One of the greatest challenges in the design of a gun is to balance muzzle velocity and recoil,especially for guns on aircrafts and deployable vehicles.To resolve the conflict between gun power and recoil force,a conc...One of the greatest challenges in the design of a gun is to balance muzzle velocity and recoil,especially for guns on aircrafts and deployable vehicles.To resolve the conflict between gun power and recoil force,a concept of rarefaction wave gun(RAVEN)was proposed to significantly reduce the weapon recoil and the heat in barrel,while minimally reducing the muzzle velocity.The main principle of RAVEN is that the rarefaction wave will not reach the projectile base until the muzzle by delaying the venting time of an expansion nozzle at the breech.Developed on the RAVEN principle,the purpose of this paper is to provide an engineering method for predicting the performance of a low-recoil gun with front nozzle.First,a two-dimensional two-phase flow model of interior ballistic during the RAVEN firing cycle was established.Numerical simulation results were compared with the published data to validate the reliability and accuracy.Next,the effects of the vent opening times and locations were investigated to determine the influence rules on the performance of the RAVEN with front nozzle.Then according to the results above,simple nonlinear fitting formulas were provided to explain how the muzzle velocity and the recoil force change with the vent opening time and location.Finally,a better vent venting opening time corresponding to the vent location was proposed.The findings should make an important contribution to the field of engineering applications of the RAVEN.展开更多
To improve prediction accuracy of strip thickness in hot rolling, a kind of Dempster/Shafer(D_S) information reconstitution prediction method(DSIRPM) was presented. DSIRPM basically consisted of three steps to impleme...To improve prediction accuracy of strip thickness in hot rolling, a kind of Dempster/Shafer(D_S) information reconstitution prediction method(DSIRPM) was presented. DSIRPM basically consisted of three steps to implement the prediction of strip thickness. Firstly, iba Analyzer was employed to analyze the periodicity of hot rolling and find three sensitive parameters to strip thickness, which were used to undertake polynomial curve fitting prediction based on least square respectively, and preliminary prediction results were obtained. Then, D_S evidence theory was used to reconstruct the prediction results under different parameters, in which basic probability assignment(BPA) was the key and the proposed contribution rate calculated using grey relational degree was regarded as BPA, which realizes BPA selection objectively. Finally, from this distribution, future strip thickness trend was inferred. Experimental results clearly show the improved prediction accuracy and stability compared with other prediction models, such as GM(1,1) and the weighted average prediction model.展开更多
Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanc...Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.展开更多
The fatigue life for components can be predicted by the plot method which is easy and convenient in engineering. Based on the usual fatigue life prediction formula, a new formula for estimating the low stress and hig...The fatigue life for components can be predicted by the plot method which is easy and convenient in engineering. Based on the usual fatigue life prediction formula, a new formula for estimating the low stress and high cycle fatigue life is proposed and deduced, which has adopted more accurate SN curve relationship——WeibullSN curve formula. The solution of the new formula is given, too. In addition, an example has been calculated and proved in practice. The results of the new formula and the old one are given and compared.展开更多
The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soil...The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.展开更多
The impact of vibrations due to underground trains on Beijing metro line 15 on sensitive equipment in the Institute of Microelectronics of Tsinghua University was discussed to propose a viable solution to mitigate the...The impact of vibrations due to underground trains on Beijing metro line 15 on sensitive equipment in the Institute of Microelectronics of Tsinghua University was discussed to propose a viable solution to mitigate the vibrations.Using the state-of-the-art three-dimensional coupled periodic finite element-boundary element(FE-BE) method,the dynamic track-tunnel-soil interaction model for metro line 15 was used to predict vibrations in the free field at a train speed of 80 km/h.Three types of tracks(direct fixation fasteners,floating slab track and floating ladder track) on the Beijing metro network were considered in the model. For each track,the acceleration response in the free field was obtained.The numerical results show that the influence of vibrations from underground trains on sensitive equipment depends on the track types.At frequencies above 10 Hz,the floating slab track with a natural frequency of 7 Hz can be effective to attenuate the vibrations.展开更多
Fighters and other complex engineering systems have many characteristics such as difficult modeling and testing, multiple working situations, and high cost. Aim at these points, a new kind of real-time fault predictor...Fighters and other complex engineering systems have many characteristics such as difficult modeling and testing, multiple working situations, and high cost. Aim at these points, a new kind of real-time fault predictor is designed based on an improved k-nearest neighbor method, which needs neither the math model of system nc, the training data and prior knowledge. It can study and predict while system＇s running, so that it can overcome the difficulty of data acquirement. Besides, this predictor has a fast prediction speed, and the false alarm rate and missing alarm rate can be adjusted randomly. The method is simple and universalizable. The result of simulation on fighter F-16 proved the effidency.展开更多
This study aims to reveal the macroscopic permanent deformation(PD)behavior and the internal structural evolution of construction and demolition waste(CDW)under loading.Firstly,the initial matric suction of CDW was me...This study aims to reveal the macroscopic permanent deformation(PD)behavior and the internal structural evolution of construction and demolition waste(CDW)under loading.Firstly,the initial matric suction of CDW was measured by the filter paper method.Secondly,the PD of CDW with different humidity and stress states was investigated by repeated load triaxial tests,and a comprehensive prediction model was established.Finally,the discrete element method was performed to analyze the internal structural evolution of CDW during deformation.These results showed that the VAN-GENUCHTEN model could describe the soil-water characteristic curve of CDW well.The PD increases with the increase of the deviator stress and the number of cyclic loading,but the opposite trend was observed when the initial matric suction and confining pressure increased.The proposed model in this study provides a satisfactory prediction of PD.The discrete element method could accurately simulate the macroscopic PD of CDW,and the shear force,interlock force and sliding content increase with the increase of deviator stress during the deformation.The research could provide useful reference for the deformation stability analysis of CDW under cyclic loading.展开更多
A prediction method to obtain harmonic reference for active power filter is presented. It is a new use ofthe adaptive predictive filter based on FIR. The delay inherent in digital controller is successfully compensate...A prediction method to obtain harmonic reference for active power filter is presented. It is a new use ofthe adaptive predictive filter based on FIR. The delay inherent in digital controller is successfully compensated by u-sing the proposed method, and the computing load is not very large compared with the conventional method. Moreo-ver, no additional hardware is needed. Its DSP-based realization is also presented, which is characterized by time-va-riant rate sampling, quasi synchronous sampling, and synchronous operation among the line frequency, PWM gener-ating and sampling in A/D unit. Synchronous operation releases the limitation on PWM modulation ratio and guar-antees that the electrical noises resulting from the switching operation of IGBTs do not interfere with the sampledcurrent. The simulation and experimental results verify the satisfactory performance of the proposed method.展开更多
This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modif...This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modifications(PMs)are considered.For the prediction,a discrete gear model for generating the error tooth profile based on the ISO accuracy grade is presented.Then,the gear model and a tooth deflection model for calculating the tooth compliance on gear meshing are coupled with the transmission error model to make the prediction by checking the interference status between gear and pinion.The prediction method is validated by comparison with the experimental results from the literature,and a set of cases are simulated to study the effects of MEs,AEs,TDs and PMs on the static transmission error.In addition,the time-varying backlash caused by both MEs and AEs,and the contact ratio under load conditions are also investigated.The results show that the novel method can effectively predict the range of the static transmission error under different accuracy grades.The prediction results can provide references for the selection of gear design parameters and the optimization of transmission performance in the design stage of gear systems.展开更多
Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionl...Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionless time were derived from 10 influencing factors of the problem by using dimensional analysis. Simulations of horizontal well in reservoir with bottom water were run to find the prediction correlation. A general and concise functional relationship for predicting breakthrough time was established based on simulation results and theoretical analysis. The breakthrough time of one conceptual model predicted by the correlation is very close to the result by Eclipse with less than 2% error. The practical breakthrough time of one well in Helder oilfield is 10 d, and the predicted results by the method is 11.2 d, which is more accurate than the analytical result. Case study indicates that the method could predict breakthrough time of horizontal well under different reservoir conditions accurately. For its university and ease of use, the method is suitable for quick prediction of breakthrough time.展开更多
The failure of AA3003 aluminum alloy sheet metal was predicted for non-isothermal viscous pressure bulging (VPB). Utilizing the coupled thermo-mechanical finite element method combined with ductile fracture criterion,...The failure of AA3003 aluminum alloy sheet metal was predicted for non-isothermal viscous pressure bulging (VPB). Utilizing the coupled thermo-mechanical finite element method combined with ductile fracture criterion, the calculations were carried out for non-isotherm VPB at various temperatures and the influences of the initial temperature of viscous medium on failure mode of bulge specimens were investigated. The results show that the failure modes are different for the non-isothermal VPB with different initial temperatures of viscous medium. For the non-isothermal VPB of AA3003 aluminum alloy sheet with initial temperature of 250 ℃, when the initial temperature of viscous medium ranges from 150 to 180 ℃, the formability of sheet metal can be improved to a full extent. The validity of the predictions is examined by comparing with experimental results.展开更多
Based on the finite element method(FEM)in the frequency domain and particle-in-cell approach in the time domain,a hybrid domain multipactor threshold prediction algorithm is proposed in this paper.The proposed algorit...Based on the finite element method(FEM)in the frequency domain and particle-in-cell approach in the time domain,a hybrid domain multipactor threshold prediction algorithm is proposed in this paper.The proposed algorithm has the advantages of the frequency domain and the time domain algorithms at the same time in terms of high computational accuracy and considerable computational efficiency.In addition,the compute unified device architecture(CUDA)acceleration technique also can be employed to further enhance its simulation efficiency.Numerical examples are carried out to demonstrate the effectiveness of the proposed algorithm.The results indicate that the multipactor threshold can be accurately predicted and the computational efficiency can be improved.展开更多
Accurate springback prediction of wide sheet metal air bending process is important to improve product quality and ensure the precision in dimension. The definition of elastic limit bend angle was proposed. Based on c...Accurate springback prediction of wide sheet metal air bending process is important to improve product quality and ensure the precision in dimension. The definition of elastic limit bend angle was proposed. Based on cantilever beam elastic deforming theory, the geometrical parameters of forming tools, sheet thickness and the material yielding strain were derived and validated by the finite element method (FEM). Employing the degree of elastic limit bend angle, the equation for springback prediction was constructed, the results calculated fit well with experimental data. Especially for the small bend angle, the predicted results by equation were applied to conduct the springback prediction and compensation in industries and give closer correlation to the experimental data than those calculated by engineering theory of plastic bending.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.11502114)the Fundamental Research Funds for the Central Universities(Grant No.30918011323)
文摘One of the greatest challenges in the design of a gun is to balance muzzle velocity and recoil,especially for guns on aircrafts and deployable vehicles.To resolve the conflict between gun power and recoil force,a concept of rarefaction wave gun(RAVEN)was proposed to significantly reduce the weapon recoil and the heat in barrel,while minimally reducing the muzzle velocity.The main principle of RAVEN is that the rarefaction wave will not reach the projectile base until the muzzle by delaying the venting time of an expansion nozzle at the breech.Developed on the RAVEN principle,the purpose of this paper is to provide an engineering method for predicting the performance of a low-recoil gun with front nozzle.First,a two-dimensional two-phase flow model of interior ballistic during the RAVEN firing cycle was established.Numerical simulation results were compared with the published data to validate the reliability and accuracy.Next,the effects of the vent opening times and locations were investigated to determine the influence rules on the performance of the RAVEN with front nozzle.Then according to the results above,simple nonlinear fitting formulas were provided to explain how the muzzle velocity and the recoil force change with the vent opening time and location.Finally,a better vent venting opening time corresponding to the vent location was proposed.The findings should make an important contribution to the field of engineering applications of the RAVEN.
基金Projects(61174115,51104044)supported by the National Natural Science Foundation of ChinaProject(L2010153)supported by Scientific Research Project of Liaoning Provincial Education Department,China
文摘To improve prediction accuracy of strip thickness in hot rolling, a kind of Dempster/Shafer(D_S) information reconstitution prediction method(DSIRPM) was presented. DSIRPM basically consisted of three steps to implement the prediction of strip thickness. Firstly, iba Analyzer was employed to analyze the periodicity of hot rolling and find three sensitive parameters to strip thickness, which were used to undertake polynomial curve fitting prediction based on least square respectively, and preliminary prediction results were obtained. Then, D_S evidence theory was used to reconstruct the prediction results under different parameters, in which basic probability assignment(BPA) was the key and the proposed contribution rate calculated using grey relational degree was regarded as BPA, which realizes BPA selection objectively. Finally, from this distribution, future strip thickness trend was inferred. Experimental results clearly show the improved prediction accuracy and stability compared with other prediction models, such as GM(1,1) and the weighted average prediction model.
基金Project(2012CB725403)supported by the National Basic Research Program of ChinaProjects(71210001,51338008)supported by the National Natural Science Foundation of ChinaProject supported by World Capital Cities Smooth Traffic Collaborative Innovation Center and Singapore National Research Foundation Under Its Campus for Research Excellence and Technology Enterprise(CREATE)Programme
文摘Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.
文摘The fatigue life for components can be predicted by the plot method which is easy and convenient in engineering. Based on the usual fatigue life prediction formula, a new formula for estimating the low stress and high cycle fatigue life is proposed and deduced, which has adopted more accurate SN curve relationship——WeibullSN curve formula. The solution of the new formula is given, too. In addition, an example has been calculated and proved in practice. The results of the new formula and the old one are given and compared.
基金Project(51878078)supported by the National Natural Science Foundation of ChinaProject(2018-025)supported by the Training Program for High-level Technical Personnel in Transportation Industry,ChinaProject(CTKY-PTRC-2018-003)supported by the Design Theory,Method and Demonstration of Durability Asphalt Pavement Based on Heavy-duty Traffic Conditions in Shanghai Area,China。
文摘The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.
基金Projects(50538010,50848046) supported by the National Natural Science Foundation of ChinaProject(BIL07/07) supported by the Research Council of K.U.Leuven and the National Natural Science Foundation of China
文摘The impact of vibrations due to underground trains on Beijing metro line 15 on sensitive equipment in the Institute of Microelectronics of Tsinghua University was discussed to propose a viable solution to mitigate the vibrations.Using the state-of-the-art three-dimensional coupled periodic finite element-boundary element(FE-BE) method,the dynamic track-tunnel-soil interaction model for metro line 15 was used to predict vibrations in the free field at a train speed of 80 km/h.Three types of tracks(direct fixation fasteners,floating slab track and floating ladder track) on the Beijing metro network were considered in the model. For each track,the acceleration response in the free field was obtained.The numerical results show that the influence of vibrations from underground trains on sensitive equipment depends on the track types.At frequencies above 10 Hz,the floating slab track with a natural frequency of 7 Hz can be effective to attenuate the vibrations.
文摘Fighters and other complex engineering systems have many characteristics such as difficult modeling and testing, multiple working situations, and high cost. Aim at these points, a new kind of real-time fault predictor is designed based on an improved k-nearest neighbor method, which needs neither the math model of system nc, the training data and prior knowledge. It can study and predict while system＇s running, so that it can overcome the difficulty of data acquirement. Besides, this predictor has a fast prediction speed, and the false alarm rate and missing alarm rate can be adjusted randomly. The method is simple and universalizable. The result of simulation on fighter F-16 proved the effidency.
基金Project(52025085)supported by the National Science Fund for Distinguished Young Scholars,ChinaProjects(51927814,51878078)supported by the National Natural Science Foundation of China+3 种基金Project(2018-025)supported by the Training Program for High-level Technical Personnel in Transportation Industry,ChinaProject(CTKY-PTRC 2018-003)supported by the Design Theory,Method and Demonstration of Durability Asphalt Pavement Based on Heavy-duty Traffic Conditions in Shanghai Area,ChinaProject(2020RC4048)supported by the Science and Technology Innovation Program of Hunan Province,ChinaProject(SJCX202001)supported by the Construction Project for Graduate Students of Changsha University of Science&Technology,China。
文摘This study aims to reveal the macroscopic permanent deformation(PD)behavior and the internal structural evolution of construction and demolition waste(CDW)under loading.Firstly,the initial matric suction of CDW was measured by the filter paper method.Secondly,the PD of CDW with different humidity and stress states was investigated by repeated load triaxial tests,and a comprehensive prediction model was established.Finally,the discrete element method was performed to analyze the internal structural evolution of CDW during deformation.These results showed that the VAN-GENUCHTEN model could describe the soil-water characteristic curve of CDW well.The PD increases with the increase of the deviator stress and the number of cyclic loading,but the opposite trend was observed when the initial matric suction and confining pressure increased.The proposed model in this study provides a satisfactory prediction of PD.The discrete element method could accurately simulate the macroscopic PD of CDW,and the shear force,interlock force and sliding content increase with the increase of deviator stress during the deformation.The research could provide useful reference for the deformation stability analysis of CDW under cyclic loading.
基金Project(2498) supported by State Plan Committee Automation Hi-tech Special Project Foundation
文摘A prediction method to obtain harmonic reference for active power filter is presented. It is a new use ofthe adaptive predictive filter based on FIR. The delay inherent in digital controller is successfully compensated by u-sing the proposed method, and the computing load is not very large compared with the conventional method. Moreo-ver, no additional hardware is needed. Its DSP-based realization is also presented, which is characterized by time-va-riant rate sampling, quasi synchronous sampling, and synchronous operation among the line frequency, PWM gener-ating and sampling in A/D unit. Synchronous operation releases the limitation on PWM modulation ratio and guar-antees that the electrical noises resulting from the switching operation of IGBTs do not interfere with the sampledcurrent. The simulation and experimental results verify the satisfactory performance of the proposed method.
基金Project(51675061)supported by the National Natural Science Foundation of China。
文摘This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modifications(PMs)are considered.For the prediction,a discrete gear model for generating the error tooth profile based on the ISO accuracy grade is presented.Then,the gear model and a tooth deflection model for calculating the tooth compliance on gear meshing are coupled with the transmission error model to make the prediction by checking the interference status between gear and pinion.The prediction method is validated by comparison with the experimental results from the literature,and a set of cases are simulated to study the effects of MEs,AEs,TDs and PMs on the static transmission error.In addition,the time-varying backlash caused by both MEs and AEs,and the contact ratio under load conditions are also investigated.The results show that the novel method can effectively predict the range of the static transmission error under different accuracy grades.The prediction results can provide references for the selection of gear design parameters and the optimization of transmission performance in the design stage of gear systems.
基金Project(2011ZX05009-004)supported by the National Science and Technology Major Projects of China
文摘Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionless time were derived from 10 influencing factors of the problem by using dimensional analysis. Simulations of horizontal well in reservoir with bottom water were run to find the prediction correlation. A general and concise functional relationship for predicting breakthrough time was established based on simulation results and theoretical analysis. The breakthrough time of one conceptual model predicted by the correlation is very close to the result by Eclipse with less than 2% error. The practical breakthrough time of one well in Helder oilfield is 10 d, and the predicted results by the method is 11.2 d, which is more accurate than the analytical result. Case study indicates that the method could predict breakthrough time of horizontal well under different reservoir conditions accurately. For its university and ease of use, the method is suitable for quick prediction of breakthrough time.
基金Projects(50805034, 50275035) supported by the National Natural Science Foundation of China
文摘The failure of AA3003 aluminum alloy sheet metal was predicted for non-isothermal viscous pressure bulging (VPB). Utilizing the coupled thermo-mechanical finite element method combined with ductile fracture criterion, the calculations were carried out for non-isotherm VPB at various temperatures and the influences of the initial temperature of viscous medium on failure mode of bulge specimens were investigated. The results show that the failure modes are different for the non-isothermal VPB with different initial temperatures of viscous medium. For the non-isothermal VPB of AA3003 aluminum alloy sheet with initial temperature of 250 ℃, when the initial temperature of viscous medium ranges from 150 to 180 ℃, the formability of sheet metal can be improved to a full extent. The validity of the predictions is examined by comparing with experimental results.
基金This work was supported by the National Natural Science Foundation of China(61571022,61971022)the National Key laboratory Foundation(HTKJ2019KI504013,61424020305).
文摘Based on the finite element method(FEM)in the frequency domain and particle-in-cell approach in the time domain,a hybrid domain multipactor threshold prediction algorithm is proposed in this paper.The proposed algorithm has the advantages of the frequency domain and the time domain algorithms at the same time in terms of high computational accuracy and considerable computational efficiency.In addition,the compute unified device architecture(CUDA)acceleration technique also can be employed to further enhance its simulation efficiency.Numerical examples are carried out to demonstrate the effectiveness of the proposed algorithm.The results indicate that the multipactor threshold can be accurately predicted and the computational efficiency can be improved.
基金Project(20050216013) supported by the Research Fund for the Doctoral Program of Higher Education
文摘Accurate springback prediction of wide sheet metal air bending process is important to improve product quality and ensure the precision in dimension. The definition of elastic limit bend angle was proposed. Based on cantilever beam elastic deforming theory, the geometrical parameters of forming tools, sheet thickness and the material yielding strain were derived and validated by the finite element method (FEM). Employing the degree of elastic limit bend angle, the equation for springback prediction was constructed, the results calculated fit well with experimental data. Especially for the small bend angle, the predicted results by equation were applied to conduct the springback prediction and compensation in industries and give closer correlation to the experimental data than those calculated by engineering theory of plastic bending.
