2348512
Project Grant
Overview
Grant Description
Sttr Phase I: AI- and laser-assisted targeted noise control -the broader/commercial impact of this small business technology transfer (STTR) Phase I project enables engineers to identify the root cause and weak spots of noise within a structure and apply local fixes rather than global treatments to mitigate noise emission.
Employing the proposed AI and laser-assisted targeted noise control technology will enable the design and implementation of quieter and lighter metal structures. Studies have exhibited a direct correlation between weight reduction and CO2 emission.
Statistics have revealed that for every 1 kg of steel used, 2.75 kg of CO2 will be emitted, and every 1 kg of aluminum used, 8.25 kg of CO2 will be released. In general, reducing 1% material weight in an automobile will decrease 1.25% CO2 emission.
Our preliminary test results showed that using the proposed technology, sound transmission loss through a steel panel was increased, but its overall weight reduced by 38%. Therefore, this technology is not only cost-effective in mitigating noise issues, but also ideal for sustainability by simultaneously reducing structural weight and CO2 emissions.
This small business technology transfer (STTR) Phase I project is expected to produce a disruptive tool for engineers to perform targeted suppression of structure-borne sound radiation and transmission with higher precision, flexibility, and control than conventional sound characterization techniques. Specifically, the proposed technologies will enable engineers to see and determine: 1) where and how much acoustic energy is radiating from a complex vibrating machine; 2) where and how much sound is transmitting through a panel structure; and 3) where and how much to suppress acoustic radiation or sound transmission to meet noise mitigation requirements.
Most importantly, it enables engineer to reveal the most critical components of structural vibrations that are responsible for sound radiation and uncover the root causes of noise issues. Accordingly, engineers will be able to enhance local stiffness, viscous damping, and mass without re-engineering the entire structure or increasing its weight.
These targeted treatments can greatly shorten production cycle, cut production costs, enhance competitiveness, and increase profitability for U.S. manufacturing industries. 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 planned for this award.
Employing the proposed AI and laser-assisted targeted noise control technology will enable the design and implementation of quieter and lighter metal structures. Studies have exhibited a direct correlation between weight reduction and CO2 emission.
Statistics have revealed that for every 1 kg of steel used, 2.75 kg of CO2 will be emitted, and every 1 kg of aluminum used, 8.25 kg of CO2 will be released. In general, reducing 1% material weight in an automobile will decrease 1.25% CO2 emission.
Our preliminary test results showed that using the proposed technology, sound transmission loss through a steel panel was increased, but its overall weight reduced by 38%. Therefore, this technology is not only cost-effective in mitigating noise issues, but also ideal for sustainability by simultaneously reducing structural weight and CO2 emissions.
This small business technology transfer (STTR) Phase I project is expected to produce a disruptive tool for engineers to perform targeted suppression of structure-borne sound radiation and transmission with higher precision, flexibility, and control than conventional sound characterization techniques. Specifically, the proposed technologies will enable engineers to see and determine: 1) where and how much acoustic energy is radiating from a complex vibrating machine; 2) where and how much sound is transmitting through a panel structure; and 3) where and how much to suppress acoustic radiation or sound transmission to meet noise mitigation requirements.
Most importantly, it enables engineer to reveal the most critical components of structural vibrations that are responsible for sound radiation and uncover the root causes of noise issues. Accordingly, engineers will be able to enhance local stiffness, viscous damping, and mass without re-engineering the entire structure or increasing its weight.
These targeted treatments can greatly shorten production cycle, cut production costs, enhance competitiveness, and increase profitability for U.S. manufacturing industries. 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 planned for this award.
Awardee
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
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Troy,
Michigan
48098-6548
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the End Date has been extended from 04/30/25 to 10/31/25 and the total obligations have increased 7% from $275,000 to $295,000.
Signal-Wise was awarded
Project Grant 2348512
worth $295,000
from National Science Foundation in May 2024 with work to be completed primarily in Troy Michigan 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
STTR Phase I
Title
STTR Phase I: AI- and Laser- Assisted Targeted Noise Control
Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project enables engineers to identify the root cause and weak spots of noise within a structure and apply local fixes rather than global treatments to mitigate noise emission. Employing the proposed AI and laser-assisted targeted noise control technology will enable the design and implementation of quieter and lighter metal structures. Studies have exhibited a direct correlation between weight reduction and CO2 emission. Statistics have revealed that for every 1 kg of steel used, 2.75 kg of CO2 will be emitted, and every 1 kg of aluminum used, 8.25 kg of CO2 will be released. In general, reducing 1% material weight in an automobile will decrease 1.25% CO2 emission. Our preliminary test results showed that using the proposed technology, sound transmission loss through a steel panel was increased, but its overall weight reduced by 38%. Therefore, this technology is not only cost-effective in mitigating noise issues, but also ideal for sustainability by simultaneously reducing structural weight and CO2 emissions.
This Small Business Technology Transfer (STTR) Phase I project is expected to produce a disruptive tool for engineers to perform targeted suppression of structure-borne sound radiation and transmission with higher precision, flexibility, and control than conventional sound characterization techniques. Specifically, the proposed technologies will enable engineers to see and determine: 1) where and how much acoustic energy is radiating from a complex vibrating machine; 2) where and how much sound is transmitting through a panel structure; and 3) where and how much to suppress acoustic radiation or sound transmission to meet noise mitigation requirements. Most importantly, it enables engineer to reveal the most critical components of structural vibrations that are responsible for sound radiation and uncover the root causes of noise issues. Accordingly, engineers will be able to enhance local stiffness, viscous damping, and mass without re-engineering the entire structure or increasing its weight. These targeted treatments can greatly shorten production cycle, cut production costs, enhance competitiveness, and increase profitability for U.S. manufacturing industries.
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
M
Solicitation Number
NSF 23-515
Status
(Ongoing)
Last Modified 5/5/25
Period of Performance
5/1/24
Start Date
10/31/25
End Date
Funding Split
$295.0K
Federal Obligation
$0.0
Non-Federal Obligation
$295.0K
Total Obligated
Activity Timeline
Transaction History
Modifications to 2348512
Additional Detail
Award ID FAIN
2348512
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
V23JEG6QT1A3
Awardee CAGE
9M0K5
Performance District
MI-11
Senators
Debbie Stabenow
Gary Peters
Gary Peters
Modified: 5/5/25