A Magic Cube Approach for Crashworthiness Design University of Michigan

Format:

Conference/Event

Author/Creator:

Qi, Chang, author.

Conference Name:

SAE 2006 World Congress & Exhibition (2006-04-03 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2006

Summary:

Vehicle structure crashworthiness design is one of the most challenging problems in product development and it has been studied for decades. Challenges still remain, which include developing a reliable and systematic approach for general crashworthiness design problems, which can be used to design an optimum vehicle structure in terms of topology, shape, and size, and for both structural layout and material layout. In this paper, an advanced and systematic approach is presented, which is called Magic Cube (MQ) approach for crashworthiness design. The proposed MQ approach consists of three major dimensions: Decomposition, Design Methodology, and General Considerations. The Decomposition dimension is related to the major approaches developed for the crashworthiness design problem, which has three layers: Time (Process) Decomposition, Space Decomposition, and Scale Decomposition. The Design Methodology dimension is related to the techniques applied to the crashworthiness design, the three layers in this dimension are: Target Cascading, Failure Mechanism Analysis, and Optimization Method. The General Considerations dimension has three layers, which are: Multidisciplinary Objectives, Loading Conditions, and Uncertainty Effects. All these layers are coupled with each other to form a 27- element magic cube. A crashworthiness design problem can be then solved by employing the elements in the magic cube. Examples will be given to demonstrate the proposed approach and its successful application in real vehicle crashworthiness design problems

Notes:

Vendor supplied data

Publisher Number:

2006-01-0671

Access Restriction:

Restricted for use by site license