Katare, S., Reddy, D., Ourchane, A., and Nammalwar, G., "Towards a One Day Frame Model Build," SAE Technical Paper 2017-01-1314, 2017, doi:10.4271/2017-01-1314.
Virtual Verification (VV) of engineering designs is a critical enabler in the Product Development (PD) process to reduce the time-to-market in a cost efficient manner. Reliance on cost effective VV methods have significantly increased with increased pressure to meet customer expectations for new products at reduced PD budgets. Computer Aided Engineering (CAE) is one such VV method that affords an engineer to make decisions about the ability of the designs to meet the design criteria even before a prototype is built. The first step of the CAE process is meshing which is a time consuming, manual and laborious process. Also mesh development time and accuracy significantly varies with the (1) component (trim body, engine, suspension, brakes, etc.), (2) features predominantly occurring in the component (welds, ribs, fillets, etc.), meshing guidelines based on which the model needs to be developed (durability, safety, NVH, etc.), and the expertise of the meshing engineer involved. This paper proposes techniques that reduces the turn-around-time of seam weld meshing process in an automobile frame.In the context of an automobile frame we demonstrate that efficient usage of CAD tools for generating a CAE-enabled “intelligent CAD” significantly reduces the time taken in the downstream meshing process in a CAE pre-processor. Specifically, mid-surfaces and weld curves generated using a CAD tool are used to convert the welds that are traditionally represented as solids into surfaces. This change in representation of the input to the CAE tool makes the meshing process more efficient. In addition, key improvements in geometry cleanup, base metal and seam weld meshing, quality correction with techniques such as zone-cut and set creation, and automated assessment of the quality of the resultant meshes, are shown to reduce the overall turn-around-time from CAD-to-mesh by 48%.