Modelling & Simulation






















The development of new materials depends on our ability to simulate and optimize their structure, properties and processing. At UBC, researchers use digital models to design, test and manufacture new advanced metals, composites and biomaterials for multiple applications, greatly reducing the cost, risk and time to bring novel advanced materials to market.

Computational modelling and simulation are powerful tools to better understand and improve every step of the manufacturing system from the material to the end product. At UBC, the team has historic strengths in deterministic, physics-based modelling but recently have expanded to theory guided machine learning (probabilistic machine learning) and are now investigating quantum computing approaches to materials modelling and product optimization.


  • Improved machining productivity: Computer simulations of complex machining systems such as those used to make critical jet engine parts led to substantial machining productivity improvements and up to 85% cost savings. LEARN MORE →
  • Building the Composites Factory of the Future: The Digital Learning Factory combines sensors and big data analytics from a physical aerospace factory with a virtual factory based on physics-based simulations to better understand, control and optimize the production of advanced aerospace composites structures. LEARN MORE →
  • Stronger, lighter, lower-cost wheels: Development of mathematical models to optimize the design of low-pressure die-casting of aluminium alloys led to Toyota transferring its die design operations from Japan to BC.  LEARN MORE →
  • Accelerated material discovery: A self-driving laboratory powered by artificial intelligence and robotics, named 'Ada', can optimize properties of thin film materials for use in clean energy applications. LEARN MORE →