One of history’s greatest engineering feats was the result of a highly creative team exercise. Kelly Johnson’s group at Lockheed Martin conceived and brought to reality the SR-71 Blackbird family of aircraft through brilliance, trial and error, and design evolution based upon deep insight into the complex parameters behind making a reconnaissance craft fly at Mach 3 and altitudes of up to 85,000 ft. What is most astounding is that it was able to chart the unknowns, understand performance trade-offs, and actually build the “bird” without benefit of today’s software and computing power.
Not every design project can afford its own Skunk Works, as was the case with development of the SR-71, but using team-like power and superior management to explore multiple parameters is not only possible but practical. And creating high-performing products on budget, to tighter time frames, is just what engineers do today.
Regardless of how an answer to such challenges is finally arrived at, it usually all boils down to making the “right” choices between many things. This is where having a more mapped-out route, through process automation and optimization software coupled with realistic simulation, makes clear sense. Such activity is already going on. Manufacturers have employed these tools for more than a decade to virtually design, optimize, and prove out their results from the earliest moment of product genesis.
What can stand in the way of reaching the best and right solutions? Design decisions can become more complicated—and produce poor results—when typical organizational processes interfere. Often, a team must propose complex and competing designs. Sometimes, due to internal politics or individual personalities, it’s the best PowerPoint presentation that wins—not the design configuration that is truly best.
This kind of unchecked cultural competition for direction needs to be balanced with quantitative feedback. Simulation process automation and optimization software provides the environment for mapping out and transforming less-than-perfect methods. With a built-in best-practice workflow that guides—and challenges—engineering decision makers throughout the design process, software such as Dassault Systèmes’ Isight from SIMULIA focuses on a goal, yet widens the spotlight and trades off every possibility en route to that goal. And it happens automatically, quickly, and accurately. The process does not crimp creativity—it channels it—ensuring that all ideas get a fair “apples-to-apples” comparison and are properly vetted. While targeting the behavior and/or performance attributes that are wanted, users are free to vary inputs, such as one material against another, and then reproduce inquiries across different sets of assumptions.
Using the software in this way lets designers look beyond their familiar design “ruts” to consider alternatives they might not even have thought of.
How does the software work? First it helps clarify objectives and constraints. Next, a drag-and-drop function enables users to build a process or simulation flow that integrates whatever analyses (CAD, CFD, FEA) that are considered critical, and identify decision points. The third step adds, if warranted, a Design of Experiments run-through (such as DOE, Monte Carlo). Finally, the software optimizes the results by identifying those inputs that best meet the specified objectives.
The ability of simulation process automation to dramatically improve designs has been documented by customers in very diverse fields from baby diapers to aircraft engines. Aerospace manufacturers, for example, are achieving multiple goals such as simultaneously increasing power output and reducing engine weight and lowering turbine inlet temperature. Such results underscore the role that simulation process automation and optimization can play in honing creativity and streamlining design decision making. Imagination and inventiveness—supported by facts—ensure repeatability, promote quality, and achieve full alignment of engineering and business objectives.
Alex Van der Velden, Director, SLM, SIMULIA Product Management, Dassault Systèmes, wrote this article for Aerospace Engineering.