arXiv subjects

Maha N. Haji

Publications and source records attributed to Maha N. Haji.

4 recordsLinked to original sources

arXiv2026

Multidisciplinary Design Optimization for Wave-Driven Desalination Systems

Wave-driven desalination systems are an innovative solution to the global freshwater crisis, leveraging the complementary characteristics of seawater reverse osmosis and wave energy converters. However, the high costs of this system pose a significant barrier to widespread adoption. Optimization can help these systems reach a more competitive levelized cost of water, but the highly coupled nature of the system necessitates a multidisciplinary design optimization approach. This paper presents a holistic, multidisciplinary design optimization framework for wave-driven desalination system design, integrating models for wave energy converter hydrodynamics, power take-off transmission, seawater reverse osmosis constraints, and economic analysis. This study demonstrates the impact of multidisciplinary design optimization for wave-driven desalination systems, resulting in a 69.5% reduction in levelized cost of water within this modeling framework compared to a nominal design. We demonstrate that multidisciplinary design optimization outperforms two different sequential design approaches, yielding lower levelized costs of water and substantially different optimal designs. The multidisciplinary design optimization results suggest major design changes compared to designs found in the literature. Notably, smaller wave energy converters and larger pistons, along with smaller accumulators and larger seawater reverse osmosis plant installations, are preferred within this modeling framework. These design trends are consistent across a range of sea states, suggesting potential generalizability beyond a single location. This study demonstrates the importance of holistic modeling and co-design for wave-driven desalination systems and establishes an effective optimization framework for future studies to build upon.

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arXiv2026

Multidisciplinary Design Optimization of Wave Energy Converter Farms Considering Uncertainty through Polynomial Chaos Expansion

In this paper, a multidisciplinary design optimization problem under uncertainty is formulated for wave energy converter array. An array of heaving point absorbers for grid-scale energy production with decision variables and parameters chosen from the coupled disciplines of geometry, hydrodynamics, layout, and trajectory optimization thus resulting in a control co-design formulation of the plant and the control together. We study the benefits of MDO as applied to WEC farm layout optimization. We vary the wave energy converter (WEC) dimensions, array layout, and control gain to minimize the power per volume. Uncertainty in the electrical power is handled using regression based on polynomial chaos expansion (PCE) method at each design iteration. Traditional WEC farm design optimization approaches often neglect the multidisciplinary, coupled nature of WECs and the inherent uncertainty in ocean wave conditions and control responses. This leads to designs that may under perform in real-world environments. In this work, we address this limitation by incorporating uncertainty directly into the design optimization process using the technique of polynomial chaos expansion (PCE) to quantify the variability of the performance due to uncertain wave environment.

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arXiv2025

Advancing Offshore Renewable Energy: Techno-Economic and Dynamic Performance of Hybrid Wind-Wave Systems

Offshore wind and wave energy offer high energy density and availability. While offshore wind has matured significantly, wave energy remains costly and under development. Integrating both technologies into a hybrid system can enhance power generation, stabilize output, and reduce costs. This study explores the benefits of combining an offshore floating wind turbine with the two-body heaving point absorber wave energy converter, Reference Model 3 (RM3). Six configurations are analyzed: RM3 integrated with the National Renewable Energy Laboratory 5 MW and the International Energy Agency 15 MW wind turbines, each tested on both spar and semi-submersible platforms. The analysis examines dynamic response, mooring loads, and power production under varying environmental conditions, considering the influence of the wave energy converter float motion and an optional reaction plate. Results indicate that the reaction plate improves damping for the spar platform, enhancing wave energy absorption and power output. A comparative analysis indicates that integrating the wave energy converter reduces its levelized cost of energy by 15-83%, while leaving the wind turbine levelized cost of energy unaffected. Hybridization significantly reduces power fluctuations by 50%, reduces the levelized cost of energy with the 5 MW wind turbine, and slightly increases it with the 15 MW wind turbine. The results highlight a mutualistic relationship between the wave energy converter and the offshore wind turbine, where the former benefits substantially while the latter experiences slight improvements or negligible effects. Additional findings quantify hydrodynamic interactions, mooring performance, and economic feasibility. This research provides insights into optimizing hybrid offshore renewable systems, demonstrating their potential to lower costs and support sustainable energy solutions.

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arXiv2024

Multi-Objective Multidisciplinary Optimization of Wave Energy Converter Array Layout and Controls

This study utilizes multidisciplinary design optimization (MDO) to design an array of heaving wave energy converters (WECs) for grid-scale energy production with decision variables and parameters chosen from the coupled disciplines of geometry, hydrodynamics, layout, motor-actuated reactive controls (with a force maximum constraint) and economics. We vary a WEC's dimensions, array layout, and control gain to minimize two objectives: the levelized cost of energy (LCOE) and the maximum separation distance. This multi-objective optimization approach results in a set of optimal design configurations that stakeholders can choose from for their specific application and needs. The framework yields a range of optimal (minimum) LCOE values from 0.21 to 0.23 \$/kWh and a separation distance ranging from 97 to 62 meters. The WEC radius of 4m is found to be optimal, and the q-factor for optimal designs are greater than 1 up to 1.06 for a rhombus-like layout. Additionally, a post-optimality global sensitivity analysis of a design shows that wave heading, wave frequency, WEC lifetime, amplitude and interest rate accounts for most of the variance. Different designs in the Pareto set may be appealing for different decision makers based on their trade-off analysis. To that end, regression model is developed for design heuristics.

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