Journal of Recent Trends in Mechanics

Comparative Thermal Analysis of Turbine Blades with and Without Internal Cooling Passages

2026-03-16T08:08:00+00:00

This study investigates the thermal performance of gas turbine blades operating under extreme temperature conditions where the working temperatures often exceed the melting limits of conventional materials. To address this challenge, advanced cooling strategies are essential for maintaining blade integrity and operational efficiency. In this research, a comprehensive computational fluid dynamics (CFD) analysis was performed to evaluate the thermal behavior of turbine blades with and without internal cooling passages. The simulations were conducted using ANSYS Fluent, based on a turbine blade geometry derived from the patent WO2014042720A2. The baseline blade material selected for the study was Inconel 792 due to its high-temperature strength and oxidation resistance. The results indicate that the incorporation of internal cooling passages significantly enhances thermal management by reducing the average blade wall temperature from 1439.5 to 1357.4 K, corresponding to a reduction of approximately 82 K (5.7%). Furthermore, a parametric analysis involving eight high-temperature materials was conducted to assess the influence of thermophysical properties on blade temperature distribution. The study reveals that materials with higher thermal conductivity and specific heat capacity contribute to improved heat dissipation and more uniform temperature profiles. Overall, the findings highlight the critical role of internal cooling mechanisms and appropriate material selection in improving turbine blade durability and preventing thermal failure in high-temperature gas turbine applications.

Optimized Design of Standalone Solar Photovoltaic System for Rural Electrification Using Metaheuristic Techniques

2026-05-14T04:15:48+00:00

Access to dependable electricity in remote and rural regions remains a persistent challenge due to high grid‐extension costs, difficult terrain, and low load density. Standalone solar photovoltaic (PV) systems supported by battery energy storage provide a clean and modular alternative; however, improper component sizing often leads either to excessive capital investment or unacceptable supply interruptions. This study presents a comprehensive techno-economic optimization methodology for designing an off-grid PV-battery system capable of delivering reliable power at minimum lifecycle cost. Detailed mathematical models are developed for solar energy conversion, temperature-dependent PV efficiency, battery state-of-charge evolution, load variation, and power balance. Metaheuristic techniques, namely genetic algorithm (GA) and particle swarm optimization (PSO), are employed to determine optimal PV capacity and storage size while constraining the loss of power supply probability (LPSP) within acceptable limits. Simulation studies performed under realistic rural demand profiles demonstrate that the optimized configuration ensures high service continuity with LPSP below the prescribed threshold. Results further reveal that moderate PV oversizing improves battery health, reduces deep discharge events, and lowers long-term replacement expenses. Economic analysis based on net present cost confirms the competitiveness of the proposed system compared with conventional diesel-based supply. The developed framework provides practical design guidance for engineers and policymakers and supports accelerated deployment of sustainable electrification solutions.

Smart Dust Control: Vacuum and Blower Solutions for Safer Construction

2026-05-08T11:26:54+00:00

Construction sites are prone to excessive dust, debris, and airborne particles, posing risks to worker health, equipment reliability, and operational efficiency. This study proposes an Internet of Things (IoT)-enabled smart vacuum cleaner system that integrates vacuum and blower functionalities to enhance dust control, sustainability, and safety in construction environments. Unlike conventional robotic cleaners with limited intelligence and poor navigation, the proposed system employs microcontroller-based architecture, sensor fusion (infrared and ultrasonic), and adaptive path-planning strategies to achieve autonomous navigation, obstacle avoidance, and efficient coverage. Real-time monitoring and remote control are facilitated through IoT frameworks, enabling data transmission via Wi-Fi for cloud-based analytics, predictive maintenance, and user interaction through mobile/web platforms. Experimental evaluation across varied indoor scenarios demonstrates improved cleaning efficiency, reduced energy consumption, and enhanced automation compared to traditional systems. The adaptive cleaning strategies dynamically adjust suction power and movement speed based on dirt levels, optimizing energy use while maintaining high cleaning effectiveness. Results confirm reliable obstacle detection, stable navigation, and robust performance under diverse environmental conditions. By combining vacuum and blower systems within an IoT framework, the solution offers a scalable, sustainable, and cost-effective approach to dust management in construction sites. This research contributes to advancing smart cleaning technologies by bridging occupational health, environmental sustainability, and intelligent automation, positioning IoT-based vacuum systems as a transformative solution for modern construction practices.

Design and Development of Guide Fixture for Precision Pin Assembly in Hydraulic Valve Bodies

2026-01-23T08:24:10+00:00

Hydraulic valve assemblies demand micron-level precision during pin insertion to ensure reliability, prevent leakage, and extend service life. Conventional manual pressing methods often fail to achieve the required transition fit of 20–30 µm, leading to misalignment, eccentric fits, and high rejection rates. This study presents the design and development of a precision guide fixture tailored for hydraulic valve pin assembly. The fixture integrates a slotted base, a locating pin mechanism, a pressing interface, and anti-rotation supports to achieve concentric alignment. Computer-aided design (CAD) tools were used for modeling, while finite element analysis (FEA) validated stress distribution and tolerance control. Fabrication employed hardened steel and EN-series alloys, followed by experimental validation using micrometers and dial gauges. Results demonstrated concentricity accuracy improvement from ±80 µm to ±20–30 µm, error rate reduction from 10–12% to 2–3%, and enhanced operator safety. The fixture reduced setup time and proved scalable for different valve sizes. This research contributes to fixture design literature by addressing micron-level press-fit tolerances in hydraulic assemblies and establishes a foundation for future semi-automated assembly systems.

Viability Analysis of a Steam Turbine Plant in Nigeria

2026-05-28T05:38:26+00:00

This study evaluates the technical and economic viability of the Egbin steam turbine power plant in Nigeria using operational data obtained over eleven years (2010–2020). The assessment focused on key performance indicators such as thermal efficiency, steam flow rate, steam plant heat rate, capacity factor, power availability, and levelized cost of electricity (LCOE). Thermodynamic performance equations and economic evaluation principles were applied, while MATLAB was used for simulation and validation of results. The plant, with an installed capacity of 1320 MW, recorded an average thermal efficiency of 45.79%, indicating satisfactory operational performance within acceptable industrial standards for steam power plants. The average steam plant heat rate was 87,637 kJ/kWh, while the capacity factor was 57.38%, showing moderate utilization of installed capacity. The plant generated approximately 91% of its total installed capacity during the study period, reflecting good operational availability. Economic analysis showed an average LCOE of ₦45.33/kWh, confirming the plant’s economic sustainability. The findings demonstrate that the Egbin steam power plant remains both thermodynamically efficient and economically viable for reliable electricity generation in Nigeria.

Design and Optimization of Nano-enhanced Phase Change Material-based Thermal Energy Storage Systems for Solar Thermal Applications

2026-05-13T05:50:27+00:00

The intermittent nature of solar energy necessitates efficient thermal energy storage (TES) systems to ensure reliability and a continuous energy supply. Phase change materials (PCMs), due to their high latent heat storage capacity, have emerged as promising candidates for TES. However, their low thermal conductivity limits heat transfer efficiency. This study investigates the design and optimization of nano-enhanced phase change materials (NEPCMs) for solar thermal applications. By incorporating nanoparticles such as graphene, metal oxides, and carbon nanotubes into base PCMs, significant improvements in thermal conductivity, heat transfer rate, and energy storage performance are achieved. A combined experimental-numerical approach is used to evaluate system performance. Results demonstrate that NEPCMs can enhance thermal conductivity by up to 60–200% and reduce charging/discharging time significantly. Optimization techniques such as response surface methodology (RSM) and computational fluid dynamics (CFD) are applied to determine optimal nanoparticle concentration and system geometry. The findings highlight NEPCMs as a viable solution for high-efficiency solar thermal energy storage systems.