This thesis investigates the buying behaviour of consumers towards Pochampally Handloom Silk Sarees (PHSS) and the sustainability of the weavers. Theory of Planned Behavior (TPB) and marketing mix components were adopted to assess consumer behaviour and weavers’ sustainability. Primary data from 412 consumers and 142 weavers were collected through structured questionnaires. The data was analysed using factor-based partial least square structural equation modelling. This study provides new insights into consumer behaviour for PHSS and proposed effective marketing strategies for handloom products, extending the TPB model and marketing mix elements.

An oscillating heat pipe (OHP) consists of a meandering tube of capillary-sized dimensions that is bend in a serpentine manner and joined at the ends to form a closed loop. The tube is initially evacuated and then partially filled with a working fluid. This fluid naturally distributes itself inside the tube as alternating liquid slugs and vapor plugs. OHP consists of three distinct sections: an insulated (adiabatic) section, which connects the evaporator (heat source) and condenser (heat sink). Heat transferred from the evaporator section to the condenser section by a pulsating action of the liquid-vapor system. Numerical investigations were performed to study the effects of different wettability on different sections on the start-up characteristics and heat transfer performance of a single-loop OHP using volume of fluid method (VOF) in ANSYS Fluent. To improve the accuracy of the numerical model thermo-physical properties of the working fluid along with local pressure dependent saturation temperature and saturation temperature dependent latent heat of the working fluid are considered using user defined functions (UDFs). In a conventional oscillating heat pipe (COHP), the wettability is uniform across all sections, while in a hybrid OHP (HOHP), the wettability varies between different sections. Preliminary studies focused on the impact of wettability on the evaporator and condenser surfaces. HOHP with a hydrophilic evaporator and a super-hydrophobic condenser enhanced the heat transfer performance of OHP. To a HOHP, the effects of different wettability on the left and right adiabatic tube referred as the adiabatic hybrid OHP (aHOHP), are investigated further. A net circulatory motion with intermittent oscillations is observed in aHOHP with hydrophilic left adiabatic tube and super-hydrophobic right adiabatic tube, which resulted in enhancement of heat transfer performance by 63%. Since, different wettability on the left and right adiabatic tubes induced a net circulatory motion, the effects of different surface wettability on the left and right vertical tubes referred to as alternate wettability OHP (AWOHP), are further investigated. Similar to aHOHP, net circulatory motion with intermittent oscillations is observed in AWOHP with a hydrophilic left and a super-hydrophobic right tube. The heat transfer performance of AWOHP enhanced by 55% compared to COHP, but reduced by 10% compared to aHOHP. Further investigations were conducted on dual-diameter OHP (DD-OHP) to compare heat transfer performance of DD-OHP with aHOHP 3. A net circulatory motion was also observed in DD-OHP with diameter ratio of 4:2, the heat transfer performance of DD-OHP reduced by 10% compared to aHOHP 3. Overall, it can be concluded that the heat transfer performance of OHP can be enhanced maximum by altering surface wettability than that of geometrical modifications.

Fiber optic sensors have advantages like immunity to electromagnetic interference, remote sensing, and high sensitivity. They are used in industrial, medical, and structural health monitoring applications. Challenges include expensive equipment and poor spatial resolution, though Fiber Bragg Gratings (FBGs) improved resolution. Fiber Specklegram Sensors (FSSs) offer a cost-effective alternative by analyzing speckle patterns for parameters like temperature and vibration. Our work integrates deep learning with FSSs to enhance their capabilities in various applications. FSSs analyze speckle pattern changes in multimode fibers to measure parameters like weight and vibration. We develop CNN models for weight and weight-location recognition on plastic optical fibers (POFs). Key contributions include a custom CNN for single-region weight detection and transfer learning models for accuracy improvement. Transfer learning with VGG-16 and VGG-19 significantly enhances recognition accuracy. This research advances weight-sensing technologies and highlights deep learning’s potential in fiber optic sensor applications.

Composite pressure vessels such as rocket motor cases, launch tubes, and air bottles etc. are widely used in mass-sensitive launch vehicles. The higher specific strength and specific modulus properties of composites make them the most attractive material worldwide, especially for aerospace applications. Filament winding is the core processing technology for manufacturing composite pressure vessels. As composites are highly process intensive, winding parameters need to be minutely monitored and controlled while manufacturing filament (wet) wound composite structures for optimum exploitation of constituent materials properties. Proper control of filament winding parameters can also ensure better reliability and enhanced performance of the structures. Considering efficient and reliable pressure vessels like rocket motor cases, air bottles, launch tubes, etc., for aerospace application in mind, the effect of filament winding parameters for manufacturing carbon/epoxy composite pressure vessels is studied.

This thesis addresses the growing demand for high data-rate communications and the spectrum crisis by advancing Non-Orthogonal Multiple Access (NOMA) for 5G and beyond. It explores innovative resource allocation techniques, including user pairing, power allocation, and integration with SWIPT and MIMO systems. A novel user pairing strategy enhances throughput, while a Modified Artificial Bee Colony (MABC)-based power allocation optimizes the sum rate. A cooperative NOMA-SWIPT system with Power Splitting (PS) mitigates SIC imperfections, and an Improved Grey Wolf Optimizer (IGWO) accelerates power allocation in MIMO-NOMA. Additionally, an FPGA-based hardware accelerator significantly improves SIC decoding speed. These advancements collectively enhance system performance, optimize spectral efficiency, and improve computational efficiency, strengthening NOMA’s viability for future wireless networks.

The increasing energy demand in the transportation sector, driven by population growth, coupled with the depletion of fossil fuels and escalating costs, has spurred significant research into alternative fuels. This thesis investigates the performance, combustion characteristics, and emission reductions of diesel engines fueled by hydrogen-diesel blends and biodiesel derived from waste plastic oil. The study aims to optimize engine performance while minimizing environmental impact, leveraging advanced techniques such as Reactivity Controlled Compression Ignition (RCCI) and Artificial Neural Network (ANN) modeling. Experimental investigations were conducted on single-cylinder diesel engines using hydrogen-diesel blends (DH5, DH10, DH15) and biodiesel-hydrogen blends (DP20, DP20H5, DP20H10, DP20H15) under varying injection pressures, compression ratios, and injection timings. The results demonstrate that hydrogen supplementation significantly improves brake thermal efficiency (up to 17.6% for DH15) and reduces fuel consumption (up to 31.6%). Additionally, emissions such as smoke, carbon monoxide (CO), and hydrocarbons (HC) were markedly reduced, although an increase in nitrogen oxide (NOx) emissions was observed. In RCCI engine operations, hydrogen's high reactivity enhanced combustion efficiency and fuel economy, aligning with decarbonization goals. The use of ANN models provided over 99% prediction accuracy, confirming their effectiveness for performance optimization and emission prediction. This research underscores the potential of hydrogen integration, combined with biodiesel and innovative combustion strategies, to address the dual challenges of fuel sustainability and environmental impact, paving the way for achieving net-zero greenhouse gas emissions by 2050.

Indole and its derivatives serve as essential structural motifs in numerous biologically active compounds, pharmaceuticals, and natural products. Beyond medicinal chemistry, indole finds applications across diverse industries, including dyes, materials science, fragrances, and agriculture. Its significance as a privileged pharmacophore enables interactions with various biological systems, making indole-based compounds valuable in drug discovery. Notably, these compounds exhibit therapeutic potential in antiviral, anti-inflammatory, antihypertensive, and anticancer treatments, as well as in central nervous system (CNS) therapeutics. Among them, azepinoindole alkaloids such as paullones are recognized for their potent antitumor activity, while ibogaine and its derivatives are used in the treatment of neurological and psychiatric disorders. Our research focuses on the selective functionalization of indoles at the C2 and C3 positions using transition-metal-free, halogen-mediated strategies. Conventional methods often rely on transition metals, which pose environmental concerns, or require harsh acidic conditions. To address these challenges, we have developed an innovative I 2 /Cs 2 CO 3 system for the synthesis of thiosulfonate-containing 2-iminoindolin-3-one scaffolds from C3-phenylthio indoles. In this transformation, Cs 2 CO 3 functions as an oxygen source, driving an oxidative rearrangement with [1,4]-sulfonyl migration to yield the desired products. Additionally, using I₂ as a mediator, we have established a bis-sulfenylation strategy for C3-phenylthio indoles, leading to a novel bis-sulfenyl indole framework. Furthermore, we have developed an iodine-mediated approach for synthesizing biologically significant indole-fused benzothiazepinones. This transformation employs C3-sulfenyl indoles in the presence of I₂ and K 2 CO 3 , affording the benzothiazepinone scaffold. Beyond these halogen-mediated strategies, we demonstrated a CBr₄- catalyzed Michael addition of indole to α,β-unsaturated ketones, enabling the synthesis of β- indolylketones via halogen-bonding catalysis. Moreover, we have synthesized 3-indolyl furanoid motifs through a one-pot sequence involving Michael addition followed by Paal-Knorr cyclization of unsymmetrical 1,4-enediones.

Soil pollution, particularly from alkali, acid, and heavy metal contamination, poses severe environmental risks. Conventional remediation methods have limitations, necessitating alternative materials. This study synthesizes nano calcium silicates (NCS) from granite and marble waste, reducing costs and supporting circular economy principles. Characterization confirmed SiO₂-rich granite and CaO-dominant marble; a 1:1 mix calcined at 1000°C yielded wollastonite-rich NCS. Ball milling enhanced surface area, optimizing adsorption. Adding 1.5–2% NCS mitigated swelling in contaminated soils by forming stabilizing minerals. NCS also effectively removed Pb(II) and Cd(II), with adsorption models showing R² values of 0.968 and 0.978, respectively. The results highlight NCS as a rapid, cost-effective adsorbent with regeneration potential. This study demonstrates NCS’s efficacy in soil stabilization and heavy metal removal, offering a sustainable solution for environmental remediation and resource management.

Antenna is a major element for wireless communication and drone-based surveillance systems. The quality and efficiency of these systems largely depend on the efficient antenna design in a compact size. To cater emerging wireless communication and drone-based surveillance applications, miniature antennas in novel configurations are investigated, realized and presented in the thesis work. Antenna miniaturization methods discussed in the literature generally involve applying the concept of fractal geometry as a means to fill space, utilizing substrates with high permittivity, experimenting with various slot shapes in the radiating patch, incorporating Defected Ground Structures, using metamaterials, or a combination of these approaches. The research objectives and main research findings as an outcome of thesis work can be summarized as fractal inspired DGS, fractal inspired hybrid microstrip patch antenna, study on the effect of Sierpinski carpet fractal DGS on the linear arrays of microstrip patch antennas and metamaterial configurations applied in microstrip patch antennas all operating at 2.4 GHz. All the antennas developed have promising applications in wireless and drone based surveillance applications. The methodology outlined in the thesis work can be further extended to evolve newer antenna configurations for various applications.