Parallel computing for interactions between fluids and flexible structures with application to suspended longline aquaculture farms
The structural dynamics of the aquaculture farms in unsteady flow are essential to assess the performance and resilience of aquaculture farms in environmental change. Moreover, the feedback of the aquaculture farms to the flow is significant for the environment, ecology, and coastal management, such as hydrodynamics impacts, habitat resilience, nutrient transportation, wave attenuation, coastal erosion control, etc. The computational fluid dynamics (CFD) method is used to analyze the interaction between aquaculture farms and the flow. The longline aquaculture farms such as kelp farms and mussel farms are consisting of multiple flexible structures such as mussel droppers and kelp blades. Considering hundreds or thousands of large deformed structures in the fluid-structure interaction (FSI) computing is time-consuming. Therefore, computer science research and parallel computing implementation are essential to make progress on this project. The computer science aspects we initially envision are converting the FSI code to c++ from MATLAB, as well as parallelizing the code. If you have any ideas beyond that, we would love to hear them.
Model Mie scattering and light propagation through a high scattering medium using Monte Carlo simulation
In this project, we will first use numerical approaches to model light scattering off single particles using Monte Carlo simulation. We will obtain results that follow Rayleigh scattering and Mie scattering. The program will then be extended to simulate light propagation in a highly scattering turbid medium like biological tissue which consists of various arrangements of particles and bulk geometry and calculate the light distribution in the medium and on the boundary. The program will eventually be used for imaging tumors in biological tissue, which will be achieved through an inverse problem.
Mycobacterium tuberculosis infected one third of world population and current therapies involve up to 4 antibiotics and 6 months of treatment. Using MTB gene expression data from the main available drugs, KEGG and other databases for pathways and Linear-in-flux-expression (briefly LIFE) methodology, we aim to evaluate the potential effectiveness of drug combination therapies. We can do this by simulating the evolution of metabolites with the LIFE technique.
Another goal is to include hybrid methods to model metabolic pathway changes in MTB due to immune system, drug action, and other environmental conditions. Large scale metabolic and gene-regulation network dynamics will be used to assess drug treatment.
|Cornell Virtual Workshop||Learning||performance-tuning, python, r, matlab, slurm, mpi, cuda, file-transfer, globus||Beginner, Intermediate, Advanced, Expert|
|HPC University||Learning||python, r, matlab, mpi, compiling, debugging, professional-development||Beginner, Intermediate, Advanced, Expert|
|Jetstream-2||Jetstream2 is a transformative update to the NSF’s science and engineering cloud infrastructure and provides 8 petaFLOPS of supercomputing power to simplify data analysis, boost discovery, and…||cloud-open-source, cloud-storage, openstack, ai, machine-learning, tensorflow, science gateway, gpu, nvidia, cuda, jupyterhub, matlab, vnc, containers, singularity|