Altair AcuSolve™ Performance with AMD EPYC™ 7003 Series Processors

Fluid mechanics simulation is a critical tool for late-stage failure risk mitigation, as well as a driver of design insights throughout the product development process. Used across all levels of product design and validation, from design engineers seeking to understand fluid and thermal effects on a design proposal to analysts performing advanced aerodynamic modeling, Computational Fluid Dynamics (CFD) serves a broad array of applications and a range of users with varied levels of expertise. The sometimes complex and computationally intensive nature of CFD necessitates careful consideration of the software and hardware investments required to produce accurate solutions and scale them at the speed of a company’s development process.

Today, most products are complex mechatronic combinations of advanced technologies, mixing electrical parts with controllers and embedded software. To efficiently manage innovative products, organizations are turning to a Model-Based Development approach for concept studies, control design, multi-domain system simulation and optimization. To meet this demand, Altair’s simulation and optimization suite aims to transform design and decision-making throughout product lifecycles with their multi-disciplinary software tools and consultancy services.

A company specializing in 3D printing relies on simulation to make tools for injection molding that are less expensive, lighter and better than those created with traditional methods.

To design and build an aerial ladder for a firetruck, the engineer needs to accurately determine the working loads the ladder will encounter. Some of these can be easy to interpret such as the weight of the firefighter in the basket at the end of the ladder, or the weight of the water being supplied to the nozzle. Other loads can be a little harder to quantify, such as how wind affects the ladder. There are several different ways to determine this effect, and two of those will be explored in this paper: the standard equation (ASCE 7-10), and CFD.

Optimal design methods involving the coupling of fluid and structural solutions are a topic of active research; particularly for aerospace applications. The paper presents a coupled fluid and structure approach to topology optimization using two commercial finite element solutions; AcuSolve and OptiStruct. A gradient based method is used to minimize the compliance of a structure subject to thermal loading. The optimal material distribution to minimize compliance is computed using the Solid-Isotropic Material with Penalty (SIMP) method available in OptiStruct. A volume fraction constraint is imposed in order to iteratively reduce the parts mass. Draw constraints are used to ensure manufacturability. The thermal loading is computed iteratively using a computational fluid dynamics (CFD) solution from AcuSolve. The optimization produces an innovative design which increases the heat rejection rate of the part while reducing the mass.

Nowadays, it is more and more difficult to design electro-technique devices without having a look at thermal stress. In more and more applications (more electric vehicles, more electric aircrafts, …) designers need to reduce weight, cost, increase efficiency, and keep the same security factor. One possibility is to increase current for the same device, needing to check how to draw away the heat. This is why the classical approximations need to be cross checked with complementary analysis. These new tools have to be rapid and accurate in order to run parametric and even optimization analysis. There is also a need for fast model in order to check robustness versus driving cycles. The goal in this article is to review rapidly the different methods available, depending on the accuracy required and the solving speed. The method includes equivalent thermal circuits, Finite elements methods and CFD analysis.

Development tools and methods, such as simulation, are increasingly important to face and address the pressure of innovation. As an example, for successful new design methods and to show how simulation tools are used, Altair developed a virtual demonstrator based on a cobot application. This complex machine interacts with a human operator as the ultimate smart manufacturing equipment - to show how challenges in modern product design can be overcome.

When applied to engineering, Machine Learning can be a powerful tool to aid in a range of applications, from faster finite-element (FE) model building to optimizing manufacturing processes and obtaining more accurate results from physics-based simulations. Although incorporating this collection of technology is relatively new in the field of engineering, Altair has made leaps forward in this space to provide users with the tools they need to make a difference.