Dr. Antonio H. Velazquez Profile

Dr. Antonio H. Velazquez

at Ohio Univ

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Author

Publications (7)

Proceedings Article | 27 March 2015 Paper

Low-force magneto-rheological damper design for small-scale structural control experimentation

Benjamin Winter, Antonio Velazquez, R. Andrew Swartz

Proceedings Volume 9435, 943511 (2015) https://doi.org/10.1117/12.2082715

KEYWORDS: Control systems, Actuators, Foam, Prototyping, Magnetism, Metals, Electroluminescence, Structural health monitoring, Feedback control, Polyurethane

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Experimental validation of novel structural control algorithms is a vital step in both developing and building acceptance for this technology. Small-scale experimental test-beds fulfill an important role in the validation of multiple-degree-offreedom (MDOF) and distributed semi-active control systems, allowing researchers to test the control algorithms, communication topologies, and timing-critical aspects of structural control systems that do not require full-scale specimens. In addition, small-scale building specimens can be useful in combined structural health monitoring (SHM) and LQG control studies, diminishing safety concerns during experiments by using benchtop-scale rather than largescale specimens. Development of such small-scale test-beds is hampered by difficulties in actuator construction. In order to be a useful analog to full-scale structures, actuators for small-scale test-beds should exhibit similar features and limitations as their full-scale counterparts. In particular, semi-active devices, such as magneto-rheological (MR) fluid dampers, with limited authority (versus active mass dampers) and nonlinear behavior are difficult to mimic over small force scales due to issues related to fluid containment and friction. In this study, a novel extraction-type small-force (0- 10 N) MR-fluid damper which exhibits nonlinear hysteresis similar to a full-scale, MR-device is proposed. This actuator is a key development to enable the function of a small-scale structural control test-bed intended for wireless control validation studies. Experimental validation of this prototype is conducted using a 3-story scale structure subjected to simulated single-axis seismic excitation. The actuator affects the structural response commanded by a control computer that executes an LQG state feedback control law and a modified Bouc-Wen lookup table that was previously developed for full-scale MR-applications. In addition, damper dynamic limitations are characterized and presented including force output magnitude and frequency characteristics.

Proceedings Article | 10 April 2014 Paper

Modeling stability of flap-enabled HAWT blades using spinning finite elements

A. Velazquez, R. Andrew Swartz, Qingli Dai, Xiao Sun

Proceedings Volume 9063, 90631Q (2014) https://doi.org/10.1117/12.2045135

KEYWORDS: Aerodynamics, Wind energy, Control systems, Turbulence, Chemical elements, Actuators, Matrices, Data modeling, Atmospheric modeling, Wind turbine technology

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Proceedings Article | 10 April 2014 Paper

Operational model updating of spinning finite element models for HAWT blades

Antonio Velazquez, R. Andrew Swartz, Kenneth Loh, Yingjun Zhao, Valeria La Saponara, Robert Kamisky, Cornelis van Dam

Proceedings Volume 9061, 90610U (2014) https://doi.org/10.1117/12.2046434

KEYWORDS: Data modeling, Structural health monitoring, Algorithms, Stochastic processes, Matrices, Systems modeling, System identification, Wind energy, Process modeling, Wind turbine technology

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Proceedings Article | 19 April 2013 Paper

Cyclo-stationary linear parameter time-varying subspace realization method applied for identification of horizontal-axis wind turbines

Antonio Velazquez, R. Andrew Swartz

Proceedings Volume 8692, 86921I (2013) https://doi.org/10.1117/12.2011723

KEYWORDS: Picosecond phenomena, Stochastic processes, Matrices, Phase shift keying, Sensors, System identification, Data modeling, Control systems, Systems modeling, Wind turbine technology

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Wind energy is becoming increasingly important worldwide as an alternative renewable energy source. Economical, maintenance and operation are critical issues for large slender dynamic structures, especially for remote offshore wind farms. Health monitoring systems are very promising instruments to assure reliability and good performance of the structure. These sensing and control technologies are typically informed by models based on mechanics or data-driven identification techniques in the time and/or frequency domain. Frequency response functions are popular but are difficult to realize autonomously for structures of higher order and having overlapping frequency content. Instead, time-domain techniques have shown powerful advantages from a practical point of view (e.g. embedded algorithms in wireless-sensor networks), being more suitable to differentiate closely-related modes. Customarily, time-varying effects are often neglected or dismissed to simplify the analysis, but such is not the case for wind loaded structures with spinning multibodies. A more complex scenario is constituted when dealing with both periodic mechanisms responsible for the vibration shaft of the rotor-blade system, and the wind tower substructure interaction. Transformations of the cyclic effects on the vibration data can be applied to isolate inertia quantities different from rotating-generated forces that are typically non-stationary in nature. After applying these transformations, structural identification can be carried out by stationary techniques via data-correlated Eigensystem realizations. In this paper an exploration of a periodic stationary or cyclo-stationary subspace identification technique is presented here by means of a modified Eigensystem Realization Algorithm (ERA) via Stochastic Subspace Identification (SSI) and Linear Parameter Time-Varying (LPTV) techniques. Structural response is assumed under stationary ambient excitation produced by a Gaussian (white) noise assembled in the operative range bandwidth of horizontal-axis wind turbines. ERA-OKID analysis is driven by correlation-function matrices from the stationary ambient response aiming to reduce noise effects. Singular value decomposition (SVD) and eigenvalue analysis are computed in a last stage to get frequencies and mode shapes. Proposed assumptions are carefully weighted to account for the uncertainty of the environment the wind turbines are subjected to. A numerical example is presented based on data acquisition carried out in a BWC XL.1 low power wind turbine device installed in University of California at Davis. Finally, comments and observations are provided on how this subspace realization technique can be extended for modal-parameter identification using exclusively ambient vibration data.

Proceedings Article | 19 April 2013 Paper

Damped gyroscopic effects and axial-flexural-torsional coupling using spinning finite elements for wind-turbine blades characterization

Antonio Velazquez, R. Andrew Swartz

Proceedings Volume 8692, 86924D (2013) https://doi.org/10.1117/12.2011722

KEYWORDS: Chemical elements, Mathematical modeling, Wind energy, Motion models, Finite element methods, Aerodynamics, Neodymium, Matrices, Systems modeling, Wind turbine technology

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Renewable energy sources like wind are important technologies, useful to alleviate for the current fossil-fuel crisis. Capturing wind energy in a more efficient way has resulted in the emergence of more sophisticated designs of wind turbines, particularly Horizontal-Axis Wind Turbines (HAWTs). To promote efficiency, traditional finite element methods have been widely used to characterize the aerodynamics of these types of multi-body systems and improve their design. Given their aeroelastic behavior, tapered-swept blades offer the potential to optimize energy capture and decrease fatigue loads. Nevertheless, modeling special complex geometries requires huge computational efforts necessitating tradeoffs between faster computation times at lower cost, and reliability and numerical accuracy. Indeed, the computational cost and the numerical effort invested, using traditional FE methods, to reproduce dependable aerodynamics of these complex-shape beams are sometimes prohibitive. A condensed Spinning Finite Element (SFE) method scheme is presented in this study aimed to alleviate this issue by means of modeling wind-turbine rotor blades properly with tapered-swept cross-section variations of arbitrary order via Lagrangian equations. Axial-flexural-torsional coupling is carried out on axial deformation, torsion, in-plane bending and out-of-plane bending using super-convergent elements. In this study, special attention is paid for the case of damped yaw effects, expressed within the described skew-symmetric damped gyroscopic matrix. Dynamics of the model are analyzed by achieving modal analysis with complex-number eigen-frequencies. By means of mass, damped gyroscopic, and stiffness (axial-flexural-torsional coupling) matrix condensation (order reduction), numerical analysis is carried out for several prototypes with different tapered, swept, and curved variation intensities, and for a practical range of spinning velocities at different rotation angles. A convergence study for the resulting natural frequencies is performed to evaluate the dynamic collateral effects of tapered-swept blade profiles in spinning motion using this new model. Stability analysis in boundary conditions of the postulated model is achieved to test the convergence and integrity of the mathematical model. The proposed framework presumes to be particularly suitable to characterize models with complex-shape cross-sections at low computation cost.

Proceedings Article | 3 April 2012 Paper

Probabilistic characterization of wind turbine blades via aeroelasticity and spinning finite element formulation

Antonio Velazquez, R. Andrew Swartz

Proceedings Volume 8345, 83451N (2012) https://doi.org/10.1117/12.915276

KEYWORDS: Chemical elements, Failure analysis, Statistical analysis, Wind energy, Stochastic processes, Resistance, Aerodynamics, Calibration, Roentgenium, Wind turbine technology

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Proceedings Article | 1 April 2011 Paper

Probabilistic analysis of mean-response along-wind induced vibrations on wind turbine towers using wireless network data sensors

Antonio Velazquez, Raymond Swartz

Proceedings Volume 7984, 798421 (2011) https://doi.org/10.1117/12.881131

KEYWORDS: Failure analysis, Resistance, Stochastic processes, Data modeling, Sensors, Wind energy, Finite element methods, Sensor networks, Calibration, Wind turbine technology

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