Myers Awarded $500K NSF CAREER Award
CEE Assistant Professor Andrew Myers was received a $500K NSF CAREER award for his project entitled "Advancing Multi-hazard Assessment and Risk-based Design for Offshore Wind Energy Technology." This project will develop approaches to reduce the cost of offshore wind energy through understanding the interaction of multiple offshore hazards and the development of system-level performance metrics for offshore wind farms.
Abstract Source: NSF
Offshore wind energy is a resource of renewable energy that is conveniently accessible to many major population centers, but harvesting offshore wind energy currently costs more than traditional sources. The research goal of this Faculty Early Career Development (CAREER) Program grant is to advance knowledge that can lead to reduction in the cost of offshore wind energy through (1) a much sharper understanding and modeling of the spatio-temporal interaction of multiple offshore hazards that impact the system-level performance of offshore wind energy farms to reduce insurance and financing costs, (2) the calculation of novel system-level performance metrics, and (3) the advancement of shallow water wave modeling to mitigate the current reliance on overly conservative design methods. The educational goals of this project are to leverage field experiences at state-of-the-art offshore wind-themed sites in New England to inspire high school students to pursue science, engineering, mathematics, and technology careers and to transfer knowledge of multi-hazard assessment and design to the public, other researchers, and the practicing engineering community.
This project will achieve the research goal through fundamental advancements to metamodels (surrogate models) to overcome restrictions that have previously limited the impact of such models in the context of multi-hazard assessment of spatially-distributed infrastructure. Specifically, novel metamodels will be developed to include several important features, such as spatio-temporally varying hazards, high-dimensionality of the input and output vectors, explicit accounting of model adequacy by quantifying inter- and intra-event uncertainty in the model predictions compared to measurements, and a coupling of multi-hazard and system/structural metamodels. The research will also explore innovative models that overcome important deficiencies in the modeling of nonlinear, highly skewed shallow water waves and their associated hydrodynamic loads, including breaking waves. The research will synthesize these advances and generate system-level performance metrics that will provide a fundamentally different paradigm for designing offshore wind farms. The project will leverage partnerships with state, city, academic, and industry organizations. The research outcomes are expected to have broad impact beyond the offshore wind industry, given the national needs in multi-hazard analysis and infrastructure system resilience, and the potential of metamodeling applications in civil engineering and other fields.