VARIABLE CROSS-SECTION RECTANGULAR BEAM AND SENSITIVITY ANALYSIS FOR LIGHTWEIGHT DESIGN OF BUS FRAME

Wenjie Zuo,Jiaxin Fang,Minghui Zhong,Guikai Guo 한국자동차공학회 2018 International journal of automotive technology Vol.19 No.6

Timoshenko beam element of variable cross-section rectangular tube is developed and applied in the lightweight design of bus frame in this paper. Firstly, the finite element formulations of variable cross-section beam (VCB) are derived under the loadsteps of axial deformation, torsional deformation and bending deformation. Secondly, bending deformation experiment and its detailed shell finite element model (FEM) simulation of variable cross-section rectangular tube were conducted; and the proposed VCB, detailed shell FEM and experimental results can be highly consistent. Thirdly, VCBs are used to substitute for parts of the uniform ones in a bus frame. An innovatively lightweight bus frame is obtained and all the performance responses are improved simultaneously. Finally, rollover analysis further shows the advantage of variable cross-section bus frame in crashworthiness design.

DHEM: a deep heat energy method for steady-state heat conduction problems

Huanhuan Gao,Wenjie Zuo,Zengming Feng,Jinxing Yang,Tingting Li,Ping Hu 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.11

Based on the deep energy method recently brought forward to handle linearelastic or hyper-elastic finite deformation problems in solid mechanics, in this paper, we propose a deep heat energy method (DHEM) which is specially tailored to deal with structural steady-state heat conduction problems with the help of deep learning techniques. In our work, the deep neural networks are utilized to construct the admissible temperature fields; secondly, the potential energy functional in the heat conduction process which works as the loss function of the deep neural networks is calculated by numerical integration techniques; finally, the parameters of the network including weights and bias, are optimized by the quasi-Newton method to yield the minimal of the potential energy functional which indicates the heat conduction has entered a steady state. Numerical examples with a diversity of materials, including the isotropic and homogeneous material, the orthotropic material, the non-homogeneous materials and temperature dependent materials, are carried out to illustrate the validity and capacity of DHEM in both linear uncoupled and thermal-material coupling heat conduction problems.

Rollover crashworthiness analysis and optimization of bus frame for conceptual design

Jiantao Bai,Guangwei Meng,Wenjie Zuo 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.7

At the conceptual design stage, utilizing the detailed model to determine the rollover crashworthiness of bus structure would need long design cycle. Currently, rectangular thin-walled beams (RTWBs) are extensively used to create the real bus because of the excellent manufacturability. Remarkably, dual rectangular thin-walled beams (DRTWBs) can generate higher bending resistance. Therefore, this paper presents a rollover crashworthiness analysis and optimization method of bus frame using the RTWBs and DRTWBs. The bus frame with tire, suspension and platform structures is created in the CarFrame software. Analysis numerical example verifies that the frame model, which reduces the modeling and computational costs, is in excellent agreements with the detailed model, and optimization numerical example verifies that the frame model can obtain high rollover crashworthiness and lightweight bus structure. Therefore, the frame model can effectively replace the detailed model for the rollover crashworthiness analysis and optimization.

ANALYTICAL SENSITIVITY ANALYSIS METHOD OF CROSSSECTIONAL SHAPE FOR THIN-WALLED AUTOMOBILE FRAME CONSIDERING GLOBAL PERFORMANCES

Yanhua Ma,Xinchen Wang,Wenjie Zuo 한국자동차공학회 2020 International journal of automotive technology Vol.21 No.5

At the conceptual design stage, thin-walled beams (TWBs) with the complex cross-sectional shapes are extensively used to compose the automobile frame. Thus, the performances of automobile frame are determined by crosssectional shapes of TWBs. Currently, the modifications of complex cross-sectional shapes depend on the experience of engineers, which often causes the design risk. Meanwhile, to our knowledge, the previous studies mainly focused on the regular cross sections and paid little attention for the complex cross-sectional shape for the automobile frame. Therefore, this paper proposes an analytical sensitivity analysis method to modify the complex cross-sectional shapes. This method regards the coordinates of points and the thicknesses of sheets as design variables to describe the cross-sectional shapes. The bending stiffness, torsional stiffness and frequency are used to evaluate the performances of automobile frame. Finally, an example of the RAV4 automobile frame verifies that the analytical sensitivity analysis method can effectively guide the modification of the cross-sectional shape and achieve the lightweight automobile frame.

Lightweight Design of CFRP-Laminated Structures by Combining Microscopical Homogenization and Macroscopical Optimization

Cheng Fei,Zheng Chenggong,Liu Yunfei,Zuo Wenjie,Wang Xinzhe,Guo Guikai 한국자동차공학회 2021 International journal of automotive technology Vol.22 No.5

We developed a new method for the design of carbon-fiber reinforced plastic (CFRP)-laminated structures, which combined the asymptotic homogenization method and ply optimization. The equivalent mechanical properties of a single-layer CFRP were calculated using the asymptotic homogenization method. The ply optimization of the laminated structures was divided into three parts: an initial free-size optimization to identify the optimal ply shapes and locations of patches per ply orientation; an optimization of the final size to identify the optimal thicknesses of each ply; and an optimization of the final ply stacking sequence to obtain the optimal stacking sequence. Using the example of the floor of a body-in-white model, our method provided a reasonable optimization result with reduced mass by 60 %. The proposed method provides an efficient way to investigate laminated structures and has potential for lightweight design and analysis of automobile components.

SHAPE OPTIMIZATION OF THIN-WALLED CROSS SECTION FOR AUTOMOBILE BODY CONSIDERING STAMPING COST, MANUFACTURABILITY AND STRUCTURAL STIFFNESS

Yanhua Ma,Rui Chen,Jiantao Bai,Wenjie Zuo 한국자동차공학회 2020 International journal of automotive technology Vol.21 No.2

At the conceptual design stage, the cross-sectional shapes of thin-walled beams (TWBs) need to be optimized to improve the performance of automobile structure. Therefore, this paper innovatively proposes a cross-sectional shape optimization method to acquire a low cost, high stiffness, manufacturable and lightweight TWB. Meanwhile, the stamping cost of thin-walled beams is analytically derived. The cross-sectional area is taken as the objective function to establish an optimization formulation with multiple constraints such as cross-sectional stiffness, manufacturability and cost of TWBs. The single-objective genetic algorithm based on non-dominant principle is introduced to solve the problem. The effectiveness of the proposed method is verified by an example of double cell cross-sectional shape.

State trend prediction of hydropower units under different working conditions based on parameter adaptive support vector regression machine modeling

Guo Zhao,Shulin Li,Wanqing Zuo,Haoran Song,Heping Zhu,Wenjie Hu 전력전자학회 2023 JOURNAL OF POWER ELECTRONICS Vol.23 No.9

To address the problem where the different operating conditions of hydropower units have a large influence on the parameters of the trend prediction model of the operating condition indicators, a support vector regression machine prediction model based on parameter adaptation is proposed in this paper. First, the Aquila optimizer (AO) is improved, and a sine chaotic map is introduced to influence the population initialization process. An improved adaptive weight factor is used to balance the local search and global search capabilities. Second, according to the power and the head, the operating conditions of the unit are refined into several typical sets of operating conditions. On this basis, an SVR model is established using the improved AO search algorithm proposed in this paper, and the prediction parameters under each of the operating condition are optimized to establish the data of the operating conditions and optimal parameters. Then a neural network is used to fit the working condition and the optimal prediction parameters. In addition, the nonlinear function mapping of the complex relationship between the two is constructed. Finally, the constructed mapping relationship is added to the traditional SVR, and an adaptive SVR prediction model suitable for changes in the working conditions of hydropower units is realized. Simulation results show that when compared to the traditional SVR prediction model, the adaptive SVR prediction model designed in this paper can automatically adjust the prediction parameters according to changes in the working conditions and achieve the goal of maintaining optimal prediction performance under different working conditions. In addition, it has the ability to accurately predict the development trend of the unit operating state index within a certain time scale.