{"title":"Experimental study of Overtopping Breakwater for Energy Conversion (OBREC) device under various sea states and structural geometries","authors":"Parisa Setayesh, Mohammad Navid Moghim","doi":"10.1016/j.renene.2026.125246","DOIUrl":null,"url":null,"abstract":"<div><div>The Overtopping Breakwater for Energy Conversion (OBREC) harnesses wave energy by capturing overtopping waves into a reservoir on a rubble mound breakwater, generating electricity via low-head turbines using the water level difference. This study enhances understanding of overtopping behavior under varying OBREC geometries and sea states through 140 two-dimensional experimental tests. A novel dimensionless parameter (<em>H*√T*</em>) was introduced to jointly assess wave height and period effects, alongside a new overtopping parameter (<em>N</em><sub><em>OT</em></sub>) accounting for wave breaker type. Results reveal distinct overtopping trends linked to the surf similarity parameter (ξ), with plunging breakers below <em>ξ</em><sub><em>m-1,0</em></sub> = 4.2 and surging breakers above this threshold. The <em>N</em><sub><em>OT</em></sub> parameter showed strong predictive capability for both breaker types, achieving coefficients of determination of <em>R</em><sup><em>2</em></sup> = 88 % and <em>R</em><sup><em>2</em></sup> = 97 % for plunging and surging breakers, respectively. Ramp geometry significantly influences performance: higher ramps reduce overtopping but increase turbine head, gentler breakwater slopes lower overtopping, while gentler reservoir slopes increase it. A predictive equation was developed for both plunging and surging breakers, achieving <em>R</em><sup><em>2</em></sup> = 82 % and <em>R</em><sup><em>2</em></sup> = 84 % with low mean relative errors (<em>E</em> = 0.003 and <em>E</em> = 0.016, respectively; <em>E</em> = 0.008 overall). Compared to the best existing model by Iuppa et al., the proposed formula reduced the mean relative error by approximately 98 % and achieved an average <em>R</em><sup><em>2</em></sup> of 83 %.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"261 ","pages":"Article 125246"},"PeriodicalIF":9.1000,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0960148126000716","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/1/13 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
The Overtopping Breakwater for Energy Conversion (OBREC) harnesses wave energy by capturing overtopping waves into a reservoir on a rubble mound breakwater, generating electricity via low-head turbines using the water level difference. This study enhances understanding of overtopping behavior under varying OBREC geometries and sea states through 140 two-dimensional experimental tests. A novel dimensionless parameter (H*√T*) was introduced to jointly assess wave height and period effects, alongside a new overtopping parameter (NOT) accounting for wave breaker type. Results reveal distinct overtopping trends linked to the surf similarity parameter (ξ), with plunging breakers below ξm-1,0 = 4.2 and surging breakers above this threshold. The NOT parameter showed strong predictive capability for both breaker types, achieving coefficients of determination of R2 = 88 % and R2 = 97 % for plunging and surging breakers, respectively. Ramp geometry significantly influences performance: higher ramps reduce overtopping but increase turbine head, gentler breakwater slopes lower overtopping, while gentler reservoir slopes increase it. A predictive equation was developed for both plunging and surging breakers, achieving R2 = 82 % and R2 = 84 % with low mean relative errors (E = 0.003 and E = 0.016, respectively; E = 0.008 overall). Compared to the best existing model by Iuppa et al., the proposed formula reduced the mean relative error by approximately 98 % and achieved an average R2 of 83 %.
期刊介绍:
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