The ASC Predictive Science Academic Alliance Program (PSAAP) centers focus on the emerging field of predictive science—the application of verified and validated computational simulations to predict the behavior of complex systems where routine experiments are not feasible. The centers focus on unclassified applications of interest to the National Nuclear Security Administration (NNSA) and its three national laboratories: LLNL, LANL, and SNL. The PSAAP centers develop not only the science and engineering models and software for their large-scale simulations but also pursue advanced computer science developments needed to enable such sophisticated simulations on the next generation of computing platforms. They are also integrating state-of-the-art practices in verification and validation (V&V) and uncertainty quantification (UQ) into their integrated simulation plans so that precise statements can be made about the degree of confidence they have in their simulation-based predictions.
Recognizing the need for a healthy pipeline of top graduate students in science and technology fields, which is crucial to the success of ASC, two complementary graduate fellowship programs, both administered by the Krell Institute, are supported.
PSAAP II Centers
- University of Utah: The Carbon-Capture Multidisciplinary Simulation Center
- University of Ilinois, Urbana-Champaign: Center for Exascale Simulation of Plasma-Coupled Combustion
- Stanford University: Predictive Simulations of Particle-laden Turbulence in a Radiation Environment
- University of Florida: Center for Compressible Multiphase Turbulence
- Texas A&M University: Center for Exascale Radiation Transport
- University of Notre Dame: Center for Shock Wave Processing of Advanced Reactive Materials
Ana Kupresanin, Lawrence Livermore National Laboratory (kupresanin1 [at] llnl.gov)
Fernando Grinstein, Los Alamos National Laboratory (fgrinstein [at] lanl.gov)
John Feddema, Sandia National Laboratories (jtfedde [at] sandia.gov)
Refer to the Alliances archive for historical information.