Vehicle Profile Optimization using Central Composite Design for Pedestrian Injury Mitigation

Pedestrian injury poses a significant problem throughout the world. Pedestrians contribute to the second largest category of motor vehicle deaths accounting for about 13% of fatalities, after occupant injuries. Therefore is vital to design pedestrian friendly vehicles to mitigate injuries and fatali...

Full description

Bibliographic Details
Published in:Applied Mathematics and Information Sciences
Main Author: Kausalyah V.; Shasthri S.; Abdullah K.A.; Idres M.M.; Shah Q.H.; Wong S.V.
Format: Article
Language:English
Published: Natural Sciences Publishing 2015
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108580320&doi=10.12785%2fAMIS%2f010125&partnerID=40&md5=9626c768d14142a805279747f1e49e99
Description
Summary:Pedestrian injury poses a significant problem throughout the world. Pedestrians contribute to the second largest category of motor vehicle deaths accounting for about 13% of fatalities, after occupant injuries. Therefore is vital to design pedestrian friendly vehicles to mitigate injuries and fatalities. A statistical methodology employing the Design of Experiments (DoE) is adopted in this work to obtain the optimum design parameters for the vehicle front end geometry. The work studies the feasibility of the use of Central Composite Designs (CCD) between a Circumscribed design (CCC) and a Faced design (CCF). A total of 100 simulation runs are performed and the response is tabulated. Multi linear regression analysis is performed following which, quadratic programming is used to carry out the optimization task using the Response Surface models obtained. It is concluded that the CCC offers a better prediction for the optimum values in comparison to the CCF design. The SSR value for the CCC design offers a better fit for the model yielding the value of 2.68 which is lesser than CCF's value of 2.87. In addition, the practical error margin between the predicted CCC designs and observed experimental values are 43.68 for CCC and 187.66 for CCF respectively, thus affirming the conclusion made. © 2015 NSP Natural Sciences Publishing Cor. All Rights Reserved.
ISSN:19350090
DOI:10.12785/AMIS/010125