Historically, universities have had a close relationship with NNSA National Laboratories. In fact, Los Alamos and Lawrence Livermore have been operated for NNSA by the University of California for many years. The mission of the Defense Programs laboratories is focused on Science-Based Stockpile Stewardship, and ASC and the universities share a common and critical interest in making that vision a reality. The success of ASC depends on the ability to demonstrate that simulations can credibly be used to replace nuclear testing as a means of ensuring stockpile confidence. Universities recognize the challenge in developing new kinds of simulation tools across a number of related disciplines to accomplish this mission.

About ASC and the Universities

Collaborations with universities involve training, recruiting, and working with top researchers in key disciplines required by stockpile stewardship. These partnerships help establish and validate large-scale, multidisciplinary research in modeling and simulation. Collaborating universities are integrated into program activities that are intended to challenge existing notions about what is possible in science-based modeling and simulation. Students gain unique experience using state-of-the-art equipment and the associated resources of three national laboratories. After graduation, the opportunity may exist to join the laboratory teams providing cutting-edge technologies to ensure the nation’s security. Students and faculty are invited to explore the possibilities with ASC.

Alliances

Both the ASC Academic Strategic Alliance Program (ASAP) and the Predictive Science Academic Alliance Program (PSAAP) engaged the U.S. academic community in making significant advances in predictive modeling and simulation technologies.  Research conducted through these partnerships contributed to the knowledge base required to demonstrate the capabilities of predictive modeling and simulation across a broad spectrum of science and engineering applications using some of the most powerful computers in the world.  Both the ASAP and PSAAP encouraged collaboration between the national laboratories and universities in advancing multi-disciplinary predictive modeling and simulation technologies, and educating and recruiting individuals with skills critical to the ASC Program.

Both ASAP and PSAAP involved demonstrating the power of simulation to build models of large-scale complex multi-physics systems requiring ASC-class computers.  The difference is that PSAAP focused more strongly on integrating modeling with predictive science disciplines of verification and validation (V&V was also an increasing focus of the later stage of the ASAP program) and uncertainty quantification.  The goal was both to further these disciplines and more accurately identify and bound the uncertainty of predictions made by simulations. 

ASC Academic Strategic Alliance Program (1997-2010)

• California Institute of Technology, “Center for Simulating the Dynamic Response of Materials”
• Stanford University, “Center for Integrated Turbulence Simulations”
• University of Chicago, “Center for Astrophysical Thermonuclear Flashes”
• University of Illinois at Urbana-Champaign, “Center for Simulation of Advanced Rockets”
• University of Utah, “Center for the Simulation of Accidental Fires & Explosions”

ASC Predictive Science Academic Alliance Program (2008-2013)

• California Institute of Technology, “Center for Predictive Modeling and Simulation of High-Energy Density Dynamic Response of Materials”
• Purdue University, “Center for Prediction of Reliability, Integrity and Survivability of Microsystems”
• Stanford University, “Predictive Simulations of Multi-Physics Flow Phenomena, with Application to Integrated Hypersonic Systems”
• University of Michigan at Ann Arbor, “Center for Radiative Shock Hydrodynamics”
• University of Texas at Austin, “Center for predictive Engineering and Computational Science” 

ASC Predictive Science Academic Alliance Program (2014-2019)

The goal of this program is to support fundamental science at U.S. universities in the emerging field of predictive science.  Predictive Science is the development and application of verified and validated computational simulations, in a high-performance computing (HPC) environment, to predict properties and dynamics of complex systems, with quantified uncertainty.  The centers are either Multidisciplinary Simulation Centers (MSC) or Single-Discipline Centers (SDC) solving a problem that advances basic science/engineering; verification and validation/uncertainty quantification; and contributing towards achieving effective exascale computing, to demonstrate predictive science in a HPC environment.  The following are the current centers:

• University of Utah, Salt Lake City, Utah, “The Uncertainty Quantification-Predictive Multidisciplinary Simulation Center for High Efficiency Electric Power Generation with Carbon Capture,” an MSC
• University of Illinois-Urbana-Champaign, Champaign, Ill., “Center for Exascale Simulation of Plasma-Coupled Combustion,” an MSC
• Stanford University, Stanford, Calif., “Predictive Simulations of Particle-laden Turbulence in a Radiation Environment,” an MSC
• University of Florida, Gainesville, Fla., “Center for Compressible Multiphase Turbulence,” an SDC
• Texas A&M University, College Station, Texas, “Center for Exascale Radiation Transport,” an SDC
• University of Notre Dame, Notre Dame, Ind., “Center for Shock Wave-processing of Advanced Reactive Materials,” an SDC

Predictive Science Academic Alliance Program

The primary goal of the Predictive Science Academic Alliance Program (PSAAP) is to establish validated, large-scale, multidisciplinary, simulation-based “Predictive Science” as a major academic and applied research program. The Program Statement lays out the goals for a multiyear program as follow-on to the present ASC Alliance program. This “Predictive Science” is the application of verified and validated computational simulations to predict properties and dynamics of complex systems. This process is potentially applicable to a variety of applications, from nuclear weapons effects to efficient manufacturing, global economics, to a basic understanding of the universe. Each of these simulations requires the integration of a diverse set of disciplines; each discipline in its own right is an important component of many applications. Success requires both software and algorithmic frameworks for integrating models and code from multiple disciplines into a single application and significant disciplinary strength and depth to make that integration effective.

For more information, please visit www.sandia.gov/psaap.