Sentient Science, based in Buffalo, New York, is a leader in prognostic technology and life extension services.Today, energy, heavy machinery, and aerospace customers use Sentient’s services to maximize the operating efficiencies and life of their industrial assets.
A major focus of Sentient Science is reducing the cost of wind energy. To do this, Sentient uses cloud-based modeling and simulation service called DigitalClone that offers concrete data and a whole new way of looking at machine performance, failure, and life-extending solutions for wind turbine gearboxes, bearings, and other applications.
Today, operators have three strategies to maximize wind turbine efficiencies: increasing revenue (uprating), reducing operational expenses, and extending life.
DigitalClone Live uses a live data feed to deploy the predictive information from the component and assembly models to individual fielded assets.By accounting for the environmental, mechanical, and operational variables, the DigitalClone software-as-a-service can evaluate operators’ decisions of how to run each wind turbine to eliminate guesswork and ensure owners get the most output and return-on-investment possible from their assets.
According to Ward Thomas, CEO at Sentient, "DigitalClone provides our customers with the tools they need to optimize operational strategies and extend the life of their assets. In just one year, we have contracted to provide prognostic and life extension services to more than 4,000 wind turbines in North America.”
By interfacing DigitalClone prognostic models to improve the life of customer’s fielded assets, Sentient supports what GE and others call the Industrial Internet.
For 12 years, Sentient has built and validated its core multi-physics prognostic technology into commercial services since 2001 with over $20M ofcontracts from U.S. federal and state agencies including the Department of Energy, Department of Defense, National Science Foundation, and NYSERDA.The U.S. Small Business Administration presented Sentient Science with the 2014 Tibbetts Award at the White House for its role that in research and development for the Government and for success in deriving innovation into the industrial and energy marketplace.
To power its computational models on the Industrial Internet, Sentient relocated its headquarters to Buffalo, New York where an active and symbiotic relationship with the University at Buffalo had been forged. By actually locating in a UB facility, that relationship was solidified and has given the company unparalleled access to new technical talent coming out the university’s PhD programs as well as to the university’s powerful Center of Computational Research.
With NY-BEST, Sentient recognizes that energy storage can provide wind fleet operators new abilities to run wind turbines more profitable. Wind turbines are often curtailed by electricity grid operators because wind turbines can ramp down and ramp up energy production quickly. However, these curtailment requirements from the electricity grid can prevent owners from operating wind turbines at the optimal rating to maximize their profits. Storage could remove the need for grid curtailment requirements so wind farms can operate in a way that’s most efficient.
With manufacturers, Sentient Science is unique because they use their new technology to perform “smart testing” – an optimal blend of computational and hardware testing. In the past, companies have had to rely on vast amounts of time-consuming and expensive physical testing to develop and validate their products. Sentient’s technology provides the ability to calculate the point in time when critical components and systems will begin to fail and to make recommendations to extend the life of components, systems and assets. These “Smart Testing” commercial services are called DigitalClone Component® and DigitalClone System®.
Modeling starts at the system level with DigitalClone System, a high-level open modeling language for mechanical systems, not unlike what Verilog or VHDL offers for electronic systems. Early on in the design process, before CAD or FEA, this tool provides a rapid preliminary design understanding at the macro level that determines the right components to meet your needs and simulates the inputs needed for the next step.
Once the critical component is identified, DigitalClone Component models that component. Using a state-of-the-art, microstructure-based approach that takes into account factors such as grain size distribution, orientation, inclusions, and void density, a probabilistic model is created that can more accurately predict failure than traditional analysis methods.
These DigitalClone models are then harnessed in DigitalClone Live to provide new optimization services from the OEM.
To learn more about Sentient Science and case studies of prognostics at work, please visit www.sentientscience.com.