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Directorate for Engineering

Engineering Sciences for Modeling, Simulation, Decision-Making and Emerging Technologies

This program has been archived.

CONTACTS

Name Email Phone Room
Ken  P. Chong kchong@nsf.gov (703) 292-8360  545 S  
George  A. Hazelrigg ghazelri@nsf.gov (703) 292-7068  550 S  
James  Mink jmink@nsf.gov   675 S  

 

PROGRAM GUIDELINES

Solicitation  03-505

Important Notice to Proposers

A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG), NSF 13-1, was issued on October 4, 2012 and is effective for proposals submitted, or due, on or after January 14, 2013. Please be advised that, depending on the specified due date, the guidelines contained in NSF 13-1 may apply to proposals submitted in response to this funding opportunity.

Please be aware that significant changes have been made to the PAPPG to implement revised merit review criteria based on the National Science Board (NSB) report, National Science Foundation's Merit Review Criteria: Review and Revisions. While the two merit review criteria remain unchanged (Intellectual Merit and Broader Impacts), guidance has been provided to clarify and improve the function of the criteria. Changes will affect the project summary and project description sections of proposals. Annual and final reports also will be affected.

A by-chapter summary of this and other significant changes is provided at the beginning of both the Grant Proposal Guide and the Award & Administration Guide.

DUE DATES

Archived

SYNOPSIS

This is a continuation of a collaborative research program between the National Science Foundation (NSF) and Sandia National Laboratories (Sandia) that was started in 1997. The objective of this collaborative program is to fund research projects that are focused on advancing the fundamental knowledge base needed to support advanced computer simulations. Advances are needed in the following broad classes of technical development: the fidelity of the simulation models, experimental discovery necessary for the determination of the models and their validations, uncertainty quantification of the resulting computations, and computational techniques for the solution of the simulation models on high performance computing platforms. 



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