Metamodeling Development for Vehicle Frontal Impact Simulation

2001 ◽  
Author(s):  
R. J. Yang ◽  
N. Wang ◽  
C. H. Tho ◽  
J. P. Bobineau ◽  
B. P. Wang
Keyword(s):  
Response Surface ◽  
Impact Analysis ◽  
Hybrid Approach ◽  
Latin Hypercube Sampling ◽  
Element Model ◽  
Least Square ◽  
Frontal Impact ◽  
Response Surface Methods ◽  
Moving Least Square ◽  
Highly Nonlinear

Abstract Response surface methods or metamodels are commonly used to approximate large engineering systems. This paper presents a new metric for evaluating a response surface method or a metamodeling technique. Five response surface methods are studied: Stepwise Regression, Moving Least Square, Kriging, Multiquadratic, and Adaptive and Interactive Modeling System. A real world frontal impact design problem is used as an example, which is a complex, highly nonlinear, transient, dynamic, large deformation finite element model. The optimal Latin Hypercube Sampling method is used to distribute the sampling points uniformly over the entire design space. The Root Mean Square Error is used as the error indicator to study the accuracy and convergence rate of the metamodels for this vehicle impact analysis. A hybrid approach/strategy for selecting the best metamodels of impact responses is proposed.

scholarly journals The High-Speed Train Seat Design Based on the Human Lumbar Biomechanical Analysis

2014 ◽  
Vol 6 ◽  
pp. 524802
Author(s):  
Yunpeng Guo ◽  
Guiqiu Song
Keyword(s):  
High Speed ◽  
Element Model ◽  
Least Square ◽  
Biomechanical Analysis ◽  
High Speed Train ◽  
Design Standards ◽  
Engineering Technology ◽  
Moving Least Square ◽  
Physical Ergonomics ◽  
The Finite Element Model

This paper, aimed at the problems of high-speed train seat design standards that lack biomechanical analysis, analyzed the lumbar force of sitting position and verified the validity of the finite element model of human lumbar L1–L5 that had been built by reverse engineering technology. Based on the lumbar force distribution, the methods of exterior penalty and moving least square were adopted to establish a high-speed train seat equation that caters for physical ergonomics and a new high-speed train seat model was designed so as to improve the comfort for passengers.

Analysis and optimization of the strain concentration factor in countersunk rivet holes via finite element and response surface methods

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohannad Jreissat ◽  
Mohammad A. Gharaibeh
Keyword(s):  
Finite Element ◽  
Response Surface ◽  
Concentration Factor ◽  
Element Model ◽  
Rectangular Plates ◽  
Element Analysis ◽  
Content Type ◽  
Response Surface Methods ◽  
Strain Concentration ◽  
Factor Data

PurposeThe purpose of this paper is to investigate the strain concentration factor in a central countersunk hole riveted in rectangular plates under uniaxial tension using finite element and response surface methods.Design/methodology/approachIn this work, ANSYS software was elected to create the finite element model of the present structure, execute the analysis and generate strain concentration factor (,) data. Response surface method was implemented to formulate a second order equation to precisely compute (,) based on the geometric and material parameters of the present problem.FindingsThe computations of this formula are accurate and in a great agreement with finite element analysis (FEA) data. This equation was further used for obtaining optimum hole and plate designs.Originality/valueAn optimum design of the countersunk hole and the plate that minimizes the (,) value was achieved and hence validated with FEA findings.

Constructing Continuous Strain and Stress Fields From Spatially Discrete Displacement Data in Soft Materials

2015 ◽  
Vol 83 (1) ◽  
Author(s):  
Wanru Liu ◽  
Rong Long
Keyword(s):  
Finite Element ◽  
Interpolation Method ◽  
Local Strain ◽  
Soft Materials ◽  
Element Model ◽  
Least Square ◽  
Stress Fields ◽  
Moving Least Square ◽  
Data Points ◽  
Mls Method

A recent study demonstrated that three-dimensional (3D) continuous displacement fields in transparent soft gels can be constructed from discrete displacement data obtained by optically tracking fluorescent particles embedded in the gels. Strain and stress fields were subsequently determined from gradients of the displacement field. This process was achieved through the moving least-square (MLS) interpolation method. The goal of this study is to evaluate the numerical accuracy of MLS in determining the displacement, strain, and stress fields in soft materials subjected to large deformation. Using an indentation model as the benchmark, we extract displacement at a set of randomly distributed data points from the results of a finite-element model, utilize these data points as the input for MLS, and compare resulting displacement, strain, and stress fields with the corresponding finite-element results. The calculation of strain and stress is based on finite strain kinematics and hyperelasticity theory. We also perform a parametric study in order to understand how parameters of the MLS method affect the accuracy of the interpolated displacement, strain, and stress fields. We further apply the MLS method to two additional cases with highly nonuniform deformation: a plate with a circular cavity subjected to large uniaxial stretch and a plane stress crack under large mode I loading. The results demonstrate the feasibility of using optical particle tracking together with MLS interpolation to map local strain and stress field in highly deformed soft materials.

Approximations for Safety Optimization of Large Systems

2000 ◽  
Author(s):  
R. J. Yang ◽  
L. Gu ◽  
L. Liaw ◽  
C. Gearhart ◽  
C. H. Tho ◽  
...  
Keyword(s):  
Latin Hypercube Sampling ◽  
Response Surfaces ◽  
Least Square ◽  
Multivariate Adaptive Regression Splines ◽  
Benchmark Problems ◽  
Moving Least Square ◽  
Adaptive Regression ◽  
Large Systems ◽  
Optimal Latin Hypercube Sampling ◽  
Adaptive Regression Splines

Abstract This paper presents four approximation methods for the construction of safety related functions. These methods are: Enhanced Multivariate Adaptive Regression Splines, Stepwise Regression, Artificial Neural Network, and the Moving Least Square. The optimal Latin Hypercube Sampling method is used to distribute the sampling points uniformly over the entire design space. Four benchmark problems used in crash and occupant simulation are employed to investigate the accuracy of the approximate or surrogate models. An occupant safety optimization problem is solved using these four response surfaces. Based on numerical results, a best, applicable approximation strategy for safety optimization is proposed in the end.

Sign in / Sign up

Export Citation Format

Share Document