Karthik Birur Manjunathaiah

1. Wind energy is increasingly being deployed in environments for which conventional turbines were not designed, including rooftops, enclosed compounds and semi-urban sites. The wind available at s...

Multilevel inverters (MLIs) based on IGBT switches have gained prominence in AC power applications due to their capability to reduce harmonic distortion while offering cost‐effective operation. They are widely adopted in power electronic systems; however, under high‐stress conditions, power switches are prone to faults that can impair system performance. Hence, effective identification of faulty switches is crucial. This study focuses on detecting single and multiple switch open‐circuit faults (OCFs) in reduced device count (RDC) MLI. A machine learning (ML)–based diagnostic framework is proposed, which utilizes only the output voltage signals for fault analysis. From these signals, three key features are extracted: standard deviation, half‐cycle moving average, and total harmonic distortion for fault classification. Several ML classifiers are evaluated and benchmarked against recent approaches, with the decision tree (DT) model achieving the highest accuracy of 99.84% under a 70:30 training‐to‐testing split. The proposed method accurately identified both single and multiple switch OCFs in RDC‐MLI within 10–30 ms. The complete diagnostic system is implemented and validated in the MATLAB/Simulink environment.

Recent progress in metal matrix composites (MMCs) has led to significant research efforts aimed at refining reinforcement methods and processing techniques and enhancing material properties. Incorporating reinforcements has notably improved both mechanical strength and tribological performance while addressing issues such as porosity and particle agglomeration. This study investigates the impact of copper reinforcement (1–4 wt.%) on the tribological characteristics of A356 alloy under both as-cast and heat-treated conditions. The process of heat treatment involved age hardening, where the composites were solution heat treated (SHT) at 535 °C for 2 h, followed by rapid quenching and aging at 100 °C and 200 °C. The results demonstrate that increasing the copper content enhances the composite’s mechanical properties. Specifically, heat treatment promoted the redistribution of the Al₂Cu intermetallic phase during peak aging, leading to improved hardness and wear resistance. Wear testing demonstrated that heat-treated composites exhibited significantly better wear resistance than their as-cast counterparts, with improvements of 50–60% under lower loads and 80–90% under higher loads. Among the tested samples, A356 alloy reinforced with 4 wt.% copper showed the lowest wear rate across all the applied loads, along with a reduced coefficient of friction and enhanced load-bearing capacity, minimizing material deformation. Additionally, aging at 100 °C resulted in the greatest hardness and the lowest wear rate in comparison to untreated A356 alloy. These findings underscore the viability of copper-reinforced A356 composites for applications demanding enhanced mechanical characteristics and wear resistance.

The “immersed boundary method (IBM)” is considered to be the most efficacious and versatile technique to solve flow problems associated with intricate geometries. The first part of this review examines recent advancements in IBM, essential for the simulation of “fluid–structure interactions (FSIs)” in sophisticated systems. This review highlights significant developments in turbulence modeling, adaptive mesh refinement, and complex geometric simulations, demonstrating IB methods’ capacity to seamlessly integrate arbitrary geometries into structured computational grids while preserving computational efficiency. Various IB techniques are analyzed for enforcing boundary conditions on dynamic immersed boundaries, with notable breakthroughs in managing velocity discontinuities, spurious oscillations, and large-scale deformations. Recent findings illustrate the versatility of IB methods, with applications encompassing biological fluid dynamics, turbulent multiphase flows, and cavitating flows. These innovations not only enhance computational performance but also address evolving challenges across engineering and scientific fields, establishing IB methods as a robust tool for resolving complex, multidisciplinary problems with high accuracy and efficiency.

Magnesium (Mg) composites exhibit exceptional properties, making them ideal for diverse applications in the medical, aerospace, and energy industries. The extensive use of Mg-based composites has driven ongoing efforts to enhance their properties and performance. Therefore, the present work focused on the fabrication of Mg-Zn-Mn surface composites reinforced with Zinc oxide (ZnO) through friction stir processing (FSP). The effect of the addition of ZnO on microstructure, mechanical properties, corrosion, and wear behavior was investigated. The development of the microstructure is analyzed using a scanning electron microscope (SEM) and X-ray diffraction analysis. Surface topography and roughness are analyzed using atomic force microscopy (AFM) and revealed a Ra value of 68.4 nm. The mechanical properties of the friction stir processed samples are investigated using Vickers microhardness equipment. The FSP/ZnO-Mg-Zn-Mn surface nanocomposites demonstrated a microhardness of 152.7 Hv, which is 2.4 times greater than that of the H-Mg-Zn-Mn base materials. The enhancement in the corrosion resistance of the FSP/ZnO-Mg-Zn-Mn surface nanocomposites is primarily due to the combined effect of the refined grains and the uniform dispersion of ZnO particles. Furthermore, this surface composite had the best wear resistance as a result of significant grain refinement and higher hardness.

This study investigates the mechanical properties of Al6061-TiB₂-fly ash reinforced monolithic and hybrid composites, fabricated using the stir casting technique. The experiment involved the preparation of both monolithic composites by varying TiB2 (3–6 wt%) and hybrid composites by varying TiB₂ (1–3 wt%) and fly ash (3–5 wt%) within the Al6061 matrix. Preheated reinforcement particles were introduced to the matrix alloy under controlled stirring conditions to ensure proper dispersion. Mechanical testing was conducted on the fabricated composites to evaluate their hardness and tensile strength. The results indicate that the hybrid composites exhibit superior mechanical properties compared to the base Al6061 alloy and the monolithic composites. The hardness of the hybrid composites A1T3F (Al6061 + 1%TiB₂ + 3% fly ash) and A3T5F (Al6061 + 3%TiB₂ + 5% fly ash) were significantly improved, reaching 134 HV and 146 HV, respectively, compared to 74 HV for the base alloy. The tensile strength of the hybrid composites also exceeded that of the monolithic composites, demonstrating the synergistic reinforcement effect of TiB₂ and fly ash. However, attempts to incorporate higher levels of reinforcement (TiB₂ 5% and fly ash 7%) were unsuccessful due to agglomeration issues. The results indicate that the hybrid composites provide a cost-effective solution with enhanced mechanical properties, making them a more economical and efficient alternative to monolithic composites reinforced solely with TiB₂.