Browsing by Autor "Andrés González-Mancera"
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Item type: Item , Ai-Powered Dynamic Fault Detection and Performance Assessment in Photovoltaic Systems(RELX Group (Netherlands), 2024) Nelson Salazar-Peña; Alejandra Tabares; Andrés González-ManceraItem type: Item , Ai-Powered Dynamic Fault Detection and Performance Assessment in Photovoltaic Systems(RELX Group (Netherlands), 2025) Nelson Salazar-Peña; Alejandra Tabares; Andrés González-ManceraItem type: Item , Characterization and Computational Validation of Multi-Layer Carbon Fiber Based Polymer Matrix Composite Material for Rocket Engine Combustion Chamber Applications(2025) Santiago Gonzalez Buenaventura; Fabio Arturo Rojas Mora; Andrés González-ManceraAbstract Carbon Fiber Reinforced Polymers (CFRPs) have enormous potential for weight reduction in load bearing components. This study explores their viability as an alternative material for rocket engine combustion chambers through the redesign of the hybrid rocket engine ‘Ragnar X’. Aiming to increase its Thrust/Weight ratio through the replacement of its combustion chamber steel cylinder for one developed in a CFRP-based multi-fiber composite structure. To overcome the challenge of using Carbon Reinforced Polymers for high temperature applications (2000K), an initial layer of ceramic wool was included as thermal insulation to reduce heat transfer. The mechanical properties of the CFRP were characterized according to the ASTM D3039 method [1]. This process was adapted to determine the variation of the ultimate strength with respect to the environment’s temperature. The results indicate a valid ultimate strength for the design for temperatures under 190°C. A multi-step computational validation was used to determine the thermal conditions and heat transfer the engine would be subjected to during operation. The results in conjunction with the characterization show that the engine can withstand its logistical maximum of 40 seconds of operation without failure and up to a theoretical 73 seconds of continuous operation before failure. The prototype manufactured based on the theoretical design managed to reduce the combustion chamber’s weight almost by a factor of 2 and increased the Thrust/Weight ratio from 8.58 to 15.52.Item type: Item , Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets(RELX Group (Netherlands), 2026) Nelson Salazar-Peña; Alejandra Tabares; Andrés González-ManceraItem type: Item , MARLEM: A Multi-Agent Reinforcement Learning Simulation Framework for Implicit Cooperation in Decentralized Local Energy Markets(RELX Group (Netherlands), 2025) Nelson Salazar-Peña; Alejandra Tabares; Andrés González-Mancera