic refrigerator,magnetic refrigeration materials are expected to have not only a considerable magnetocaloric effect but also excellent thermal conductivity.The poor thermal conductivity of many competitive oxide-based magnetic refrigerants,exemplified by EuTiO3-based compounds,acts as a major limitation to their practical application.Therefore,improving the thermal conductivity of magnetic refrigeration materials has become a research emphasis of magnetic refrigeration in recent years.In this work,a series of EuTiO_(3)(ETO)/Cu composites with different copper additives was prepared using a solid-phase reaction method by introducing appropriate amounts of copper powder.The influence of the introduction of copper on the phase composition,microstructure,thermal conductivity,and magnetocaloric effect of the composites was systematically investigated.Unexpectedly,the thermal conductivity of the composites is enhanced by up to 260%due to copper addition,accompanied by only a 5%decrease in magnetic entropy change and refrigerating capacity.Copper additive forms localized thermal conductive networks and promotes the densification process,resulting in significantly enhanced thermal conductivity of the composites.This work demonstrates the feasibility of improving the thermal conductivity of oxide-base d magnetic refrigeration materials by introducing highly thermally conductive substances.展开更多
For distribution optimization of the flow rate of cold fluid and heat transfer area in the parallel thermal network of the thermal control system in spacecraft,a physical and mathematical model is set up,analyzed and ...For distribution optimization of the flow rate of cold fluid and heat transfer area in the parallel thermal network of the thermal control system in spacecraft,a physical and mathematical model is set up,analyzed and discussed with the entransy theory.It is found that the optimization objective of this problem and the optimization direction of the extremum entransy dissipation principle are consistent in theory.For a two-branch thermal network system,the distributions of the flow rate of the cold fluid and the heat transfer area are optimized by calculating the extremum entransy dissipation with the Newton method.The influential factors of the optimized distributions are also analyzed and discussed.The results show that the main influence factors are the heat transfer rate of the branches and the total heat transfer area.The total flow rate of the cold fluid has a threshold,beyond which further increasing its value brings very little influence on the optimization results.Moreover,the difference between the extremum entransy dissipation principle and the minimum entropy generation principle is also discussed when they are used to analyze the problem in this paper,and the extremum entransy dissipation principle is found to be more suitable.In addition,the Newton method is mathematically efficient to solve the problem,which could accomplish the optimized distribution in a very short time for a ten-branch thermal network system.展开更多
The one-stream hybrid thermal network is analyzed and discussed based on the entransy theory,and the results are compared with those from the entropy generation optimization.The theoretical analysis indicates that the...The one-stream hybrid thermal network is analyzed and discussed based on the entransy theory,and the results are compared with those from the entropy generation optimization.The theoretical analysis indicates that the minimum heat-flow-weighted temperature of the thermal networks corresponds to the minimum entransy dissipation rate and the minimum thermal resistance.For a simple hybrid thermal network consisting of three thermal components,the expression of entransy dissipation is conducted,and the heat transfer area and the mass flow rate are calculated and optimized.The optimal results are obtained in order to minimize the entransy dissipation and the thermal resistance.The optimal results are calculated for various combinations,such as series connection,parallel connection and other hybrid connections.The numerical results are in accordance with the theoretical analysis.Both the theoretical analysis and the numerical results show that the minimum entransy dissipation and the minimum thermal resistance correspond to the minimum heat-flow-weighted temperature of the thermal networks while the minimum entropy generation does not.展开更多
Hermetically Sealed Electromagnetic Relay(HSER), used in aviation and aerospace,demands high reliability due to its critical applications. Given its complex operating conditions, efficient thermal analysis is essentia...Hermetically Sealed Electromagnetic Relay(HSER), used in aviation and aerospace,demands high reliability due to its critical applications. Given its complex operating conditions, efficient thermal analysis is essential for optimizing reliability. The commonly used Finite Element Method(FEM) is often time-consuming and may not be efficient or adaptable for complex multi-dimensional system calculations and design processes. This paper introduces an analysis method for thermal networks based on matrix perspective technology, encompassing matrix transformation, backpropagation of the heat path model, temperature rise calculation, solution comparison, and product implementation. Using the similarity theory of heat circuits, a basic thermal unit is established. Based on the fundamental connection between key components, a thermal network for a typical HSER is designed. An experimental system is set up, and the thermal network model's accuracy is confirmed using test data. Employing the topology analysis method, the topology of the thermal network is analyzed under both coil-energized and de-energized states. Potential thermal paths are identified, leading to optimized solutions for the HSER. Utilizing these solutions, the thermal path matrix topology model is backpropagated to the thermal path for temperature rise calculations. When compared to prototype HSER test data, the efficiency and accuracy of this matrix topology-based analysis method are confirmed.展开更多
With the continuous development of the electronics industry,the energy density of modern electronic devices increases constantly,thus releasing a lot of heat during operation.Modern electronic devices take higher and ...With the continuous development of the electronics industry,the energy density of modern electronic devices increases constantly,thus releasing a lot of heat during operation.Modern electronic devices take higher and higher request to the thermal interface materials.Achieving high thermal conductivity needs to establish an interconnecting thermal conductivity network in the matrix.For this purpose,the suspension of Al203 and curdlan was first foamed to construct a bubble-templated continuous ceramic framework.Owing to the rapid gelation property of curdlan,we can easily remove moisture by hot air drying.Finally,the high thermally conductive composites are prepared by vacuum impregnation of silicone rubber.The result showed that composites prepared by our method have higher thermal conductivity than the samples obtained by traditional method.The thermal conductivity of the prepared composite material reached 1.253 W·m^(-1)·K·^-(1)when the alumina content was 69.6 wt%.This facile method is expected to be applied to the preparation of high-performance thermal interface materials.展开更多
Accurate estimation of liquid thermal conductivity is highly necessary to appropriately design equipments in different industries. Respect to this necessity, in the current investigation a feed-forward artificial neur...Accurate estimation of liquid thermal conductivity is highly necessary to appropriately design equipments in different industries. Respect to this necessity, in the current investigation a feed-forward artificial neural network(ANN) model is examined to correlate the liquid thermal conductivity of normal and aromatic hydrocarbons at the temperatures range of 257–338 K and atmospheric pressure. For this purpose, 956 experimental thermal conductivities for normal and aromatic hydrocarbons are collected from different previously published literature.During the modeling stage, to discriminate different substances, critical temperature(Tc), critical pressure(Pc)and acentric factor(ω) are utilized as the network inputs besides the temperature. During the examination, effects of different transfer functions and number of neurons in hidden layer are investigated to find the optimum network architecture. Besides, statistical error analysis considering the results obtained from available correlations and group contribution methods and proposed neural network is performed to reliably check the feasibility and accuracy of the proposed method. Respect to the obtained results, it can be concluded that the proposed neural network consisted of three layers namely, input, hidden and output layers with 22 neurons in hidden layer was the optimum ANN model. Generally, the proposed model enables to correlate the thermal conductivity of normal and aromatic hydrocarbons with absolute average relative deviation percent(AARD), mean square error(MSE), and correlation coefficient(R^2) of lower than 0.2%, 1.05 × 10^(-7) and 0.9994, respectively.展开更多
To develop a high performance gray cast iron with high tensile strength and thermal conductivity, multivariable analysis of microstructural effects on properties of gray cast iron was performed. The concerned paramete...To develop a high performance gray cast iron with high tensile strength and thermal conductivity, multivariable analysis of microstructural effects on properties of gray cast iron was performed. The concerned parameters consisted of graphite content, maximum graphite length, primary dendrite percentage and microhardness of the matrix. Under the superposed influence of various parameters, the relationships between thermal conductivity and structural characteristics become irregular, as well as the effects of graphite length on the strength. An adaptive neuro-fuzzy inference system was built to link the parameters and properties. A sensitivity test was then performed to rank the relative impact of parameters. It was found that the dominant parameter for tensile strength is graphite content, while the most relative parameter for thermal conductivity is maximum graphite length. The most effective method to simultaneously improve the tensile and thermal conductivity of gray cast iron is to reduce the carbon equivalent and increase the length of graphite flakes.展开更多
Electrical transformers are vital components found virtually in most power-operated equipments. These transformers spontaneously radiate heat in both operation and steady-state mode. Should this thermal radiation inhe...Electrical transformers are vital components found virtually in most power-operated equipments. These transformers spontaneously radiate heat in both operation and steady-state mode. Should this thermal radiation inherent in transformers rises above allowable threshold a reduction in efficiency of operation occurs. In addition, this could cause other components in the system to malfunction. The aim of this work is to detect the remote causes of this undesirable thermal rise in transformers such as oil distribution transformers and ways to control this prevailing thermal problem. Oil transformers consist of these components: windings usually made of copper or aluminum conductor, the core normally made of silicon steel, the heat radiators, and the dielectric materials such as transformer oil, cellulose insulators and other peripherals. The Resistor-Inductor-Capacitor Thermal Network (RLCTN) model at architectural level identifies with these components to have ensemble operational mode as oil transformer. The Inductor represents the windings, the Resistor representing the core and the Capacitor represents the dielectrics. Thermography of transformer under various loading conditions was analyzed base on Infrared thermal gradient. Mathematical, experimental, and simulation results gotten through RLCTN with respect to time and thermal image analysis proved that the capacitance of the dielectric is inversely proportional to the thermal rise.展开更多
This study explored the potential of using probabilistic neural networks (PNN) to predict shrinkage of thermal insulation mortar.Probabilistic results were obtained from the PNN model with the aid of Parzen non-parame...This study explored the potential of using probabilistic neural networks (PNN) to predict shrinkage of thermal insulation mortar.Probabilistic results were obtained from the PNN model with the aid of Parzen non-parametric estimator of the probability density functions (PDF).Five variables,water-cementitious materials ratio,content of cement,fly ash,aggregate and plasticizer,were employed for input variables,while a category of 56-d shrinkage of mortar was used for the output variable.A total of 192 groups of experimental data from 64 mixtures designed using JMP7.0 software were collected,of which 120 groups of data were used for training the model and the other 72 groups of data for testing.The simulation results showed that the PNN model with an optimal smoothing parameter determined by the curves of the mean square error (MSE) and the number of unrecognized probability densities (UPDs) exhibited a promising capability of predicting shrinkage of mortar.展开更多
We introduce a thermal flux-diffusing model for complex networks. Based on this model, we propose a physical method to detect the communities in the complex networks. The method allows us to obtain the temperature dis...We introduce a thermal flux-diffusing model for complex networks. Based on this model, we propose a physical method to detect the communities in the complex networks. The method allows us to obtain the temperature distribution of nodes in time that scales linearly with the network size. Then, the local community enclosing a given node can be easily detected for the reason that the dense connections in the local communities lead to the temperatures of nodes in the same community being close to each other. The community structure of a network can be recursively detected by randomly choosing the nodes outside the detected local communities. In the experiments, we apply our method to a set of benchmarking networks with known pre-determined community structures. The experiment results show that our method has higher accuracy and precision than most existing globe methods and is better than the other existing local methods in the selection of the initial node. Finally. several real-world networks are investigated.展开更多
Asymmetric tree-like branched networks are explored by geometric algorithms. Based on the network, an analysis of the thermal conductivity is presented. The relationship between effective thermal conductivity and geom...Asymmetric tree-like branched networks are explored by geometric algorithms. Based on the network, an analysis of the thermal conductivity is presented. The relationship between effective thermal conductivity and geometric structures is obtained by using the thermal-electrical analogy technique. In all studied cases, a clear behaviour is observed, where angle （δ,θ） among parent branching extended lines, branches and parameter of the geometric structures have stronger effects on the effective thermal conductivity. When the angle δ is fixed, the optical diameter ratio β＋ is dependent on angle θ. Moreover, γand m are not related to β＊. The longer the branch is, the smaller the effective thermal conductivity will be. It is also found that when the angle θ〈δ2, the higher the iteration m is, the lower the thermal conductivity will be and it tends to zero, otherwise, it is bigger than zero. When the diameter ratio β1 〈 0.707 and angle δ is bigger, the optimal k of the perfect ratio increases with the increase of the angle δ; when β1 〉 0.707, the optimal k decreases. In addition, the effective thermal conductivity is always less than that of single channel material. The present results also show that the effective thermal conductivity of the asymmetric tree-like branched networks does not obey Murray＇s law.展开更多
基金National Key R&D Program(Grant No.2020YFB2007700),National Natural Science Foundation of China(Grant Nos.11790282,12032017,12002221 and 11872256)S&T Program of Hebei(Grant No.20310803D)+1 种基金Natural Science Foundation of Hebei Province(Grant No.A2020210028)State Foundation for Studying Abroad.
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(5187719252107211)the Zhejiang Provincial Natural Science Foundation of China(LQ21E070006).
文摘The press-pack power module with multi-chip layout has drawn increasing attention from industry and academia with its thermal analysis becoming an essential issue.However,the pressure-dependent thermal variables,such as thermal contact resistance and thermal coupling resistance,are often neglected.In this paper,a pressure-dependent thermal network model is developed to characterize the thermal performance and mechanical status of press-pack power modules.By including the thermal contact resistance and thermal coupling resistance as the function of pressure,the proposed model ensures a more precise thermo-mechanical evaluation inside the press-pack power module.The influence of pressure on self-heating effects and thermal coupling effects of power modules is studied using the knowledge of elastic mechanics.A press-pack prototype with variable pressure loads is assembled.Then,thermal experiments under different pressures on chips are conducted and the pressure-variable temperature responses of the thermal network are measured.Consequently,the feasibility of the proposed thermal network model is validated.A cost-effective prognostic method on the mechanical status of press-pack power module is also achieved.
基金supported by the National Natural Science Foundation of China (Grant Nos. 22475179 and 22275173)。
文摘Realizing effective enhancement in the thermally conductive performance of polymer bonded explosives(PBXs) is vital for improving the resultant environmental adaptabilities of the PBXs composites. Herein, a kind of primary-secondary thermally conductive network was designed by water-suspension granulation, surface coating, and hot-pressing procedures in the graphene-based PBXs composites to greatly increase the thermal conductive performance of the composites. The primary network with a threedimensional structure provided the heat-conducting skeleton, while the secondary network in the polymer matrix bridged the primary network to increase the network density. The enhancement efficiency in the thermally conductive performance of the composites reached the highest value of 59.70% at a primary-secondary network ratio of 3:1. Finite element analysis confirmed the synergistic enhancement effect of the primary and secondary thermally conductive networks. This study introduces an innovative approach to designing network structures for PBX composites, significantly enhancing their thermal conductivity.
文摘Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations.A unique three-dimensional(3D)lumped parameter thermal network(LPTN)is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator(OR-HPMFSG)for direct-drive applications.First,the losses of the OR-HPMFSG are calculated using 3D finite element analysis(FEA).Subsequently,all machine components considering the thermal contact resistance,anisotropic thermal conductivity of materials,and various heat flow paths are comprehensively modeled based on the thermal resistances.In the proposed 3-D LPTN,internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components.Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN.A comparison of the results at various operating points between the developed 3-D LPTN,experimental test,and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.
基金financially supported by the National Natural Science Foundation of China(No.51973173)Technological Base Scientific Research Projects(Highly Thermally Conductive Nonmetal Materials)+3 种基金Natural Science Foundation of Chongqing,China(No.2023NSCQ-MSX2547)Shaanxi Province Key Research and Development Plan Project(No.2023-YBGY-461)Fundamental Research Funds for the Central Universities,the Innovation Capability Support Program of Shaanxi(No.2024RS-CXTD-57)financially supported by Polymer Electromagnetic Functional Materials Innovation Team of Shaanxi Sanqin Scholars。
文摘Constructing controllable thermal conduction networks is the key to efficiently improve thermal conductivities of polymer composites.In this work,graphite oxide(GO)and functionalized carbon nanotubes(f-CNTs)are combined to prepare“Line-Plane”-like hetero-structured thermally conductive GO@f-CNTs fillers,which are then performed to construct controllable 3D GO@f-CNTs thermal conduction networks via selfsacrificing template method based on oxalic acid.Subsequently,thermally conductive GO@f-CNTs/polydimethylsiloxane(PDMS)composites are fabricated via casting method.When the size of oxalic acid is 0.24 mm and the volume fraction of GO@f-CNTs is 60 vol%,GO@f-CNTs/PDMS composites present the optimal thermal conductivity coefficient(λ,4.00 W·m^(-1)·K^(-1)),about 20 times that of theλof neat PDMS(0.20 W·m^(-1)·K^(-1)),also much higher than theλ(2.44 W·m^(-1)·K^(-1))of GO/f-CNTs/PDMS composites with the same amount of randomly dispersed fillers.Meanwhile,the obtained GO@f-CNTs/PDMS composites have excellent thermal stability,whoseλdeviation is only about 3%after 500 thermal cycles(20-200℃).
基金Project supported by the National Key R&D Program of China(2021YFB3501204)the National Science Fund for Distinguished Young Scholars(51925605)+1 种基金the National Science Foundation for Excellent Young Scholars(52222107)the National Natural Science Foundation of China(52171195,52201036)。
文摘As one of the core components of a magnetic refrigerator,magnetic refrigeration materials are expected to have not only a considerable magnetocaloric effect but also excellent thermal conductivity.The poor thermal conductivity of many competitive oxide-based magnetic refrigerants,exemplified by EuTiO3-based compounds,acts as a major limitation to their practical application.Therefore,improving the thermal conductivity of magnetic refrigeration materials has become a research emphasis of magnetic refrigeration in recent years.In this work,a series of EuTiO_(3)(ETO)/Cu composites with different copper additives was prepared using a solid-phase reaction method by introducing appropriate amounts of copper powder.The influence of the introduction of copper on the phase composition,microstructure,thermal conductivity,and magnetocaloric effect of the composites was systematically investigated.Unexpectedly,the thermal conductivity of the composites is enhanced by up to 260%due to copper addition,accompanied by only a 5%decrease in magnetic entropy change and refrigerating capacity.Copper additive forms localized thermal conductive networks and promotes the densification process,resulting in significantly enhanced thermal conductivity of the composites.This work demonstrates the feasibility of improving the thermal conductivity of oxide-base d magnetic refrigeration materials by introducing highly thermally conductive substances.
基金supported by Tsinghua University Initiative Scientific Research Program
文摘For distribution optimization of the flow rate of cold fluid and heat transfer area in the parallel thermal network of the thermal control system in spacecraft,a physical and mathematical model is set up,analyzed and discussed with the entransy theory.It is found that the optimization objective of this problem and the optimization direction of the extremum entransy dissipation principle are consistent in theory.For a two-branch thermal network system,the distributions of the flow rate of the cold fluid and the heat transfer area are optimized by calculating the extremum entransy dissipation with the Newton method.The influential factors of the optimized distributions are also analyzed and discussed.The results show that the main influence factors are the heat transfer rate of the branches and the total heat transfer area.The total flow rate of the cold fluid has a threshold,beyond which further increasing its value brings very little influence on the optimization results.Moreover,the difference between the extremum entransy dissipation principle and the minimum entropy generation principle is also discussed when they are used to analyze the problem in this paper,and the extremum entransy dissipation principle is found to be more suitable.In addition,the Newton method is mathematically efficient to solve the problem,which could accomplish the optimized distribution in a very short time for a ten-branch thermal network system.
基金supported by the Natural Science Foundation of China(Grant No. 51136001)the Tsinghua University Initiative Scientific Research Program
文摘The one-stream hybrid thermal network is analyzed and discussed based on the entransy theory,and the results are compared with those from the entropy generation optimization.The theoretical analysis indicates that the minimum heat-flow-weighted temperature of the thermal networks corresponds to the minimum entransy dissipation rate and the minimum thermal resistance.For a simple hybrid thermal network consisting of three thermal components,the expression of entransy dissipation is conducted,and the heat transfer area and the mass flow rate are calculated and optimized.The optimal results are obtained in order to minimize the entransy dissipation and the thermal resistance.The optimal results are calculated for various combinations,such as series connection,parallel connection and other hybrid connections.The numerical results are in accordance with the theoretical analysis.Both the theoretical analysis and the numerical results show that the minimum entransy dissipation and the minimum thermal resistance correspond to the minimum heat-flow-weighted temperature of the thermal networks while the minimum entropy generation does not.
基金supported by the National Natural Science Foundation of China (No. 52177134)。
文摘Hermetically Sealed Electromagnetic Relay(HSER), used in aviation and aerospace,demands high reliability due to its critical applications. Given its complex operating conditions, efficient thermal analysis is essential for optimizing reliability. The commonly used Finite Element Method(FEM) is often time-consuming and may not be efficient or adaptable for complex multi-dimensional system calculations and design processes. This paper introduces an analysis method for thermal networks based on matrix perspective technology, encompassing matrix transformation, backpropagation of the heat path model, temperature rise calculation, solution comparison, and product implementation. Using the similarity theory of heat circuits, a basic thermal unit is established. Based on the fundamental connection between key components, a thermal network for a typical HSER is designed. An experimental system is set up, and the thermal network model's accuracy is confirmed using test data. Employing the topology analysis method, the topology of the thermal network is analyzed under both coil-energized and de-energized states. Potential thermal paths are identified, leading to optimized solutions for the HSER. Utilizing these solutions, the thermal path matrix topology model is backpropagated to the thermal path for temperature rise calculations. When compared to prototype HSER test data, the efficiency and accuracy of this matrix topology-based analysis method are confirmed.
基金the financial support from the Joint Foundation of Ministry of Education for equipment pre-research(No.6141A020222XX)Post-doctoral Science Fund(No.2020M680405).
文摘With the continuous development of the electronics industry,the energy density of modern electronic devices increases constantly,thus releasing a lot of heat during operation.Modern electronic devices take higher and higher request to the thermal interface materials.Achieving high thermal conductivity needs to establish an interconnecting thermal conductivity network in the matrix.For this purpose,the suspension of Al203 and curdlan was first foamed to construct a bubble-templated continuous ceramic framework.Owing to the rapid gelation property of curdlan,we can easily remove moisture by hot air drying.Finally,the high thermally conductive composites are prepared by vacuum impregnation of silicone rubber.The result showed that composites prepared by our method have higher thermal conductivity than the samples obtained by traditional method.The thermal conductivity of the prepared composite material reached 1.253 W·m^(-1)·K·^-(1)when the alumina content was 69.6 wt%.This facile method is expected to be applied to the preparation of high-performance thermal interface materials.
文摘Accurate estimation of liquid thermal conductivity is highly necessary to appropriately design equipments in different industries. Respect to this necessity, in the current investigation a feed-forward artificial neural network(ANN) model is examined to correlate the liquid thermal conductivity of normal and aromatic hydrocarbons at the temperatures range of 257–338 K and atmospheric pressure. For this purpose, 956 experimental thermal conductivities for normal and aromatic hydrocarbons are collected from different previously published literature.During the modeling stage, to discriminate different substances, critical temperature(Tc), critical pressure(Pc)and acentric factor(ω) are utilized as the network inputs besides the temperature. During the examination, effects of different transfer functions and number of neurons in hidden layer are investigated to find the optimum network architecture. Besides, statistical error analysis considering the results obtained from available correlations and group contribution methods and proposed neural network is performed to reliably check the feasibility and accuracy of the proposed method. Respect to the obtained results, it can be concluded that the proposed neural network consisted of three layers namely, input, hidden and output layers with 22 neurons in hidden layer was the optimum ANN model. Generally, the proposed model enables to correlate the thermal conductivity of normal and aromatic hydrocarbons with absolute average relative deviation percent(AARD), mean square error(MSE), and correlation coefficient(R^2) of lower than 0.2%, 1.05 × 10^(-7) and 0.9994, respectively.
文摘To develop a high performance gray cast iron with high tensile strength and thermal conductivity, multivariable analysis of microstructural effects on properties of gray cast iron was performed. The concerned parameters consisted of graphite content, maximum graphite length, primary dendrite percentage and microhardness of the matrix. Under the superposed influence of various parameters, the relationships between thermal conductivity and structural characteristics become irregular, as well as the effects of graphite length on the strength. An adaptive neuro-fuzzy inference system was built to link the parameters and properties. A sensitivity test was then performed to rank the relative impact of parameters. It was found that the dominant parameter for tensile strength is graphite content, while the most relative parameter for thermal conductivity is maximum graphite length. The most effective method to simultaneously improve the tensile and thermal conductivity of gray cast iron is to reduce the carbon equivalent and increase the length of graphite flakes.
文摘Electrical transformers are vital components found virtually in most power-operated equipments. These transformers spontaneously radiate heat in both operation and steady-state mode. Should this thermal radiation inherent in transformers rises above allowable threshold a reduction in efficiency of operation occurs. In addition, this could cause other components in the system to malfunction. The aim of this work is to detect the remote causes of this undesirable thermal rise in transformers such as oil distribution transformers and ways to control this prevailing thermal problem. Oil transformers consist of these components: windings usually made of copper or aluminum conductor, the core normally made of silicon steel, the heat radiators, and the dielectric materials such as transformer oil, cellulose insulators and other peripherals. The Resistor-Inductor-Capacitor Thermal Network (RLCTN) model at architectural level identifies with these components to have ensemble operational mode as oil transformer. The Inductor represents the windings, the Resistor representing the core and the Capacitor represents the dielectrics. Thermography of transformer under various loading conditions was analyzed base on Infrared thermal gradient. Mathematical, experimental, and simulation results gotten through RLCTN with respect to time and thermal image analysis proved that the capacitance of the dielectric is inversely proportional to the thermal rise.
基金Project (No. 2006BAJ05B03) supported by the National Key Tech-nologies Supporting Program of China during the 11th Five-Year Plan Period
文摘This study explored the potential of using probabilistic neural networks (PNN) to predict shrinkage of thermal insulation mortar.Probabilistic results were obtained from the PNN model with the aid of Parzen non-parametric estimator of the probability density functions (PDF).Five variables,water-cementitious materials ratio,content of cement,fly ash,aggregate and plasticizer,were employed for input variables,while a category of 56-d shrinkage of mortar was used for the output variable.A total of 192 groups of experimental data from 64 mixtures designed using JMP7.0 software were collected,of which 120 groups of data were used for training the model and the other 72 groups of data for testing.The simulation results showed that the PNN model with an optimal smoothing parameter determined by the curves of the mean square error (MSE) and the number of unrecognized probability densities (UPDs) exhibited a promising capability of predicting shrinkage of mortar.
基金Project supported by the National Natural Science Foundation of China (Grant No. 60672095)the Fundamental Research Funds for the Central Universities,China (Grant No. KYZ201300)the Youth Sci-Tech Innovation Fund of Nanjing Agricultural University, China (Grant No. KJ2010024)
文摘We introduce a thermal flux-diffusing model for complex networks. Based on this model, we propose a physical method to detect the communities in the complex networks. The method allows us to obtain the temperature distribution of nodes in time that scales linearly with the network size. Then, the local community enclosing a given node can be easily detected for the reason that the dense connections in the local communities lead to the temperatures of nodes in the same community being close to each other. The community structure of a network can be recursively detected by randomly choosing the nodes outside the detected local communities. In the experiments, we apply our method to a set of benchmarking networks with known pre-determined community structures. The experiment results show that our method has higher accuracy and precision than most existing globe methods and is better than the other existing local methods in the selection of the initial node. Finally. several real-world networks are investigated.
基金Project supported by the State Key Development Program for Basic Research of China (Grant No 2006CB708612)the National Natural Science Foundation of China (Grant No 10572130)the Natural Science Foundation of Zhejiang Province, China (Grant No Y607425)
文摘Asymmetric tree-like branched networks are explored by geometric algorithms. Based on the network, an analysis of the thermal conductivity is presented. The relationship between effective thermal conductivity and geometric structures is obtained by using the thermal-electrical analogy technique. In all studied cases, a clear behaviour is observed, where angle （δ,θ） among parent branching extended lines, branches and parameter of the geometric structures have stronger effects on the effective thermal conductivity. When the angle δ is fixed, the optical diameter ratio β＋ is dependent on angle θ. Moreover, γand m are not related to β＊. The longer the branch is, the smaller the effective thermal conductivity will be. It is also found that when the angle θ〈δ2, the higher the iteration m is, the lower the thermal conductivity will be and it tends to zero, otherwise, it is bigger than zero. When the diameter ratio β1 〈 0.707 and angle δ is bigger, the optimal k of the perfect ratio increases with the increase of the angle δ; when β1 〉 0.707, the optimal k decreases. In addition, the effective thermal conductivity is always less than that of single channel material. The present results also show that the effective thermal conductivity of the asymmetric tree-like branched networks does not obey Murray＇s law.
