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    DEVELOPMENT OF AL-BASED METAL MATRIX COMPOSITES REINFORCED WITH HYBRID NANO PARTICLES AND ITS MACHINABILITY TEST
    (2024-09) KABIR NAYEEM, MUHAMMED HASNAIN
    Aluminum is a significant material for all type of manufacturing industries due to its wide range of alloys and composites. Despite the fact that aluminum alloys have been used in a wide range of industries due to their excellent and diverse functional characteristics, composite materials can be modified to provide specific mechanical and tribological properties. An aluminum alloy with lesser hardness and tensile strength has been strengthened dramatically by adding ceramic reinforcements. This study aims at formulate and develop hybrid particle reinforced Al-metal matrix composites using stir casting method, a novel fabrication process in our country to fabricate metal matrix composite. Also, followed by investigation of its the physical, mechanical, morphological and machinability characteristics of the developed metal matrix composites. Three unique compositions of composites have been obtained by varying the wt. % amount of carbon nanotube, alumina and silicon carbide particulate reinforcements respectively 1%, 2.5% and 2.5%. Various mechanical properties, essentially the tensile strength, flexural strength, hardness, impact resistance; and physical properties like porosity, and density were tested; and a morphological and machinability study has been carried out for investigating the performance of the newly developed composites. The study showed that there was an 128.57% increment of tensile strength, an 7.1349% increment of hardness, an 45% increment of impact resistance, and a 0.8301% reduction of density by adding the particulate reinforcements in aluminum metal matrix composite. The morphological analysis demonstrated a more homogenous dispersion of reinforcement particles in the composite, which indicated the effectiveness of the stir-casting fabrication method. From the optimized machining parameters, it was evident that higher cutting speed and feed rate can be obtained by introducing multiple particulate reinforcement in the metal matrix, which eventually increased the productivity, efficiency and product quality of the developed composites.
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    EXPERIMENTAL INVESTIGATION OF ELECTROMAGNETIC BEHAVIOR OF ALUMINA REINFORCED COPPER MATRIX COMPOSITES
    (2024-02) ISLAM, TARIQUL
    Copper is the third highest used metal in the industry because of its excellent electrical conductivity (100% IACS) with relatively high hardness at room temperature. However, the continuous degradation of mechanical performance of pure copper with increasing temperature eventually limits its use for electronic construction, especially for high temperature applications. Moreover, due to the conventional theoretical assumption of electromagnetic properties of metallic copper, scientists hardly made attempts to reveal the potential applicability of copper for next generation technology. In this research, attempts have been made to overcome the high temperature degradation of pure copper using trace addition of nano-crystalline Al2O3 particle as well as to evaluate the corresponding electromagnetic performance of copper. 99.99% pure copper was subjected to reinforcement using 0.5%, 1%, 2% and 5% white Al2O3 particles through conventional sand stir casting technique. The little percentage of Al2O3 made significant impact on the mechanical and electromagnetic properties of copper, especially when subjected to thermal treatments. The microhardness of Cu-Al2O3 composite increased with the increase of annealing temperature up to 6000C according to Hall Petch theory. The electrical conductivity was found to be very close to that of copper observed at room-temperature condition. The diamagnetic behavior of copper was transformed to paramagnetic behavior with the trace addition of Al2O3 particles, which was further influenced significantly by the thermal treatments. Dielectric behavior of pure copper was also investigated and the result of which were justified using Jonscher’s theory of colossal permittivity. The present investigation suggested that the proper selection of composition and appropriate post thermal treatment can improve the mechanical as well as electromagnetic property of Cu-Al2O3 composite, thereby revealing the potential applicability of copper for future high-temperature/power applications.
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    DEVELOPMENT OF EPOXY COMPOSITES REINFORCED WITH CARBON NANOTUBE AND NATURAL FIBER FOR COMMERCIAL APPLICATIONS
    (2023-09) BHADRA, DEBANAN
    The global economy has gone through significant alterations in recent years, particularly after Covid-19 epidemic, with an increasing importance on biodegradability, resource effieacy, as well as environmental responsibility. Keeping that in mind, this study focuses on developing composite materials with Epoxy resin as matrix material, natural fibers as reinforcements and Multi-Walled Carbon Nanotubes (MWCNT) as nanofiller. This present study is intended to develop natural fiber and MWCNT reinforced epoxy composites with a view to investigate their physical and mechanical properties, as well as to model the mechanical properties using Finite Element Method (FEM). However, as there are lot of different natural fibers with varying mechanical properties, this study has employed a fuzzy Multi Criteria Decision Making method to select the best natural fibers among twelve alternatives and found that the pineapple fiber and coir fiber are the top two candidates among different fibers. Therefore, this study used pineapple, coir, and sisal fiber as natural fiber reinforcements. Alkali treatment using sodium hydroxide (NaOH) was employed for surface modification of natural fibers, enhancing their compatibility with the epoxy matrix. Moreover, ultrasonication technique was used for achieving uniform dispersion of CNTs within the epoxy matrix. Different physieal properties such as, density, void contents, and water absorption, as well as some mechanical properties such as tensile strength, Young's modulus, elongation at break, flexural strength, flexural modulus, Rockwell hardness number and impact energy were measured. Fourier Transform InfraRed (FTIR) spectroscopy was earried out to observe the change of molecular structure of the composites because of the interaction among epoxy, natural fibers and MWCNT. Scanning Electron Microscopic (SEM) images were analyzed to understand the microstructure of the composites. Furthermore, Microstructure-Free Finite Element Model (MF-FEM) was applied to simulate the mechanical behavior of the composites. Findings from the study showed satisfactory improvement in most of the physical and mechanical properties with addition of MWCNT up to a certain extent. However, addition of CNT resulted in increased density and brittleness of the composites.
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    CHARACTERIZATION AND PREDICTIVE MODELING OF THERMALLY AGED GLASS FIBER REINFORCED PLASTIC COMPOSITES
    (2023-07) RAHMAN, MD MIJANUR
    This study investigated the characterization and predictive modeling of thermally aged Glass Fiber Reinforced Plastic (GFRP) Composites. The experimental part of the study explored the effect of fiber orientation, laser cutting and thermal aging on GFRP mechanical properties. The development of a predictive model for estimating the mechanical properties of thermally aged GFRP was explored in the computational part. GFRP composites were fabricated with woven and random glass fiber and epoxy resin hardener and subjected to mechanical and laser machining. Mechanical property testing reveals that Tensile and flexural properties are found to be superior in mechanically cut samples. Compromised surface integrity due to thermal damage in the case of laser cut samples is also noted. All results indicated that woven GFRP has superior mechanical properties than random GFRP. Woven GFRP tensile test samples were thermally aged at 50°C, 100°C, 150°C and 200°C for 30 mins, 60 mins, 90 mins and 120 mins. The samples showed a gradually increasing brown color at temperatures above 150°C. The tensile test showed that the Ultimate Tensile Strength (UTS) value had a general decreasing trend as the thermal aging temperature increased. The predictive model read the photographic image of a thermally aged sample and used the color change due to thermal aging as an identifier for the image processing algorithm. Artificial Neural Networks (ANN) estimated the thermal aging temperature and time from the image processing algorithm’s Red Green Blue (RGB) color matrix output. A regression equation was also developed which creates a mathematical relationship between the UTS values and the thermal aging variables from the experimental data. Finally, the ANN’s output was forwarded to the developed regression equation to get the estimated UTS. The predictive model’s estimated UTS showed an average accuracy of 97% compared to the experimental results. The results of the characterization of mechanical properties of thermally aged GFRP can contribute meaningful insights into the existing literature. The developed predictive model can have potential applications in aerospace line maintenance operations with the promise of cost and time savings.
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    CHARACTERIZATION AND PREDICTIVE MODELING OF THERMALLY AGED GLASS FIBER REINFORCED PLASTIC COMPOSITES
    (DEPARTMENT OF AERONAUTICAL ENGINEERING, 2023-07) RAHMAN, MD MIJANUR
    This study investigated the characterization and predictive modeling of thermally aged Glass Fiber Reinforced Plastic (GFRP) Composites. The experimental part of the study explored the effect of fiber orientation, laser cutting and thermal aging on GFRP mechanical properties. The development of a predictive model for estimating the mechanical properties of thermally aged GFRP was explored in the computational part. GFRP composites were fabricated with woven and random glass fiber and epoxy resin hardener and subjected to mechanical and laser machining. Mechanical property testing reveals that Tensile and flexural properties are found to be superior in mechanically cut samples. Compromised surface integrity due to thermal damage in the case of laser cut samples is also noted. All results indicated that woven GFRP has superior mechanical properties than random GFRP. Woven GFRP tensile test samples were thermally aged at 50°C, 100°C, 150°C and 200°C for 30 mins, 60 mins, 90 mins and 120 mins. The samples showed a gradually increasing brown color at temperatures above 150°C. The tensile test showed that the Ultimate Tensile Strength (UTS) value had a general decreasing trend as the thermal aging temperature increased. The predictive model read the photographic image of a thermally aged sample and used the color change due to thermal aging as an identifier for the image processing algorithm. Artificial Neural Networks (ANN) estimated the thermal aging temperature and time from the image processing algorithm’s Red Green Blue (RGB) color matrix output. A regression equation was also developed which creates a mathematical relationship between the UTS values and the thermal aging variables from the experimental data. Finally, the ANN’s output was forwarded to the developed regression equation to get the estimated UTS. The predictive model’s estimated UTS showed an average accuracy of 97% compared to the experimental results. The results of the characterization of mechanical properties of thermally aged GFRP can contribute meaningful insights into the existing literature. The developed predictive model can have potential applications in aerospace line maintenance operations with the promise of cost and time savings.
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    PREDICTION OF ICE ACCRETION AND CFD ANALYSIS OF NACA 2412 AIRFOIL FOR EVALUATION OF AERODYNAMIC PERFORMANCE DEGRADATION
    (DEPARTMENT OF AERONAUTICAL ENGINEERING, 2019-08) FERDOUS, MAHBUBA
    High altitude flights possess significant icing hazard in certain type of atmospheric conditions. This ice accretion on aircraft wing leading edges and engine nacelle pose threat to the flight safety. From early days of beginning of high altitude flights, numerous studies have been undertaken to determine the effects of icing on aircraft performance. Bangladesh is now moving at galloping pace in the aviation industry, and is expected to take leap of high altitude flight designs in near term period. This could be accomplished if several technologies are developed in-house prior to design and development of high altitude flights. One such requirement is the development of code for prediction of ice accretion and subsequently to design the anti-icing system. With this long term goal in mind, the present research focuses on understanding of the analytical approaches to predict ice accretion physics on aircraft wing cross section. Using the existing ice accretion thermodynamic and other conservation laws presented in open literature, a computer code was developed to predict the ice accretion over the airfoil. The code developed was validated against the experimental ice shapes from the open literatures. Using the developed code, the ice accretion prediction is undertaken on a specific airfoil i.e. NACA 2412, a most common airfoil cross section for moderately high altitude flights. The aerodynamic performance of the predicted ice accretion was analyzed using the Computational Fluid Dynamic (CFD) technique. The aerodynamic study was undertaken for three different icing conditions and it suggests that the ice accreted airfoil possesses lower lift than the base airfoil. It is also observed that the increase in the drag for ice accreted airfoil is significant as compared to base airfoil. Results of the study show that, most critical and worst icing occurs in presence of altocumulus clouds forming mixed ice on the airfoil leading edges. Such icing conditions result in reduction in lift coefficient and increase in drag coefficient approximately by 90% and 800% respectively compared to the base airfoil. These observations are in consonance with the published literature available in open domain. The current research is considered as the stepping stone for subsequent development and improvement of icing codes as well as design of anti-icing systems.
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    STUDY OF MULTISPECIES NANO-PARTICLES TO ENHANCE THERMO-HYDRAULIC PERFORMANCE IN MICROCHANNELS
    (DEPARTMENT OF AERONAUTICAL ENGINEERING, 2019-08) RASHID, MOHSINA
    Nanofluid is the colloidal suspension of nano-sized solid particles of metals or metal oxides in base fluids such as water, ethylene glycol etc. When liquid is mixed with nanoparticles, it exhibits substantially higher thermal conductivity than those of the corresponding base fluids. The augmented thermal conductivity of nanofluids over the base fluids is considered one of the driving factors for enhanced heat transfer performance of nano-fluids. The forced convection heat transfer of nanofluid is investigated by numerous researchers over the last few years. Recently, multispecies nanofluids have been defined as a new class of nanofluids with possible applications in almost all fields of heat transfer. The idea of using multispecies nano-fluids is expected to improve the heat transfer characteristics of individual nanofluids and to beneficially combine different properties from metal oxides, metals etc. The present research work is undertaken using the Computational Fluid Dynamics (CFD) to analysis and assess the high performing nanofluid for micro-channel applications. The study considers three metal oxide, two metal nano particles and their combinations in the base fluid i.e. desalinated water. The study is conducted for different Reynolds numbers and heat capacity. The performance of the nano-fluids is assessed based on the convective heat transfer coefficient, Nusselt number and pumping power requirement based on total pressure loss. The extensive numerical analysis suggests that MgO-Water nano-fluid possesses excellent heat transfer performance over other combinations considered. Study also reveals that the metal oxides possess better cooling performance in terms of convective heat transfer coefficient as compared to metal nanofluids. Among multispecies nanofluids of Ag-MgO-Water, Al2O3-Cu-Water and CuO-Cu-Water, the Al2O3-Cu-Water nano fluid performed better providing highest Nusselt number which is approximately 6% over and above that provided by pure water. Utilizing the data generated by parametric study for different nano-fluids, two combinations nanofluids are utilized for design of a compact heat exchanger with three different heat capacities i.e. 1 kW, 50kW and 100 kW. The hydraulic performance of this heat exchanger was compared in terms of pumping power requirements and it revealed that pumping power requirement increases nearly exponentially for higher Reynolds numbers.