Collegium Helveticum
Switzerland
fellow
Danny van der Haven
2024-2025
Discipline(s)
Computers and intelligent systems; Earth, environmental and climate sciences; Engineering
Theme(s)
Environment, Sustainability & Biodiversity
Fellowship dates
›
Biography
Danny van der Haven (born 1995 in the Netherlands) is a computational and materials scientist. His research focuses on granular materials such as gravel, sand, and powders. His primary interest lies in connecting how the microscopic properties of granular materials, such as the individual grain size, shape, and stiffness, affect their macroscopic behavior. He aims to use this knowledge to improve the properties and sustainability of, e.g., concrete and other materials that use sand as a starting material. By doing this, he hopes to tackle the societal and economic problems that come with our current large-scale usage of, and dependence on, sand.
Danny received his PhD in 2024 from the University of Cambridge (UK). In his doctoral thesis, he worked on improving the compression of pharmaceutical powders into tablets using a combination of experimental and computational techniques. His work has received widespread attention in the pharmaceutical and scientific computing community, giving webinars at Dassault Systemes and Medelpharm. His work on pharmaceutical tablets recently appeared on the front page of the national magazine by the Institute of Materials, Minerals & Mining (IOM3) in the UK.
Research Project
Saving Sand: Upscaling Predictions of Grainy Materials for Sustainability
With a throughput of more than fifty billion tonnes per year, the sand-mining industry significantly impact on our economy, society, and environment. Different types of sand result in various material properties, such as concrete or asphalt. Consequently, the industry relies on tried-and-tested types of sand, often extracted from ecologically vulnerable areas. Our current lack of understanding of granular materials is a significant barrier to achieving current sustainability goals. This project aims to create a general computer model to effectively simulate billions of individual grains of sand, enabling meaningful predictions for dunes, dykes, concrete, and asphalt. Unlike fluids, there is no universal mathematical formulation to perform large-scale continuum simulations of granular materials. While simulating each grain is possible, even supercomputers can handle only a few million grains. This project plans to use local symmetries and coupled discrete and continuum computational methods to develop a large-scale prediction method and explore its applications to current material and sustainability challenges.
Research Interests:
granular materials; computational modelling; sand mining; materials science; sustainability; environmental impact; continuum mechanics; discrete element methods; multiscale modelling; concrete; asphalt; dune dynamics.