Rolling bearing is widely used in mechanical support, its general components are the inner ring, outer ring, the ball, retainer etc.. Now many companies in developed countries and university in the rolling bearing as ...Rolling bearing is widely used in mechanical support, its general components are the inner ring, outer ring, the ball, retainer etc.. Now many companies in developed countries and university in the rolling bearing as the research object, and has made great progress in design theory, the experiment method and production technology etc. We will use the finite element ANSYS to establish the model of deep groove ball bearing. Through the contact analysis, we can get the contact stress between the rings and balls, strain, contact state, penetration, sliding distance and the friction stress distribution. These values are compared to the theoretical values with Hertz theory, and they have better consistency, provide the good theoretical basis for the optimization design of rolling bearings.展开更多
To date,with the increasing attention of countries to urban drainage system,more and more regions around the world have begun to build water conveyance tunnels,sewage pressure deep tunnels and so on.However,the suffic...To date,with the increasing attention of countries to urban drainage system,more and more regions around the world have begun to build water conveyance tunnels,sewage pressure deep tunnels and so on.However,the sufficient bearing capacity and corrosion resistance of the structure,which can ensure the actual service life and safety of the tunnel,remain to be further improved.Glass Fiber Reinforced Plastics(GFRP)pipe,with light weight,high strength and corrosion resistance,has the potential to be applied to the deep tunnel structure.This paper proposed a new composite structure of deep tunnel lined with GFRP pipe,which consisted of three layers of concrete segment,cement paste and GFRP pipe.A new pipe-soil spring element model was proposed for the pipesoil interaction with gaps.Based on the C3D8R solid model and the Combin39 spring model,the finite element numerical analysis of the internal pressure status and external pressure stability of the structure was carried out.Combined with the checking calculation of the theoretical formula,the reliability of the two finite element models was confirmed.A set of numerical analysis methods for the design and optimization of the three-layer structure was established.The results showed that from the internal GFRP pipe to the outer concrete pipe,the pressure decreased from 0.5 to 0.32 MPa,due to the internal pressure was mainly undertaken by the inner GFRP pipe.The allowable buckling pressure of GFRP pipe under the cover of 5 GPa high modulus cement paste was 2.66 MPa.The application of GFRP pipe not only improves the overall performance of the deep tunnel structure but also improves the construction quality and safety.The three-layer structure built in this work is safe and economical.展开更多
The effect of temperature distribution on warm forming performance was investigated for 5083-O (Al-Mg) sheet metal blanks. Combined isothermal/non-isothermal FEA with design of experiments tools were used to predict a...The effect of temperature distribution on warm forming performance was investigated for 5083-O (Al-Mg) sheet metal blanks. Combined isothermal/non-isothermal FEA with design of experiments tools were used to predict appropriate warm forming temperature conditions for deep drawing and two-dimensional stamping cases. In the investigated temperature range of 25?250 ℃, the formability of Al-5083 alloy is found to be greatly dependent on the temperature distribution of the die and punch. To achieve increased degrees of forming, different temperature levels should be assigned to the corner and body of the die and punch. And the optimal temperature distributions for warm deep drawing and warm two-dimensional stamping are not identical.展开更多
A concept design, named integrated suction foundation, is proposed for a tension leg platform（TLP） in deep ocean. The most important improvement in comparing with the traditional one is that a pressure-resistant sto...A concept design, named integrated suction foundation, is proposed for a tension leg platform（TLP） in deep ocean. The most important improvement in comparing with the traditional one is that a pressure-resistant storage module is designed. It utilizes the high hydrostatic pressure in deep ocean to drive water into the module to generate negative pressure for bucket suction. This work aims to further approve the feasibility of the concept design in the aspect of penetration installation and the uplift force in-place. Seepage is generated during suction penetration, and can have both positive and negative effects on penetration process. To study the effect of seepage on the penetration process of the integrated suction foundation, finite element analysis（FEA） is carried out in this work. In particular, an improved methodology to calculate the penetration resistance is proposed for the integrated suction foundation with respect to the reduction factor of penetration resistance. The maximum allowable negative pressure during suction penetration is calculated with the critical hydraulic gradient method through FEA. The simulation results of the penetration process show that the integrated suction foundation can be installed safely. Moreover, the uplift resistance of the integrated suction foundation is calculated and the feasibility of the integrated suction foundation working on-site is verified. In all, the analysis in this work further approves the feasibility of the integrated suction foundation for TLPs in deep ocean applications.展开更多
针对基于深度学习轴承故障诊断模型由于工况因素导致诊断效果不佳的问题,提出了一种用聚类与插值(Clustering and interpolation,CAI)改进深度学习算法实现变工况轴承故障诊断的方法。首先,采用有限元法仿真多工况、多故障类型的轴承振...针对基于深度学习轴承故障诊断模型由于工况因素导致诊断效果不佳的问题,提出了一种用聚类与插值(Clustering and interpolation,CAI)改进深度学习算法实现变工况轴承故障诊断的方法。首先,采用有限元法仿真多工况、多故障类型的轴承振动信号数据,获取足够样本;然后,完成宽卷积核深度卷积神经网络(Deepconvolutionalneuralnetworks with widekernel,WDCNN)模型构建,并利用任一工况下的数据完成模型训练;最后,利用CAI算法统一其余工况数据的转速信息,调用WDCNN模型完成对其余工况样本的故障诊断。结果显示,WDCNN模型对训练数据所属工况故障诊断准确率达99.9%,对经过CAI算法处理其他工况数据故障诊断识别率分别为98.7%、99.2%,是一种简单、准确有效、泛化能力强的故障诊断方法。展开更多
In recent years,there has been significant research on the application of deep learning(DL)in topology optimization(TO)to accelerate structural design.However,these methods have primarily focused on solving binary TO ...In recent years,there has been significant research on the application of deep learning(DL)in topology optimization(TO)to accelerate structural design.However,these methods have primarily focused on solving binary TO problems,and effective solutions for multi-material topology optimization(MMTO)which requires a lot of computing resources are still lacking.Therefore,this paper proposes the framework of multiphase topology optimization using deep learning to accelerate MMTO design.The framework employs convolutional neural network(CNN)to construct a surrogate model for solving MMTO,and the obtained surrogate model can rapidly generate multi-material structure topologies in negligible time without any iterations.The performance evaluation results show that the proposed method not only outputs multi-material topologies with clear material boundary but also reduces the calculation cost with high prediction accuracy.Additionally,in order to find a more reasonable modeling method for MMTO,this paper studies the characteristics of surrogate modeling as regression task and classification task.Through the training of 297 models,our findings show that the regression task yields slightly better results than the classification task in most cases.Furthermore,The results indicate that the prediction accuracy is primarily influenced by factors such as the TO problem,material category,and data scale.Conversely,factors such as the domain size and the material property have minimal impact on the accuracy.展开更多
基金Supported by Fundamental Research Funds for Central Universities(No.FRF-TP-12-067A)
文摘Rolling bearing is widely used in mechanical support, its general components are the inner ring, outer ring, the ball, retainer etc.. Now many companies in developed countries and university in the rolling bearing as the research object, and has made great progress in design theory, the experiment method and production technology etc. We will use the finite element ANSYS to establish the model of deep groove ball bearing. Through the contact analysis, we can get the contact stress between the rings and balls, strain, contact state, penetration, sliding distance and the friction stress distribution. These values are compared to the theoretical values with Hertz theory, and they have better consistency, provide the good theoretical basis for the optimization design of rolling bearings.
基金This project was supported by the Fundamental Research Funds for the Central Universities(WUT:2018IB001)the Fundamental Research Funds for the Central Universities(WUT:2019III130CG).
文摘To date,with the increasing attention of countries to urban drainage system,more and more regions around the world have begun to build water conveyance tunnels,sewage pressure deep tunnels and so on.However,the sufficient bearing capacity and corrosion resistance of the structure,which can ensure the actual service life and safety of the tunnel,remain to be further improved.Glass Fiber Reinforced Plastics(GFRP)pipe,with light weight,high strength and corrosion resistance,has the potential to be applied to the deep tunnel structure.This paper proposed a new composite structure of deep tunnel lined with GFRP pipe,which consisted of three layers of concrete segment,cement paste and GFRP pipe.A new pipe-soil spring element model was proposed for the pipesoil interaction with gaps.Based on the C3D8R solid model and the Combin39 spring model,the finite element numerical analysis of the internal pressure status and external pressure stability of the structure was carried out.Combined with the checking calculation of the theoretical formula,the reliability of the two finite element models was confirmed.A set of numerical analysis methods for the design and optimization of the three-layer structure was established.The results showed that from the internal GFRP pipe to the outer concrete pipe,the pressure decreased from 0.5 to 0.32 MPa,due to the internal pressure was mainly undertaken by the inner GFRP pipe.The allowable buckling pressure of GFRP pipe under the cover of 5 GPa high modulus cement paste was 2.66 MPa.The application of GFRP pipe not only improves the overall performance of the deep tunnel structure but also improves the construction quality and safety.The three-layer structure built in this work is safe and economical.
基金Project(50225520) supported by the National Found for Distinguished Young Scholars
文摘The effect of temperature distribution on warm forming performance was investigated for 5083-O (Al-Mg) sheet metal blanks. Combined isothermal/non-isothermal FEA with design of experiments tools were used to predict appropriate warm forming temperature conditions for deep drawing and two-dimensional stamping cases. In the investigated temperature range of 25?250 ℃, the formability of Al-5083 alloy is found to be greatly dependent on the temperature distribution of the die and punch. To achieve increased degrees of forming, different temperature levels should be assigned to the corner and body of the die and punch. And the optimal temperature distributions for warm deep drawing and warm two-dimensional stamping are not identical.
基金financially supported by the National Basic Key Research Program of China(973 Program,Grant No.2014CB46804)the Tianjin Research Program of Application Foundation and Advanced Technology(Grant No.15JCYBJC21700)
文摘A concept design, named integrated suction foundation, is proposed for a tension leg platform（TLP） in deep ocean. The most important improvement in comparing with the traditional one is that a pressure-resistant storage module is designed. It utilizes the high hydrostatic pressure in deep ocean to drive water into the module to generate negative pressure for bucket suction. This work aims to further approve the feasibility of the concept design in the aspect of penetration installation and the uplift force in-place. Seepage is generated during suction penetration, and can have both positive and negative effects on penetration process. To study the effect of seepage on the penetration process of the integrated suction foundation, finite element analysis（FEA） is carried out in this work. In particular, an improved methodology to calculate the penetration resistance is proposed for the integrated suction foundation with respect to the reduction factor of penetration resistance. The maximum allowable negative pressure during suction penetration is calculated with the critical hydraulic gradient method through FEA. The simulation results of the penetration process show that the integrated suction foundation can be installed safely. Moreover, the uplift resistance of the integrated suction foundation is calculated and the feasibility of the integrated suction foundation working on-site is verified. In all, the analysis in this work further approves the feasibility of the integrated suction foundation for TLPs in deep ocean applications.
文摘针对基于深度学习轴承故障诊断模型由于工况因素导致诊断效果不佳的问题,提出了一种用聚类与插值(Clustering and interpolation,CAI)改进深度学习算法实现变工况轴承故障诊断的方法。首先,采用有限元法仿真多工况、多故障类型的轴承振动信号数据,获取足够样本;然后,完成宽卷积核深度卷积神经网络(Deepconvolutionalneuralnetworks with widekernel,WDCNN)模型构建,并利用任一工况下的数据完成模型训练;最后,利用CAI算法统一其余工况数据的转速信息,调用WDCNN模型完成对其余工况样本的故障诊断。结果显示,WDCNN模型对训练数据所属工况故障诊断准确率达99.9%,对经过CAI算法处理其他工况数据故障诊断识别率分别为98.7%、99.2%,是一种简单、准确有效、泛化能力强的故障诊断方法。
基金supported in part by National Natural Science Foundation of China under Grant Nos.51675525,52005505,and 62001502Post-Graduate Scientific Research Innovation Project of Hunan Province under Grant No.XJCX2023185.
文摘In recent years,there has been significant research on the application of deep learning(DL)in topology optimization(TO)to accelerate structural design.However,these methods have primarily focused on solving binary TO problems,and effective solutions for multi-material topology optimization(MMTO)which requires a lot of computing resources are still lacking.Therefore,this paper proposes the framework of multiphase topology optimization using deep learning to accelerate MMTO design.The framework employs convolutional neural network(CNN)to construct a surrogate model for solving MMTO,and the obtained surrogate model can rapidly generate multi-material structure topologies in negligible time without any iterations.The performance evaluation results show that the proposed method not only outputs multi-material topologies with clear material boundary but also reduces the calculation cost with high prediction accuracy.Additionally,in order to find a more reasonable modeling method for MMTO,this paper studies the characteristics of surrogate modeling as regression task and classification task.Through the training of 297 models,our findings show that the regression task yields slightly better results than the classification task in most cases.Furthermore,The results indicate that the prediction accuracy is primarily influenced by factors such as the TO problem,material category,and data scale.Conversely,factors such as the domain size and the material property have minimal impact on the accuracy.
