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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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- Simulation of vacuum distillation unit in oil refinery: Operational strategies for optimal yield efficiency(MDPI, 2024-08-02) Muhammad, Shahrukh Atta; Haris, Khan; Muhammad, Ali; Rasikh, Tariq; Ahmed Usman, Yasir; Muhammad Mubashir, Iqbal; Sullah Ud, Din; Jaroslaw, Krzywanski; https://ror.org/040gykh71; https://ror.org/048g2sh07; https://ror.org/03ayjn504; https://ror.org/0566yhn94Oil refineries play a crucial role in meeting global energy demands, and optimizing the efficiency of critical processes is vital for economic feasibility and environmental sustainability. Simulation is an essential tool for the optimization of valuable products. This work presents the rigorous simulation of a vacuum distillation unit (VDU) based on actual data from the vacuum distillation processes using Aspen HYSYS V10. The Peng–Robinson fluid package is used in this simulation, and an input assay with a standard density of 29 API_60 (879.8 kg/m3) is employed. True boiling point (TBP) assay data are the type that is being used. Methane, ethane, propane, i-Butane, n-Butane, i-Pentane, and n-Pentane are the components listed in the simulation. The research determines that achieving a yield capacity of 685 tons/h requires thirty stages in the atmospheric distillation unit and twelve stages in the vacuum distillation unit while operating at 420 °C temperature and 9 kPa pressure. Adjustments in the flash section temperature (FST) and steam flow rate (SFR) are proposed to enhance operational efficiency. Increasing the FST from 370 °C to 400 °C and adjusting SFR from 10 tons/h to 26 tons/h increases the Light Vacuum Gas Oil (LVGO) yield by 7.2% while elevating the FST from 400 °C to 430 °C and adjusting SFR from 10 tons/h to 26 tons/h enhances the High Vacuum Gas Oil (HVGO) yield by 7.4%. These optimization strategies offer a practical and effective approach for refineries to improve the economic benefits of vacuum distillation units. The implications of this research can act as a computational thinking exercise for higher education students considering the case study where only through changing the operational strategies can the yield be enhanced by 10.81% in the vacuum distillation unit of the oil refinery.
- 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.
- Components of computational thinking in citizen science games and its contribution to reasoning for complexity through digital game-based learning: A framework proposal(Taylor and Francis, 2023-03-21) Alfaro Ponce, Berenice; Patiño Zúñiga, Irma Azeneth; Sanabria Zepeda, Jorge Carlos; Tecnológico de Monterrey; https://ror.org/03ayjn504Education has undergone many changes in teaching and learning, intensified by the significant technological developments that have responded to the fourth industrial revolution and other emergent situations. In this context, developing information and communication technologies has become vital in supporting new ways and learning models in the various educational levels to address a complicated environment where individuals must have complex and computational skills to respond to challenges. This study proposes a complex thinking framework that links citizen science and digital game-based learning to develop university students’ computational thinking skills. The results indicate that (a) it is possible to consider the sub-competencies of complex thinking in the design of a digital citizenscience game to develop computational thinking, and (b) the digital game-based learning framework for citizen science topics can potentially increase students’ engagement and teamwork in data collection and analysis while building their knowledge and computational thinking skills, and their complex thinking competency and sub-competencies.
- Educational challenges for computational thinking in K–12 education: A systematic literature review of “Scratch” as an innovative programming tool(MDPI journals, 2021-05-21) Montiel, Hugo; Gómez Zermeño, Marcela Georgina; Instituto Tecnológico y de Estudios Superiores de MonterreyThe use of information and communications technologies (ICTs) has emerged as an educational response amidst the COVID-19 pandemic, providing students the technological tools that enable them to acquire or strengthen the necessary digital skills to develop computational knowledge. The purpose of this study was to analyze Scratch, a programming language used to foster the teaching of computational thinking, particularly in K–12 education. A systematic literature review (SLR) was conducted, identifying 30 articles on the topic of Scratch and computational thinking in the database ProQuest Central from January 2010 to May 2020. These articles were analyzed to identify the use of Scratch worldwide and the educational impact it has on computational thinking, specifically in K–12 education. The results highlight the following: (1) countries which incorporated Scratch into their teachers’ study plans (curricula); (2) the transformation of learning environments that Scratch promotes; and (3) the importance of incorporating tools like Scratch in the current curricula and, more importantly, developing the framework for innovative ICTs capable of transforming education.