A Search-Based Approach for Prediction of Flexible Hose Shapes

Abstract

Flexible hoses and cables are vital components used in a variety of artifacts, including complex products such as automobiles. When designing a vehicle, it is important to know the shape that a flexible component will take between its two endpoints. Incorrect information regarding hose shapes can lead to shortened component lifespans and even costly recalls. Several efforts have attempted to predict the shape of flexible components. In the past, Computer Aided Engineering (CAE) simulations using mathematical models have been used to predict hose and cable shapes, providing fairly accurate results. However, CAE simulations of hoses and cables are extremely time-consuming, often taking several hours to weeks for completion. In this paper, we propose an approach to dramatically reduce this time burden. We propose the idea of “looking up” a solution. Rather than mathematically calculating a hose shape, our approach called Search-based Real-time Prediction of CAE Solutions (SRPCS) relies on a large database of intelligently represented problems and solutions. The query problem is then intelligently decomposed into problems with known solutions and the individual solutions are then recombined to obtain the overall shape, i.e., solution to the problem. We generated real hose shapes in a test rig and stored in a database. Analysis of the results shows that the SRPCS provides an accurate and rapid solution to obtain the shape of flexible components.