Monolith, an artificial intelligence (AI) software provider for the world’s leading automotive, aerospace and industrial engineering teams, has acquired Textron Inc. (NYSE: TXT) announced the results of its collaboration with Coutex, the company and one of the top 100 automotive suppliers. Global OEM. Monolith’s highly intelligent AI technology enabled Coutex-Textron’s validation engineering team to solve one of its most complex engineering challenges with fuel ‘spillover’, while reducing design iterations and manufacturing costs, prototyping and testing did. Using the power of AI to accurately predict vehicle slow-gen slosh noise, Coutex-Textron engineers to expand application of AI to solve more engineering challenges in an era of unprecedented work electrification Opens up a world of opportunities for
Dr. Bernhardt Ludeke, Global Head of Verification at Kautex-Textron, said: : “Using Monolith’s machine learning methodology, we not only solved the challenge, we also reduced design iteration time and prototyping and testing costs. The software reduced design analysis time from days to minutes with improved accuracy. We are pleased with the results and believe we have found a way to improve the design solutions of the future.”
The core of the challenge for Coutex engineers was to reliably understand the relationship between fuel tank properties, test parameters and the resulting sloshing noise, a difficult physical process that typically requires multiple physical tests with full prototype tanks. at different levels.
l Dr. Elin Petcu, Global Lead, Virtual Validation Projects, Coutex Textron, Dijo : “Predicting fuel slosh noise during vehicle deceleration is one of the most complex multi-physics challenges for our engineering team to model and understand. Using Monolith AI software, we have now tackled this most difficult and previously unforeseen challenge. Solved physics problem to be solved.By combining our engineering expertise, acoustic data and monolith AI software, we can quickly and reliably understand the relationship between tanks, test parameters and sloshing noise, and quickly and reliably translate into new designs Can predict expected noise.
Through the power of machine learning, Monolith’s highly sophisticated AI platform was able to combine valuable existing acoustic test data, 3D CAD tank sizes and various internal component configurations to produce highly accurate models for fuel spill behavior. , eliminating the need to perform a series. Time and cost consuming tests and complex simulations under multiple parameters.
Dr Richard Ahlfeld, CEO and Founder of Monolith AI, said: : “This innovative application of machine learning enabled Coutex’s visionary engineering team to significantly reduce design time and testing costs, greatly simplifying a very complex process. Among other use cases in your product design work The possibilities of implementing AI technology are very exciting to us, and we look forward to delivering even more spectacular results for Coutex and our automotive OEM customers.”
The powerful machine learning capabilities offered by Monolith’s AI platform can be applied to electric vehicles as well. Coutex engineers are exploring the potential of using monoliths to help streamline the battery pack case crash testing process, reducing development costs and helping the company bring cost- and performance-competitive EV solutions to new markets around the world. is enabled.
More information on monolith solutions can be found here, with more information on Coutex-Textron available here.
