Similar to solar panels and wind turbines, wave energy converters harness energy from Mother Nature’s resources – specifically ocean waves – and turn them into electricity. While this process has not yet been perfected, it has the potential to reduce our reliance on fossil fuels.
While several challenges, such as operating complex devices in harsh ocean conditions, must be overcome before wave energy becomes a realistic option for mainstream power, one step toward a solution was recently studied and validated by an international team of engineering researchers. The team’s findings related to their wave energy simulation toolJournal of Computational Physics, with the outcomes validated using the Comet supercomputer at the San Diego Supercomputer Center (SDSC) and Bridges at the Pittsburgh Supercomputing Center (PSC).
Focused on modeling complex fluid-structure interaction problems, the research team’s study encompassed simulations such as heavy rigid structures interacting with high winds, breaking waves, and other complex marine characteristics.
“We primarily used our simulation techniques to investigate inertial sea wave energy converters, which are renewable energy devices developed by our collaborators at the that convert wave energy from large bodies of water into electrical energy,” explained study co-author Amneet Pal Bhalla, an a
Some large-scale modeling challenges were also encountered by the researchers while conducting their study. For example, while their work required hundreds of processors and multiple days of time to run, computational time on Comet and Bridges enabled them to demonstrate the parallel scalability of their simulation technique as well as validate various three-dimensional, large-scale test cases. The researchers also used the College of Engineering’s Fermi high-performance computing service at San Diego State University.
The research was supported by the National Science Foundation (NSF) Graduate Research Fellowship Program (award DGE1324585) and the NSF’s SI2 program (awards OAC 1450327 and OAC 1450374). Supercomputer time was allocated via the NSF’s Extreme Science and Engineering Discovery Environment (XSEDE).