Soumyabrata Chakravarty

Cupola furnace slag (CFS) poses significant challenges for casting industrialists, who must navigate the complexities of its disposal to maintain operational efficiency and environmental responsibility. This study aims to investigate and implement the reuse of CFS in the construction industry which in turn creates a new method for solid waste management. This study clarifies the mechanical and durability properties of concrete that contains CFS‐coarse‐aggregates (CCA) and cupola‐fine‐aggregates (CFA), which are natural fine and coarse aggregate substitutes. To accomplish this, compressive strength, split tensile strength, water penetration, impact resistance, surface abrasion loss, and rapid chloride penetration tests were conducted. In M30 grade concrete, the experimental procedures involved varying degrees of weight replacement (0% to 40%) of natural fine‐aggregate (FA) and natural coarse‐aggregates (CA) with CFA and CCA, respectively. The experimental findings revealed that compressive strength increased with up to 20% replacement of FA, but decreased afterward. Conversely, compressive strength decreased with the replacement of CA, though up to 30%, replacement still met M30 grade concrete requirements. A leachability test was conducted to detect toxic and heavy materials in CFS. SEM, EDX and XRD techniques were also employed. Replacing FA and CA with CFA and CCA, respectively, proved economically beneficial compared to standard concrete.

Laser welding of plastics has developed into a significant area of research, encompassing a range of complex methods. This process finds extensive applications across various sectors of modern society, such as science, medicine, and electronics. Despite substantial progress made in this field, there remains considerable potential for research to better understand how process parameters – like weld speed, laser power, frequency, and stand-off distance – affect outcomes like weld strength and geometry. Dongxia et al. (2012) applied the Taguchi method to optimize weld bead width in laser welding, considering factors such as laser power, welding speed, and wire feed rate. They concluded that higher welding speed, wire feed rate, and laser power tend to reduce weld quality. Shanmugarajan et al. (2016) used grey relational analysis (GRA) for multi-objective optimization in laser welding of P92 steel, with input parameters including laser power, welding power, welding speed, and focal position. Their measured outcomes included depth of penetration, weld width (WW), and the heat-affected zone (HAZ) width. Tilekar and Kamble (2017) conducted a review of the effects of various input parameters, such as laser power, weld speed, focal length, fiber diameter, and shielding gas, on the outcomes of laser welding for different materials. They observed that laser power and welding speed are closely associated as far as their impact on the weld is concerned. Solati et al. (2019) explored how beam pulse energy, travel speed, and focal position affect the fusion zone in laser welding of stainless steel. They conducted multi-objective optimization using Taguchi-based GRA to assess the depth of penetration and WW. Kumar et al. (2014) examined the influence of current, stand-off distance, and clamping pressure on joint strength and WW through transmission laser welding of thermoplastics in a lap joint configuration. Shin and Choi (2014) investigated how scanning speed impacts laser-welded joints between acrylonitrile butadiene styrene (ABS) plastic and polycarbonate (PC)-based polymers, focusing on how energy inputs affect the fusion zone, the HAZ, and the mechanical properties of the weld. Nakhaei et al. (2013) used the Taguchi method to optimize the joint strength of polypropylene–clay nanocomposite sheets by considering clay content, power, scan speed, and focal position as input parameters. Dawood et al. (2013) reported that increasing laser power results in a wider weld due to higher energy input, which increases the melt pool size. Chen et al. (2017) observed a linear relationship between laser power and WW up to a certain threshold, beyond which the WW stabilized. In a study by Haupt et al. (2015), it was found that reducing the laser speed during welding could increase the energy deposition in the welding zone, which ultimately leads to a weld. Nonetheless, if the speed is decreased much, it may cause damage to the material. Hsu and He (2014) showed that there exists a speed range where the WW is maximized without sacrificing the integrity of the material. Kim and Shin (2016) in their study demonstrated that infrared lasers are better at creating welds, in specific types of plastics compared to visible or ultraviolet lasers. This is because they are absorbed efficiently and reflect less at wavelengths. White et al. (2018) studied how carbon black impacts polyamide, thereby discovering that adding amounts leads to broader and more consistent welds by improving the material’s absorption capacity. Kumar et al. (2017) concluded that thicker material can lead to tighter welds because of the larger thermal mass, hence absorbing heat more effectively. On the contrary, darker materials have higher absorption, thus resulting in a wider weld, a finding also backed up by Nguyen et al. (2019). Zhang and Li (2017) found that higher clamping pressures lead to narrower welds by restricting the flow of molten plastic. Conversely, low clamping pressures can cause gaps, resulting in inconsistent welds. Wu et al. (2016) highlighted those higher ambient temperatures preheat the material, resulting in wider welds due to the reduced thermal gradient.

Epoxy based composites reinforced with natural and synthetic fibres have been studied to assess their suitability for structural applications where both mechanical and sustainability are required. Natural fibres such as hemp and jute have been recognized to show environmental benefits but often limited by lower strength and inconsistent mechanical behaviour. These limitations can be mitigated by fibre hybridisation which combines the ductility of natural fibres with strength and stiffness of synthetic counter reinforcements. In this study, laminates composed of hemp-jute (HJ₃), Kevlar (K₉), Kevlar—glass (KG₅) and hemp—jute—glass (HJG₂) have been fabricated by hand layup method and tested under impact, indentation and tensile loading. The highest tensile strength and hardness were recorded in KG₅ laminates, while HJ₃ composites showed the lowest values in all tests. The HJG₂ hybrid laminate demonstrated improved impact energy absorption and high tensile strain, attributed to progressive failure mechanisms and fibre pull-out behaviour. The reduced hardness observed in HJG₂ was associated with poor interfacial bonding and non-uniform fibre distribution. These findings indicated that fibre selection and stacking architecture significantly influence composite performance. A balance between mechanical performance and sustainability can be obtained by tailoring fibre combinations. The study supports the broader application of natural—synthetic hybrid composites in engineering system.

This work compared different machine learning models such as linear regression, polynomial regression and XG-Boost for the prediction of laser welding qualities in aluminum alloys. The key weld quality parameters are ultimate load, weld width and penetration depth. Each model was trained and validated based on data experimentally collected by varying laser power, scanning speed and offset distance to compare them. Quantitative results are shown to prove that XG-Boost produces a better predictive accuracy, as it gives a root mean square error (RMSE) of 0.05 for ultimate load, 0.03 for penetration depth, and 0.02 for weld width. On the other hand, its linear regression counterpart has higher values of 0.08, 0.06, and 0.05, while polynomial regression-clearly outperforming its linear variant-averaged about 0.04 in these metrics. While this is so, high R-squared values, predicted by the XG-Boost model across ultimate loads, are indicative of its better competency in the capturing of complicated patterns, especially with regard to data outliers. These findings confirm the capability of XG-Boost to perform precise parameter optimization in laser welding by significantly reducing experimental trial needs and helping manufacturing efficiency with reliable data-driven predictions.

This experimental work presents machinability characteristics of waste derived cupola slag reinforced aluminum metal matrix composites in solution treated condition during dry turning operations. Composites used in this work were fabricated by an economical stir-casting method using 100 μm-sized cupola slag particles as reinforcement at 0, 3, 5, and 7 wt% in an Al-4.5-Cu aluminum alloy (LM11) matrix. Post fabrication the samples have been heat treated. The physical, mechanical and microstructural characterizations are conducted to evaluate the changes in base alloy by cupola slag inclusion and subsequent heat treatment. The dry turning experiments has been performed in a conventional lathe with varying feed rate and spindle speed with constant depth of cut. Key machinability indices such as tool wear, chip thickness, power consumption, surface quality, force requirement and material removal rate (MRR) by loss of weight method have been investigated. A detailed tool wear study, along with analysis of chips have been presented for introspection of underlying cutting mechanisms. The results indicates that 7 wt% slag reinforced composites show improved physical, mechanical and machinability behaviors due to uniform slag dispersion and refinement of grains. This work establishes one of the possibilities of reusing cupola slag as an eco-friendly and cost-effective reinforcement in high-performance MMCs.

This study explores through transmission laser welding of dissimilar, optically transparent polymers, acrylic and polycarbonates using a novel hybrid approach that integrates Response Surface Methodology (RSM) and Finite Element Method (FEM). Quantitative analysis involved a 3 factor, 3 level central composite design with process inputs of laser power, frequency and scanning speed. The resulting weld qualities, such as weld width, Heat Affected Zone (HAZ), ware measured, showing weld width ranges from 112.65 μm to 302.64 μm and HAZ between 20.85 μm to 105 μm. The thermal modelling provided predictions for depth of penetration, with values spanning from 106.25 μm to 228.65 μm. validated against experimental data, demonstrating an average error of 8.09%. Qualitatively, the investigation indicatees that laser power and scanning speed substantially effect the weld quality, with higher power leading to broader weld widths and greater HAZ. The FEM simulations confirmed these trends and provided insights into temperature distributions. The investigation contributes to the existing knowledge pool that would be beneficial to the academia and industries.

Rapid evolution in engineering and manufacturing demands light weight material with enhanced mechanical properties. Aluminium metal matrix composites with ceramic reinforcement particulates serve this demand due to their reduced density, improved strength and hardness along with higher resistance to wear and corrosion. However, the material cost and reduced machinability hinders the full potential of utilization. To overcome these challenges, in this work cupola slag, an industrial waste generated as by product of cast iron production, has been incorporated as reinforcement of aluminium composites using low cost stir casting method. The enhancement of material properties and machinability by cupola slag inclusion on base alloy has been investigated in detail. Moreover, introspection about the underlying mechanisms responsible for the improvement in material properties has been studied using detailed microstructure and fractographic analysis. The results show improvement of in material properties and machinability up to 7 wt.–% cupola slag inclusion, beyond which the reduced wettablity prohibits sound castings. The ultimate tensile strength and specific strength observed to be improved by 18.20 % and 33.23 % respectively for 7 wt.–% slag reinforced composites when compared with base alloy. This work can be a successful addition to the knowledge pool of ongoing research on low‐cost novel material with enhanced properties.

In this experimental work, magnesium nanocomposite reinforced with various percentage of boron carbide (0.5%, 1.0%, 1.5%, 2.0% by volume) is fabricated using conventional powder metallurgy technique. Characterisation and wear test of the fabricated composite have been performed using scanning electron microscopy, tribology test monitor respectively. It is observed that addition of B₄C increases the hardness and wear resistance linearly. Addition of 2% B₄C produces the hardness of the nanocomposites as high as 57.93 ± 4.9 Hv. Furthermore, the nanocomposites displayed improved wear resistance and lower friction coefficient compared to the base magnesium. The influence of sliding speed on these properties has been systematically presented. The paper provides an in-depth exploration of wear mechanisms through a meticulous analysis of SEM micrographs of worn surfaces. This work offers valuable insights into the microstructural characteristics and tribological behaviour of Mg-B₄C nanocomposites. These findings underscore the potential application of Mg-B₄C nanocomposites in the development of lightweight wear-resistant materials. The impact of incorporating minute amounts of nano-sized boron carbide into Mg, on its behaviour under small loads and repeated scratching has been investigated in this study. Moreover, introspection of the wear mechanisms and the effectiveness of the powder metallurgy technique in fabricating composite materials is presented.