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Permanent URI for this collectionhttps://hdl.handle.net/11285/345284
Artículo científico o editorial en una publicación periódica académica sujeto a revisión de pares. Cumple con los índices internacionales o bases de datos de amplia cobertura, como el listado del Current Contents, ISI WEB of Knowledge (http://isiknowledge.com/) e índice de revistas mexicanas de CONACYT (www.conacyt.mx/dac/revistas). Éstos indizan y resumen los artículos de revistas seleccionadas, en todas las áreas del saber.
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- Comparative multi-objective optimization using neural networks for ejector refrigeration systems with LiBr and LiCl working agents(Science Direct, 2024-08) Khanmohammadi, Shoaib; Ahmadi, Pouria; Jahangiri, Ali; Izadi, Ali; Tariq, Rasikh; https://ror.org/05hkxne09; https://ror.org/05hkxne09; https://ror.org/05vf56z40; https://ror.org/0091vmj44; https://ror.org/03ayjn504Education's evolution in the context of energy systems is essential for addressing sustainable energy challenges and developing a workforce equipped for future innovations, emphasizing both formal curricula and informal lifelong learning through successful energy case studies. As the global energy sector transforms to reduce carbon emissions and reliance on fossil fuels, innovations in renewable technologies like solar thermal are pivotal for promoting energy security and economic stability, supported by an educational foundation that fosters awareness and technical skills for sustainable development. Exposure to successful renewable energy systems, such as solar-powered refrigeration, offers an informal educational experience that enhances understanding and supports global educational goals, initiating with the innovative design and optimization of these systems using artificial intelligence (neural networks). Based on this formulation, the current article developed two sustainable energy systems by comparing the refrigeration cycles with two different operating fluids and various arrangements, and multi-objective optimization with an evolutionary genetic algorithm is performed for the proposed systems. The studied systems are refrigeration cycles using an ejector and without an ejector with two working fluids of lithium bromide and lithium chloride. The present work's main aim is to examine the working fluid and refrigeration system arrangements. Energy and economic modeling were performed for the proposed systems, and then parametric analysis and two-objective optimization were extracted. Parameters such as generator temperature, condenser temperature, absorber temperature, and evaporator temperature, which significantly impact the proposed system's performance, have been selected as decision parameters, and parametric analysis has been extracted for them. In addition to the mentioned parameters, diffusion mixing efficiency, nozzle efficiency, and heat exchanger have also been studied in the ejector asset system. To find the best values of decision variables, multi-objective optimization for both arrangements is conducted, and results are presented. The results have indicated that the refrigeration system using lithium chloride working fluid without an ejector achieves a coefficient of performance of 0.766 and a cost of 0.922 $/h at the optimal point, while the system with an ejector yields a higher coefficient of performance (1.047) and a slightly lower cost rate (0.991 $/h). The outcomes of this work can play a critical role for higher education institutions in advancing innovative solutions to pressing energy challenges. Lifelong learning, at the heart of educational innovation, can benefit from the integration of sustainable energy systems as a core component of informal education through the optimization of ejector refrigeration systems.
- Synergy of Internet of things and education: cyber-physical systems contributing towards remote laboratories, improved learning, and school management(2024-06) Tariq, Rasikh; Casillas Muñoz, Fidel Antonio Guadalupe; Hassan, Syed Tauseef; Ramírez Montoya, María Soledad; https://ror.org/03ayjn504; https://ror.org/041sj0284The modern Industrial Revolution has ushered in a wave of technological advancements, including the proliferation of over 20 billion digital identities associated with the Internet of Things (IoT) devices worldwide. Amid this complexity, IoT has emerged as a beacon of hope, offering multitudinous solutions from the perspectives of school management, instructors, and learners. The prime objective of this article is to review the current state-of-the-art in IoT and education specifically in areas like remote laboratories, improved learning, and school management. The implemented method is systematic literature review of IoT technology's practical applications and case studies to meet these key educational stakeholders' unique needs. The studies focus on remote labs, learning experiences, and campus administration. This comprehensive analysis gathered data from sources like Scopus and WoS and summarized insights from 122 articles. These cases encompass the foundational principles of IoT, its diverse applications in higher education, its challenges, and future avenues for research. Our findings indicate that (a) the implementation of IoT-based remote laboratories has transformed engineering education by enhancing the safety and operational efficiency of labs, improving students' comprehension of complex concepts, and facilitating a more interactive and engaging educational experience, (b) the integration of IoT systems within educational settings has profoundly enhanced both teaching and learning experiences by creating interactive, immersive environments and significantly improving student engagement and understanding through personalized and hands-on learning approaches, and (c) the integration of IoT technology within educational administration has significantly advanced the digitalization of traditional school management systems, enhancing administrative efficiency in areas such as schedule management, student records, and financial operations through automation, thereby streamlining processes and enhancing responsiveness in educational institutions. However, it must be noted that the current infrastructure, particularly in public universities, often falls short of fully harnessing IoT technologies to optimize the learning experience. Investments in infrastructure, teacher training, and curriculum design are imperative to fully leverage IoT's benefits for education.