FE simulation of the curing behavior of the epoxy adhesive Hysol EA-9321

Cold-curing adhesives, characterized by an unsteady curing degree, present various advantages for assembling large scale structures set up under outdoor conditions. Thus various applications can be found in aerospace and automotive industries where structures are affected by thermal and mechanical loads. Hence, the curing state of the adhesive must be known to evaluate the lifetime of such bonded structures. The evolution of the polymerization of the adhesive Hysol EA-9321 during the curing process was examined in this paper. To that end, the curing degree of the adhesive was experimentally and analytically investigated for different curing cycles with a view to a potential application in the aerospace domain, where structures are assembled at low temperatures. Existing dynamic and isothermal curing models were applied to simulate the curing behavior of the adhesive. Then, an FEM model was developed to simulate the process of adhesive curing by taking into account a thermo-kinetic coupling.     

A high performance crashworthiness simulation system based on GPU

Crashworthiness simulation system is one of the key computer-aided engineering (CAE) tools for the automobile industry and implies two potential conflicting requirements: accuracy and efficiency. A parallel crashworthiness simulation system based on graphics processing unit (GPU) architecture and the explicit finite element (FE) method is developed in this work. Implementation details with compute unified device architecture (CUDA) are considered. The entire parallel simulation system involves a parallel hierarchy-territory contact-searching algorithm (HITA) and a parallel penalty contact force calculation algorithm. Three basic GPU-based parallel strategies are suggested to meet the natural parallelism of the explicit FE algorithm. Two free GPU-based numerical calculation libraries, cuBLAS and Thrust, are introduced to decrease the difficulty of programming. Furthermore, a mixed array and a thread map to element strategy are proposed to improve the performance of the test pairs searching. The outer loop of the nested loop through the mixed array is unrolled to realize parallel searching. An efficient storage strategy based on data sorting is presented to realize data transfer between different hierarchies with coalesced access during the contact pairs searching. A thread map to element pattern is implemented to calculate the penetrations and the penetration forces; a double float atomic operation is used to scatter contact forces. The simulation results of the three different models based on the Intel Core i7-930 and the NVIDIA GeForce GTX 580 demonstrate the precision and efficiency of this developed parallel crashworthiness simulation system.     

基于活塞形状改变的空气弹簧特性仿真研究

研究汽车装用空气弹簧刚度优化问题,活塞形状对膜式空气弹簧刚度特性的影响较大。为了提高整车的平顺性能,建立空气弹簧简化模型,得到圆台和倒圆台活塞形状下空气弹簧的有效承载半径影响因素。利用ABAQUS软件建立安装圆柱、圆台和倒圆台活塞的空气弹簧有限元模型进行,研究了不同圆台角下圆台活塞空气弹簧的刚度特性。仿真结果表明,在一定范围内,圆台角度越大,空气弹簧刚度也越大,证明与理论分析吻合,并对空气弹簧的设计和匹配具有一定的指导意义。     

基于多工况的车门结构多目标优化设计方法研究

车门结构的单一工况优化设计常难以满足车门设计要求。本文基于车门垂直刚度和一阶模态两工况,提出一种车门结构多工况多目标优化设计方法。以车门垂直刚度、一阶频率和车门质量为优化目标,通过均匀拉丁方试验设计和响应面方法得出车门垂直刚度和一阶频率的近似数学模型,并在此基础构建车门结构多目标优化模型。最后采用多目标遗传算法对其进行求解,最终优化结果在车门质量减少的情况下,垂直刚度和一阶频率均达到设计要求,达到预期优化效果。     

Ensemble deep transfer learning driven by multisensor signals for the fault diagnosis of bevel-gear cross-operation conditions

The existing intelligent fault diagnosis techniques of bevel gear focus on single-sensor signal analysis under the steady operation condition. In this study, a new method is proposed based on ensemble deep transfer learning and multisensor signals to enhance the fault diagnosis adaptability and reliability of bevel gear under various operation conditions. First, a novel stacked autoencoder(NSAE) is constructed using a denoising autoencoder, batch normalization, and the Swish activation function. Second, a series of source-domain NSAEs with multisensor vibration signals is pretrained. Third, the good model parameters provided by the source-domain NSAEs are transferred to initialize the corresponding target-domain NSAEs. Finally, a modified voting fusion strategy is designed to obtain a comprehensive result. The multisensor signals collected under the different operation conditions of bevel gear are used to verify the proposed method. The comparison results show that the proposed method can diagnose different faults in an accurate and stable manner using only one target-domain sample, thereby outperforming the existing methods.     

Design and experimental study of a compact quasi-zero-stiffness isolator using wave springs

Science China Technological Sciences - The quasi-zero-stiffness (QZS) vibration isolation has been proven to be an effective way to isolate low-frequency vibration. However, most of the existing...     

A reanalysis method for local modification and the application in large-scale problems

A novel reanalysis method, named independent coefficients (IC) method is suggested in this study. This method is proposed to reanalyze structures with local modification which leads to a low-rank change in the stiffness matrix. IC method requires only initial solution as input, and can determine the independent coefficients for each degree of freedoms (DOFs) influenced by structural modifications. Since any extra operations such as decomposition of the initial stiffness matrix is not involved in computation procedure, the IC is a “cheap” algorithm and can be an alternative choice for reanalysis. In order to verify the performance of IC method, several large scale numerical examples are tested. The results demonstrate that the IC method has high accuracy as well as efficiency when the modification is local. The cases involving beyond 1,500,000 DOFs and 3,000,000 DOFs show that IC method has low demands on computer storage, and large scale problems can be easily reanalyzed by this method.     

Study on hydrogen atom adsorption and diffusion properties on Mg (0001) surface

Hydrogen atom adsorption and diffusion properties on clean and vacancy defective Mg (0001) surface have been investigated systematically by using a first-principles calculations method based on the density functional theory. The calculation results of adsorption energy and diffusion energy barrier show that hydrogen atom is apt to be adsorbed at fcc and hcp sites on clean Mg (0001) surface, and fcc adsorption site is found to be more preferred. The highest diffusion energy barrier is estimated as 0.6784 eV for the diffusion of hydrogen from clean Mg (0001) surface into its bulk. Surface effects, which affect hydrogen diffusion obviously, results in a slow diffusion velocity of hydrogen from surface to subsurface, while a fast one from subsurface to bulk, indicating the range of surface effects is only restricted within two topmost layers of Mg (0001) surface. Comparatively, Mg atom vacancy on Mg (0001) surface not only enhances the chemisorption interaction between H and Mg surface, but also benefits H atom diffusion in Mg bulk with relatively more diffusion paths compared with that of clean surface. Besides, hydrogen atom is found to occupy mostly the tetrahedral interstice when it diffuses into the Mg bulk. Further analysis of the density of states (DOS) shows that the system for hydrogen atom to be adsorbed at fcc site has a lower DOS value (N (E _F)) at Fermi level and more bonding electrons at the energy range blow the Fermi level of H/Mg (0001) system as compared with that at hcp site. On the other hand, the enhanced chemisorption interaction between hydrogen and defective surface should be attributed to the fact that the electronic structures of Mg (0001) surface are modified by an Mg vacancy, and the bonding electrons of the topmost layer Mg atoms are transferred from low energy range to Fermi level, which is in favor of improving the surface activity of Mg (0001) surface. Supported by the PhD Programs Foundation of Ministry of Education of China (Grant No. 200805321032), the Science and Technology Program Project of Hunan Province (Grant No. 2008GK3083) and the Program for Changjiang Scholars and the Innovative Research Team in university (Grant No. 531105050037)