MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

THE HYDROSOCIAL COSTS OF HIGH-VOLUME HYDRAULIC FRACTURING: A TALE OF TWO COUNTIES IN MICHIGAN

Although natural gas has been praised as a clean and abundant energy source, the varying impacts and uncertainties surrounding the process of extracting natural gas from unconventional sources, known as horizontal high-volume hydraulic fracturing (HVHF) or “fracking,” have raised important concerns. The practice of HVHF is expanding so quickly that the full impacts are not yet known. This thesis project, using a grounded theory methodological approach, explores the risks and benefits associated with HVHF as recognized by the residents of two Michigan counties, one that currently produces natural gas by HVHF (Crawford County) and one that does not (Barry County). Through an analysis of media content related to HVHF in each case study site and interviews with stakeholders in both counties, this study examines perceptions of risks and benefits by comparing two communities that differ in their level of experience with HVHF operations, contributing to our understanding of how perceptions of risks and benefits are shaped by natural gas development. The comparative analysis of the case study counties revealed similarities and differences between the case study counties. Overall, Barry County residents identified fewer benefits and more risks, and had stronger negative perceptions than Crawford County residents. This study contributes to the social science literature by developing a richer theoretical frame for understanding perceptions of HVHF and also shares recommendations for industry, organizations, regulators, and government leaders interested in effectively communicating with community stakeholders about the benefits and risks of HVHF.