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2333122

Project Grant

Overview

Grant Description
Sbir Phase I: Designing the Future: Generative Configuration Design -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.- subawards are not planned for this award.
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23515
Place of Performance
Chester, New Hampshire 03036-4192 United States
Geographic Scope
Single Zip Code
Analysis Notes
Amendment Since initial award the End Date has been extended from 09/30/24 to 06/30/25.
Stargazer Design Technologies was awarded Project Grant 2333122 worth $274,644 from in January 2024 with work to be completed primarily in Chester New Hampshire United States. The grant has a duration of 1 year 5 months and was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships. The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.

SBIR Details

Research Type
SBIR Phase I
Title
SBIR Phase I: Designing the Future: Generative Configuration Design
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.
Topic Code
AI
Solicitation Number
NSF 23-515

Status
(Complete)

Last Modified 6/20/25

Period of Performance
1/15/24
Start Date
6/30/25
End Date
100% Complete

Funding Split
$274.6K
Federal Obligation
$0.0
Non-Federal Obligation
$274.6K
Total Obligated
100.0% Federal Funding
0.0% Non-Federal Funding

Activity Timeline

Interactive chart of timeline of amendments to 2333122

Transaction History

Modifications to 2333122

Additional Detail

Award ID FAIN
2333122
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
H4TSQF9FQNM4
Awardee CAGE
9FUN5
Performance District
NH-01
Senators
Jeanne Shaheen
Margaret Hassan
Modified: 6/20/25