Intelligent Twin Machine Solver
Lead Participant:
TIN ARM ENGINEERING LTD
Abstract
Tin Arm Engineering has developed a cloud-based platform that allows users to run multiphysics simulations in parallel through an API or its browser-based user interface.
The Linked Tool Chain (LTC) aims to provide scalable, high-performance computing resources, accessible from anywhere, to facilitate complex simulations across various physical domains.
LTC allows existing geometry/mesh generators, multiphysics solvers and post-processing tools, both open and closed-source, to be chained together into domain-specific simulation applications; a digital twin of the item under investigation.
Tin Arm's core expertise lies in the advanced design of energy-efficient electric powertrains for automotive and transportation. In line with this, our first LTC application, MotorTwin, focuses on designing and manufacturing electrical machines. MotorTwin allows users to carry out the Electromagnetic, Mechanical and Thermal simulations necessary to progress an electrical machine rapidly into cost-effective production.
In this next project, we will apply a variety of Model Order Reduction (MOR) and Machine Learning (ML) approaches to extend MotorTwin into a system geared towards rapid design and evaluation of advanced electrical systems.
The Intelligent Twin Machine Solver, combined with LTC's ability to run hundreds of simulations in parallel, will reduce the cost and time-to-production of electrical machine design.
The Linked Tool Chain (LTC) aims to provide scalable, high-performance computing resources, accessible from anywhere, to facilitate complex simulations across various physical domains.
LTC allows existing geometry/mesh generators, multiphysics solvers and post-processing tools, both open and closed-source, to be chained together into domain-specific simulation applications; a digital twin of the item under investigation.
Tin Arm's core expertise lies in the advanced design of energy-efficient electric powertrains for automotive and transportation. In line with this, our first LTC application, MotorTwin, focuses on designing and manufacturing electrical machines. MotorTwin allows users to carry out the Electromagnetic, Mechanical and Thermal simulations necessary to progress an electrical machine rapidly into cost-effective production.
In this next project, we will apply a variety of Model Order Reduction (MOR) and Machine Learning (ML) approaches to extend MotorTwin into a system geared towards rapid design and evaluation of advanced electrical systems.
The Intelligent Twin Machine Solver, combined with LTC's ability to run hundreds of simulations in parallel, will reduce the cost and time-to-production of electrical machine design.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| TIN ARM ENGINEERING LTD | £46,000 | £ 46,000 |
Participant |
||
| INNOVATE UK |
People |
ORCID iD |
| Chris Wallis (Project Manager) |