Search-based real-time prediction of CAE solutions

Flexible hoses and cables are important components in the construction of an automobile. When designing a vehicle, it is vital to know the shape that a flexible component will take between its two endpoints. Incorrect information regarding hose routings can lead to shortened component lifespans and even costly recalls. Because of this, great lengths have been taken to predict the shape of flexible components. In the past computer simulations using mathematical models have been used to predict hose and cable routings. Over time, these models have made many strides in terms of accurately predicting flexible component shape. However, computer simulations of hoses and cables are extremely time consuming, often times taking several hours or days. A new method of predicting hose shapes is needed to dramatically reduce this time burden. This thesis paper proposes the idea of “looking up” a solution. Rather than calculating a hose shape, a search-based approach would be used that relies on a large database of intelligently represented solutions. A large amount of processing, indexing, and optimizing would be done offline on a backend database so a solution can be quickly generated. This method is known as the Search-based Real-time Prediction of CAE solutions (SRPCS). In this research real hose shapes were generated in a test rig and stored in a database. This database was then used to search for other flexible component shape solutions in a feasibility study. The authors of this paper found that the SRPCS method provided an accurate and very rapid solution of flexible components. We believe that the concept of search-based solutions has been proven out in this research. The potential of this method needs to be further explored, including areas outside of flexible components