Indian Journal of Engineering and Materials Sciences (IJEMS)

Usefulness of X-ray diffraction and Raman Spectra for understanding metal alloy microstructure repeatability

2024-04-09T13:58:12+0530

This is a quantitative methodology for checking repeatability in microstructure using X-ray diffraction (XRD) and Raman spectra of aluminium and brass. The crystallinity and microstructure of the aluminium or brass samples are different if their manufacturing sources are different, due to differences in processing methodologies. It was quantitatively estimated from their Raman spectral profile. Aluminium and brass, from the same source and batch, showed more comparable XRD and Raman patterns. This method highlighted extent of uniformity achieved using a certain production method and also suggests scope for improvements. It improves testing repeatability of ferrous and non-ferrous metals and alloy products, using these two techniques alone, rather than using a plethora of analytical testing techniques currently used for a metal manufacturing process.

Growth, Characterization and Magneto-transport of single crystal Bismuth

2024-04-09T13:10:46+0530

We report the growth of Bi single crystal via the modified Bridgman technique. The structural and microstructural morphological characterization of the as-grown Bismuth (Bi) single crystal includes Field Emission Scanning Electron Microscopy (FESEM), X-ray Diffractometer (XRD) and Energy Dispersive X-ray Analysis (EDAX). Additionally, the Raman Spectra analysis has been used to study the vibrational modes of the Bi. The UV-Vis spectroscopy has revealed a bulk band gap of approximately 5.23eV in the as-grown Bi crystal. The electrical transport measurements have demonstrated metallic behavior with an R_300K /R_2K (RRR) ratio of around 6.5. However, under the applied field, the as-grown Bi shows change from metallic to semiconducting behavior. The bulk band gap of the as-grown crystal has been indirectly determined based on its semiconducting behavior under the applied magnetic field which increases with the applied field. Notably, at low temperatures (<10K), the synthesized Bi crystal exhibits large magneto-resistance (MR) of the order of ~10⁵% under applied fields up to ±14Tesla as along with Shubnikov-de Haas (SdH) oscillations.

Design analysis of AISI 1080 and carbon fibre composite hybrid and conventional chassis

2024-01-21T14:22:18+0530

Chassis is a structural backbone of any vehicle, so it should be rigid enough to withstand stresses, shocks and vibrations. Generally, chassis are made from structural steel and has required strength, however gross weight of vehicle increases. Heavy weight affects the performance, range and recharge cycle in case of electric vehicles. In present research new material proposed for the chassis is carbon fibre epoxy woven composite (CFEWC). Chassis made from conventional structural steel AISI 1080 and hybrid chassis developed using both AISI 1080 and CFEWC materials are discussed. Smart utility vehicle chassis is considered for case study and analysis. Structural strength, torsional stiffness, and harmonic response analysis are carried in commercial FEA tools. Also, dynamic stability of hybrid chassis performed under different road roughness, bump profile and vehicle speeds. Chassis performance verified in terms of displacement, acceleration, force and stresses induced. Results shows hybrid chassis is 32% lighter than conventional steel chassis and it has excellent strength in bending-torsion and also in vibrations. Hybrid chassis design approach offers benefit of both materials to improve the performance of electric vehicles by reducing weight of chassis up to 32%.

Assessment of up-flow and down-flow dual media filters for secondary treated wastewater

2024-04-09T12:27:11+0530

The present research study has investigated the effectiveness of vertically down-flow and up-flow dual media filters in secondary treated domestic wastewater. Dual media filters, incorporating gravel, sand, and granular activated carbon, have been designed to overcome the challenges of tertiary wastewater treatment, such as the removal of fine suspended solids, microbial contaminants, odors, and nutrients. The up-flow dual media filter has achieved higher removal efficiencies for suspended solids and organic matter, resulting in effluent that meets discharge standards. Specifically, the up-flow configuration has enhanced contact time between the wastewater and the filter media, thereby improving the adsorption and filtration processes. Additionally, up-flow filter has exhibited reduced clogging issues and lower operational and aintenance requirements, as accumulated contaminants tend to settle at the bottom, facilitating ease in removal as compared to down-flow dual media filter.

Real-time mass estimation of connected commercial vehicle using artificial neural network model

2024-01-22T20:48:03+0530

In recent years, the automotive industry has experienced a remarkable transformation with the advent of digital technologies. The internet of things (IoT) revolutionizes the automobile industry by enabling intelligent, connected vehicles. IoT-generated data enhances vehicle safety through real-time diagnostics, predictive maintenance, and remote monitoring, reducing accidents and breakdowns. Very few studies have used IoT data thread inference in product design. Knowing the real-time mass of the vehicle is significant for design engineers during aggregate design selection and optimizing the vehicle design. This study shows a novel approach to predicting the real-time active mass of a connected medium-duty commercial truck using an artificial neural network (ANN) deep learning (DL) multilayer perceptron (MLP) deep learning algorithm. In this process, the raw data collected from the vehicle is cleaned, and the vehicle's mass is estimated by applying the vehicle dynamics system longitudinal forces model. Different load conditions of the vehicle are calculated with an accuracy of 87%. Later, the estimated mass with the five mass-influencing operating parameters from the data is used as an input in the MLP deep learning model to predict the vehicle's mass as output. The model is trained and tested using overload, rated load, and no-load conditions; when testing the model using the real-time operating parameters, the deep learning model predicted the mass with >90% accuracy. This deep learning model, when integrated into the data-driven digital twin framework, will be instrumental in controlling various actuators based on the predicted mass in future work. Moreover, the predicted real-time active mass is not only helpful for the optimum design of many vehicle systems but also for building application-based design configurations, thereby demonstrating the practical relevance and potential applications of this research in vehicle design and control systems.

Synthesis and performance evaluation of magnetorheological fluid for continuous flow finishing process

2024-02-20T15:31:37+0530

In this study, Magnetorheological (MR) finishing fluid samples are synthesized and experiments are conducted to investigate the rheological properties namely off-state viscosity and on-state yield stress of prepared samples. The compositions of the MR finishing fluid are determined by employing Taguchi based design of experiment approach. The rheological properties are characterized on a rheometer, using MR device accessory. Bingham Plastic, Casson fluid and Herschel Bulkley are the three fluid models utilized for the modelling of the fluid. The Hershel–Bulkley model has resulted as the most apposite model for fluid with the highest coefficient of regression (R²) value i.e., 0.9049. Further, Technique for order of preference by similarity to ideal solution (TOPSIS) is also utilized to establish the effect of its constituents on both the considered rheological properties. To determine the magnetic saturation of the developed MR finishing fluid, graphs between magnetic field strength and on-state yield stress are plotted. Analysis of Variance (ANOVA) publicized the weight percentage of Fe powder as the most notable parameter, contributing 66.12% which is followed by the weight percentage of SiC abrasives with 8.09%. The MR finishing fluid samples attained the highest yield stress at a magnetic field intensity of around 0.7 Tesla, which is considered as the limiting value for the finishing process. The optimized fluid sample is used for finishing 2 mm hole using an indigenously developed finishing process.

Enhancing concrete flexural behaviour with euphorbia tortilis cactus: Sustainable additive for improved load-carrying capacity and ductility

2024-01-02T23:25:12+0530

This study delves into the flexural behavior of concrete beams incorporating Euphorbia tortilis cactus (ETC) as an environmentally friendly additive. Six sets of reinforced concrete beams with varying compositions, including ETC and reference concrete, were subjected to two-point load tests. The results revealed several critical findings. All tested beams exhibited a flexural mode of failure, indicating a ductile response. ETC-incorporated beams displayed superior load-carrying capacity, with initial crack loads increasing by up to 47.9%. ETC beams exhibited lower crack widths, reduced deformations, and enhanced stiffness. The stiffness gradient relative to the ultimate load demonstrated the improved resistance of ETC beams. Energy absorption was significantly higher in ETC beams, signifying their capacity to withstand energy fluctuations. ETC fibers effectively prevented pull-out failures. Overall, ETC-enhanced concrete beams exhibited enhanced performance, highlighting their potential for sustainable construction.

Optimization and property evaluation of 0.5 mm SS304 thick sheets welded by microplasma arc welding with and without post heat treatment

2023-11-07T15:41:08+0530

The present work investigates the micro plasma arc welding (MPAW) of SS304L of 0.5 mm steel sheets. It primarily highlights the weld quality of SS304 of 0.5 mm thickness with and without post weld heat treatment (PWHT). Thin sheets are more prone to distortion at time of solidification because of residual stress induced. After PWHT of the welded sample, the distortion is reduced. The effect of input parameters such as pulse current, gas flow rate and welding speed were taken into consideration. Property evaluation and comparison of weld were carried out before and after the PWHT by hardness, tensile test, microstructure, X-Ray Diffraction (XRD) and scanning electron microscope (SEM). Furthermore, artificial neural network (ANN) was applied for optimization of the weld quality at chosen process parameters and compared to that of the experimental results by considering tensile strength as am output. The ANN will be useful for estimating the welding current to yield an optimum tensile strength, thus providing better process control.

Enhancing frequency regulation in Nuclear-Renewable hybrid energy systems through optimally configured FOPID controllers and adaptive pelican optimization algorithm

2023-12-19T13:34:30+0530

This study has explored the application of Fractional Order Proportional-Integrator-Derivative (FOPID) controllers within Nuclear-Renewable Hybrid Energy Systems (N-RHES). N-R HES has played a pivotal role in the transition to decarbonized energy systems, holding substantial promise for establishing sustainable, carbon-free energy infrastructure in the near future. The investigation has focused on an N-R HES that incorporates diverse energy sources such as solar, wind, nuclear, fuel cell systems, Battery Energy Storage Systems (BESS), and Flywheel Energy Storage Systems (FESS). To achieve performance objectives, the study has employed various meta-heuristic algorithms, including the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Pelican Optimization Algorithm (POA), and Adaptive POA (APOA), to optimize the parameters of the FOPID controllers. Additionally, the research has introduced an enhanced version of the conventional POA, incorporating a velocity computation strategy to enhance the tuning capabilities of FOPID controllers. The results have indicated that optimally configured FOPID controllers effectively manage system frequency and ensure stability within the examined N-R HES. The incorporation of the velocity computation strategy in the POA has contributed to improved tuning performance for FOPID controllers. This study has highlighted the potential of advanced optimization techniques for achieving superior control strategies for N-R HES.

Innovative fabrication methods for agricultural equipment: The case of a 3-D printed paddy drum seeder-cum-fertilizer applicator

2024-04-09T12:58:48+0530

Rice is a vital staple for nearly half of the global population. It is sown through methods like transplanting and direct-seeded rice (DSR). However, DSR offers more benefits than transplanting methods. While DSR offers advantages such as reduced labour and environmental impact, the separate manual application of fertilizers poses a significant challenge. Innovative 3D printing technology, also known as additive manufacturing, has sparked a transformative shift across multiple industries, facilitating the production of complex three-dimensional structures based on digital blueprints. Its recent application within the agricultural sector has demonstrated significant potential in the fabrication of vital components for farm machinery. Considering this, an attempt has been made to develop components of a four-row manual-operated paddy drum seeder-cum-fertilizer applicator using 3D printing technology in the Farm Power and Soil Dynamics laboratory of the Division of Agricultural Engineering, ICAR-IARI, New Delhi. The paper explores the 3D printing techniques used for fabricating a complex drum seeder, utilizing a 3-D printer with a bed size of 220×220×240 mm. The drum of the seeder comprises two truncated seed chambers and a central cylinder chamber for efficient seed and fertilizer application in two rows. The process involves printing 14 components, including square guides for the drive shaft, truncated conical and cylindrical chambers, hoppers, lids, and orifice covers for each chamber, with printing durations ranging from 1 to 40 hours. The study highlights the significant advantages of 3D printing technology in the fabrication of the drum seeder. The resulting four-row paddy drum-seeder-cum-fertilizer applicator effectively addresses key challenges by integrating fertilizer application with the drum-seeding process. The cost of fabrication of 3-D printed drums was Rs. 3290.4 which is 40% of the total cost of equipment. The cost of operation of a paddy drum seeder-cum-fertilizer applicator per hectare is 2.55 times less than the earlier reported cost of operation with a four-row paddy drum seeder.

Adsorption of Pb(II) on modified ground nut shell (MGNS): Isotherm, kinetic, and thermodynamic study

2024-01-06T20:14:33+0530

The environmental impact of lead compounds is significant. Lead compounds are typically consumed through drinking water and offer a substantial danger. Pb(II) and related compounds are hazardous and have been classified as probable human carcinogens by distinct regulatory authorities. For a regulatory and health standpoint, Pb(II) ion removal from waste water and water is crucial. By sulfuric acid activation, groundnut shell (GNS) has been converted into low-cost activated carbon and grafted with EDTA to make modified groundnut shell (MGNS) powder. An analysis has been conducted on its capacity to adsorb Pb(II) ions from aquatic solutions. An MGNS sample has been examined using SEM, BET, and FTIR techniques, revealing the presence of a porous framework with a surface area of 2143 m2/g. The absorption system adhered to a pseudo-second-order kinetic model, with the equilibrium time being determined at 120 minutes. The adsorption isotherms have been accurately simulated by the Langmuir model. A mechanism involving ion exchange has been suggested by the substantial pH dependence of Pb(II) adsorption on MGNS. Studies on regeneration have shown that MGNS can be reused repeatedly by desorbing them with HCl.

Permeation of Iron slag and recycled aggregates concrete with microstructural characteristics

2023-08-26T11:46:56+0530

Construction and demolition wastes can be used as recycled aggregates (RA) in development of concrete. Iron slag (IS)
has further addeda vision towards its successful replacement of fine aggregates (FA) in non-conventional concrete. This
study investigates the permeation potential of structural grade concrete containing IS and RA as alternative for FA and
coarse aggregates (CA) respectively. The CA have been replaced with RA up to 100% while FA has been substituted with
the fixed amount of IS (i.e. 30%). After achieving of desired strength criterion, concrete mixes have been tested for
resistance towards water, salts and gas permeation. Further, the effect of permeation has also been related with the scanning
electron microscopic (SEM) images. The findings have revealed that both IS and RA resulted in significant variation
towards water (64%), salt (-13%) and gas (47%) ingression making concrete permeable for higher replacements. However,
the findings have been reversed for lower order replacements. The diverse geometry of hydration compounds as noted in
SEM images has also confirmed the potential utilization of IS and RA in the development of non-conventional concrete.

A simplified approach to detect and diagnose the faults in PV array electricity generation system

2023-07-31T09:38:00+0530

Photovoltaic (PV) energy has become recognized as an important alternative energy source because of its efficient conversion method. Nevertheless, issues such as partial shade and faults can considerably diminish the power output of PV arrays, requiring the implementation of efficient fault detection and diagnosis methods to ensure safe and optimal operation. This article presents a simplified mathematical model for photovoltaic (PV) systems and proposes a fault detection method based on the use of solar irradiance, voltage, and current parameters. The system utilizes voltage and current ratios, together with irradiation data, to determine threshold values that can be used to diagnose different fault modes. The fault detection approach has been examined on a 4×4 PV array with a power capacity of 1600 W using MATLAB/Simulink R2019a. The method's accuracy has been verified by further experimental setups. The results demonstrate that the technique is uncomplicated, requires a smaller amount of data for identifying defects, and automatically characterizes faults with a high level of precision.