Bristol-based aviation and technology company Vertical Aerospace has partnered with London-based artificial intelligence software provider Monolith to transform its eVTOL testing and simulation programmes in the hop of improving performance and accelerating time to market.
Flight and ground tests for eVTOL are complex, expensive and time-consuming, typically requiring engineers to spend hundreds of hours validating simulations across tens of thousands of parameters and operating conditions.
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Vertical Aerospace will use Monolith to accelerate development of its VX4 eVTOL aircraft by using AI for new design insights and more efficient test plans. The first project focuses on testing and simulation of the VX4’s supporting pylon structures for ground tests of the propeller and electric motor structural and performance requirements.
Monolith’s Next Test Recommender AI-driven algorithm will provide Vertical Aerospace engineers with a ranked selection of the most impactful tests to run, increasing design space coverage in unknown areas with a more efficient and trustworthy test plan.
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‘Urban air mobility has the potential to revolutionise how we travel, and one of the most promising contributors to this transformation is Vertical’sVX4,’ said Richard Ahlfeld, CEO and founder of Monolith. ‘With Monolith, Vertical will model complex systems faster and accelerate test campaigns, enabling the company to learn more about design performance while reducing development and testing time.’
‘Transforming how the world moves requires constant innovation,’ said David King, chief engineer at Vertical Aerospace. ‘Collaborating with Monolith allows us to harness cutting-edge AI technology to streamline our testing processes, enabling us to focus on the most impactful areas and accelerate the VX4’s journey to market. By integrating Monolith’s tools, we can enhance our engineering precision, reduce timelines and continue setting the benchmark for the eVTOL industry.’
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Monolith has a proven track record in aerospace engineering following recent projects with Airbus and BAE Systems on aircraft and drones. According to the company, it’s already democratising AI for engineering with its bespoke SaaS platform, which uses no-code, machine-learning software, giving domain experts the power to leverage existing, valuable testing datasets for their product development. The platform analyses and learns from this information, using it to generate accurate, reliable predictions that enable engineering teams to reduce costly, time-intensive prototype testing programmes.