My research in the Mechanical Engineering Department at the Johns Hopkins University lies at the intersection of physics, mathematics, and computer science. I work at the Maryland Advanced Research Computing Center, where I develop new tools to support research initiatives across multiple disciplines from molecular dynamics to global climate modeling.
Particle-resolved flow simulation
I am the lead developer of an open-source disperse two-phase flow solver called Bluebottle. With applications ranging from forecasting dust storms to designing more efficient fluidized bed reactors, we often find systems of fluids (such as air or water) entraining particles (like sand or biomass) in both nature and industry.
Between the vast ranges of length and time scales and the extreme complexity involved in such two-phase flow systems, there remains much to learn about their behavior in order to accurately model them. The simulation tool that I have developed, Bluebottle, focuses on a small piece of a real-world disperse two-phase flow system to, with high accuracy, simulate the physics behind thousands of fluidized particles. It exclusively utilizes graphics processing units (GPUs) to solve the incompressible Navier-Stokes equations that govern fluid flow in the presence of numerically well-resolved particles. Learn more about my Ph.D. dissertation here.
Publications
- D.P. Willen, A.J. Sierakowski, G. Zhou, and A. Prosperetti, Continuity waves in resolved-particle simulations of fluidized beds, Phys. Rev. Fluids, 2 (2017) 114305, doi.org/10.1103/PhysRevFluids.2.114305
- Y. Wang, A.J. Sierakowski, and A. Prosperetti, Fully-resolved simulation of particulate flows with particles-fluid heat transfer, J. Comput. Phys., 350 (2017) 638-656, doi.org/10.1016/j.jcp.2017.07.044
- A.J. Sierakowski, GPU-centric resolved-particle disperse two-phase flow simulation using the Physalis method, Comput. Phys. Comm., 207 (2016) 24-34 doi.org/10.1016/j.cpc.2016.05.006
- A.J. Sierakowski & A. Prosperetti, Resolved-particle simulation by the Physalis method: Enhancements and new capabilities, J. Comput. Phys. 309 (2016) 164-184, doi.org/10.1016/j.jcp.2015.12.057
