A broad range of projects are being carried out in the areas of energy and sustainability, including improving efficiency in combustion and energy systems, renewable energy, pollution abatement, hydrogen utilization, fuel cells, carbon capture and sequestration, sustainable chemical processes, and design of energy efficient buildings.
Computational research in nanoscience and materials engineering spans orders of magnitude in time and length scales, ranging from fundamental studies of materials at the atomic level to designing materials with tailored properties on the micron length scale to simulating properties of granular materials on the millimeter length scale, to materials and lifecycle issues associated with macroscale systems.
High-performance computing plays an integral role in emerging areas of medicine and biology. At the smallest scale, medical and biological research deals with molecular interactions, e.g., modeling of proteins, and enzymes. Modeling of subcellular assemblies, such as ion channels and cell membranes, involves modeling of systems of biomolecules. At still larger scales, entire cellular systems are modeled.
The use of high-performance computing to tackle important problems in public health, including epidemic control, behavioral dynamics, and health systems, is a relatively new endeavor. Pitt is playing a leadership role in this new field.
Computer modeling is playing an increasingly important role in economic forecasting and in predicting human behavior in response to various economic contingencies. Pitt researchers are working to develop numerical methods capable of converting theoretical models into statistical models capable of quantifying predicted reactions to various contingencies. The ultimate goal is to guide policy decisions regarding, for example, social security reform, credit-market interventions, etc.
Advanced visualization methods are essential in the modeling of complex systems. Modern visualization research involves the development of new techniques to blend modeling, simulation, visualization, and analysis of data into a seamless loop. The loop provides computational steering and helps guide investigations.
Many other areas within the University of Pittsburgh utilize high-performance computing to make advances in research. Examples include high-energy physics, astronomy, and geology.