Akselos has succeeded in developing next-generation software for simulating large-scale engineering systems. Engineering simulation software is a multi-billion dollar industry, but conventional methods such as Finite Element Analysis (FEA) are very time-consuming and computationally intensive. Akselos’ technology on the other hand breaks through these barriers and provides simulation results for large-scale systems in seconds.
The technology is based on over 12 years of research at MIT, and leverages new mathematical methods as well as massively parallel high-performance computing deployment on the cloud. The software provides results up to 1000x faster than with current best-in-class software. This enables a paradigm shift in how engineers can use simulations in the design/analysis process. The Akselos software could essentially benefit mining, oil & gas and power systems industries.
With its technology, Akselos aims to make 3D simulations more accessible worldwide to promote efficient engineering design, says David Knezevic, Akselos’ chief technology officer, who co-founded the startup with former MITians, Phuong Huynh and Thomas Leurent.
“We’re trying to unlock the value of simulation software, since for many engineers current simulation software is far too slow and labor-intensive, especially for large models,” Knezevic says. “High-fidelity simulation enables more cost-effective designs, better use of energy and materials, and generally an increase in overall efficiency.”
Akselos’ software runs on a novel technique called the “reduced basis (RB) component method,” co-invented by Anthony Patera, the Ford Professor of Engineering at MIT, and Knezevic and Huynh.
This technique merges the concept of the RB method — which reproduces expensive FEA results by solving related calculations that are much faster — with the idea of decomposing larger simulations into an assembly of components.
“We developed a component-based version of the reduced basis method, which enables users to build large and complex 3D models out of a set of parameterized components,” Knezevic says.
In a demonstration, a mining company was able to create modified simulation of shiploader infrastructure in few minutes after adding the inspection report by on-site inspectors.
“The software also allows people to model the machinery in its true state,” Knezevic says. “Often infrastructure has been in use for decades and is far from pristine — with damage, or holes, or corrosion — and you want to represent those defects,” Knezevic says. “That’s not simple for engineers today, since with other software it’s not feasible to simulate large structures in full 3D detail.”
Ultimately, pushing the data to the cloud has helped Akselos, by leveraging the age-old tradeoff between speed and storage: By storing and reusing more data, algorithms can do less work and hence finish more quickly.
“These days, with cloud technology, storing lots of data is no big deal. We store a lot more data than other methods, but that data, in turn, allows us to go faster, because we’re able to reuse as much precomputed data as possible,” said Knezevic.
Image courtesy of Akselos