Researchers at the College of Engineering, led by principal investigator Yahya Modarres-Sadeghi of the Mechanical and Industrial Engineering Department (MIE), together with their collaborator at Northeastern University have received a $440,000 grant from the National Science Foundation to conduct intensive research on controlling wind turbine blade instabilities.
The title of the project is “Active Control of Nonlinear Flow-Induced Instability of Wind Turbine Blades under Stochastic Perturbations,” and the co-principal investigators are Christopher Hollot, head of the Electrical and Computer Engineering Department, and Matthew Lackner of MIE. Their collaborator on this project is Luca Caracoglia from the Department of Civil and Environmental Engineering of Northeastern University, who spent his sabbatical leave here at UMass this past spring, hosted by the Fluid-Structure Interactions lab and the MIE department.
As the abstract of the collaborative project explains, “Wind turbine blades continue to grow in length to extract more energy from the wind. This trend results in more flexible blades that are more susceptible to flow-induced instabilities, which can lead to sudden and catastrophic failures.”
The researchers note that the onset of these dynamic instabilities can be impacted by the inherent uncertainties in any wind turbine system and is dangerously close to its designed operational speed. This possible instability poses a threat to the integrity of the system. Being able to control such instabilities is critical for the successful operation of future wind turbine blades.
Consequently, according to the researchers, “The goal of this project is to examine and understand appropriate methodologies to actively control nonlinear flow-induced instabilities of large wind turbine blades, considering their inherent stochastic nature. This project will support the ability to design and operate larger, more flexible, wind turbine blades, which will eventually increase energy capture and reduce the cost of energy from offshore wind.”
The NSF research project will consider a fully-coupled continuous fluid-structure interaction model of the flexible, rotating blades, accounting for varying blade shapes and cross-sections, as well as bending and torsional properties.
“We will use this nonlinear model to examine the effect of a number of non-deterministic system parameters on the onset of flow-induced instabilities,” say the researchers, “using perturbation methods as well as stochastic calculus, and to investigate strategies to actively control these flow-induced instabilities using advances in bifurcation control, probabilistic robustness, and multivariable robust control.”
The researchers add that this project promises a unified methodology to advance the fundamental understanding and analysis of control strategies for large wind-turbine systems, which involve the interaction of a flexible structure (the blade) and unsteady flow. These systems contain combined nonlinearities from the structure, the fluid flow around it, and the interaction between the fluid and the structure.
As the abstract concludes, “This research is transformative because it provides fundamental insights into the underlying physics and control of nonlinear stochastic fluid-structure interaction systems with non-uniform properties, including future wind turbine blades, by combining several different areas of expertise.”
The NSF grant was issued by the Division of Civil, Mechanical, and Manufacturing Innovation (CMMI), one of the five divisions in the Directorate for Engineering at the NSF. The CMMI mission is to fund fundamental research and education in support of the NSF’s mission through:
advances in knowledge to enable manufacturing, design and use of engineering materials, and building technologies across scales from nanometers to kilometers;
advances that improve the resilience and sustainability of the nation's civil infrastructure, including reduction of risk and damage from natural and human-induced disasters;
and advances in engineering mathematics, engineering decision-making, and systems control and engineering.
The CMMI encourages cross-disciplinary research partnerships at the intersections of traditional disciplines supported across NSF to promote transformative advances in support of the CMMI mission. It also encourages discovery enabled by the use of cross-cutting technologies such as adaptive systems, nanotechnology, and simulation. (November 2015)