Cloud-Based CAD Parametrization for Design Space Exploration and Design Optimization in Numerical Simulations

Joel Guerrero,Luca Mantelli,Sahrish B Naqvi

doi:10.3390/fluids5010036

Abstract

In this manuscript, an automated framework dedicated to design space exploration and design optimization studies is presented. The framework integrates a set of numerical simulation, computer-aided design, numerical optimization, and data analytics tools using scripting capabilities. The tools used are open-source and freeware, and can be deployed on any platform. The main feature of the proposed methodology is the use of a cloud-based parametrical computer-aided design application, which allows the user to change any parametric variable defined in the solid model. We demonstrate the capabilities and flexibility of the framework using computational fluid dynamics applications; however, the same workflow can be used with any numerical simulation tool (e.g., a structural solver or a spread-sheet) that is able to interact via a command-line interface or using scripting languages. We conduct design space exploration and design optimization studies using quantitative and qualitative metrics, and, to reduce the high computing times and computational resources intrinsic to these kinds of studies, concurrent simulations and surrogate-based optimization are used.

Highlights

Consumer demand, government regulations, competitiveness, globalization, better educated end-users, environmental concerns, market differentiation, social media trends, and even influencers, they are all driving products manufacturers and industry to reduce production expenditures and final cost of goods, and at the same time improving the quality and reliability of the products with the lowest environmental impact
For the design optimization (DO) case, we used as starting point 0 degrees, and the case converged to the optimal value in 31 function evaluations
In the design space exploration (DSE) case, we explored the design space from 0 to 180 degrees, in steps of 5 degrees, so roughly speaking, we used the same number of function evaluations as for the DO case

Summary

Introduction

Government regulations, competitiveness, globalization, better educated end-users, environmental concerns, market differentiation, social media trends, and even influencers, they are all driving products manufacturers and industry to reduce production expenditures and final cost of goods, and at the same time improving the quality and reliability of the products with the lowest environmental impact. To reach these goals and to develop revolutionary products, the manufacturing sector is relying more on virtual prototypes, computer simulations, and design optimization. Though the optimization might take different forms in different fields (e.g., finance, health, construction, operations, manufacturing, transportation, construction, engineering design, sales, public services, mail, and so on), the ultimate goal is always getting the best out of something under given circumstances, either by minimizing, maximizing, equalizing, or zeroing a quantity of interest (QoI).

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Conclusion