Appendix D

Example of Peer Advice During the Planning Phase of R&D

This appendix describes a successful example of an assessment of program content during the program planning phase. This assessment occurred when the Army Research Laboratory (ARL) involved invited experts during the formulation of a request for proposal for two multiscale modeling programs.

The ARL wished to initiate a complex, multi-organizational attack on problems deemed critical to future Army needs in areas requiring advanced materials. Influenced by developments in this field as reflected in the Defense Advanced Research Project Agency’s Accelerated Insertion of Materials (DARPA AIM) program of the early 2000s and many subsequent efforts by other agencies, the ARL elected to focus on the development of computational tools to assist the effort. This multiscale modeling approach had recently been codified in a report of the National Research Council (NRC) on integrated computational materials engineering1 and supported by the Office of Science and Technology Policy (OSTP) through its Materials Genome Initiative.

The ARL scoped its needs in two areas, electronics and high-speed deformation, and developed a conceptual framework for addressing these areas. Broadly speaking, the program envisioned was to include both extramural and intramural entities working in partnership. The funding of the extramural entities would arise from a competition stimulated through the conventional process of the release of a program announcement. The intramural programs would span the areas of structural materials and functional materials and would include extensive computational expertise. The centers of excellence for these three areas are located in three different directorates in the ARL, ensuring that a cross-organizational effort would be required.

Of great significance to the consideration of best practices was the inclusion of extramural assessment in the development of the program announcement of funding opportunity. Members of the NRC panels that conduct the usual peer assessments of the ARL were invited to participate in the public forum that preceded finalization of the call for proposals. This group of invited visitors offered, as individuals rather than as representatives of the NRC panels, observations that were deemed valuable by ARL management and that led directly to modification of the program scope and characterization in the final call for proposals. The selection of experts from a known and highly credible set of peer reviewers was a key factor in the successful planning activity described here—the experts were already familiar with those elements of the intramural research that would be impacted by the planned program; they knew the overall mission, structure, and operational procedures of the ARL and could assess how the new proposed activities might fit. Because these individuals were already well known and respected by ARL senior management, their advice perhaps carried with it more credibility than might have been accorded an ad hoc group of strangers, no matter what their credentials. To protect against conflict of interest, no member of the advisory group nor their colleagues were permitted to submit proposals for the multiscale modeling work.

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1 National Research Council, 2008. Integrated Computational Materials Engineering: A Transformational Discipline for Improved Competitiveness and National Security. The National Academies Press, Washington, D.C.



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Appendix D Example of Peer Advice During the Planning Phase of R&D This appendix describes a successful example of an assessment of program content during the program planning phase. This assessment occurred when the Army Research Laboratory (ARL) involved invited experts during the formulation of a request for proposal for two multiscale modeling programs. The ARL wished to initiate a complex, multi-organizational attack on problems deemed critical to future Army needs in areas requiring advanced materials. Influenced by developments in this field as reflected in the Defense Advanced Research Project Agency's Accelerated Insertion of Materials (DARPA AIM) program of the early 2000s and many subsequent efforts by other agencies, the ARL elected to focus on the development of computational tools to assist the effort. This multiscale modeling approach had recently been codified in a report of the National Research Council (NRC) on integrated computational materials engineering1 and supported by the Office of Science and Technology Policy (OSTP) through its Materials Genome Initiative. The ARL scoped its needs in two areas, electronics and high-speed deformation, and developed a conceptual framework for addressing these areas. Broadly speaking, the program envisioned was to include both extramural and intramural entities working in partnership. The funding of the extramural entities would arise from a competition stimulated through the conventional process of the release of a program announcement. The intramural programs would span the areas of structural materials and functional materials and would include extensive computational expertise. The centers of excellence for these three areas are located in three different directorates in the ARL, ensuring that a cross-organizational effort would be required. Of great significance to the consideration of best practices was the inclusion of extramural assessment in the development of the program announcement of funding opportunity. Members of the NRC panels that conduct the usual peer assessments of the ARL were invited to participate in the public forum that preceded finalization of the call for proposals. This group of invited visitors offered, as individuals rather than as representatives of the NRC panels, observations that were deemed valuable by ARL management and that led directly to modification of the program scope and characterization in the final call for proposals. The selection of experts from a known and highly credible set of peer reviewers was a key factor in the successful planning activity described here--the experts were already familiar with those elements of the intramural research that would be impacted by the planned program; they knew the overall mission, structure, and operational procedures of the ARL and could assess how the new proposed activities might fit. Because these individuals were already well known and respected by ARL senior management, their advice perhaps carried with it more credibility than might have been accorded an ad hoc group of strangers, no matter what their credentials. To protect against conflict of interest, no member of the advisory group nor their colleagues were permitted to submit proposals for the multiscale modeling work. 1 National Research Council, 2008. Integrated Computational Materials Engineering: A Transformational Discipline for Improved Competitiveness and National Security. The National Academies Press, Washington, D.C. 56