SBIR/STTR Research Award

SBIR Phase I: Residual Stress and Part Distortion Prediction in Machined Workpiece Surfaces

Award identifier 0c40e905f14c02a312dfa20ec806fc27164b7fe2dcf33734c7e243639d4bcf19Awarding agency National Science Foundation

Award amount

$100,000

Program and phase

SBIR · Phase I

Award year

2002

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
Third Wave Systems, Inc.
Proposal award date
Not reported
Contract end date
Not reported
UEI
N9AQJLAWNAF4
Solicitation number
Not reported
Topic code
Not reported

Research abstract

This Small Business Innovative Research Phase I project will develop and validate a three-dimensional finite element modeling capability to predict machining induced residual stresses. This project will significantly extend the current state-of-the-art that is limited to 2D residual stress analysis and recently, 3D oblique cutting models of single cutting edge geometries. Residual stress has become increasingly important because of its effects upon surface quality, fatigue, and workpiece distortion. Residual stress has high economic impact to industry since the cost of manufacture is incurred prior to any measurement or detection. Testing methods are very expensive, difficult, and not developed for production purposes. Industry and government testing has determined that machining induced residual stresses can be significant enough in magnitude to induce part distortion and out-of tolerance conditions on completed workpieces. This project will demonstrate an integrated approach to predicting residual stress effects upon completely manufactured parts. Workpiece residual stress due to machining parameters will be modeled, verified, and then integrated into a complete part analysis to determine the final state of stress and distortion for a complete workpiece part prior to any manufacture. The commercial applications include large, thin walled aerospace parts (such as wing spars), structural components, and parts susceptible to high rates of fatigue (rotor wing hubs and load carrying parts, spindles, structural, and powertrain components). The economic impact to predict and control part distortion induced by machining processes is very high. The cost of rejection of one part due to out-of-tolerance conditions can easily exceed $100,000 and routinely create weeks in production delay and scrap. The automotive sector, primarily within engine block manufacture, piston liners, bearings, spindles, and hard turning applications (generally) could also benefit from this technology.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

35 SBIR/STTR records share this UEI (2001–2022). Reported award amounts total $16,585,528. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation

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.