Unconventional Resources最新文献

{"title":"Influence of adsorbed water on diffusion coefficient and permeability of coal","authors":"Hao Wu ,&nbsp;Yan Zhang ,&nbsp;Xinrui Lyu ,&nbsp;Zhelin Wang ,&nbsp;Feng Qiu","doi":"10.1016/j.uncres.2026.100349","DOIUrl":"10.1016/j.uncres.2026.100349","url":null,"abstract":"<div><div>Understanding the influence of water adsorption on gas transport properties is critical for optimizing coalbed methane (CBM) extraction. This study investigates the influence of adsorbed water on methane diffusion and apparent permeability in three coals representing sub-bituminous, bituminous, and anthracite ranks. The samples were selected as geologically representative end-members from major coalbed methane basins in China. Adsorbed water was introduced via humidity equilibration at 97% relative humidity, simulating residual moisture conditions typical of partially dewatered reservoirs. Pressure decay experiments show that under dry conditions, apparent permeability exhibits a non-monotonic variation with coal rank, with the medium-rank coal displaying the highest value among the three tested samples. Upon exposure to adsorbed water, apparent permeability decreases by 39% to 70% across all ranks, with greater suppression observed in low-rank and high-rank coals compared to the medium-rank sample. This rank-dependent response is attributed to differences in pore structure and water distribution associated with coalification history. While the findings are based on single samples per rank and reflect a simplified moisture condition, they provide mechanistic insight into how coal maturity modulates the sensitivity of gas transport to adsorbed water, offering implications for permeability modeling during the dewatering phase of coalbed methane recovery.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"11 ","pages":"Article 100349"},"PeriodicalIF":4.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146192909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced optimization approaches for demand side management in renewable energy generation system","authors":"Challa Krishna Rao ,&nbsp;Sarat Kumar Sahoo ,&nbsp;Saroj Padhan","doi":"10.1016/j.uncres.2025.100302","DOIUrl":"10.1016/j.uncres.2025.100302","url":null,"abstract":"<div><div>Demand Side Optimization (DSO) is a critical approach to enhancing energy efficiency and sustainability by actively managing and reducing energy consumption at the consumer level. This study investigates the performance of three prominent optimization algorithms the Backtracking Search Algorithm (BSA), the Artificial Bee Colony Algorithm (ABC), and Binary Particle Swarm Optimization (BPSO) for demand-side energy management applications. Experimental evaluations were conducted for sample sizes of 100 and 600 consumers. For a sample size of 100 iterations, BPSO exhibited superior performance with a minimum cost of $0.031, an execution time of 0.49145 s, and a mean deviation (MD) of 25 %. The ABC algorithm achieved a best cost of $0.32 in 1.89324 s (MD = 25 %), while BSA reached a best cost of $ 0.022 in 0.96125 s with the same MD. For a larger sample size of 600 iterations, both BPSO and BSA attained a best cost of $405, whereas ABC recorded $433. The comparative results highlight the distinct strengths of each algorithm: BSA's efficient search space exploration, ABC's balance between exploration and exploitation, and BPSO's effective handling of binary decision variables. The integration of these optimization algorithms with real-time analytics, smart metering, and intelligent energy management systems can significantly improve the reliability, economic efficiency, and environmental sustainability of demand-side energy systems.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"11 ","pages":"Article 100302"},"PeriodicalIF":4.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146192908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid solar–exhaust heat recovery heat pump system: A combined experimental and numerical study for high-efficiency sustainable heating","authors":"Rabih Murr ,&nbsp;Tarek Ibrahim ,&nbsp;Nicolas Youssef ,&nbsp;Samer Ali ,&nbsp;Wassim Salameh ,&nbsp;Jalal Faraj ,&nbsp;Mahmoud Khaled","doi":"10.1016/j.uncres.2026.100348","DOIUrl":"10.1016/j.uncres.2026.100348","url":null,"abstract":"<div><div>A significant portion of building energy consumption is attributed to space heating, while a significant amount of power generator waste heat is left unused. At the same time, solar energy's sporadic nature restricts its use as a stand-alone heating source. The objective of this research is to design and evaluate a hybrid heat pump system that combines solar air heating with power generator exhaust gas recovery in order to minimize greenhouse gas emissions, improve energy efficiency, and consume less fuel in cold-climate operations. In contrast to traditional exhaust-recovery or solar-assisted systems, the suggested setup integrates waste-heat and dual renewable sources in various configurations to find the best thermodynamic performance. Through experimental validation and computational modelling, the unique hybrid design for sustainable heating is established by integrating solar and exhaust heat recovery with a heat pump cycle. Six system configurations were examined covering all possible integration sequences of the heat pump, exhaust gas recovery, and solar air heating components. Field data from a 45 kVA generator and 12 m-long solar air tubes were integrated with thermodynamic modelling in a combined simulation experimental framework. At −5 °C ambient conditions, the configuration combining the heat pump, solar air heater, and exhaust gas recovery produced the highest coefficient of performance, with a boost of up to 4770%. The system achieved significant monthly energy and cost savings, as well as up to 98% reductions in carbon dioxide emissions. While the integration of these distinct dynamic heat sources present control challenges, the modular nature of the system affirms feasible application across different scales of buildings. For next-generation building heating systems, this hybrid heat recovery technology provides an extremely effective and environmentally friendly option. This study illustrates the capabilities of hybrid renewable–waste heat recovery systems for the sustainable heating of buildings, paving the road for future experimental work and thermal energy storage integration.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"11 ","pages":"Article 100348"},"PeriodicalIF":4.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning for forecasting production in tight oil reservoirs: Application to the Bakken formation of Williston basin","authors":"Yeonpyeong Jo ,&nbsp;Rasoul B. Sorkhabi ,&nbsp;Palash Panja ,&nbsp;Milind Deo","doi":"10.1016/j.uncres.2026.100335","DOIUrl":"10.1016/j.uncres.2026.100335","url":null,"abstract":"<div><div>Despite the tremendous growth of oil production from tight reservoirs in the US, characterizing and forecasting these tight formations faces significant uncertainties and risks. Machine learning (ML) techniques have emerged as insightful complementary methods to physics-based unconventional reservoir simulations for predicting oil production due to complex reservoir properties that make traditional modeling challenging. This study applies ML approaches to predict oil production from the Bakken formation in the Williston basin and employs normalized production indices (NPIs) by normalizing cumulative oil production with time and completion parameters. Key parameters include surface coordinates, lateral perforated length, total base water volume and total proppant used in hydraulic fracturing, number of stimulated fracture stages, and water volume and proppant per stimulated fracture stage. Five scenarios were analyzed: raw cumulative oil and four NPIs. Feature importance analysis was conducted using SHAP, followed by prediction using random forest, XGBoost, and Multilayer perceptron. Results revealed that well location ranked among the top features, demonstrating superior production potential at the eastern Bakken formation. Total base water and water volume per fracture stage showed a contrasting trend, indicating that the water distribution strategy is critical for stage-level performance. Proppant variables displayed complex non-monotonic relationships with multiple optimal ranges. XGBoost outperformed other algorithms. Stage-normalized NPI₂ achieved optimal prediction accuracy with 37% improvement in R² compared to raw cumulative oil, while spacing-normalized NPI₃ offered the most practical implementation. These findings demonstrate that completion optimization strategies should align with specific production objectives, providing quantitative guidance for improved capital efficiency in unconventional oil development.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"11 ","pages":"Article 100335"},"PeriodicalIF":4.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative study of optimized rock-physics templates (RPTs) and machine learning (ML) approaches for sweet spot delineation in shale gas reservoir","authors":"Nandito Davy ,&nbsp;Ammar El-Husseiny ,&nbsp;Manzar Fawad ,&nbsp;Umair bin Waheed ,&nbsp;Korhan Ayranci ,&nbsp;Nicholas B. Harris","doi":"10.1016/j.uncres.2026.100334","DOIUrl":"10.1016/j.uncres.2026.100334","url":null,"abstract":"<div><div>Accurate prospectivity assessment for unconventional reservoir requires defining sweet spots, a methodology that delineates prospective areas based on quality factors such as organic richness, fracability, and maturity-related reservoir characteristics. In shale gas systems, critical parameters are typically defined by total organic carbon (TOC), brittleness index (BI), and gas saturation <span><math><mrow><msub><mi>S</mi><mi>g</mi></msub></mrow></math></span>. This study compares sweet spot delineation using conventional rock-physics templates (RPTs) with machine learning (ML) algorithms, specifically Artificial Neural Networks (ANNs), Extreme Gradient Boosting (XGB), and Logistic Regression (LR). The RPT-based approach utilizes cross plots between different elastic parameters and employs a statistically supported objective function with two thresholding techniques—box-shaped and mathematical-function thresholds—where the former demonstrates superior performance. The ML approach leverages elastic parameters as features and applies a randomized search for hyperparameter optimization. Results show that the optimized ML-based approach is superior to the RPT-based one, achieving an <span><math><mrow><mi>F</mi><mn>1</mn></mrow></math></span>-score (obtained from precision and recall metrics) of 0.801 against 0.746. The analysis reveals that <span><math><mrow><msub><mi>I</mi><mi>p</mi></msub></mrow></math></span>, <span><math><mrow><msub><mi>I</mi><mi>s</mi></msub></mrow></math></span>, and <span><math><mrow><msub><mi>V</mi><mi>p</mi></msub><mo>/</mo><msub><mi>V</mi><mi>s</mi></msub></mrow></math></span> consistently rank as the most impactful elastic parameters based on validation performance across multiple feature combinations and ML algorithms for delineating prospective zones. Though less powerful, the RPT-based approach offers simplicity and may be optimized further or combined with the ML technique. Our findings underline the practicality and reliability of the proposed ML-based methodologies for unconventional reservoir assessment to accurately delineate sweet spots and improve reservoir evaluation practices.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"11 ","pages":"Article 100334"},"PeriodicalIF":4.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146192907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real time implementation for robust adaptive sliding mode predictive control of PMSM","authors":"Rachid Ibrahimi ,&nbsp;Mohamed said Adouairi ,&nbsp;Abdennabi Morchid ,&nbsp;Badre Bossoufi ,&nbsp;Paweł Skruch ,&nbsp;Saleh Mobayen","doi":"10.1016/j.uncres.2026.100304","DOIUrl":"10.1016/j.uncres.2026.100304","url":null,"abstract":"<div><div>Model Predictive Control is recognized as a promising approach for electric drives, with particular interest in the development of robust and high-performance predictive models. In this work, we propose an Adaptive Integral Sliding Mode Predictive Control for Permanent Magnet Synchronous Motors, combining a predictive model with an adaptive law based on the integral sliding mode. This method automatically adjusts the sliding function limit, reducing the chattering phenomenon while enhancing the system dynamics.</div><div>To ensure compatibility with industrial electronic boards, the Adaptive Integral Sliding Mode Predictive Control was implemented following the V-cycle development process, including Model-in-the-Loop, Software-in-the-Loop, and Processor-in-the-Loop validation. This framework facilitates the deployment of embedded control software in the automotive sector and provides a cost-effective evaluation of the hardware implementation.</div><div>Furthermore, real-time simulations of control, Invariant Sliding Mode Predictive Control, and Sliding Mode Control configurations were carried out on the dSPACE DS1104 platform, showing excellent correlation with MATLAB/Simulink results. Experimental validation on the STM32F4 board confirms that the proposed approach offers faster response to load torque disturbances and better performance over a wide speed range, demonstrating its reliability, robustness, and effectiveness.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100304"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145950283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reestablishing turbulence intensity as a critical parameter for NACA2414 airfoil performance at low Reynolds number: A computational study","authors":"Anupam Krishnan,&nbsp;Abdulkareem Sh. Mahdi Al-Obaidi,&nbsp;Lee Ching Hao","doi":"10.1016/j.uncres.2026.100329","DOIUrl":"10.1016/j.uncres.2026.100329","url":null,"abstract":"<div><div>Small wind turbines operate under low Reynolds number conditions, where improving aerodynamic efficiency becomes crucial due to the adverse inflow characteristics. This study systematically investigates the isolated effect of a broad range of inflow turbulence intensities on the aerodynamic performance of a NACA2414 airfoil at a Reynolds number of 10⁵ using two-dimensional finite volume Unsteady Reynolds-Averaged Navier-Stokes simulations. The computational domain was discretized as a structured grid and a Realizable <em>k-ɛ</em> model was utilized as the closure model in ANSYS Fluent. Three turbulence intensities (1 %, 5 %, and 10 %) were examined over angles of attack spanning from 0° to 30°. Significant reduction in lift-to-drag ratio was observed pre-stall with a contrasting enhancement post-stall with increasing turbulence intensities. In addition, onset of stall was delayed. Statistical analysis, employing ANOVA, based on 800 design points from 0.1 % to 20 % confirmed turbulence intensity as a significant parameter governing lift-to-drag ratio explaining 42.5 % of the associated variance. The effect was substantial at lower angles of attack and diminished at higher angles as post-stall conditions dominated. The present work demonstrates a non-linear and regime-dependent influence of turbulence intensity over NACA2414 airfoil performance at a transitional flow regime, directly relevant to small-scale wind turbine operation. Rotor-level analysis using a validated blade element momentum model further indicates a reduction in mechanical power output with increasing turbulence intensity. The findings establish turbulence intensity as a critical design parameter for low-Reynolds number wind turbine airfoils.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100329"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding Africa's energy divide: A systematic review of SDG 7 progress, structural determinants, and pathways to inclusive electrification","authors":"Idriss Dagal","doi":"10.1016/j.uncres.2026.100330","DOIUrl":"10.1016/j.uncres.2026.100330","url":null,"abstract":"<div><div>Africa remains the world's least electrified continent, with approximately 600 million people lacking access to electricity and persistent urban-rural disparities. Despite recent advances, progress toward Sustainable Development Goal 7 remains uneven, with fewer than one in six African countries currently on track to achieve universal access by 2030. This study provides a comprehensive assessment of Africa's electrification trajectory by synthesizing evidence on the structural, institutional, and socio-spatial determinants shaping energy access outcomes. Using an integrated mixed-methods approach, the analysis draws on a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-based systematic review of 120 studies (2015–2025), complemented by geospatial and policy analysis, to evaluate patterns of access, reliability, and inclusion across the continent. The study introduces an Energy Justice Index to capture multidimensional inequities and develops an investment prioritization framework to support more equitable electrification strategies. Results indicate that decentralized renewable energy systems can reduce electrification costs by up to 40% in low-density areas, yet service quality remains a critical challenge, with a substantial share of connected households receiving limited daily supply. Overall, the findings suggest that achieving universal access will require a shift from grid-centric expansion toward coordinated deployment of decentralized solutions, strengthened regulatory environments, and inclusion-focused financing mechanisms. These insights offer policy-relevant guidance for accelerating equitable and sustainable progress toward SDG 7 in Africa.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100330"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microbialite fabric evolution controlled by marine redox conditions in the Qigebrak Formation, NW Tarim Basin: Implications for hydrocarbon exploration","authors":"Chang Fang ,&nbsp;Da Gao ,&nbsp;Hui Zhou ,&nbsp;Lili Huang ,&nbsp;Yangxiao Hu ,&nbsp;Ngong Roger Ngia","doi":"10.1016/j.uncres.2026.100325","DOIUrl":"10.1016/j.uncres.2026.100325","url":null,"abstract":"<div><div>Microbialites constitute key archives for reconstructing the co-evolution of early life and Earth surface environments. Although the environmental controls on microbialite formation are widely acknowledged, the response of specific microbialite architectures to changes in pelagic ocean chemistry still remain poorly constrained. This paper integrates detailed field mapping, sedimentary facies analysis, and geochemical profiling of the Qigebrak Formation at the Xigou section on the northwestern margin of the Tarim Basin, to characterize microbialite fabrics and assess the role of contemporaneous marine redox conditions in shaping their development during the late Ediacaran. The microbialites at Xigou are well preserved and exhibit diverse fabrics, deposited in mid-to inner-ramp settings. Member II is dominated by laminated microbialites with subordinate clotted and binding fabrics. In contrast, Member III is typified by foam spongy fabrics, marking a significant shift in microbialite architecture. Bulk-rock δ¹³C values record a pronounced positive excursion (∼+5 ‰ to +6 ‰) at the base of the formation, followed by a prolonged interval of isotopic stability. This isotopic variation exhibits global correlation significance and, when combined with the Dengying Formation age constraints, limits the depositional interval to approximately 551.1 ± 0.7 Ma to 538.8 Ma. Trace element and rare earth element data from microbial components indicate that both δCe values and V/(V + Ni) ratios in Member III are markedly lower than those in Member II, reflecting a significant marine redox transition from anoxic to more oxic conditions during the late-Ediacaran ocean. This redox shift exerted a primary control on microbialite fabric development: anoxic conditions favored microbial mats accretion and preservation of laminated fabrics, whereas subsequent oxygenation enhanced organic matter degradation, facilitating the emergence and dominance of foam spongy fabrics. The fabric transition may also reflect increased ecological disturbance linked to the rise of metazoans, pointing to a potential coupling between microbialite decline and biotic innovation in the terminal Ediacaran. Our study underscores that changes in marine redox chemistry, coupled with ecological interactions, were primary controls on the evolution of microbialite in the late Ediacaran, and further elucidates the implications of these fabric transformations for hydrocarbon exploration.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100325"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rear-surface water cooling for photovoltaic panels: A thermo-hydrodynamic pathway to high-efficiency and sustainable solar power in hot climates","authors":"Wassim Salameh ,&nbsp;Samer Ajeeb ,&nbsp;Kamal Itawi ,&nbsp;Mohamad Arnaout ,&nbsp;Rabih Murr ,&nbsp;Jalal Faraj ,&nbsp;Mahmoud Khaled","doi":"10.1016/j.uncres.2026.100326","DOIUrl":"10.1016/j.uncres.2026.100326","url":null,"abstract":"<div><div>Photovoltaic (PV) modules functioning in high-temperature environments face considerable efficiency declines as a result of increased cell temperatures, driving the need for innovative and resource-efficient cooling solutions. This study explores the rear-surface water cooling of photovoltaic modules through a coupled thermal–hydrodynamic numerical model, aiming to identify crucial design and operational parameters that influence thermal and electrical performance. The model undergoes initial validation using published experimental data for air-cooled PV systems, followed by an extension to include rear-surface water cooling as an added convective boundary condition. A thorough parametric analysis is conducted to evaluate the effects of duct height, flow regime, inlet water temperature, and climatic conditions on the reduction of module temperature and the improvement of electrical efficiency. The findings indicate that implementing rear-surface water cooling can lower the operating temperature of photovoltaic systems by as much as 20 % in hot urban environments, resulting in enhancements in electrical efficiency ranging from 15 % to 20 %, contingent on the hydraulic configuration employed. The analysis further illustrates that suitable duct geometry and flow management facilitate efficient cooling while minimizing water usage, underscoring the practicality of closed-loop operation. The proposed framework offers a physically consistent approach for designing and optimizing rear-surface water-cooled PV systems, effectively addressing significant limitations found in current studies that overlook the interplay between thermal and hydrodynamic effects. The results enhance the development of scalable PV cooling solutions tailored for hot climates and provide direction for future experimental validation and techno-economic evaluation.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100326"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}