The Implement of Optimization Design of a Car Body Based on VCD-ICAE System

2012 ◽  
Vol 479-481 ◽  
pp. 2577-2581
Author(s):  
Wen Bin Hou ◽  
Zhen Jun Bi ◽  
Hong Zhe Zhang ◽  
Ping Hu
Keyword(s):  
The Body ◽  
Vehicle Body ◽  
Whole Body ◽  
Design Parameters ◽  
Concept Design ◽  
Multi Objective Optimization ◽  
Detailed Model ◽  
Car Body ◽  
Multi Objective ◽  
Body Concept

In order to get the optimistic structure property and design parameters of a car body, the system of vehicle body concept design (VCD-ICAE) was developed by us to make the body design in the conceptual phase in the paper. It can build parametric geometry modeling and FEM model of body-in-white (BIW) automatically, and the structural stiffness was calculated. Based on the former model, a multi-objective optimization of the total body was designed to afford the reasonable parameters for detailed model of BIW, which realized lightweight of the whole body and high stiffness. In the paper, the total theory and flowchart of vehicle body concept design were afforded. An example with real body’s data was shown to prove the validity of the multi-objective optimization module in VCD-ICAE system. Finally, the optimal design scheme of the body was provided.

Multi-objective optimization of squirrel cage fan for range hood based on Kriging model

2021 ◽  
pp. 095440622199586
Author(s):  
Qianhao Xiao ◽  
Jun Wang ◽  
Boyan Jiang ◽  
Weigang Yang ◽  
Xiaopei Yang
Keyword(s):  
Flow Rate ◽  
Optimization Design ◽  
Volume Flow Rate ◽  
Kriging Model ◽  
Volume Flow ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Squirrel Cage

In view of the multi-objective optimization design of the squirrel cage fan for the range hood, a blade parameterization method based on the quadratic non-uniform B-spline (NUBS) determined by four control points was proposed to control the outlet angle, chord length and maximum camber of the blade. Morris-Mitchell criteria were used to obtain the optimal Latin hypercube sample based on the evolutionary operation, and different subsets of sample numbers were created to study the influence of sample numbers on the multi-objective optimization results. The Kriging model, which can accurately reflect the response relationship between design variables and optimization objectives, was established. The second-generation Non-dominated Sorting Genetic algorithm (NSGA-II) was used to optimize the volume flow rate at the best efficiency point (BEP) and the maximum volume flow rate point (MVP). The results show that the design parameters corresponding to the optimization results under different sample numbers are not the same, and the fluctuation range of the optimal design parameters is related to the influence of the design parameters on the optimization objectives. Compared with the prototype, the optimized impeller increases the radial velocity of the impeller outlet, reduces the flow loss in the volute, and increases the diffusion capacity, which improves the volume flow rate, and efficiency of the range hood system under multiple working conditions.

Multi-Objective Optimization of Human Gait With a Discomfort Function

2016 ◽  
Author(s):  
Hyun-Jung Kwon ◽  
Hyun-Joon Chung ◽  
Yujiang Xiang
Keyword(s):  
Joint Torque ◽  
Upper Body ◽  
Whole Body ◽  
Human Gait ◽  
Multi Objective Optimization ◽  
Joint Angles ◽  
Backward Walking ◽  
Multi Objective ◽  
Body Model ◽  
Neutral Angle

The objective of this study was to develop a discomfort function for including a high DOF upper body model during walking. A multi-objective optimization (MOO) method was formulated by minimizing dynamic effort and the discomfort function simultaneously. The discomfort function is defined as the sum of the squares of deviation of joint angles from their neutral angle positions. The dynamic effort is the sum of the joint torque squared. To investigate the efficacy of the proposed MOO method, backward walking simulation was conducted. By minimizing both dynamic effort and the discomfort function, a 3D whole body model with a high DOF upper body for walking was demonstrated successfully.

Multi-objective optimization of hydro-viscous flexible drive for dynamic characteristics using genetic algorithm

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jianzhong Cui ◽  
Hu Li ◽  
Dong Zhang ◽  
Yawen Xu ◽  
Fangwei Xie
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Characteristics ◽  
Transmission Efficiency ◽  
Outer Radius ◽  
Transmission Model ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Dynamic Transmission Model

Purpose The purpose of this study is to investigate the flexible dynamic characteristics about hydro-viscous drive providing meaningful insights into the credible speed-regulating behavior during the soft-start. Design/methodology/approach A comprehensive dynamic transmission model is proposed to investigate the effects of key parameters on the dynamic characteristics. To achieve a trade-off between the transmission efficiency and time proportion of hydrodynamic and mixed lubrication, a multi-objective optimization of friction pair system by genetic algorithm is presented to obtain the optimal combination of design parameters. Findings Decreasing the engagement pressure or the ratio of inner and outer radius, increasing the lubricating oil viscosity or the outer radius will result in the increase of time proportion of hydrodynamic and mixed lubrication, as well as the transmission efficiency and its maximum value. After optimization, main dynamic parameters including the oil film thickness, angular velocity of the driven disk, viscous torque and total torque show remarkable flexible transmission characteristics. Originality/value Both the dynamic transmission model and multi-objective optimization model are established to analyze the effects of main design parameters on the dynamic characteristics of hydro-viscous flexible drive.

A Thompson Sampling Efficient Multi-Objective Optimization Algorithm (TSEMO) for Lithium-Ion Battery Liquid-Cooled Thermal Management System: Study of Hydrodynamic, Thermodynamic, and Structural Performance

2020 ◽  
Vol 18 (2) ◽  
Author(s):  
A. Garg ◽  
Cheng Liu ◽  
A. K. Jishnu ◽  
Liang Gao ◽  
My Loan Le Phung ◽  
...  
Keyword(s):  
Thermal Management ◽  
Optimization Algorithm ◽  
Cooling System ◽  
Hydrodynamic Performance ◽  
Design Parameters ◽  
Inlet Temperature ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Thompson Sampling ◽  
Conflicting Objectives

Abstract The efficient design of battery thermal management systems (BTMSs) plays an important role in enhancing the performance, life, and safety of electric vehicles (EVs). This paper aims at designing and optimizing cold plate-based liquid cooling BTMS. Pitch sizes of channels, inlet velocity, and inlet temperature of the outermost channel are considered as design parameters. Evaluating the influence and optimization of design parameters by repeated computational fluid dynamics calculations is time consuming. To tackle this, the effect of design parameters is studied by using surrogate modeling. Optimized design variables should ensure a perfect balance between certain conflicting goals, namely, cooling efficiency, BTMS power consumption (parasitic power), and size of the battery. Therefore, the optimization problem is decoupled into hydrodynamic performance, thermodynamic performance, and mechanical structure performance. The optimal design involving multiple conflicting objectives in BTMS is solved by adopting the Thompson sampling efficient multi-objective optimization algorithm. The results obtained are as follows. The optimized average battery temperature after optimization decreased from 319.86 K to 319.2759 K by 0.18%. The standard deviation of battery temperature decreased from 5.3347 K to 5.2618 K by 1.37%. The system pressure drop decreased from 7.3211 Pa to 3.3838 Pa by 53.78%. The performance of the optimized battery cooling system has been significantly improved.

scholarly journals Study on application of MSOT method for lightweight design of automobile body structure

2020 ◽  
Vol 12 (10) ◽  
pp. 168781402096504
Author(s):  
Li Jixiong ◽  
Wang Daoyong
Keyword(s):  
Weight Reduction ◽  
Lightweight Design ◽  
The Body ◽  
Body Structure ◽  
Multi Objective Optimization ◽  
Pareto Solution ◽  
Multi Objective ◽  
Automobile Body ◽  
Collision Safety ◽  
Side Collision

In this study, the integrated MSOT (M-Multi-dimensional factor autobody model, S-Screening autobody component, O-Optimization of plate thickness, T-Testing, and validation) integration method is adopted to optimize the automobile body structure design for weight reduction. First, a multi-dimensional factor body model is established, then components of the vehicle are screened for the most important targets related to weight reduction and performance, and a multi-objective optimization is performed. Virtual experiments were carried out to validate the analysis and the MSOT method were proposed for lightweight design of the automobile body structure. A multi-dimensional performance model that considers stiffness, modality, strength, frontal offset collision, and side collision of a domestic passenger car body structure. Components affecting the weight of the vehicle were identified. Sheet metal thickness was selected as the main optimization target and a multi-objective optimization was carried out. Finally, simulations were performed on the body structure. The comprehensive performance, in terms of fatigue strength, frontal offset collision safety, and side collision safety, was verified using the optimized Pareto solution set. The results show that the established MSOT method can be used to comprehensively explore the weight reduction of the body structure, shorten the development process, and reduce development costs.

scholarly journals Multi-Objective Design Optimization of the Leg Mechanism for a Piping Inspection Robot

2014 ◽  
Author(s):  
Renaud Henry ◽  
Damien Chablat ◽  
Mathieu Porez ◽  
Frédéric Boyer ◽  
Daniel Kanaan
Keyword(s):  
Nuclear Power ◽  
Pareto Front ◽  
Design Parameters ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Dimensional Synthesis ◽  
Force Factor ◽  
Multi Objective ◽  
Inspection Robot ◽  
Contact Points

This paper addresses the dimensional synthesis of an adaptive mechanism of contact points ie a leg mechanism of a piping inspection robot operating in an irradiated area as a nuclear power plant. This studied mechanism is the leading part of the robot sub-system responsible of the locomotion. Firstly, three architectures are chosen from the literature and their properties are described. Then, a method using a multi-objective optimization is proposed to determine the best architecture and the optimal geometric parameters of a leg taking into account environmental and design constraints. In this context, the objective functions are the minimization of the mechanism size and the maximization of the transmission force factor. Representations of the Pareto front versus the objective functions and the design parameters are given. Finally, the CAD model of several solutions located on the Pareto front are presented and discussed.

A Parametric Optimization Approach of an Induction Heating System for Energy Consumption Reduction

2017 ◽  
Author(s):  
Paolo Cicconi ◽  
Anna Costanza Russo ◽  
Mariorosario Prist ◽  
Francesco Ferracuti ◽  
Michele Germani ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Induction Heating ◽  
Heating System ◽  
High Energy ◽  
Design Parameters ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Molding Process ◽  
Multi Objective ◽  
Induction Heating System

Nowadays, electromagnetic high-frequency induction is very used for different non-contact heating applications such as the molding process. Every molding process requires the preheating and the thermal maintenance of the molds, to enhance the filling phase and the quality of the final products. In this context, an induction heating system, mostly, is a customized equipment. The design and definition of an induction equipment depends on the target application. This technology is highly efficient and performant, however it provides a high-energy consumption. Therefore, optimization strategies are very suitable to reduce energy cost and consumption. The proposed paper aims to define a method to optimize the induction heating of a mold in terms of time, consumption, and achieved temperature. The proposed optimization method involves genetic algorithms to define the design parameters related to geometry and controller. A test case describes the design of an induction heating system for a polyurethane molding process, which is the soles foaming. This case study deals with the multi-objective optimization of parameters such as the geometrical dimensions, the inductor sizing, and the controller setting. The multi-objective optimization aims to reduce the energy consumption and to increase the wall temperature of the mold.

Multi-Objective Optimization of Axial Crush Performance of Square Metal–Composite Hybrid Tubes

2013 ◽  
Author(s):  
Roozbeh Kalhor ◽  
Hossein Akbarshahi ◽  
Scott W. Case
Keyword(s):  
Impact Load ◽  
Pareto Frontier ◽  
Back Propagation ◽  
Design Parameters ◽  
Metal Composite ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Axial Crush ◽  
Composite Layers ◽  
Test Sets

This article deals with the multi objective optimization of square hybrid tubes (metal-composite) under axial impact load. Maximum crushing load and absorbed energy are objective functions and fiber orientation angles of the composite layers are chosen as design parameters while the maximum crush load is limited. Back-propagation artificial neural networks (ANNs) are utilized to construct the mapping between the variables and the objectives. Non-dominated sorting Genetic algorithm–II (NSGAII) is applied to obtain the optimal solutions and the finite element commercial software LS-DYNA is used to generate the training and test sets for the ANNs. Optimum results are presented as a Pareto frontier.

A Genetic Algorithm Based Multi-Objective Optimization of Squealer Tip Geometry in Axial Flow Turbines: A Constant Tip Gap Approach

2019 ◽  
Vol 142 (2) ◽  
Author(s):  
H. Maral ◽  
C. B. Şenel ◽  
K. Deveci ◽  
E. Alpman ◽  
L. Kavurmacıoğlu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Tip Clearance ◽  
Design Parameters ◽  
Leakage Flow ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Tip Leakage Flow ◽  
Tip Leakage ◽  
Multi Objective ◽  
Blade Tip

Abstract Tip clearance is a crucial aspect of turbomachines in terms of aerodynamic and thermal performance. A gap between the blade tip surface and the stationary casing must be maintained to allow the relative motion of the blade. The leakage flow through the tip gap measurably reduces turbine performance and causes high thermal loads near the blade tip region. Several studies focused on the tip leakage flow to clarify the flow-physics in the past. The “squealer” design is one of the most common designs to reduce the adverse effects of tip leakage flow. In this paper, a genetic-algorithm-based optimization approach was applied to the conventional squealer tip design to enhance aerothermal performance. A multi-objective optimization method integrated with a meta-model was utilized to determine the optimum squealer geometry. Squealer height and width represent the design parameters which are aimed to be optimized. The objective functions for the genetic-algorithm-based optimization are the total pressure loss coefficient and Nusselt number calculated over the blade tip surface. The initial database is then enlarged iteratively using a coarse-to-fine approach to improve the prediction capability of the meta-models used. The procedure ends once the prediction errors are smaller than a prescribed level. This study indicates that squealer height and width have complex effects on the aerothermal performance, and optimization study allows to determine the optimum squealer dimensions.

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