DOE funding awarded for prognostic wind-turbine blade solution

Sandia National Laboratories and the National Renewable EnergyLaboratory (NREL) have been awarded Department of Energy funding to work with Sentient Science on the development of a prognostic solution to predict and extend wind-turbine blade life.

Researchers will subject a DOE National Rotor Testbed 13-m turbine blade to continual fatigue testing, and use optics to identify the wear of the blade over time. The physical test data will be used during the development of the computational model and then validate the accuracy of the digital approach.

Sentient Science, which developed its DigitalClone Live software using four technical pillars (materials science, data science, tribology, and multi-body dynamic system modeling) to predict the life and provide life extension actions for rotating mechanical equipment, has been enhancing its DigitalClone technology to include turbine blade early failure predictions.

The collaboration with Sandia and NREL will give Sentient access to intellectual and technical resources at both laboratories to accelerate blade modeling capabilities within DigitalClone Live.

“A single defective wind-turbine blade could cost wind operators up to $300,000 if it’s not caught early enough for repair,” said Elon Terrell, Ph.D. and Computational Tribologist at Sentient Science. “We’re developing a predictive health-monitoring solution to detect contact bending fatigue and wear rates of wind turbine blades. The partnership and access to the lab resources and brilliant minds at Sandia and NREL will help us accelerate this program.”

The U.S. Department of Energy’s program encourages collaboration between national lab researchers and American small businesses. The Small Business Vouchers program facilitates access to DOE national laboratories for competitively selected small businesses, enabling them to tap into the intellectual and technical validation resources needed to validate critical technology enhancements in an effort to advance energy products, lower the cost of energy and gain a global competitive advantage.

As part of the project, researchers will subject a Sandia-designed DOE National Rotor Testbed 13-m turbine blade to continual fatigue testing, and use optics to identify the wear of the blade over time. The physical test data will be used during the development of the computational model and then validate the accuracy of the digital approach.

DigitalClone Live helps users better predict when turbine failures can be expected in their fleet, and which life extension actions will provide the greatest return on investment.

“We look forward to the opportunity to partner with Sentient Science in leveraging Sandia’s decades of work in sensors, prognostic structural health monitoring and damage modeling,” said Jon White, Ph.D. and Principal Member of the Technical Staff at Sandia.

“Partnering with Sentient Science provides a unique opportunity to advance predictive turbine blade monitoring solutions,” NREL Mechanical Engineer Scott Hughes said. “NREL’s structural verification research helps validate tools that can extend the life of wind turbine blades.”

Once the DigitalClone blade model is completed, the software capabilities will be built into Sentient’s DigitalClone Live Software as a Service, which is used by wind turbine operators to lower their cost of energy through prognostics and life extension recommendations.

“Our DigitalClone Live prognostic technology is being used by wind operators and OEMs around the world to achieve life extension on their wind turbines. We see what sensors can’t see, and predict early failure initiation months and years before a sensor or a CBM (condition-based monitoring) system detects a field failure,” said Ward Thomas, CEO & President of Sentient Science.

“Users understand which turbines to climb and which components need attention with enough advanced notice to optimize their supply chain, lower inventory, reduce lead times and coordinate maintenance plans to reduce cost and downtime. We expect to reduce the user’s cost of energy by an additional $1/MWh with the integration of blade life extension through the software’s watchlist and asset action recommendations,” Thomas added.

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