SBIR/STTR Research Award

STTR Phase I: Triboluminescent sensor system for quasi-distributed load sensing on wind blades for active control of wind turbines

Award identifier 31c43e4f7cabbdcade0d7eda631a632a7fcf1f84cdf11716e2066d112b4dcd9aAwarding agency National Science Foundation

Award amount

$224,999

Program and phase

STTR · Phase I

Award year

2016

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
NANOTECHNOLOGY PATRONAS GROUP INC
Proposal award date
2016-01-01
Contract end date
2016-12-31
UEI
Not reported
Solicitation number
Not reported
Topic code
MI

Research abstract

This Small Business Technology Transfer Phase I project is for the development of a triboluminescent sensor system (ITOFPress) for quasi-distributed load sensing along the length of a wind blade for active control of wind turbines. According to experts, this innovation could result in a 20% increase in wind turbine power generation through enhanced inputs for active turbine control and better understanding of the load profile along the span of a blade. Such knowledge is critical as wind blades become larger and are installed higher. This new system will also help to protect the blades and other expensive components from damage and overload, thereby reducing operation & maintenance (O&M) costs and making wind energy more attractive to investors. The installation of the ITOFPress system would increase the initial capital costs of a large wind turbine by a very small amount (about a half a percent), creating a strong value proposition for turbine manufacturers and operators. The estimated market potential for this system is expected to be $1.5 billion in 2018. The intellectual merit of this project addresses the technical hurdles in developing the proposed sensor system. The ITOFPress technology is highly sensitive to deformation-induced excitation and can withstand high loading cycles. The sensor combines the light-emitting property of ZnS:Mn with the highly desirable features of optical fibers (i.e. they are lightweight, smaller, immune to electromagnetic interference, and have the capacity for distributed sensing). The ITOFPress does not require external power at the sensing location or for signal transmission to the blade's hub, which makes it very attractive for use in wind turbines. The sensor can accurately detect loads that are not anticipated by models which rely on inputs from inflow sensors like anemometers. In this effort, increased sensor sensitivity will be achieved through experimental design studies involving critical design factors. The sensor's long term stability will be studied by subjecting samples to flexural and compressive load cycles. Finite element analysis will be performed to establish relationships between sensor response, sensor deformation and applied load. Strain gages and load sensors will be used for sensor calibration. A lab-sized wind blade will also be instrumented and tested under compressive cyclic loading to demonstrate quasi-distributed load sensing with the new sensor system.

Technology keywords

Not reported

Agency intelligence

National Science Foundation

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.