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NSFEXP PROG TO STIM COMP RES

SBIR Phase I: Designing the Future: Generative Configuration Design

Completed
Institution
STARGAZER DESIGN TECHNOLOGIES INC, NH
Principal investigator
Emilio Botero
Funding
$275K
Duration
2024–2025

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Abstract

This Small Business Innovation Research (SBIR) Phase I project develops generative artificial intelligence (AI) algorithms that assist engineers and designers in developing new products. As a sustainable Software-as-a-Service (SaaS) business model, engineers can design more quickly than “brainstorming” and thereby discover novel, high performing solutions. For the aerospace and defense sector, this technology will be used to quickly design innovative solutions to counter growing threats from potential near-peers. The short design cycles lead to less wasted effort in reengineering solutions to fit within rapidly changing program requirements. The technology may also be used to decarbonize air travel. By lowering the barriers to entry for design engineering, this project will enable a broader cross-section of the American populace to engage with design, engineering, product development, and invention. The results of this project can accelerate the promotion of safer, more efficient, and more cost-effective products in various industries. This Small Business Innovation Research (SBIR) Phase I project advances the state of the art in generative artificial intelligence, particularly regarding algorithms’ ability to engage with complex non-media datatypes and develop methods that can generate novel cyber-physical system architectures in the absence of large pre-existing databases. Currently, computer-aided engineering software excels at rendering precise analytical results for the dynamics of a given system architecture but offers little to no information as to the variety of architectures that can satisfy performance requirements. Simultaneously, generative AI currently excels at generating media products without the constraint of performance, physics, or logic. This project will develop a framework for incorporating simulation-based physics information into generative algorithms to enable engineers to create physically realizable systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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EXP PROG TO STIM COMP RESDirectorate for Technology, Innovation, and PartnershipsARTIFICIAL INTELL & COGNIT SCISBIR Phase Igenerativebusinessbusiness innovationinnovation researchgenerative artificialresearch phaseengineerstechnology used

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