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Alireza Maheri

Researcher at University of Aberdeen

Publications -  118
Citations -  1730

Alireza Maheri is an academic researcher from University of Aberdeen. The author has contributed to research in topics: Wind power & Turbine blade. The author has an hindex of 18, co-authored 106 publications receiving 1393 citations. Previous affiliations of Alireza Maheri include Northumbria University & University of Bristol.

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Finite element model for vibration and buckling of functionally graded sandwich beams based on a refined shear deformation theory

TL;DR: In this article, a finite element model for vibration and buckling of functionally graded sandwich beams based on a refined shear deformation theory is presented, where the core of sandwich beam is fully metal or ceramic and skins are composed of a functionally graded material across the depth.
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Multi-objective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming

TL;DR: In this paper, an innovative method is proposed which is based on chance constrained programming (CCP) to address the uncertainties in renewable resources (wind speed and solar irradiance), a case study is used to validate the proposed method, where the results obtained are compared with the conventional method of incorporating uncertainties using Monte Carlo simulation.
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Multi-objective design optimisation of standalone hybrid wind-PV-diesel systems under uncertainties

TL;DR: In this article, the authors proposed two algorithms to find the optimum margin of safety, applicable to the peak load, which can be used to size the diesel generator towards designing a cost-effective and reliable system.
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Seismic performance of ordinary RC frames retrofitted at joints by FRP sheets

TL;DR: In this paper, the performance level and the seismic behaviour factor of the FRP retrofitted RC frame were compared with those of the original frame and the same frame retrofitted with steel bracings.
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An accurate method for the PV Model identification based on a genetic algorithm and the interior-point method

TL;DR: In this paper, a multi-objective global optimization problem is formulated using only the main equation of the PV module at these two conditions that restrains the errors due to employing the experimental temperature coefficients.