FRIEDMAN RESEARCH CORP — Department of Defense SBIR Phase I: AF192-062
FRIEDMAN RESEARCH CORP — SBIR Phase I award from Department of Defense.
Phase I SBIR feasibility signal
- Phase I awards fund proof-of-concept work. For capture teams, they mark early interest from Department of Defense in a technical approach.
- Watch for Phase II follow-ons from the same firm/topic family — that conversion path is where budgets and transition pressure rise.
- Obligated amount $149,908. Cross-check similar awards in the same agency and technology tags for going-rate context.
- Topic code AF192-062 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $149,908
- Agency
- Department of Defense · Air Force
- Program / Phase
- SBIR · Phase I
- Topic
- AF192-062
- Solicitation
- 19.2
- NAICS
- —
- Place of performance
- TX
- Period
- 2019-11-07 → 2020-11-07
Description
The result of the project will be an evidence-based technical specification and guidelines for evaluating the strain distribution in a Finite Element simulation to predict real-world failure in landing gear components. This will be accomplished through a coordinated series of material characterization tests, component level tests, and Finite Element sensitivity studies using highly-validated models. Novel analysis techniques will allow for the quantification of spatially and temporally resolved strain values and precise characterization of material failure. The detailed characterization of strain and material failure in the physical tests will provide a benchmark from which to compare FE model response. The sensitivity of FE strain characteristics on FE model parameter definition will be evaluated to understand how they affect the predicted results. The FE model strain characteristics (magnitude, location, gradient, “hot spotâ€Â size) will be compared to the known physical failure response of the material. The relationship between the two will be quantified with confidence intervals that take into account the sensitivity of the model to select FE parameters. This relationship will be able to predict the real-world effects from the FE result. Concurrently a preliminary business cases analysis will be conducted through discussions with industry and literature review.