While still a relatively new concept, most of the hype over generative design technology has centered on the ability to zero in on organic shapes that are lightweight without making tradeoffs on structural integrity.
However, generative design technologies—architected on the principle of applying infinitely-scalable computing power, artificial intelligence (AI), and machine learning to solve complex engineering challenges–are now winding their way into other areas of development, including fluid flow design. Flow engineers are tasked with finding feasible flow paths that form complex networks throughout a product while ensuring maximum flow rates. The discipline is crucial in industries like Aerospace & Defense, energy and materials, industrial equipment, even consumer goods (think about dishwasher water lines or the air/coolant channels in your fridge).
Much like structural engineers are on a perennial quest to optimize parts through lightweighting, flow engineers working in areas like jet propulsion, HVAC, and powertrains are in constant search of ways to generate optimized interior fluid flow passageways. Typically, they’ve relied on established Computational Fluid Dynamics (CFD) tools and long-standing simulation workflows to meet their targets, whether the aim is to increase flow efficiency or minimize pressure losses.
The problem is the traditional workflow is disjointed and time consuming, requiring lots of back and forth between siloed tool sets, from CAD to specialized CFD simulation packages. Each stage of the process demands data translations and hand-offs between multiple applications, each with different user interfaces, as engineering teams push geometries and CFD models through the iterative design, model, optimize, and validation cycles to arrive an optimized fluid flow pathway.
“It’s not a streamlined process and it’s painful to go through,” notes Colin Swearingen, industry process consultant for Dassault Systèmes. “Teams could be using four or five software tools to go through the process. There is so much data exchange and collaboration necessary, it makes it difficult to scale if you’re doing a ton of parts.”
Flow-Driven Generative Design
Dassault Systèmes is addressing the challenge with a new workflow designed to streamline the process and speed time to insights. The new Flow-Driven Generative Design, a set of apps fully integrated within the 3DEXPERIENCE Platform, not only streamlines the traditional workflow, but also makes flow optimization capabilities far more accessible to mainstream engineers to use earlier and systematically throughout the process. This is in sharp contrast to traditional flow design workflows where the bulk of analysis work is done at key intervals by dedicated CFD specialists.
Based on the Tosca Fluid simulation engine, the new Flow-Driven Generative Design tool leverages workflow assistants to guide engineers through the process of specifying inputs and boundary conditions and automatically optimizing the output to meet the fluid flow requirements from a single unified tool.
“Generative Flow Design unifies simulation and CAD into one environment as a non-expert solution,” Swearingen explains. “Designers can leverage best-in-class simulation capabilities like Tosca Fluid … allowing the functional part requirements to drive the design rather than relying on experience or intuition.”
Another upside to the approach: Analysts get higher-quality answers earlier, allowing them to focus on the more important aspects of their jobs rather than being bogged down with time-consuming back and forth with designers. In the end, simplifying the flow design workflow and leveraging the power of mathematical modeling to solve problems gives teams the dual advantage of more efficient engineering processes and better optimized parts.
Watch the on demand e-seminar on Flow Driven Generative Design.
Beth Stackpole is a veteran journalist covering the intersection of IT, business, and engineering technologies and trends. She is also a contributing editor to Desktop Engineering.