Amirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601Integrating digital twin for optimizing autonomous aerial monitoring of photovoltaic systems520574810.22060/aest.2025.5748ENMohammadKolahiDepartment of Mechanical Engineering, University of Isfahan, Isfahan, IranSayyed MajidEsmailifarDepartment of Aerospace Engineering, Amirkabir University of Technology, Tehran, IranMohammadrezaAghaeiDepartment of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology (NTNU), Ålesund, Norway
Department of Sustainable Systems Engineering (INATECH), Albert Ludwigs University of Freiburg, Freiburg, GermanyAmir MohammadMoradi SizkouhiDepartment of Electrical and Computer Engineering, Concordia University, Montreal, CanadaJournal Article20250106In this research, we integrate digital twin (DT) technology through a platform designed for simulating and managing the autonomous aerial monitoring procedure of photovoltaic (PV) power plants, known as Digital-PV. This innovative platform enables users to test various scenarios and configurations of PV power plants, allowing for an evaluation of their impact on the autonomous aerial monitoring process. By doing so, it reduces the risks associated with real-world experiments and helps pinpoint the most effective strategies for improving PV system monitoring. Digital-PV also provides a virtual environment for conducting tests of autonomous flights and missions, covering aspects such as boundary detection, path planning, and fault detection. It includes features for generating data that inform the development of data-driven monitoring and inspection models. The development process of Digital-PV involved creating a digital twin of a utility-scale PV plant within Unreal Engine, simulating aerial robot flight with AirSim, and expanding of application programming interface (APIs) to enable our platform to adapt to different scenarios for evaluating smart monitoring models and collecting datasets. Moreover, throughout the study, a dataset of synthetic aerial images was collected from Digital-PV, which was subsequently used to train an end-to-end segmentation model aimed at detecting bird droppings on PV panels. Ultimately, this platform evaluated a range of intelligent aerial monitoring models, providing valuable insights into their capabilities and potential effectiveness in real-world applications.https://aest.aut.ac.ir/article_5748_1db3fa8e5bbd04882892f478a301a311.pdfAmirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601SARA fraction measurements of Persian Gulf crude oil using LIF spectroscopy based on analysis of variance (ANOVA)2127574710.22060/aest.2025.5747ENFatemehAhmadinouriDepartment of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran0000-0001-7185-2479ParvizParvina Department of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, IranAhmad RezaRabbaniPetroleum Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran.Journal Article20251217Crude oil is typically categorized into four main fractions: saturates, aromatics, resins, and asphaltenes, collectively referred to as SARA. To enable the rapid identification of these fractions, a novel on-site approach is introduced based on laser-induced fluorescence (LIF) spectroscopy. This method utilizes both the solvent (with dichloromethane, DCM) densitometry and quantum efficiency as key analytical parameters. Several crude oil samples are analyzed from different oilfields in the Persian Gulf, with optical parameters of interest i.e., peak concentration (<em>C<sub>p</sub></em>) and quantum efficiency (<em>Q<sub>E</sub></em>) giving by the experimental data. The relation between these parameters and crude oil fractions is attested through analysis of variance (ANOVA). Then, the predictive statistical models are developed to estimate the values of the crude oil fractions. The findings demonstrate that these predictive models exhibit high accuracy compared to the standard methods (ASTM D 6560 & ASTM D 4124). In fact, the proposed technique significantly reduces the testing time to less than 30 minutes.https://aest.aut.ac.ir/article_5747_56d326d8139f904b679084778f1b3285.pdfAmirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601Techno-environmental and economic assessment of off-grid hybrid energy systems for combined cooling, heating, power, and battery-hydrogen storage2851574910.22060/aest.2025.5749ENMohammadRezaMehdizade MarzebaliDepartment of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran.MasoumehMohamadianDepartment of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran.Journal Article20250120This study addresses the urgent energy challenges associated with climate change, exacerbated by industrialization and rapid population growth, through the simulation of a renewable energy system at Amirkabir University. Using Design Builder, we assessed the energy demands for electricity, cooling, and heating in a faculty building, and subsequently developed a combined generation and multi-storage system in HOMER that integrates renewable energy sources, natural gas, and advanced storage solutions, including hydrogen and batteries. Our analysis compares the performance of systems utilizing 1 kW and 10 kW wind turbines, demonstrating that the 10 kW turbine significantly outperforms its smaller counterpart. Solar energy contributes 1,931,801 kWh (89%) to the system, while wind energy accounts for 216,261 kWh (10%). The economic evaluation reveals a total present cost of $6.77 million for the system with the 10 kW turbine, yielding a production cost of $0.377 per kWh and reducing CO<sub>2</sub> emissions to 102,586 kg/year. Furthermore, sensitivity analysis indicates increased wind energy production under higher wind speeds, validating the potential for wind energy in Tehran. Overall, this research highlights the effectiveness of integrated renewable energy systems in mitigating greenhouse gas emissions and meeting rising energy demands over a projected 20-year lifespan while demonstrating significant economic viability.https://aest.aut.ac.ir/article_5749_0e98aeeb54acf612b9eb4e48a269814c.pdfAmirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601A comparative study: Futuristic simulation and traditional methods within the sustainable and energy-efficient architecture planning5265575010.22060/aest.2025.5750ENAmir MahdiKeynooshArchitecture, University of Tehran, Tehran, IranHamedMazaheriArchitecture, University of Tehran, Tehran, IranJournal Article20250123Sustainable architecture has become a very important area of interest, which is focused on energy-efficient design principles and responsible management of environmental resources. The present research makes a comparative study of sustainable architectural buildings in the framework of futures studies and sustainable energy architectural modeling. Its main objective is to test the effectiveness of scenario-based futures studies in comparison with conventional approaches for formulating strategic foresight in sustainable architecture. The findings suggest that methodologies employed in future studies produce outcomes that are both more effective and more representative of real-world applications. This research adopts a mixed-method approach, integrating qualitative and quantitative analyses to evaluate traditional architectural practices against those emerging from future study scenarios. The approach is mixed methodological, in that it integrates wide literature reviews, a SWOT analysis, and the framing of ten scenarios and strategies within the realm of energy-efficient and renewable systems. Graphical modeling highlights these findings, showing the interlinkages between adaptability, innovation, and environmental outcomes. The study provides actionable insights for policymakers, architects, and researchers working to advance sustainable design paradigms. The study reveals methodologies of the futures approach significantly enhance strategic planning and execution in the development of sustainable architectural designs. Scenario-based approaches are more flexible and provide stronger frameworks, aligning better with real-life dynamics and the uncertainties of the future.https://aest.aut.ac.ir/article_5750_e347c51419ffb23ca3fd5050202f9c3d.pdfAmirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601Application of random forest algorithm in identification of key factors in building cooling system energy consumption and energy conservation strategies (for office-educational buildings in Amirkabir University of Technology)6676575110.22060/aest.2025.5751ENRominaPoursedighCivil and Environmental Engineering Faculty, Amirkabir University of TechnologyFarzadHatamiStructural and Earthquake Research Institute, Amirkabir University of TechnologyEghbalShakeriCivil and Environmental Engineering Faculty, Amirkabir University of TechnologyJournal Article20250106The increasing electricity consumption for air cooling and conditioning in buildings has become a significant challenge in Iran, driven by population growth, global warming, limited energy production and distribution capacities, and concerns about the reliance on fossil fuels for electricity generation. This study investigates energy consumption patterns of cooling systems in three buildings at Amirkabir University of Technology: Civil and Environmental Engineering (Building No. 2), Computer Engineering, and Aerospace Engineering. Using energy consumption data, the study identifies key factors related to building characteristics and user behavior that impact cooling energy usage. A Random Forest analysis revealed that among 14 factors, 9 were most significant, with the number of staff, number of students, and the distribution percentage of operating units ranked as the top three. These findings provide insights for developing effective energy conservation strategies tailored to university buildings in similar contextshttps://aest.aut.ac.ir/article_5751_a4c42bfd5f5130ddf96e34a036c75e0a.pdfAmirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601Externality evaluation in the steel industry7797575210.22060/aest.2025.5752ENGhaderHassanzadehDepartment of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), Tehran, IranMohsenSalimiRenewable Energy Research Department, Niroo Research Institute (NRI), Tehran, IranHamidrezaHabibiyanDepartment of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), Tehran, IranMortezaHosseinpourRenewable Energy Research Department, Niroo Research Institute (NRI), Tehran, IranJournal Article20250110The purpose of this study is to evaluate the externalities of the steel industry. Externalities in the steel industry refer to the impacts that steel production has on society and the environment, which are not accounted for in the final product price. One of the most robust methods of investigating this issue is the life cycle assessment (LCA) approach to evaluate the externalities of the steel industry. Our study focused on Mobarakeh Steel Company which the assessment is conducted based on the ISO 14040 standard in four steps: goal and scope definition, inventory analysis, life cycle impact assessment, and interpretation. The software SimaPro version 9.5.0.2 with the Ecoinvent database was applied with supporting ReCiPe H method, which has 18 midpoint indicators and 3 endpoint indicators. The results show the shares of mining and concentrate production process accounted for 38% of the environmental impacts while 26.6% of the impacts were related to the electric arc furnace process. The share of environmental impacts of the DRI unit was15%. In addition, three indicators, human carcinogenic toxicity, fossil resource depletion, and ozone formation in terrestrial ecosystems, were among the most influential indicators in these processes. To quantify the externalities, the cost of each of the identified environmental and social damages are evaluated based on available sources as well as the monetary value calculated for each type of damage. Accordingly, the total externality cost of producing one ton of steel sheet was approximately 846 EUR. Of this total cost, the share attributed to global warming damage was around 462 EUR, identified as the costliest environmental and social damage.https://aest.aut.ac.ir/article_5752_c7b3f097f4810cbb3c4b18c09ab893bc.pdfAmirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601Machine learning-driven insights into efficiency optimization of Si solar cells assisted by CH3NH3PbBr3 perovskite and WS₂ nano-structures98106575310.22060/aest.2025.5753ENFatemehNorouziDepartment of Physics, Imam Khomeini International University, P.O. Box: 34149-16818, Qazvin, IranSeyedeh ZahraMortazaviDepartment of Physics, Imam Khomeini International University, P.O. Box: 34149-16818, Qazvin, Iran
Department of Energy Engineering and Physics, Amirkabir University of Technology, P.O. Box 15875-4413, Tehran, IranAliReyhaniDepartment of Physics, Imam Khomeini International University, P.O. Box: 34149-16818, Qazvin, IranMajidMortazaviDepartment of Physics, Imam Khomeini International University, P.O. Box: 34149-16818, Qazvin, IranAlaaTehraniDepartment of Physics, Imam Khomeini International University, P.O. Box: 34149-16818, Qazvin, IranJournal Article20250111Machine learning techniques, by leveraging advanced algorithms can pave the way for the development of more efficient solar cells by accurately predicting their efficiency and identifying the most influential features that affect their performance. Identifying the most influential features facilitates the optimization of experiments while predicting efficiency reduces the number of experiments. This approach saves time and costs and ultimately, efficient solar cells will play a useful role in solving the energy crisis as renewable energy sources. For this purpose, in the first step of this study, machine learning techniques are used to predict the relative efficiency of silicon solar cells for 58 experimental data after drop-casting with certain concentrations of tungsten disulfide and CH<sub>3</sub>NH<sub>3</sub>PbBr<sub>3</sub> perovskite nano-structures. It was found that the extreme gradient boosting model has the best performance. This model also showed promising results for 12 new data. In the second step, Shapley additive descriptions will investigate the most influential feature on cell efficiency. According to the SHAP results, deposition of tungsten disulfide nano-structures after perovskite on the silicon solar cell surface has the best performance to increase efficiency. In fact, the sequence of drop-casting of each kind of the nano-structures influences the efficiency based on the different interaction mechanisms.https://aest.aut.ac.ir/article_5753_23f09b21324d1ed3cd722109bd55d6e7.pdfAmirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601Thermal-hydraulic analysis of new generation TVS-2M fuel in VVER-1000 reactor using porous media approach method107118575410.22060/aest.2025.5754ENSaeed ZareGanjaroodiEnergy and Physics Department, Amirkabir University of Technology, 424 Hafez Ave., Tehran, IranMaryamFaniEnergy and Physics Department, Amirkabir University of Technology, 424 Hafez Ave., Tehran, IranEhsanZarifiReactor and Nuclear Safety Research School, Nuclear Science and Technology Research Institute, Tehran, IranJournal Article20250106The TVS-2M Russian Fuel Assembly (FA) is a newly suggested fuel type that incorporates gadolinium oxide in different concentrations, combined with enriched UO2 at different levels of U-235 enrichment. TVS-2M FA is designed to improve the safety and efficiency of reactor core. In the Porous Media Approach (PMA) method, the porous medium is generally described by parameters such as permeability, porosity, and the tortuosity of the flow paths, which are utilized to represent the resistance to fluid flow and the material's heat transfer properties. The main aim of present paper is to model the hottest FA of Bushehr Nuclear Power Plant (BNPP) reactor core using the COBRA-EN code and PMA method to evaluate the thermal-hydraulic parameters such as fuel rod temperature, coolant temperature and density, Departure from Nucleate Boiling Ratio (DNBR), and Critical Heat Flux (CHF) in different axial and radial nodes. In such manner, each FA is modeled and broken down into a network of simplified regions. Although detailed geometries are specified, the thermal-hydraulic parameters are computed for each component. Results showed, the average core coolant temperature ranges from 29°C 1 to 322°C. Meanwhile, the coolant temperature in the hottest FA reaches about 328 C. Moreover, the fuel rod temperature varies from about 310°C to 930°C in the hottest FA. On the other hand, the average coolant density into the core changes from 742 kg/m³ to 675 Kg/m<sup>3</sup>.https://aest.aut.ac.ir/article_5754_0dbcf39d413231953d442f2f17f80cd5.pdfAmirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601A comprehensive review on carbon capture, transportation, storage, and utilization technologies; part Ⅰ: carbon capture technologies119132575510.22060/aest.2025.5755ENErfanAbbasian HamedaniDepartment of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran.AmirBahrami YajlooDepartment of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran.SaeedTalebiDepartment of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran.Journal Article20250118In today's world, environmental concerns have gained significant attention. The increasing effects of climate change have heightened the necessity for new strategies to reduce carbon dioxide (CO<sub>2</sub>) emissions, which are the primary driver of global warming. Carbon capture utilization and storage (CCUS) is one of the promising solutions that are being considered to address these environmental concerns. The primary objective of this review paper is to provide a comprehensive overview of the current status of carbon capture utilization and storage technologies, as well as the CO<sub>2</sub> transportation infrastructure, highlighting their potential advantages and the challenges that need to be addressed for successful implementation. This part provides a comprehensive overview of carbon capture technologies, including pre-combustion, post-combustion, oxy-fuel combustion, and direct air capture. The overview additionally discusses the current state of these technologies, their advantages, and limitations, as well as potential future developments. In addition, various CO<sub>2</sub> separation methods regarding these technologies are introduced and discussed. Finally, this paper can be used as a resource for researchers looking to explore carbon capture systems further to minimize CO<sub>2</sub> emissions.https://aest.aut.ac.ir/article_5755_840d68cbbbfa627cd4635408a6c82009.pdfAmirkabir University of TechnologyAdvances in Energy Sciences and Technologies3115-91171120250601Solar-powered energy conversion revolution: MXenes and MBenes metal carbides as key enablers for photocatalytic application133145575610.22060/aest.2025.5756ENEsmaielFarmani GheshlaghiChemical Engineering, Amirkabir University of Technology, Tehran, IranFariborzRashidiChemical Engineering, Amirkabir University of Technology, Tehran, IranMajidAbdoussChemistry, Amirkabir University of Technology, Tehran, IranJournal Article20250125The global energy crisis, driven by climate change and fossil fuel dependence, necessitates sustainable solutions. MXenes and MBenes, two-dimensional transition metal carbides and borides, emerge as revolutionary photocatalysts for solar-driven energy conversion. Derived from MAX/MAB phases via selective etching, these materials exhibit tunable bandgaps (0.5–2.5 eV), metallic conductivity (>10,000 S/cm), and surface reactivity, enabling efficient visible-light harvesting, charge separation, and catalytic activity. Their integration in hybrid systems enhances hydrogen evolution rates (10-fold improvements) and CO₂-to-fuel conversion selectivity by suppressing charge recombination and stabilizing reaction intermediates. This review analyzes their synthesis, mechanistic roles in water splitting and pollutant degradation, and strategies like heterostructuring to overcome stability and scalability challenges. While MXenes/MBenes bridge renewable energy production with circular economy principles, eco-friendly synthesis and interdisciplinary collaboration remain critical to translating lab-scale innovations into scalable technologies. By addressing material durability and industrial integration, these materials offer a transformative pathway toward decarbonized energy systems, aligning global sustainability goals with advancements in materials science.https://aest.aut.ac.ir/article_5756_7ecd070e606afbf07a07c32e7267051f.pdf