Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 56
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
