This paper was produced for the 2019 NAFEMS World Congress in Quebec Canada
In the industry today, CAE simulation software has become more easily available to companies of all sizes. In the case of companies with smaller simulation departments with limited manpower and computational resources, achieving the best possible results is often a challenge. The traditional methodology of running complex simulations to evaluate results, compare with previous runs, review with peers and produce new ideas for the next run can become too expensive in both time and man hours even for simple cases.
This paper will showcase how the use of multiple optimization techniques and simulation software can leverage the power of mathematics and numerical simulation to determine the best course of action or design at lower costs. This paper will present several examples where optimization using either finite element analysis or computational fluid dynamics was used to successfully obtain a new design when it would be a costly and lengthy process using traditional iterative procedures.
The first case presented discusses how optimization of a CFD model using morphing volumes was used to change the shape of a pump discharge in the pulp and paper industry to increase pump efficiency. It will be shown that by using a simplified version of a correlated CFD model in conjunction with an optimizer, the much more complex new discharge shape was able to increase the pump efficiency by 2.3% on an already good product. The result discussion will highlight the resources used to obtain these results and compare them to a traditional approach in the same context to emphasize how this result would not have been achieved otherwise.
The second case that will discuss how the use of optimization techniques and software with a nonlinear FEA model to improve the comfort of a foam sleeping mattress. In this specific example, it was desired to generate a model that would correctly predict the mattress flexibility versus its detailed design. It will be shown that using optimization to study the response surface and sampling of the design space, it was possible to construct a mathematical model to relate compression force to the shape of the cavities machined within the foam material. The application of this new technology would have been very difficult to achieve and extremely time-consuming using an iterative approach.
A third example will be presented to show how, in the context of the structural design of a vehicle suspension part, topology optimization can be used to guide design modifications with the goal of improving the stiffness of the system to an acceptable level. In this particular case, complex load paths in the part meant that the more traditional iterative approach initially employed was ineffective. Optimization gave insight on the right design changes to make and ultimately led to success of a project that was otherwise stagnating.
|Date||18th June 2019|