Ryan G. Coe

Sandia National Laboratories

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Giorgio Bacelli

Sandia National Laboratories

Lance Manuel

The University of Texas at Austin

Dominic Forbush

Sandia National Laboratories

Vincent S. Neary

Sandia National Laboratories

Steven J. Spencer

National Association of People with HIV Australia

Andreas F. Haselsteiner

University of Bremen

Bret Bosma

Oregon State University

Kelley Ruehl

Sandia National Laboratories

Pedro Lomónaco

Oregon State University

Rush D. Robinett

Michigan Technological University

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Sandia National Laboratories

Sandia National Laboratories California

National Renewable Energy Laboratory

Office of Scientific and Technical Information

National Technical Information Service

Oregon State University

National University of Ireland, Maynooth

The University of Texas at Austin

Michigan Technological University

University of New Mexico

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A benchmarking exercise for environmental contours

Ocean Engineering (2021)

Andreas F. Haselsteiner Ryan G. Coe Lance Manuel Wei Chai Bernt J. Leira

Environmental contours are used to simplify the process of design response analysis. A wide variety of contour methods exist; however, there have been a very limited number of comparisons of these methods to date. This paper is the output of an open benchmarking exercise, in which contributors developed contours based on their preferred methods and submitted them for a blind comparison study. The exercise had two components—one, focusing on the robustness of contour methods across different offshore sites and, the other, focusing on characterizing sampling uncertainty. Nine teams of researchers contributed to the benchmark. The analysis of the submitted contours highlighted significant differences between contours derived via different methods. For example, the highest wave height value along a contour varied by as much as a factor of two between some submissions while the number of metocean data points or observations that fell outside a contour deviated by an order of magnitude between the contributions (even for contours with a return period shorter than the duration of the record). These differences arose from both different joint distribution models and different contour construction methods, however, variability from joint distribution models appeared to be higher than variability from contour construction methods.

Benchmarking

Robustness

Contour line

Benchmark (surveying)

10.1016/j.oceaneng.2021.109504

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Citations (57)

Extending Complex Conjugate Control to Nonlinear Wave Energy Converters

Journal of Marine Science and Engineering (2020)

David G. Wilson Rush D. Robinett Giorgio Bacelli Ossama Abdelkhalik Ryan G. Coe

This paper extends the concept of Complex Conjugate Control (CCC) of linear wave energy converters (WECs) to nonlinear WECs by designing optimal limit cycles with Hamiltonian Surface Shaping and Power Flow Control (HSSPFC). It will be shown that CCC for a regular wave is equivalent to a power factor of one in electrical power networks, equivalent to mechanical resonance in a mass-spring-damper (MSD) system, and equivalent to a linear limit cycle constrained to a Hamiltonian surface defined in HSSPFC. Specifically, the optimal linear limit cycle is defined as a second-order center in the phase plane projection of the constant energy orbit across the Hamiltonian surface. This concept of CCC described by a linear limit cycle constrained to a Hamiltonian surface will be extended to nonlinear limit cycles constrained to a Hamiltonian surface for maximum energy harvesting by the nonlinear WEC. The case studies presented confirm increased energy harvesting which utilizes nonlinear geometry realization for reactive power generation.

Hamiltonian (control theory)

Limit cycle

10.3390/jmse8020084

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Citations (16)

On limiting the influence of serial correlation in metocean data for prediction of extreme return levels and environmental contours

Ocean Engineering (2022)

Ryan G. Coe Lance Manuel Andreas F. Haselsteiner

Limiting

Swell

10.1016/j.oceaneng.2022.113032

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Citations (1)

A compressible degree of freedom as a means for improving the performance of heaving wave energy converters

Renewable Energy (2024)

A. Cotten Adi Kurniawan Vincent S. Neary Ryan G. Coe Giorgio Bacelli

10.1016/j.renene.2024.120421

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Citations (1)

Extreme Conditions Modeling Workshop Report

Ryan G. Coe Vincent S. Neary Michael Lawson Yongjae Yu Johannes Weber

Sandia National Laboratories (SNL) and the National Renewable Energy Laboratory (NREL) hosted the Wave Energy Converter (WEC) Extreme Conditions Modeling (ECM) Workshop in Albuquerque, NM on May 13th-14th, 2014. The objective of the workshop was to review the current state of knowledge on how to model WECs in extreme conditions (e.g. hurricanes and other large storms) and to suggest how U.S. Department of Energy (DOE) and national laboratory resources could be used to improve ECM methods for the benefit of the wave energy industry.

National laboratory

Energy Modeling

10.2172/1149224

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Citations (12)

Design of a Physical Point-Absorbing WEC Model on which Multiple Control Strategies will be Tested at Large Scale in the MASK Basin

The Twenty-fifth International Ocean and Polar Engineering Conference (2015)

Diana Bull Ryan G. Coe Mark J. Monda Kevin Dullea Giorgio Bacelli

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Wave Energy Converter Power Take-Off Modeling and Validation From Experimental Bench Tests

IEEE Journal of Oceanic Engineering (2024)

Simone Giorgi Ryan G. Coe Meagan M. Reasoner Giorgio Bacelli Dominic Forbush

This article describes the implementation of a new numerical model of the power take-off system installed in the Monterey Bay Aquarium Research Institute wave energy converter, a device developed to provide power to various oceanic research missions. The simultaneous presence of hydraulic, pneumatic, and electrical subsystems in the power take-off system represents a significant challenge in forging an accurate model able to replicate the main dynamic characteristics of the system. The validation of the new numerical model is addressed by comparing simulations with the measurements obtained during a series of bench tests. Data from the bench tests show good agreement with the numerical model. The validated model provides deeper insights into the complex nonlinear dynamics of the power take-off system and will support further performance improvements in the future.

Test bench

Energy transformation

10.1109/joe.2023.3345903

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Citations (2)

A second benchmarking exercise on estimating extreme environmental conditions

Ocean Engineering (2021)

Andreas F. Haselsteiner Ryan G. Coe Lance Manuel

Benchmarking

10.1016/j.oceaneng.2021.109111

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Citations (0)

FOSWEC v2: System identification and control testing at Hinsdale Wave Research Laboratory

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (2020)

Ryan G. Coe Giorgio Bacelli Dominic Forbush Steven J. Spencer Kevin Dullea

Identification

10.15473/1782587

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A Scoping Study to Determine the Location-Specific WEC Threshold Size for Wave-Powered AUV Recharging

IEEE Journal of Oceanic Engineering (2020)

Blake P. Driscol L. Andrew Gish Ryan G. Coe

The aim of this study is to determine the threshold wave energy converter (WEC) type and size to charge a fleet of U.S. Navy autonomous underwater vehicles (AUVs) in various geographic locations of interest. The U.S. Navy deploys AUVs in locations around the world that must be charged manually, decreasing their operational endurance and creating operational limitations. Ocean waves are a potential power source that can be converted into electricity using a WEC and stored using a battery. It would be beneficial to develop a WEC that could autonomously charge AUVs offshore. Numerous locations were analyzed to determine the minimum size of a WEC capable of providing sufficient charging power and offering a strategic advantage. By predicting the WEC efficiency (based on empirical equations) and wave resource (based on available data), electrical power generation across numerous WEC types and locations was compared in MATLAB. The generalized process developed here could be used to determine the required size and type of WECs to charge a fleet of AUVs in different locations around the world.

10.1109/joe.2020.2973032

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Citations (15)