Search

Automobile structural components are subject to high stress, friction and corrosive environmental conditions. Though aluminum alloys exhibit lightweight and high corrosion resistance, there is a need to improve the high strength-to-weight ratio and resistance to friction. This paper presents microstructural analysis, hardness, dry sliding wear behavior, and corrosion behavior of AA7075 reinforced with silicon carbide (SiC) particles. The composite specimens were prepared at the concentration of 2.5 and 5wt.% SiC. The microstructure of AA7075 showed dendritic morphology while composite specimens showed nondendritic morphology grains. Reinforcement of SiC resulted in increased nucleation site and refinement of grain during solidification. XRD analysis of base alloy showed α matrix with η (MgZn2), T(Al–Zn–Mg–Cu) and Al7Cu2Fe phases, while the composite sample showed the presence of additional S(Al2CuMg) and θ (Al2Cu) phases. Composite samples showed higher hardness values than base alloy due to grain boundary strengthening and Orowan strengthening. The enhancement of hardness of AA7075 by 20% and 37.5% were obtained with the addition of 2.5 and 5wt.% SiC particles respectively and also predicted with less coefficient of friction and less wear rate at all the tested load conditions. At the same time, the respective reduction in wear rates of AA7075 was found to be 50 and 65%. The worn-out surface of the base alloy was found to have undergone extensive plastic deformation and resulted in delamination with extensive patches and no clear groove marks. The composite sample of 2.5wt.% SiC showed mild patches with clear groove marks, while the Composite of 5wt.% SiC showed groove marks with fine width parallel to sliding directions. The wear mechanism was found to be transferred from adhesive mode to abrasive mode through a mixed mechanical layer with an added concentration of SiC particles from 0wt.% to 5wt.%. Weight loss during immersion corrosion increases with an increase in the amount of SiC due to an increased amount of metallic phase which increases microgalvanic corrosion and pitting. Hence, composite samples showed decreased corrosion resistance than base alloy. [ABSTRACT FROM AUTHOR]

Equal channel angular pressing (ECAP) processed materials have higher grain refinement and strength, and they exhibit more surface roughness when they are machined. This enhancement in the properties highly influences the surface roughness and material removal rate of the materials. The commercial pure aluminum has a wide variety of applications when it is enhanced with high strength properties. In this paper, the machinability of commercially pure aluminum processed through ECAP is investigated in turning operations. Different ECAP processes are carried out to study the microstructural characterization and mechanical properties of the material. The material removal rate and surface roughness are tested by performing the turning operation in the CNC lathe with chemical vapor deposited carbide tool such that the feed rate, spindle speed and depth of cut are considered as the machining variables. To create a hypothesis for the experimentation, the empirical models are developed for the objective functions using the statistical technique response surface methodology (RSM) such that the response models are the objective functions and the model variables are the machining parameters. The response models are verified for the adequacy through ANOVA and p -test, and also verified for the closeness with the experimental results. Artificial neural network (ANN)-based empirical equations are also developed for the objective functions using the RSM design matrix and the results of both the RSM and ANN are compared for the suitability. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) makes connectivity between physical devices which are embedded with sensors, software, and connectivity that let them to communicate and transfer data. This technology makes it possible to collect and transfer data from a vast network device, opening the door to the development of automatic and more efficiency systems. The term "waste management" refers to all of the responsibilities essential to regulate trash, from the point of gathering through reusing and monitoring. Reducing the hazardous consequences of such garbage on the environment and human health is the goal of waste management. By considering these hazardous consequences, this research work is interested in working on an efficient waste management system. The utilization of IoT devices enables municipalities to optimize waste management operations by leveraging data insights. This information aids in scheduling waste collections more effectively and planning optimal routes. Therefore, the research work proposes an IoT-based waste management system with two vital processes such as IoT routing and waste management. At first, routing in IoT is done by proposing hybrid optimization algorithm named Snake Optimization Updated Beluga Whale Optimization algorithm (SOUBWO) under constraints such as distance, energy, link quality, delay, and trust. Secondly, waste management is worked on by following steps including pre-processing, segmentation, feature extraction, and classification. The waste images collected by IoT devices are transmitted from source node (SN) to destination node (DN) by optimal routing. Those transmitted waste images are pre-processed by Wiener filtering process. Consequently, the pre-processed images are segmented by employing proposed Balanced Iterative Reducing and Clustering Using Hierarchies-Altered Distance Metrics (BIRCH-ADM) algorithm. Subsequently, features such as multi-text on histogram feature, proposed Local Gabor XOR Pattern (LGXP)-based feature using novel image processing techniques, and statistical features are extracted. Finally, these extracted features are efficiently classified by hybrid classification model which is formed by integrating conventional deep maxout and Bidirectional-Long Short Term Memory (Bi-LSTM) networks. The effectiveness of the proposed approach is validated through various analyses, including performance and statistical analyses. Moreover, the proposed scheme demonstrates minimal energy consumption, with a recorded value of 0.123. In contrast, conventional methodologies exhibit higher energy consumption, with values such as SOA = 0.237, BWO = 0.146, BES = 0.183, SMO = 0.158, CHOA = 0.174, and PSO = 0.189, respectively. By this hybrid classification model, the process of classification on waste is effectively done and moreover its effectiveness is proved by various analyses., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The main objective of the present research work is to utilise the produced bio-oil from microwave pyrolysis of Karanja, a non-edible seed, as fuel for diesel engines by increasing some up-gradation in the quality of the fuel. The emulsification process is carried out to improve the stability of the diesel-bio-oil blend using SPAN 80 and TWEEN 80, which lasted for 28 days without any layer separation termed as EKB20. The addition of 5% DEE and 10% DEE into EKB20 is done to enhance the combustion characteristics of the diesel engine. The produced bio-oil fuels were tested in a Kirloskar make, four-stroke, single-cylinder, direct injection diesel engine of 5.2 kW rated power output. The addition of DEE reduces the peak pressure by 4 bar and increases the heat release rate due to the higher volatility of DEE. At full load conditions, the thermal brake efficiency improved by 9.31% and 14.11%, respectively, compared to EKB20. Adding 5% DEE and 10% DEE at the rated power output reduced the smoke density by 18.42% and 60.25%, respectively, compared to EKB20 and 5% and 4% compared to diesel. The addition of 5% DEE and 10% DEE shows a 39% and 51% increase in NO X concentration and a 90% reduction in CO emission at the maximum brake power output. Hence, it is concluded that the fuels EKB20 + 5% DEE and EKB20 + 10% DEE can be used as alternative fuels for diesel engines., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study focuses on the extraction and dyeing properties of natural fabric dyes derived from brown seaweeds, namely Padina tetrastromatica, Sargassum tenerrimum, and Turbinaria ornata. Various solvents (acetone, ethanol, methanol, and water) and mordants (CH 3 COOH, FeSO 4 , and NaHCO 3 ) were used to extract the dyes and achieve different shades with excellent fastness properties. Phytochemical and FTIR analyses were performed to identify the phytochemicals responsible for dyeing. The dyed cotton fabrics exhibited a range of colors based on the mordants and solvents used. Fastness assessments revealed that aqueous and ethanol dye extracts exhibited superior properties compared to acetone and methanol extracts. The influence of mordants on cotton fibers' fastness properties was also evaluated. In addition to the above findings, this study makes a significant contribution to the field by exploring the bioactive potential of natural fabric dyes derived from brown seaweeds. The utilization of these abundant and low-cost seaweed sources for dye extraction provides a sustainable alternative to synthetic dyes, addressing environmental concerns associated with the textile industry. Furthermore, the comprehensive analysis of different solvents and mordants in obtaining various shades and excellent fastness properties enhances our understanding of the dyeing process and opens avenues for further research in the development of eco-friendly textile dyes., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Diesel engines are most widely used as power plant for many applications, like automotive, agricultural purposes, portable machines and remote location power generation, because of their higher torque, power output, energy content per unit mass and cost of fuel. Because of the higher compression ratios, the diesel engines are able to produce greater cylinder pressures resulting in higher temperatures and thermal efficiency. On other hand, the diesel engines produce CO x , NO x , Soot and sulphur emissions which are harmful and these pollute the environment leading to acid rain, global warming and variety of human diseases. Also, the present emission regulations are framed such a way to ensure the environmental sustainability in addition to the economic and social importance. These constraints make the researchers find an alternate fuel for replacing the diesel fuel on the existing diesel engines for the reduction of environmental pollutions. Biodiesel is found to be a very good alternative fuel obtained from natural resources and having good energy with least possible emissions. Rubber seed methyl ester (ROME) is one kind of the biofuel can be used in the existing diesel without any engine modifications. The ROME is produced using trans esterification process and the biodiesel blends are prepared in the sequence of B20, B40, B60 and B80. The ROME is tested on the Variable Compression Ratio (VCR) engine to test the emission characteristic in line with the performance characteristics. To reduce the emissions, the prediction models are developed for CO and NO x using the Response Surface Methodology (RSM). The models are verified through the ANOVA and p-test for their adequacy to create the hypothesis of the experimentation. The NSGA II evolutionary multi-objective optimization is used to optimise the engine parameters to minimise the pollutions from the ROME fuelled engine. The optimized parameters are tested and verified experimentally for the least possible emissions., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Nowadays, the emissions from the diesel engines are focused lot to minimise the environmental pollutions in accordance with the emission standards. In this regard, biodiesels are found to be efficient for the diesel engines due to their higher energy contents and low exhaust emissions. Use of biofuel in association with diesel will be an efficient way for the cost-effective performance of the diesel engines with reduced pollutions. The COME is an efficient combustible oil, in which the diesel is blended at different proportions to identify their suitability in the diesel engines. In this regard, the properties of the COME-Diesel blends are determined and analysed for their influence on the combustion characteristics. To understand the performance and emission characteristics of blends, experiments are carried out on the variable compression ratio (VCR) engine keeping the blend, compression ratio, load, and speed as variables. The response surface methodology (RSM) used as a tool for designing and conducting the experiments according to the predetermined variables. The experimental sets generated are performed to determine the NO and HC emissions (response functions). The adequacy of the models is verified through ANOVA and through the p and F tests. The experimental design matrix is also used in training the artificial neural network (ANN) to develop the empirical models. The models from RSM and ANN are experimented and the results obtained from both the models are compared for their accuracy levels. Once the hypothesis is developed for the biodiesel and engine setup, the emission models will be used for the optimising the engine operating parameters and blends to minimise the pollutions from engine for wide operating conditions., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)