Thesis published in Dept. of M.E. http://103.99.128.19:8080/xmlui/handle/123456789/46 2026-10-05T13:29:22Z 2026-10-05T13:29:22Z Ahammed, Meraz ID:, 21MME007P http://103.99.128.19:8080/xmlui/handle/123456789/598 2026-10-04T06:19:04Z 2024-12-15T00:00:00Z

Title: Experimental Study on The Effect of Skin Friction Drag and Convective Heat Transfer for Pseudoplastic & Viscoelastic Fluid Flow. Authors: Ahammed, Meraz; ID:, 21MME007P Abstract: Drag reducing agents (DRAs) has a huge impact and a major concern in the engineering field and industrial applications. It makes the fluid flow turbulent to laminar, dampens eddy and reduces head loss by up to a certain limit and saves pumping energy costs. Viscosity is the property which dampens eddy due to viscous effect increases the fluidity up to a certain limit. Pseudoplasticity is the shear thinning effect that decreases viscosity when flowrate increases. So for viscoelastic effect we can increase the concentration up to a certain limit to reduce head loss but during flow due to pseudoplastic effect the viscosity will start decreasing which is negative effect. So these combined effect is studied to reduce skin friction drag in pipline and save energy cost which will be convenient for food industry, chemical and medicine industry. In this investigation, investigation is carried out for 0.3 g/L, 0.2 g/L and 0.15 g/L of xanthan gum in turbulent flow to observe the pressure drop and heat transfer rate. The study reveals that after increasing viscosity the pressure drop reduced significantly. Conversely the heat transfer rate also reduced due to poor mixing effect. A higher performance and less vibration of pump was also observed. It was concluded that frictional pressure drop was reduced up to 85% and heat transfer rate reduced up to 90% by increasing the concentration of the DRA(drag reducing agent) up to 0.3 g/L at 10 LPM than the pure water or base fluid as working substance on double pipe heat exchanger. As the heat transfer rate reduced up to 90% with reducing pressure drop so another aim of the study was to establish a concentration and flowrate for which heat transfer rate is maximum and it was found at concentration of 0.15 g/L of DRAs(drag reducing agents) at 22 LPM(maximum flowrate at this setup). Description: A Master of Science (M.Sc) Thesis in Mechanical Engineering (ME) Department at Chittagong University of Engineering and Technology (CUET)

2024-12-15T00:00:00Z Nuva, Tasnuva Jahan ID:, 20MME009F http://103.99.128.19:8080/xmlui/handle/123456789/594 2026-10-04T06:17:26Z 2024-11-03T00:00:00Z

Title: FAULT DETECTION IN METALLIC PRODUCT USING MACHINE LEARNING TECHNIQUES Authors: Nuva, Tasnuva Jahan; ID:, 20MME009F Abstract: In the realm of manufacturing, ensuring product quality is critical for maintaining operational efficiency and meeting customer satisfaction standards. Defect detection and anomaly identification are key elements of quality control processes. This thesis proposes a machine learning-based approach to the detection and segmentation of faults in metallic products, utilizing three advanced techniques: Mini Batch Dictionary Learning with Sparse Coder, a custom U-Net model, and DeepLabV3+ algorithms. The research focuses on six distinct metallic objects—cable, grid, metal nut, screw, transistor, and zipper—using the MVTec AD anomaly detection dataset, which includes both defective and defect-free images. For unsupervised anomaly detection, the Mini Batch Dictionary Learning method is employed, demonstrating high precision with an Average Precision (AP) score of 0.976 across the selected metallic objects. Additionally, a custom U-Net model is developed and trained for fault segmentation, providing detailed pixel-level detection of defects on metallic surfaces. The U-Net model achieved high accuracy levels, ranging from 87.92% to 99.59% for different object types, indicating its strong applicability in industrial environments. Finally, DeepLabV3+ model is incorporated to improve segmentation accuracy through the enhancement of defect detection and classification capabilities. The results of this study validate the effectiveness of machine learning algorithms in automating Defect detection in industrial products, thereby reducing human error, minimizing waste, and improving overall production quality. A comparative analysis demonstrates the competitiveness of the proposed approach against alternative algorithms. Future research should focus on refining the segmentation of faulty regions and exploring additional performance metrics. This study contributes significantly to the field of industrial anomaly detection, offering valuable insights into enhancing quality control procedures within industrial settings. Description: A Master of Science (M.Sc) Thesis in Mechanical Engineering (ME) Department at Chittagong University of Engineering and Technology (CUET).

2024-11-03T00:00:00Z NUPUR, SUROVI AKTAR http://103.99.128.19:8080/xmlui/handle/123456789/570 2026-09-06T05:38:34Z 2024-09-10T00:00:00Z

Title: Techno-Economic Feasibility Analysis of Integrated Heat Pump and Solar Cell Systems for Commercial Buildings Authors: NUPUR, SUROVI AKTAR Abstract: As economic feasilibity is one of the utmost tonality in every single thing exclusively in energy disciplines, it is consequential assesing the techno-economic feasibility of integrated heat pump and solar cell systems for commercial buildings. This thesis investigates the techno-economic feasibility of heat pump and solar system for the i4Health building at UiA considering performance evaluation, cost effectiveness, and environmental impact and a potential analysis of cost effectiveness towards 2040. In the beginning, Coefficient of Performance (COP) has been evaluated for the Ground Source Heat Pumps (GSHPs) to analyze the performance and Solar System’s (SS) performance has been analyzed on the basis of Performance Ratio (PR) and Solar Ratio (SR). Secondly, Annual cost savings from GSHPs and SS as well as the contribution of GSHPs and SS to the building’s economy along with the Payback Periods (PPs) indicate cost-effectiveness. An estimation model is developed presenting cost effectiveness towards 2040. Lastly, reduction of CO2 gas by GSHPs and SS of i4Health building has been estimated for analyzing environmental impact. Performance evaluation, cost-effectiveness, and environmental impact estimations are conducted using Python Programming and the model presenting a future scenario of cost effectiveness of GSHPs and SS for i4Health building has been developed by Multiple Variable Linear Regression Model (MVLRM) using Jupyter Notebook. The findings present that COP varies around 4.98-5.7 per week in cold weather and around 3.26-4.43 per week in warm weather. PR of solar system is 96% in 2022 whereas 89% in 2023. Solar system has highest SR in week 23 of 2023. Heat pump saves costing at 1.899 NOK/kwh in 2022 with a highest value in week 50 and 1 NOK/kwh in 2023 with a highest value in week 48. Solar system saves costing NOK 355121.69 in 2022 with a highest value in week 35 and NOK 122414.82 in 2023 with a highest value in week 24. From the cost savings model, NOK 398233.09, NOK 1474462.2, NOK 2902506.45 and NOK 3976269.33 is saved for the year 2025, 2030, 2035 and 2040 chronologically by heat pump and, at the same time NOK 293277.4, NOK 1612463.33, NOK 3370724.8 and NOK 4686860.5 is saved by solar system. The contribution of heat pump is 54.4% and 65.3% for the year 2022 and 2023 whereas the contribution of solar system is 60.27% and 56.59% at the same time. Payback period for heat pump is 16.33 years, and 30.63 years for solar system. This research also finds that heat pump and solar system reduce 32.28 ton and 36.05 ton CO2 in 2022 and, 35.66 ton and 33.69 ton in 2023. The thesis creates significant futute work opportunities. Description: A Master of Science (M.Sc) Thesis in Mechanical Engineering (ME) Department at Chittagong University of Engineering and Technology (CUET).

2024-09-10T00:00:00Z AHMED, MD. BAYAZID http://103.99.128.19:8080/xmlui/handle/123456789/569 2026-09-06T05:38:11Z 2024-09-10T00:00:00Z

Title: Conceptual Design of a Coupling Process of Hydrodynamic Cavitation and Hydrothermal Separation for Extractives and Biopolymers Extraction Authors: AHMED, MD. BAYAZID Abstract: Lignocellulosic biomass is an abundant and sustainable resource for producing biopolymers, chemicals, biofuels, and high-value-added compounds. The primary refining processes, which includes pretreatment, fractionation, and separation of components, as well as structural disconnection or partial structural change, are necessary to achieve high-value utilization of lignocellulosic materials. However, conventional pretreatment processes for biomass valorization aim to obtain high yields of cellulose without concern for utilizing other components. Focusing on a single component of lignocellulose is not only a waste of resources but also causes serious environmental pollution. This study proposed a novel and efficient biomass processing concept that, for the first time, couples two key technologies (hydrodynamic cavitation and hydrothermal separation) to enable almost all the biomass to be used for a range of high-valued products, including biopolymers and extractives. The conceptual design of coupling of hydrodynamic cavitation and hydrothermal separation was then modeled and simulated to evaluate the ease of coupling in terms of component yield and overall extraction efficiency and observed how the coupling process was affected by the process parameters with an optimal overall extraction efficiency. The simulation results showed that the coupling of the HC and HTS processes had a maximum of 25.5% higher overall extraction efficiency than the single HC process and 18.2% higher efficiency than the single HTS process for woodchips. The process parameters, including HTS temperature, HTS residence time, and S/L ratio affected component yield and overall extraction efficiency. The maximum overall extraction efficiency was predicted by the statistical approach of 80.20 ± 5.04% with a regression coefficient (R-sq) of 99.33% at optimal conditions (S/L ratio 10%, HC pressure 3 bar, HC temperature 60℃, HC residence time 20 min, HTS temperature 210 ℃, HTS residence time 25 min, and HTS pressure of 19.04 bar). The coupling of hydrodynamic cavitation and hydrothermal separation showed better biomass utilization than the conventional pretreatment processes. This coupled process focuses on more utilization of biomass rather than only one yield, which will reduce the waste with minimal environmental effect and increase the potential use of biomass from different perspectives. Description: A Master of Science (M.Sc) Thesis in Mechanical Engineering (ME) Department at Chittagong University of Engineering and Technology (CUET).

2024-09-10T00:00:00Z