Grup de Recerca en Energia i Intel·ligència Artificial (GREiA) (INSPIRES)
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The GREiA research group (Research group in energy and artificial intelligence) is born from the union of the research group in energy GREA and the research group in artificial intelligence IA. The collaboration of these two groups begins in 2014.
The general line of research that defines the activity of the group is to provide answers and solutions related to the fields of energy engineering, industrial and construction design, sustainability and intelligence artificial. [Més informació]
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Recent Submissions
- ItemOpen AccessCompatibility of carbonate mixtures to be used as molten salts with different metal alloys to be used as container materials(2025) Cabeza, Luisa F.; Martínez, Franklin R.; Borri, EmilianoThe energy transition can only be achieved if the global energy sector is transformed from a fossil-based system to a zero-carbon-based source system. To achieve this aim, two technologies have shown promising advances in high-temperature application. Concentrating solar power (CSP) plants are seen as a key technology to achieve the needed energy transition, and carbon dioxide (CO2) capture and storage (CCS) is a promising technology for decarbonizing the industrial sector. To implement both technologies, molten carbonate salts are considered promising material. However, their corrosive behavior needs to be evaluated, especially at high temperatures, where corrosion is more aggressive in metal structures. This paper presents an experimental evaluation of the static corrosion of two molten carbonate salts, a Li2CO3-Na2CO3-K2CO3-LiOH·H2O (56.65-12.19-26.66-4.51wt.%) mixture and a Li2CO3 salt, under an air atmosphere with five corrosion-resistant metal alloys, including Alloy 600, Alloy 601, Alloy 625, Alloy 214, and Alloy X1. In this study, the corrosion rate and mass losses were quantified. In addition, in all the cases, the results of the experimental evaluation showed corrosion rate values between 0.0009 mg/cm2·yr and 0.0089 mg/cm2·yr.
- ItemOpen AccessOptimizing the design of TES tanks for thermal energy storage applications an integrated biomimetic-genetic algorithm approach(2025) Mehraj, Nadiya; Mateu Piñol, Carles; Zsembinszki, Gabriel; Cabeza, Luisa F.Building upon an experimentally validated bio-inspired thermal energy storage (TES) tank design, this study introduced a novel computational framework that integrated genetic algorithms (GA) with biomimetic principles to systematically generate TES tank geometries. Inspired by natural thermal distribution patterns found in vascular networks, the AI-driven methodology explored 13 geometric parameters, focusing on branching structures and spatial distribution, and resulted in computationally generated designs with a 29% increase in heat transfer surface area while maintaining manufacturability constraints within a fixed tank diameter of 150 mm and height of 155 mm. Unlike previous biomimetic TES studies that relied on predefined geometric configurations, this approach developed AI-driven bio-inspired structures within experimentally validated dimensional constraints, ensuring geometric relevance while allowing for broader structural exploration. The resulting designs exhibited key characteristics of high-efficiency bio-inspired configurations while providing a systematic, scalable methodology for TES tank architecture. This study represented the first step in integrating AI-driven biomimicry into TES tank design, establishing a structured framework for generating high-performance, manufacturable configurations. While the current work focused on computational design, future research will emphasize experimental validation and real-world implementation to confirm the practical thermal and structural benefits of these AI-generated bio-inspired designs. By bridging the gap between computational intelligence and nature-inspired engineering, this research provided a scalable pathway for developing more efficient, manufacturable, and sustainable TES solutions for energy storage applications.
- ItemOpen AccessModeling of TES Tanks by Means of CFD Simulation Using Neural Networks(MDPI, 2025) Rojas Cala, Edgar F.; Béjar Torres, Ramón; Mateu Piñol, Carles; Borri, Emiliano; Romagnoli, Alessandro; Cabeza, Luisa F.Modeling of thermal energy storage (TES) tanks with computational fluid dynamics (CFD) tools exhibits limitations that hinder the time, scalability, and standardization of the procedure. In this study, an innovative technique is proposed to overcome the challenges in CFD modeling of TES tanks. This study assessed the feasibility of employing neural networks for TES tank modeling, evaluating the similarities in terms of structure and signal-to-noise ratio by comparing images generated by neural networks with those produced through CFD simulations. The results regarding the structural similarity index indicate that around 94% of the images obtained have a similarity index above 0.9. For the signal-to-noise ratio, the results indicate a mean value of 25 dB, which can be considered acceptable, although indicating room for improvement. Additional results show that our neural network model obtains the best performance when working with initial states close to the stable phase of the TES tank. The results obtained in this study are promising, laying the groundwork for a future pathway that could potentially replace the current methods used for TES tank modeling.
- ItemOpen AccessExperimental characterization of phase change materials for thermal energy storage in the temperature range between 270 °C and 400 °C(Elsevier, 2025) Martínez, Franklin R.; Borri, Emiliano; Ushak, Svetlana; Mani Kala, Saranprabhu; Prieto, Cristina; Cabeza, Luisa F.Thermal energy storage (TES) with phase change materials (PCM) is an interesting technology to be used to improve the energy efficiency of industrial processes, contributing to their decarbonization and the integration of renewable energy sources. Even though literature lists many materials that can be used as PCM in the temperature range between 270 °C and 400 °C, most of them lack a full characterisation, jeopardising their potential implementation by practitioners and scientists. Therefore, this paper presents a complete experimental characterisation of 24 PCMs, with melting temperature, melting enthalpy, degradation temperature, and thermal conductivity in the solid state (at room temperature) determination. Moreover, corrosion tests with two different stainless-steel fibres and with Alloy 20 fibres is presented. The findings obtained in the characterization highlight the necessity of these analyses, as notable differences were observed compared to the available data, particularly in thermal stability and thermal conductivity. Moreover, the findings obtained in the compatibility test reveals that out of the 24 selected PCMs, 11 are potentially compatible with Alloy 20, and 8 with both stainless-steel fibres under environmental conditions (air atmosphere). Finally, the results presented will allow researchers and practitioners to have very detailed data on the characterisation of those PCMs.
- ItemOpen AccessPhase change materials for thermal energy storage in industrial applications(Elsevier, 2025) Martínez, Franklin R.; Borri, Emiliano; Mani Kala, Saranprabhu; Ushak, Svetlana; Cabeza, Luisa F.This study reports the results of the screening process done to identify viable phase change materials (PCMs) to be integrated in applications in two different temperature ranges: 60–80 °C for mid-temperature applications and 150–250 °C for high-temperature applications. The comprehensive review involved an extensive analysis of scientific literature and commercial material datasheets. A total of 65 PCMs for mid-temperature applications and 36 PCMs for high-temperature applications were identified through this extensive search. Moreover, an extensive experimental characterization of 14 preselected PCMs is included. Experimental techniques including differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and hot disk were used. The values obtained were compared to the ones found in the available literature and technical datasheets to see potential differences in the thermal behavior.