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Title: Advanced Simulation and Computing Fiscal Year 2011-2012 Implementation Plan, Revision 0.5

Abstract

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering (D&E) programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC ismore » focused on increasing its predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality, and scientific details); to quantify critical margins and uncertainties; and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model from one that was very successful in delivering an initial capability to one that is integrated and focused on requirementsdriven products that address long-standing technical questions related to enhanced predictive capability in the simulation tools.« less

Authors:
 [1];  [2];  [3];  [4]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. National Nuclear Security Administration (NNSA), Washington, DC (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1124856
Report Number(s):
LLNL-TR-454593
DOE Contract Number:  
W-7405-ENG-48
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUMM MECHANICS, GENERAL PHYSICS; 97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE

Citation Formats

McCoy, Michel, Phillips, Julia, Wampler, Cheryl, and Meisner, Robert. Advanced Simulation and Computing Fiscal Year 2011-2012 Implementation Plan, Revision 0.5. United States: N. p., 2010. Web. doi:10.2172/1124856.
McCoy, Michel, Phillips, Julia, Wampler, Cheryl, & Meisner, Robert. Advanced Simulation and Computing Fiscal Year 2011-2012 Implementation Plan, Revision 0.5. United States. doi:10.2172/1124856.
McCoy, Michel, Phillips, Julia, Wampler, Cheryl, and Meisner, Robert. Mon . "Advanced Simulation and Computing Fiscal Year 2011-2012 Implementation Plan, Revision 0.5". United States. doi:10.2172/1124856. https://www.osti.gov/servlets/purl/1124856.
@article{osti_1124856,
title = {Advanced Simulation and Computing Fiscal Year 2011-2012 Implementation Plan, Revision 0.5},
author = {McCoy, Michel and Phillips, Julia and Wampler, Cheryl and Meisner, Robert},
abstractNote = {The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering (D&E) programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality, and scientific details); to quantify critical margins and uncertainties; and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model from one that was very successful in delivering an initial capability to one that is integrated and focused on requirementsdriven products that address long-standing technical questions related to enhanced predictive capability in the simulation tools.},
doi = {10.2172/1124856},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2010},
month = {9}
}

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