Structures Uniquely Resolved to Guarantee Endurance (SURGE)

Closed Posted

Opportunity number
HR001124S0018
Agency
Applications due
Award size
Not on record

Opportunity facts

Assistance listings
Funding instrument
Cooperative Agreement, Procurement Contract
Category
  • Science and Technology and other Research and Development
Eligible applicants
  • Other
Full announcement

Opportunity details come from Grants.gov. Updated .

About this opportunity

The Defense Advanced Research Projects Agency (DARPA) is soliciting innovative proposals for the Structures Uniquely Resolved to Guarantee Endurance (SURGE) program. SURGE aims to develop methods to predict the useful life of additively manufactured (AM) metal parts directly from data collected during the manufacturing process. The proposed research must investigate approaches that enable revolutionary advances in distributed AM capability, rather than evolutionary improvements. Eligible applicant types include entities beyond just educational institutions and nonprofits. Funding instruments may include cooperative agreements and procurement contracts. Proposals will be evaluated based on criteria such as technical merit, feasibility, and potential impact. The proposal deadline is July 1, 2024.

The SURGE program is funded under DARPA's Research and Technology Development federal grant program (CFDA 12.910), which supports basic, applied, and advanced research with potential military or dual-use applications. DARPA anticipates making multiple awards for this solicitation, but has not specified a total budget or award values. The program has a 24-month base effort followed by an optional 24-month follow-on phase, with the research and development activities taking place at the performer's facilities.

Synopsis

The Defense Advanced Research Projects Agency (DARPA) is soliciting innovative proposals to rethink and accelerate distributed additive manufacturing of critical structural parts. Structures Uniquely Resolved to Guarantee Endurance (SURGE) will develop methods to predict part life directly from data collected during additive manufacturing (AM) in a way that is transferable across disparate machines, materials, locations, and geometries. Research will merge in-situ sensing technologies, process modeling, and microstructure-based fatigue life methods to quantify the useful life of manufactured hardware. Predictions will be backed by extensive experimental validation demonstrating a new paradigm for efficient part qualification. Proposed research must investigate innovative approaches that enable revolutionary advances in distributed AM capability. Specifically excluded is research that primarily results in evolutionary improvements to the existing state of practice.

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