Simulating the future
The use of mathematical models for the design and manufacture of everything around us is nothing new, from the improvement in sound quality and construction of headphones, increasingly smaller and discrete, to simulations to improve autonomous vehicles. Models date from the first industrial revolution to the present day. They are indispensable for modelling new objects or for problem-solving, but what has changed dramatically is how this procedure is carried out. More than 50 years ago, one engineer in particular, John Swanson, focused on the way in which technology is used to improve or develop new ones, but in a more efficient and autonomous way through the software.
John, in the 1960s, worked in an astronuclear laboratory where the thin element method was used to solve complex mathematical equations and design new models. Within the astronuclear laboratory, the problems were everything from structural analysis, heat transfer, and fluid mechanics, among others, and to solve these, they needed more and more computing power as the reactors included new technologies, which could generate more complex problems. Nowadays, Formula 1 uses simulation to optimize race cars, achieve more aerodynamics, lowering engine temperatures, and discovering new materials; these are just some of the utilities that are given to software like this.
Years later, in the early 1970s, Swanson founded SASI, which years later would be renamed to Ansys Inc (NASDAQ: ANSS) and began to develop its own system, but this had a particularity, in the ’70s there were no computers like we have today, which is why the software was programmed on punched cards, and the system was rented by the hour. Something very curious about Ansys Inc (NASDAQ: ANSS) is that its first user was the same laboratory that did not accept the idea of automation.
The massive use of electronic devices began to facilitate the distribution of this software, and by 1990 the company was generating 30 million dollars in revenue and had managed to capture 10% of the market related to engineering, a real feat which would be surpassed in just five years; almost doubling its annual revenue to 50 million.
In these last 20 years, Ansys Inc (NASDAQ: ANSS) has acquired 27 companies that have made its software a totally vertical program, allowing it to integrate perfectly into any company that acquires the license, but a remarkable feature is that it is also modular, that is, problems can be solved in parts, from the smallest to the most complex, adding modules or layers.
The Ansys software is a tool that allows modelling almost any product or situation, giving it flexibility and versatility; this is something very useful thinking about the needs of all the companies that will use the system since it allows simulations of all kinds. Oracle Red Bull Racing has been using Ansys tools since 2008, “Ansys Fluent CFD” allows them to simulate wind tunnels, improving the aerodynamics of the cars that compete in Formula 1, and also uses it to develop the cooling circuit and evaluate its capacity in relation to the power unit. But one of the most outstanding tools is “Ansys LS-DYNA,” which simulates impacts using virtual models.
The use of these impact simulations reduces the amount of physical testing, saving time and investment and ensuring that drivers have F1 circular safety standards. Red Bull Racing won the 2022 championship with Max Verstappen at the wheel, but the Red Bull team has won the constructors’ championship, designing and putting the best car of the season on the track.
Bianchi is an electric bicycle manufacturer that is using Ansys to optimize its frames and components, while Praan is a research and development company that is using physics-related simulation modules to develop technologies to remove particulates and greenhouse gases.
Innovation in simulation allows a more predictable future, knowing with a high probability the different possible outcomes, and this software is only growing, helping not only companies to design their products but also helping scientists to test different theories and, along the way, perhaps discover new ideas that will improve our quality of life or help solve some of society’s greatest challenges.
Software that started with a simple idea of automation now allows us to simulate and model our future.