Akselos

Akselos is a Swiss company which provides an engineering simulation platform based on reduced-basis finite-element analysis.[1] The platform is used to create digital twins of energy infrastructures in order to improve their design, maintenance, reliability and lifetime.[2][3]

Akselos SA
TypePrivately held company
IndustrySimulation software
Founded2012
FounderThomas Leurent, David Knezevic, Phuong Huynh
Headquarters
Lausanne
,
Switzerland
ServicesDigital twins of energy infrastructure
Websitewww.akselos.com

The company is headquartered in Lausanne at the EPFL Innovation Park,[4] and has offices in Boston and Vietnam.[5] Thomas Leurent is the current Akselos CEO.[6]

Company history

In 2011, technology from the Massachusetts Institute of Technology (MIT) project "High resolution simulations for system analysis" was spun out into Akselos.[7] In 2012, the company was founded by David Knezevic, Thomas Leurent and Phuong Huynh, who were involved in the initial research.[8][9]

Akselos raised a first round of investment of USD 2.2 million in 2016.[10] A second round of investment of USD 10 million led by Innogy Ventures and Shell Ventures was raised in 2018.[11]

In 2020, Akselos was selected as a World Economic Forum Technology Pioneer.[12]

Reduced-basis finite-element analysis technology

Between 2000 and 2011, reduced-basis finite-element analysis was developed in research laboratories from different universities, including MIT and Pierre and Marie Curie University.[13][14][15][16] Akselos received a license from the MIT Technology licensing office on the development of the technology.[17] Later on, Akselos collaborated with EPFL for the development of a simulation software for critical infrastructures.[4]

The technology allows its user to perform simulations on a 3D physics-based digital model of an energy infrastructure, called a digital twin.[18] To build the digital twin, all available data on the energy infrastructure asset needs first to be collected. The digital twin then allows the user to monitor reliability as well as predict potential failures and may help to extend the lifetime of assets.[18] It is said by Akselos technology users that in some applications, the technology can be a thousand times faster than other methods.[19] According to the company, the technology provides more details and accuracy than conventional finite element analysis when modelling large assets.[20]

References
  1. "Extending simulation technology from the design world into the operational world". Oilfield Technology. 2019-06-17. Retrieved 2020-06-28.
  2. Sharma, Parta (2017-10-01). "'Digital twin' concept underpins successful digitization strategy". Offshore. Retrieved 2020-06-28.
  3. Leprince-Ringuet, Daphne (2019-10-15). "This power station the size of a cathedral is getting a digital twin". ZDNet. Retrieved 2020-06-28.
  4. Chavanne, Yannick (2018-10-08). "10 millions pour les jumeaux numériques du fournisseur vaudois Akselos". www.ictjournal.ch (in French). Retrieved 2020-12-10.
  5. Matheson, Rob (2014-08-11). "Unlocking the potential of simulation software". MIT News. Retrieved 2020-06-28.
  6. Cassauwers, Tom (2019-11-15). "How digital 'twins' are guiding the future of maintenance and manufacturing". Techxplore. Retrieved 2020-06-28.
  7. "High resolution simulations for system analysis | MIT Deshpande Center". deshpande.mit.edu. Retrieved 2020-06-28.
  8. Ganapati, Priya (2010-08-20). "Android Phones Can Substitute for Supercomputers". Wired. ISSN 1059-1028. Retrieved 2020-06-29.
  9. "The Innovation Space - Akselos". CFMS. Retrieved 2020-06-28.
  10. "Akselos closes CHF2.2 million financing round Startupticker.ch | The Swiss Startup News channel". www.startupticker.ch. 2016-09-14. Retrieved 2020-06-28.
  11. "Innogy and Shell Support Digital Twin Tech". Offshore Wind. 2018-10-02. Retrieved 2020-06-28.
  12. "World Economic Forum Technology Pioneers 2020".
  13. Leurent, Thomas (2001). Reduced basis output bounds for linear elasticity : application to microtruss structures (Master thesis). Massachusetts Institute of Technology.
  14. Veroy, Karen; Patera, Anthony T. (2003-11-03). "Reduced-Basis Approximation of the Viscosity-Parametrized Incompressible Navier-Stokes Equation: Rigorous A Posteriori Error Bounds". MIT Technical Report.
  15. Barrault, Maxime; Maday, Yvon; Nguyen, Ngoc Cuong; Patera, Anthony T. (2004-11-01). "An 'empirical interpolation' method: application to efficient reduced-basis discretization of partial differential equations". Comptes Rendus Mathématique. 339 (9): 667–672. doi:10.1016/j.crma.2004.08.006. ISSN 1631-073X.
  16. Grepl, Martin A.; Maday, Yvon; Nguyen, Ngoc C.; Patera, Anthony T. (2007-05-01). "Efficient reduced-basis treatment of nonaffine and nonlinear partial differential equations". ESAIM: Mathematical Modelling and Numerical Analysis. 41 (3): 575–605. doi:10.1051/m2an:2007031. ISSN 0764-583X.
  17. "Akselos". MIT Innovation Initiative. Retrieved 2020-06-28.
  18. Vella, Heidi (2020-04-20). "Inside the world's first digital twin of a hydroelectric power station". Power Technology. Retrieved 2020-06-28.
  19. "Digital twin of UAV provides predictive maintenance". eeNews Europe. 2019-12-06. Retrieved 2020-06-28.
  20. Venables, Mark (2018-08-26). "Digital Twins Provide A Window Into The Future For Ageing Assets". Forbes. Retrieved 2020-06-28.
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