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    Thermo-economic Analysis and Multi-Objective Optimization of Advanced Three-Stage Cascaded Refrigeration Technologies
    (Department of Mechanical and Production Engineering(MPE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh, 2024-11-30) Nabil, Mahdi Hafiz
    The rising global demand for refrigeration, driven by industrial, medical, and technological needs, necessitates advancing highly performing and environment-friendly cooling technologies. This study explores advanced refrigeration techniques to address the limitations of conventional vapor-compression refrigeration (VCR) systems, particularly in ultra-low temperature (ULT) applications. While widely used, conventional VCR systems suffer from significant performance degradation at temperatures lower than -40°C, primarily due to excessive compression ratios and high discharge temperatures. To overcome these challenges, cascade refrigeration systems (CRS) have emerged as a promising alternative, enabling ultra-low temperatures (ULT) by combining multiple refrigeration cycles. This research presents the modelling and analysis of two novel advanced three-stage cascade refrigeration systems: an advanced triple cascade refrigeration system (ATCRS) and an ejector-enhanced advanced triple cascade refrigeration system (EATCRS). The ATCRS integrates a suction-line heat exchanger (SLHX) and flash tank (FLT) to enhance thermodynamic performance, achieving an 8.57% improvement in coefficient of performance (COP) and a 7.24% increase in second law efficiency over traditional cascade systems. The EATCRS incorporates an ejector system in the medium-temperature circuit (MTC), further improving system efficiency. Compared to the ATCRS, the EATCRS demonstrates a 32.82% increase in COP and a 27.34% boost in exergy efficiency, significantly outperforming conventional systems as well as the ATCRS. Moreover, the economic analysis indicates that despite an initial 9.78% increase in annual costs due to the ejector integration, the EATCRS achieves a 25.73% reduction in costs compared to other advanced systems. This study fills a critical gap in the current research by providing a comprehensive analysis of three-stage cascade refrigeration systems equipped with advanced VCR modifications along with multi-objective optimization of both systems using ANN-based genetic algorithm identifying optimal operating points ensuring the maximum possible performance by keeping the system cost within acceptable limit. The results highlight the potential of these systems to accommodate the increasing demand for ultra-low temperature refrigeration while addressing critical environmental and economic concerns. This work lays the foundation for future research aimed at optimizing refrigeration systems to ensure energy sustainability and environmental protection.
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    A Machine Learning Based Modeling and Analysis of Solar-Assisted Thermal Power Plant in Bangladesh
    (Department of Mechanical and Production Engineering(MPE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh, 2024-10-30) Hasan, Muhammad Mahmood
    Global climate change, driven by carbon emissions from fossil fuels, has accelerated the global transition toward renewable energy sources. A major challenge with renewable energy, particularly solar energy, is its intermittency, which makes accurate forecasting crucial for effective energy management. This thesis addresses two critical aspects of solar energy utilization forecasting Direct Normal Irradiance (DNI) to enhance the reliability of solar energy production and optimize the energy management of a solar-assisted regenerative Rankine cycle to maximize power generation using available solar resources. These two studies complement each other by focusing on both the prediction of solar energy availability and the efficient utilization of that energy in a thermal power plant. The first study explores advanced statistical, ensemble, and deep learning models for short-term DNI forecasting in Bangladesh. By analyzing geographical data and identifying optimal solar energy locations, the study applies models such as Facebook Prophet, SARIMAX, XGBoost, Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Artificial Neural Networks (ANN). The performance of each model was evaluated using error metrics like R^2, MAE, MSE, and RMSE. Among machine learning models, XGBoost performed the best (MAE: 2.70, R^2: 0.93), while CNN was the top-performing deep learning model (MAE: 2.33, R^2: 0.991), demonstrating the effectiveness of these approaches in forecasting solar irradiance. Building on these predictions, the second study focuses on optimizing power generation in a solar-assisted regenerative Rankine cycle. The study examines various repowering configurations by closing one or more of the six feedwater heater (FWH) extractions and integrating solar energy from a Concentrated Solar Power (CSP) plant. Depending on DNI availability, the heat from the CSP plant is either used directly or stored in a Thermal Energy Storage (TES) system to be utilized during peak electricity demand. By simulating different DNI conditions, the study found that repowering could enhance the original cycle's 200 MW output to a maximum of 241.3 MW, depending on the closed extractions and thermal input from the solar system. However, this increase in power output was accompanied by a decrease in thermal efficiency from 43.63% to 39.45%, which is justified as additional power input is provided by solar energy. The study simulated energy management during the operation of the power plant, exploring various repowered cycle configurations to ensure the efficient utilization of solar energy. This energy, whether received directly or from the Thermal Energy Storage (TES) system, was optimized to meet the varying electricity demands. Together, these studies form a comprehensive approach to addressing the challenges of intermittent solar energy. Accurate DNI forecasting ensures reliable energy availability, while efficient management of solar energy within the Rankine cycle ensures optimal power generation. This combined approach not only supports Bangladesh’s commitment to Sustainable Development Goal 7 (SDG 7) but also offers broader insights into the integration of renewable energy in thermal power plants globally.
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    Thermal Analysis and Multi-Objective Optimization of Cascaded and Advanced Absorption Refrigeration Technologies
    (Department of Mechanical and Production Engineering(MPE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh, 2024-05-25) Khan, Yasin
    This thesis presents an in-depth analysis of advanced modifications of absorption refrigeration systems, with the primary aim of enabling these systems to operate at reduced evaporator temperatures while achieving higher performance. This detailed study marks a significant advancement in refrigeration technology, specifically in the realm of cascade compression absorption refrigeration systems and the advancement of standalone ARC. The goals of this research are to collectively address critical challenges faced by traditional refrigeration cycles, such as energy inefficiency, high compressor power requirements, and environmental concerns, through a comprehensive approach. The research encompasses the development and simulation of sophisticated cascade compression-absorption refrigeration setups and novel stand-alone absorption system frameworks. Initially, the study focuses on the integration of modified ARC (Absorption Refrigeration Cycle) and advanced RAC (Recompression Absorption Cycle) with enhanced VCRs, incorporated with an ejector to develop advanced proposed novel cascaded configurations: Ejector Compression Absorption Cycle (ECAC), Ejector Injection Compression Absorption Cycle (EICAC), Ejector-Compression Recompression Absorption Cycle (E-CRAC) And Ejector enhanced vapor-Injection Compression Recompression Absorption Cycle (EI-CRAC). Furthermore, the study pioneers the adaptation of novel stand-alone absorption system frameworks, incorporating ejector-injection and recompression technologies to develop Refrigerant Ejector enhanced Recompression Absorption Cycle (RE-RAC) and Vapor Injection enhanced Recompression Absorption Cycle (VI-RAC). Both the advanced cascaded and stand-alone configurations undergo extensive analysis from energy and exergy perspectives, coupled with multi-objective optimization. Utilizing Artificial Neural Network (ANN)-based predictive models, the research meticulously assesses thermal performance, establishing optimal operating conditions and identifying operational limits. This comprehensive evaluation offers profound insights into the systems' behaviors across a spectrum of conditions, enriching our understanding of their potential and constraints in various application scenarios. The findings reveal that the proposed systems significantly outperform traditional systems in terms of Coefficient of Performance (COP) and exergy efficiency. Specifically, ECAC and EICAC systems achieve approximately 15% and 6% higher COP, respectively, compared to conventional cascade systems when using the R41-LiBr/H2O refrigerant. Additionally, EICAC and ECAC show significant improvements in exergy efficiency, up to 20% and 10%, respectively, with optimal performance around 77℃ generator temperature. Furthermore, the research explores RAC based proposed cascaded systems: one basic CRAC and two advanced configurations: E-CRAC and EI-CRAC. They significantly outperform the traditional CARC system, with the COP being nearly three times higher. EI-CRAC and E-CRAC show a COP enhancement of about 10% and 20%, respectively, along with an increase in exergy efficiency of 15% and 25% over CRAC, indicating superior efficiency in cooling operations. Finally, this research introduces novel stand-alone recompression absorption refrigeration systems integrating ejector-injection setup to replace expansion valves (RE-RAC and VI-RAC). RE-RAC and VI-RAC significantly outperform conventional ARC and RAC systems. The COP of RE-RAC and VI-RAC is 76% and 63% higher than the conventional RAC system, respectively, despite RE-RAC requiring more external heat generation due to VI-RAC’s additional compressor demands. This research contributes novel insights into the field of refrigeration by analyzing the integration of advanced absorption and compression technologies, providing a pathway for the development of more efficient and environmentally friendly refrigeration systems. The comprehensive analysis from both energetic and exergetic perspectives offers valuable guidance for future improvement and optimization, potentially revolutionizing cooling applications with lower environmental impact. Implementing these systems in real-life scenarios, such as power plants and various industries (e.g., textile, manufacturing, steel), can enhance waste heat utilization by achieving lower evaporator and generator temperatures with higher performance, making them suitable for efficiently using low-grade energy.
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    Thermal Assessment and Performance Evaluation of Evacuated Flat Plate Collector
    (Department of Mechanical and Production Engineering(MPE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh, 2024-06-11) Rahman, Md. Ashiqur
    The transition towards renewable energy technologies is gaining momentum, especially within industrial domains seeking sustainable alternatives to traditional energy sources. Among these technologies, the Evacuated Flat Plate Collector (EFPC) stands out as a promising solution, amalgamating the advantages of both Flat Plate Collector (FPC) and Evacuated Tube Collector (ETC). This thesis delves into an in-depth performance analysis of EFPC. Utilizing a meticulously validated mathematical model, the study explores the study of three crucial design parameters—tube diameter, spacing, and absorber plate thickness—while investigating their impact on four key performance indicators: outlet temperature, overall heat loss coefficient, thermal efficiency, and exergy efficiency. It has been found that for an industry where daily 500 tons water is heated from 25°C to 100°C, the tube diameter should be around 12 mm and the distance between the tubes should be around 180 mm to get the maximum performance from the collector. The optimum absorber plate thickness should be around 0.2 mm for the mentioned case. Through rigorous energy and exergy analyses, the study elucidates the sensitivity of these parameters to fluid temperature, flow rate variations, and solar irradiance fluctuations across different seasons, thereby providing comprehensive insights into EFPC's performance under diverse climatic conditions. Energy and exergy analyses conducted under varying environmental conditions provide valuable insights into the operational efficiency of EFPC. By simulating different inlet fluid temperatures, flow rates, and solar irradiance levels, the study demonstrates the collector's adaptability to various boundary conditions. In the studied case, the thermal performance significantly improves with increasing flow rates up to approximately 0.003 kg/s, beyond which the improvement becomes negligible. Analysis indicates that the current system operates optimally when the inlet temperature is below 350K. If the inlet temperature surpasses this threshold, both thermal efficiency and exergy efficiency decrease, adversely affecting the system's overall performance. From off design performance analysis, it has been observed that during summer, higher solar irradiance enhances the collector's performance, while in winter, the efficiency drops slightly due to lower irradiance levels. However, EFPC maintains a relatively high efficiency across all seasons, making it a reliable choice for continuous industrial applications. The economic analysis of EFPC highlights its potential for significant cost savings. By supplying a substantial portion of the heat demand, EFPC reduces reliance on conventional energy sources, leading to lower fuel costs. The daily savings of 45.57%, when extrapolated over a year, translate to considerable financial benefits for the industry. Additionally, the reduction in CO2 emissions by up to 3.915 tons in summer underscores the environmental advantages of adopting EFPC technology. This aligns with global efforts to reduce carbon footprints and combat climate change, making EFPC an attractive option for industries aiming to achieve sustainability goals. In addition to its performance analysis, EFPC's comparative advantage over traditional FPC and ETC collectors is underscored, positioning it as a superior choice for industrial applications. It is notable that when the inlet temperature is 340 K, the exit temperature of the FPC is 341.33 K, indicating that FPC is not recommended for higher temperature applications. Both EFPC and ETC outperform the FPC at higher inlet temperatures, with no significant difference in performance between EFPC and ETC. At lower solar irradiation, the thermal efficiency of the FPC is significantly lower compared to EFPC and ETC. However, as solar irradiation increases, the thermal efficiency of the FPC also increases, reaching 81.89% at 1000 W/m². ETC demonstrates the highest thermal efficiency at around 82.7%, followed closely by EFPC with a deviation of approximately 1%. The study extends its scope to explore EFPC's integration into the Absorption Refrigeration Cycle (ARC), highlighting its versatility and potential for sustainable energy solutions across various industrial sectors. By offering assessment of EFPC's performance, economic viability, and environmental impact, this research contributes to the broader understanding of solar energy utilization and aids decision-making processes for implementing sustainable energy solutions in industrial contexts. This research provides a detailed evaluation of EFPC, emphasizing its technical, economic, and environmental benefits. The findings support the adoption of EFPC in industrial settings, highlighting its potential to enhance energy efficiency, reduce costs, and mitigate environmental impact. Future studies should focus on long-term performance monitoring and explore the integration of EFPC with other renewable energy systems to further optimize its application in various industrial processes.
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    Investigation of the NOx and SOx Emissions from Large-Scale Coal-Based Power Plants
    (Department of Mechanical and Production Engineering(MPE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh, 2024-06-12) Firoz, Mahmudul
    Coal-fired power plants are a pivotal source of energy in Bangladesh, a country with abundant coal reserves. Yet, the environmental and health risks linked to the greenhouse gas emissions from these plants are significant contributors to climate change. The international framework, including agreements like the Kyoto Protocol, enforces strict limits on emissions, focusing the need for improved environmental compliance. Specific attention is given to the temporal analysis of COx emissions, revealing trends in global CO2 emissions from fuel sources between 2001 and 2022, alongside a detailed examination of NOx, SOx, and other volatile organic compound emissions in relation to socio-economic factors such as GDP, population, and per capita metrics. This thesis focuses on the Barapukuria Thermal Power Plant (BTPP), Bangladesh's first coal-based power station, which operates with sub-critical steam technology. The plant utilizes bituminous coal and is equipped with boilers that handle a flow rate of 40 tonnes per hour at 80% load conditions, featuring a detailed configuration of burners and air nozzles. The primary objective of this thesis is to analyze the current GHGs emission characteristics of BTPP. Using the commercial CFD software ANSYS 2020R2 Fluent, the thesis investigates on various oxidizing cases including standard air-firing (AF) and multiple oxy-firing (OF) conditions, across three loading levels: 50%, 80%, and 100%. The emission pattern which are investigated in this study can be implemented in modern coal-fired power stations to reduce emissions of recalcitrant pollutants like COx (Carbon oxides), NOx (Nitrogen Oxides), and SOx (Sulfur oxides). This comprehensive study utilizes advanced numerical methodology to model the chemical kinetics of combustion, detailing the dynamic interactions between turbulence and reaction mechanisms in various oxidizing environments. The model’s accuracy is validated by comparing the predicted flue gas temperatures with actual plant data, demonstrating a satisfactory alignment. The results reveal distinct variations in flame temperature across different oxy-fired (OF) scenarios, with the lowest temperatures observed in the OF23 case and the highest in OF31. Notably, the maximum flame temperatures increase with higher coal and airflow at 100% fuel loading, correlating directly with the loading levels. Velocity patterns of the flue gases also indicate that higher loadings accelerate the flow, contributing to increased velocity, particularly in the OF31 scenario. The study examines the highest CO2, NO, NO2, N2O and SO2 concentrations in the AF (Air Fire) scenario in all loads conditions, e. g. CO2, NOx and SOx emission exceeds 400 ppm (AQI standard, DOE, Bangladesh) which is attributed to enhanced pollutants capture techniques which reduce emissions patterns in OF23 to OF31 compared to AF23. This thesis explores the heat reaction rates, labeled as Heat Reaction Rate 1(devolatilization rate) and Heat Reaction Rate 2 (Char burnout rate), crucial for understanding the kinetics of coal combustion under different firing conditions. These rates are instrumental in optimizing combustion efficiency and reducing emissions. The analysis of NOx formation includes fuel, prompt, thermal, and intermediate N2O, NOx rates, comparing scenarios from AF to OF31. The outcomes are graphically represented, providing a clear comparison of NOx emissions in parts per million (PPM), enhancing the understanding of emission patterns under varying operational conditions. Hence, the sustainable scrubbing approach is a progressive new direction with exciting potential in the fields of technology and the economy. Adapting to the climate concern and clean energy is the focus of Sustainable Development Goal (SDG) 7 (Affordable and Clean Energy) and 13 (Climate Action). It is of the utmost importance to consider the long-term goal of reducing emissions by the year 2050 or it will get worse. This would also pave the way for the retrofitting of existing power stations to open the gateway of sustainable generation of green electricity.