RSM and MLR Model for Equivalent Stress Prediction of Eicher 11.10 Chassis Frame: A Comparative Study

被引:1
|
作者
Patel, Tushar M. [1 ]
Bhatt, Nilesh M. [2 ]
机构
[1] Mewar Univ, Chittaurgarh, Rajasthan, India
[2] Gandhinagar Inst Technol, Gandhinagar, Gujarat, India
来源
PROCEEDINGS OF FIRST INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY FOR INTELLIGENT SYSTEMS: VOL 2 | 2016年 / 51卷
关键词
Chassis frame; FE analysis; RSM; MLR; Equivalent stress; ARTIFICIAL NEURAL-NETWORK; RESPONSE-SURFACE METHODOLOGY; OPTIMIZATION; LIPASE;
D O I
10.1007/978-3-319-30927-9_38
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The main objective of the study is to compare the prediction accuracy of Response Surface Methodology (RSM) and Multiple Linear Regressions (MLR) model for the Equivalent stress of the chassis frame. The chassis frame is made of two sidebars connected with a series of crossbar. The web thickness, upper flange thickness and lower flange thickness of sidebar becomes the design variables for the optimization. Since the number of parameters and levels are more, so the probable models are too many. The variants of the frame are achieved by topology modification using the orthogonal array. Then Finite Element Analysis (FEA) is performed on those models. RSM model and MLR model are prepared using the results of FEA to predict equivalent stress on the chassis frame. The results indicate that predictions of RSM model are more accurate than predictions of MLR model.
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页码:387 / 395
页数:9
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