scholarly journals Multi-Response Optimisation of Automotive Door Using Grey Relational Analysis with Entropy Weights

2021 ◽  
Author(s):  
Hao Chen ◽  
Chihua Lu ◽  
Zhien Liu ◽  
Cunrui Shen ◽  
Menglei Sun
Keyword(s):  
Structural Design ◽  
Lightweight Design ◽  
Computational Cost ◽  
Element Model ◽  
Design Parameters ◽  
Physical Experiments ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Grey Relational ◽  
The Finite Element Model

Abstract Tail-welded blanks (TWBs) are widely used in automotive bodies to improve structural performance and reduce weight. The stiffness and modal lightweight design optimisation of TWBs for automotive doors was performed in this study. The finite element model was validated through physical experiments. An L27 (312) Taguchi orthogonal array was used to collect the sample points. The multi-objective optimisation problem was transformed into a single-objective optimisation problem based on the grey relational degree. The optimal combination of structural design parameters was obtained for a tail-welded door using the proposed method; the weight of the door structure was reduced by 2.83 kg. The proposed optimisation method has fewer iterations and a lower computational cost, enabling the design of lightweight TWBs.

Electric Bus Body Lightweight Design Based on Multiple Constrains

2012 ◽  
Vol 538-541 ◽  
pp. 3137-3144 ◽  
Author(s):  
Wen Wei Wang ◽  
Cheng Jun Zhou ◽  
Cheng Lin ◽  
Jiao Yang Chen
Keyword(s):  
Finite Element ◽  
Lightweight Design ◽  
Element Model ◽  
The Body ◽  
Body Frame ◽  
Electric Bus ◽  
Free Model ◽  
Bus Body ◽  
The Finite Element Model ◽  
Torsion Condition

The finite-element model of pure electric bus has been built and the free model analysis, displacement and stress analysis under bending condition and torsion condition have been conducted. Optimally design the pure electric bus frame based on multiple constrains. Reduce the body frame quality by 4.3% and meanwhile meet the modal and stress requirements.

scholarly journals APPLICATION OF RIGID LINKS IN STRUCTURAL DESIGN MODELS

2017 ◽  
Vol 13 (3) ◽  
pp. 119-137 ◽  
Author(s):  
Sergey Yu. Fialko
Keyword(s):  
Finite Element ◽  
Structural Design ◽  
Stiffness Matrix ◽  
Sparse Matrix ◽  
Element Model ◽  
Rigid Bodies ◽  
Design Models ◽  
Adjacency Graph ◽  
Direct Solvers ◽  
The Finite Element Model

A special finite element modelling rigid links is proposed for the linear static and buckling analysis. Unlike the classical approach based on the theorems of rigid body kinematics, the proposed approach preserves the similarity between the adjacency graph for a sparse matrix and the adjacency graph for nodes of the finite element model, which allows applying sparse direct solvers more effectively. Besides, the proposed approach allows significantly reducing the number of nonzero entries in the factored stiffness matrix in comparison with the classical one, which greatly reduces the duration of the solution. For buckling problems of structures containing rigid bodies, this approach gives correct results. Several examples demonstrate its efficiency.

Air Conditioning Load Prediction of an Office Building based on Long Short Term Memory Neural Network

2021 ◽  
Vol 14 ◽  
Author(s):  
Mengxiang Zhuang ◽  
Qixin Zhu
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Air Conditioning ◽  
Short Term Memory ◽  
Load Prediction ◽  
Short Term ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Long Short Term Memory ◽  
Grey Relational

Background: Energy conservation has always been a major issue in our country, and the air conditioning energy consumption of buildings accounts for the majority of the energy consumption of buildings. If the building load can be predicted and the air conditioning equipment can respond in advance, it can not only save energy, but also extend the life of the equipment. Introduction: The Neural network proposed in this paper can deeply analyze the load characteristics through three gate structures, which is helpful to improve the prediction accuracy. Combined with grey relational degree method, the prediction speed can be accelerated. Method: This paper introduces a grey relational degree method to analyze the factors related to air conditioning load and selects the best ones. A Long Short Term Memory Neural Network (LSTMNN) prediction model was established. In this paper, grey relational analysis and LSTMNN are combined to predict the air conditioning load of an office building, and the predicted results are compared with the real values. Results: Compared with Back Propagation Neural Network (BPNN) prediction model and Support Vector Machine (SVM) prediction model, the simulation results show that this method has better effect on air conditioning load prediction. Conclusion: Grey relational degree analysis can extract the main factors from the numerous data, which is more convenient and quicker without repeated trial and error. LSTMNN prediction model not only considers the relation of air conditioning load on time series, but also considers the nonlinear relation between load and other factors. This model has higher prediction accuracy, shorter prediction time and great application potential.

The Grey Relational Analysis of Driving Forces for Water Consumed Structure

2012 ◽  
Vol 490-495 ◽  
pp. 1612-1616 ◽  
Author(s):  
Cui Mei Lv ◽  
Fa Xing Du
Keyword(s):  
Grey Relational Analysis ◽  
Driving Forces ◽  
Water Saving ◽  
Utilization Rate ◽  
Sustainable Utilization ◽  
Urbanization Level ◽  
Relational Analysis ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Grey Relational

Grey Relational Analysis is a method of analysis and calculates the relational degree of evaluated object, which can characterize the relational degree between object with viral object. In this paper it was used to analyze the driving forces of water consumed structure change, and YiChang city was selected as an example. Adopted grey relational degree analysis, the main factors were found out. The results showed that industry water utilization rate, irrigation area, urbanization level are the main driving forces, and corresponding water-saving measures were put forward. This study can provide reference for the construction of water-saving society and sustainable utilization of water resource.

Analysis of Static Bending Rigidity with Car Body Lightweight Design for Certain Model of Electric Vehicle

2014 ◽  
Vol 552 ◽  
pp. 24-28
Author(s):  
Zhen Yu Xu
Keyword(s):  
Finite Element ◽  
Electric Vehicle ◽  
Steel Plate ◽  
Lightweight Design ◽  
High Strength ◽  
Element Model ◽  
Bending Rigidity ◽  
Car Body ◽  
Before And After ◽  
The Finite Element Model

Taking a certain urban model of electric vehicle as example, DC04 steel plate has replaced with high-strength steel plate BH340 for some parts of the car body on the purpose of reducing the car weight; at the same time, reduced the thickness of steel plate at the replacing spots, and then set the finite element model for the car body to compare its bending rigidities before and after replacement. On the premise of satisfying car body’s bending rigidity, it could make car body to reduce a weight of 23.2KG to satisfy the requirement for lightweight design.

10 kw Vertical Axis Wind Turbine Spindle Design and Optimization

2014 ◽  
Vol 487 ◽  
pp. 429-434 ◽  
Author(s):  
Qiao Mei Li ◽  
Yang Cao ◽  
Guo Qing Wu ◽  
Xing Hua Chen ◽  
Yan Hua Cao
Keyword(s):  
Wind Turbine ◽  
Vibration Mode ◽  
Vertical Axis ◽  
Element Model ◽  
High Load ◽  
Design Parameters ◽  
Vertical Axis Wind Turbine ◽  
Dead Weight ◽  
Design And Optimization ◽  
The Finite Element Model

The spindle of a 10 kw vertical axis wind turbine is designed in this paper, and the relevant geometric parameters is given, and build the geometry of the finite element model. Calculation of the spindle under wind load and dead weight , and analyse the spindle Von Mess stress, deformation nephogram, and give the former six order vibration mode of the spindle. Through the analysis, Then the design parameters of the spindle are optimized. and the optimized structure of spindle has been got. optimized spindle is in lower quality, more satisfy the requirement of wind turbine running under high load at the same time .

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