Sustainable energy extraction from ocean waves represents an enormous source of renewable energy and promises to contribute towards the energy independence of the United States while addressing rising environmental concerns over fossil fuels. However, the process of bringing a wave energy converter (WEC) design from the lab to commercial deployment is long and costly and is hindered by the complexity of the underlying flow physics. There are several critical scientific concerns that are difficult or impossible to study in the lab at early design stages of WECs. They include assessing the performance of a full scale array and engineering a WEC that is optimized for a specific deployment site to achieve maximum performance. Computational methods can provide the ability to address such concerns early on in the development process and are capable of shortening the timeframe and associated costs of the design process.
Currently, almost all computational tools for analysis of WECs are based on linearized hydrodynamic equations in place of the full Navier-Stokes equations. As a result, they are unable to capture non-linear effects, e.g. wave breaking, turbulence, and fluid-structure interactions, that significantly impact the performance of WECs. Without capturing these effects, a typical linear model will have a very limited scope in the development process of WECs. Thus, there is an urgent need to bridge the gap between WEC development efforts and computational modeling techniques by introducing a comprehensive computational framework for design and optimization of WECs that includes all important effects.
This project will utilize a comprehensive computational framework for analysis and optimization of WECs under real-world conditions. The proposed computational tool incorporates non-linear effects and provides site-specific simulations including (a) a turbulent (both direct numerical simulation, and large eddy simulation), two-phase flow solver driven by wave fields derived from phase-averaged wave model for realistic and site-specific inflow conditions, (b) a fluid-structure interaction model, and (c) an uncertainty quantification model to guide sensitivity analysis and optimization studies of WEC design. To enable rapid turnaround of simulations, the PI will continue efforts in migrating these modules to a heterogeneous CPU/GPU computing environment. The PI will use the experimental datasets available publicly (Salter?s WEC) and from an industry partner (Resolute Marine Energy) to validate the proposed computational tool. The PI will then perform design and optimization studies on, among other devices, a WEC developed at UMass-Dartmouth (UMD) for small-scale, wave-driven generators for remote areas.
The proposed computational tool can accelerate the development and deployment of cost-effective WECs, which can potentially transform renewable energy efforts in the United States. The project will train two graduate and three undergraduate students. The outreach and dissemination plans target a wide spectrum of audience including high school students/teachers, local communities of New Bedford and Fall River, international scientific communities of marine renewable energy, engineering, and computational sciences, and members of social media.
