International Journal of Vehicle Structures and Systems
International Journal of Vehicle Structures and Systems (IJVSS) is a bi-monthly journal and is published by MechAero Foundation for Technical Research & Education Excellence (MAFTREE), Chennai, India from 2009 to 2022. Since January 2023, the publication has been fulfilled by Carbon Magics Ltd, UK. IJVSS will endeavour to publish high quality original research and review papers, case studies, technical notes and book reviews. All published papers in this journal will have undergone rigorous peer review.
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Reduction of Post Leak Defects in AGM-VRLA Battery Assembly Process by using Structured Problem-Solving Approach
This research aims to apply Six Sigma's DMAIC (Define, Measure, Analyse, Improve and Control) methodology to reduce leak rejection in the lead-acid battery manufacturing process. The DMAIC technique has methods for identifying and verifying the causes. The appearance and uniform post-melting of battery terminals were discovered to be highly dependent on the size and composition of the tungsten rod electrode used in inert gas welding. The number of post-leak rejections has significantly decreased when the solution is implemented.
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Enhancing Electric Vehicle Charging with RFID-Based Wireless Power Transfer System
This paper focuses on Radio-frequency identification (RFID)-based wireless charging centres that have become quite popular across the globe due to the vanished charging time, high charging efficiency and enhanced safety. Utilizing the integrated result of a literature review, a variability of methodologies was mulled over such as, wireless charging of RFID, solar based EV charging and Internet of Things (IoT) based monitoring of EV charging stations. This study reveals how these technologies have demonstrated their capacity to translate challenges to opportunities, thereby upgrading to a smart charged ecosystem. A backed-up reliability and sensitivity study gives a detailed review of critical system elements, highlighting the resilience of the proposed RFID-enabled wireless charging system. The Power Transfer Initiation section is thoroughly examined in the process that discloses the existence of a positive and non-linear relationship between one parameter and the overall system performance, which indicates how the system could fall into the saturation point through imprecise innumerable increase, as well as emphasizes the importance of the incremental changes of this parameter. The systematic process is the core of the proposed method, where the following things are defined: RFID tag initialization, product tagging, quality control process, cloud server integration, etc. This is just an overview explanation of the functions of the system. It offers the possibility of automated charging with RFID, increased efficiency and power supply and remote and real-time monitoring, which are the basic principles of any charging station.
Optimizing Nanocellulose Content for Improved Tensile and Impact Strength in Epoxy Resin Composites
This research article delves into the promising realm of nanocellulose as a potential reinforcement material in epoxy resin composites, specifically emphasizing its mechanical and thermal properties. Nanocellulose, derived from plant sources, offers exceptional characteristics such as sustainability, high aspect ratio and superior mechanical attributes, making it a valuable candidate for various applications. This study explores the effects of incorporating nanocellulose into epoxy resin through vacuum casting. Tensile, impact, hardness and thermal analyses were performed on the resulting composite materials. Tensile tests revealed that adding dry nanocellulose in epoxy resin decreased tensile strength and elongation, turning the material from ductile to brittle. However, the composite with 4% nanocellulose exhibited the highest tensile strength among the tested ratios. Impact tests demonstrated a similar trend, with 4% nanocellulose improving impact strength compared to other ratios, albeit not reaching the level of the pure solution. Hardness tests showed marginal changes in the material's hardness, making it slightly less complicated than the pure composite. Thermal analysis through Differential Scanning Calorimetry (DSC) indicated that the melting point of the composite with 4% nanocellulose increased from the pure solution, signifying potential improvements in thermal characteristics. These results contribute to understanding nanocellulose's influence on the mechanical and thermal properties of epoxy composites, emphasizing the need for further optimization to achieve desired material characteristics. By investigating the impact of nanocellulose content on epoxy composites, this study adds insights into the potential applications of nanocellulose in enhancing material properties for diverse sectors, such as defence, textile and material sciences. The research underscores the importance of tailoring nanocellulose content to achieve desired mechanical and thermal attributes, opening avenues for future research and development in green and sustainable nanomaterials.
Experimental Investigation on VCR Diesel Engine using Blends of Rubber Seed Oil and Cetane Enhancer
Non-edible vegetable oils are promising source for replacing diesel fuels partly. Rubber seed oil (RSO) is one such oil available in plenty. However, RSO cannot be directly injected into engine cylinder due to its higher viscosity and lower volatility. Hence, RSO has to be converted into methyl esters to improve its physical and chemical properties. The present investigation aims at transesterification of RSO and to use as blending fuel with cetane enhancer 2-ethylhexyl nitrate (EHN) as additive up to 10% by volume. Two blends are prepared on volume basis namely RSO90 + CE10 and RSO95 + CE5. Improved emissions are observed for blends when compared with RSO100. Marginal increase in HC and CO2 were observed for blended fuels. However, decrease in smoke and NOX emissions were observe for blended fuels. Brake thermal efficiency of RSO90 was slightly increase when compared to other fuels. These may be attributed to shorter combustion duration and ignition delay. On overall basis, RSO90 + CE10 as used as diesel fuel substitute.
Investigation of Mechanical, Microstructure Evolution and Corrosion Behaviour of AA7175/TiB2 Composite
This project aimed to create materials with enhanced strength AA7175/TiB2 composites with varying weight fractions of (0-15 %) that were processed via powder metallurgy. The study involved an examination of the powder morphology and structural features of the composites through X-ray diffraction and optical microscope analysis. Additionally, the density, Micro Vickers hardness and tensile properties of the samples were evaluated. Results from the density measurement indicated that enhancing the wt.% of TiB2 particles effectively improved the densification of Al composites. Furthermore, variations in the granularity of Al powder resulted in distinct grain characteristics and the composites exhibited a sharp interface comprising Al/ TiB2. The composite exhibited the highest relative density, hardness and tensile strength at TB15 composite compared to the fabricated composite. The fracture analysis shows both ductile and brittle failure in composite materials. TB15 composite shows a higher corrosion resistance with less pitting region with an increased corrosion duration.
Wear Equation of AA7050 Aluminium Composites Reinforced with Graphite Particles Produced by Stir Casting
This research investigates the wear behaviour of aluminium-based composites reinforced with graphite particles produced by stir casting. The objectives include evaluating the effect of graphite reinforcement on wear resistance, analysing wear mechanisms and developing a wear equation to predict the wear rate of the composites. The wear rate of composites rose as the proportion of graphite reinforcement increased due to the decrease in material hardness caused by the integration of graphite, which is a comparatively soft substance when compared to the matrix. The presence of graphite particles also resulted in abrasive wear mechanisms, in which the particles served as abrasives, producing additional material loss and increasing the wear rate. The study revealed that higher load and sliding velocities resulted in higher wear rates because they create higher contact pressures and strains at the contact interface, resulting in more severe wear mechanisms and higher wear rates. The developed wear equation, which incorporates the effects of graphite reinforcement, load, sliding velocity and material hardness, can be used to predict the wear rate of these composites.
A Comprehensive Review on Hydrogen as a Fuel
The demand for gasoline fuels has increased due to the population growth. Therefore, we must discover a fuel substitute for gasoline in the transportation sector. It has been shown that H2 fuelled internal combustion (IC) engine emits almost no emissions compared to traditional gasoline-fuelled IC engines. Future H2 energy sources have to be transparent and effective. Climate change presents a significant challenge to science when hydrogen is utilized as fuel, which lowers volumetric efficiency. We want optimum efficiency and minimal pollution in the 21st century. Comparing to fossil fuels, hydrogen is intended to lower the pollution. We take into account its particular traits, such as chemical and physical characteristics, for usage in an IC engine or spark ignition engine. Out of all the fuels, hydrogen results the huge energy content as per the unit mass. One gram of hydrogen is equivalent to 2.8 grams of gasoline. There is a significant heat gradient in hydrogen. Hydrogen, a plentiful element with potential as a clean energy vector, can be converted to electricity via fuel cells and produced sustainably. However, challenges in storage and delivery persist due to its low volumetric energy density, addressed through compression methods through mechanical (reciprocating, diaphragm, linear, ionic liquid) and non-mechanical (cryogenic, metal hydride, electrochemical, adsorption) technologies.
Comprehensive study on the application of Nano Enhanced Phase Change Materials in Battery Thermal Management Systems in Automotive Applications
As we progressively transition from conventional energy sources to more sustainable and renewable alternatives, the emergence of electric vehicles (EVs) in the market stands as a promising step towards strengthening energy security and reducing carbon emissions. The utilization of lithium-ion (Li-ion) batteries, known for their high energy density and extended cycle life, has become widespread in the realm of electric cars. Among various approaches to battery thermal management, the implementation of phase change materials (PCMs) holds significant promise, offering a more reliable solution compared to traditional active and passive cooling methods. The development of PCM-based battery thermal management systems (BTMS) presents its own set of challenges, primarily restricting from the inherently limited heat conductivity of these materials and the complexities associated with their modelling. This study paper is dedicated to addressing a pivotal objective: providing comprehensive insights into the modulation of thermal conductivity in PCMs through the incorporation of Nanoparticles. Additionally, this paper delves into different facets of Li-ion batteries and the integration of nano-enhanced PCMs.
Molecular Transport Kinetics of Benzene through Carbon Black filled ENR/CR/ HNBR Ternary Elastomeric Composites
Applications such as oil seals, gaskets and engine mounting materials of the automotive components demand elastomeric composites with superior resistance to solvent uptake and enhanced mechanical stability. In this context, the present study investigates the effect of carbon black (CB) loading on the solvent transport kinetics of benzene in ternary elastomeric composites of Epoxidized Natural Rubber (ENR)/Chloroprene Rubber (CR)/Hydrogenated Nitrile Butadiene Rubber (HNBR) (ECH) at room temperature. The results reveal a significant decrease in solvent transport in the ternary ECH composites compared to the virgin ECH blend, with a nearly linear reduction observed as CB filler loading increases. This behaviour is attributed to enhanced filler-elastomer interactions and the formation of filler networks, which reduce void spaces within the composite matrix. To model the transport behaviour of composites with varying CB filler contents, four diffusion kinetic models-zero-order kinetics, first-order kinetics, Higuchi, Korsemayer-Peppas and Peppas-Sahlin- were analysed using MATLAB optimization, minimizing the norm error of regression. Among these, the Peppas-Sahlin model exhibited the best agreement with experimental data, making it a reliable tool for predicting solvent transport behaviour. These findings provide critical insights for designing advanced elastomeric materials for automotive applications, ensuring enhanced performance and durability under demanding operational conditions.
Impact of Variable Geometry Micro Channel Heat Exchanger on Tube and Fin in an Automotive Air Conditioning
The primary objective of this study is to enhance condenser performance by employing innovative tube and port shapes that regulate the refrigerant volume, in conjunction with variable fin geometry. The aim is to comprehensively investigate the influence of refrigerant and air-side heat transfer coefficient (HTCs). Analytical calculations were conducted for both fin and tube geometries and the results were juxtaposed with findings from both CFD simulations and experimental setups. Furthermore, as an initial step, the analytical calculations delved into the effect of two-phase density on refrigerant-side heat transfer. These analytical results were cross-referenced with CFD simulations and experimental data and they were found to fall within a correlation range of 10%. It is worth noting that the rectangular tube shape, while boasting a lower pressure drop, exhibited a relatively lower HTC. Conversely, the hexagon model demonstrated a higher pressure drop, coupled with a higher HTC. The configuration of a hexagon with rectangular ports, coupled with the precise selection of fin geometry, yielded superior results when compared to other shapes, such as rectangular and oval tubes. These results highlight the feasibility of using analytical methods in the initial design phase of automotive product development. Subsequently, these analytical findings can be correlated with experimental data, offering potential cost savings in prototype part development and reducing the lead time to market.
Dynamic Stability Analysis of Aircraft Landing Gear using PID Controller
In the aviation industry, ensuring both the structural integrity and passenger comfort of aircraft stands as a primary concern, driven by the potential hazards posed by fatigue failures in structural components. This study endeavours to undertake a comparative examination of various damping coefficients and spring constants within a typical landing gear system. These parameters are then integrated with a Proportional-Integral-Derivative (PID) controller to elevate the performance standards of the landing gear control system. The overarching objectives include the reduction of peak overshoot and the minimization of settling time concerning aircraft displacement, thereby amplifying overall safety measures and passenger comfort levels. The landing gear system under investigation is delineated through a sophisticated (2 DOF) Mass-Spring-Damper model, which furnishes the foundation for deriving the equation of motion. Leveraging the specific parameters of the aircraft, alongside the derived equations, a meticulously crafted MATLAB/Simulink model is established, facilitating comprehensive analysis and simulation procedures. By applying Laplace transform methodologies, a transfer function is meticulously constructed. This facilitates the seamless integration of a PID controller with the system, thereby laying the groundwork for establishing a closed-loop control system. Such a system affords precise regulation and optimization of the landing gear dynamics, culminating in enhanced operational efficacy. A rigorous comparative analysis is conducted to gauge the efficacy of various models, prompting adjustments to the spring constants and damping coefficients based on the discerned findings. This iterative refinement process serves to fine-tune and optimize the system's performance in alignment with the predefined objectives.
Evaluation of Machine Learning Models in Predicting Diesel Engine Behaviour and Emissions with Biodiesel Blends
The fuel qualities and compatibility of biodiesel with diesel fuel derived from petroleum have been drawing more and more attention to it. As a result, testing the efficiency and pollution levels of diesel engines powered by biodiesel blends and conventional diesel fuel derived from petroleum is essential. The objective of this research is to use a variety of machine learning (ML) methods to analyse the efficiency and pollution levels of diesel engines that run on biodiesel mixes. An example of one such method is supporting vector regression, which falls under artificial neural networks (ANNs), while another is adaptive neuro-fuzzy inference systems (ANFIS). Utilizing biodiesel blends B0, B5 and B10 in a Toyota 2GD-FTV engine is the focus of the case study. The model takes the engine's process parameters as inputs and produces NOX emissions and predicted torque as outputs. We construct and evaluate numerous prediction models that rely on ML. Using RMSE (Root Mean Squared Error), MAPE and R (Mean Absolute Error and Correlation Coefficient), we evaluate and contrast the models' efficacy. Based on the outcomes, Support Vector Regression (SVR) seems like a good fit for the model that will be employed to forecast behaviour and emissions. In addition, study elucidates the impact of several engine process parameters on emissions and performance.
Enhancing Mechanical Properties and Water Resistance of Sisal-Epoxy Composites using Silicon Carbide Nanoplatelets by Vacuum Infusion Molding
Sisal composites exhibit a high strength-to-weight ratio, although its automotive application is restricted due to weak fiber-matrix interface bonding. A new method was created to produce multiphase composites by using silicon carbide nanoplatelets (SiC), sisal fibers and an epoxy matrix. Vacuum infusion molding (VIM) was employed to manufacture the composites and a bath sonicator was used to exfoliate the SiC for equal dispersion. The composites enhanced with 0.255 wt% SiC exhibited the most notable enhancement in mechanical characteristics. Many mechanical characteristics of the composites were pointedly improved: tensile strength increased by 34.2%, tensile modulus increased by 65.7%, flexural strength increased by 21.8%, flexural modulus increased by 26.9%, interlaminar shear strength increased by 39.3% and fracture toughness mode-II increased by 21.3%. Multiphase composites improved their water absorption resistance by as much as 8%. The enhancements were credited to the more even distribution of SiC and better adhesion to the fiber's surface. Vehicle dashboards, interior walls and trunks could all benefit from the composite material's use.
Design of Experiments Approach to Optimize Cutting Parameters for Tangential Cylindrical Grinding of AISI D3 Tool Steel
Utilizing the Taguchi approach, the research sought to determine the best cutting parameters for tangential cylindrical grinding of AISI D3 tool steel to minimize surface roughness. Throughout the experimental examination, surface roughness was observed at different wheel speeds, workpiece speeds, feed rates and depths. Surface roughness was studied using the Taguchi design of experiments and Analysis of Variance (ANOVA) and the signal-to-noise ratio was used to identify key machining factors. The results showed that during cutting, surface roughness was significantly influenced by wheel speed and feed rate. This implies that surface quality in grinding processes can be efficiently controlled by varying these factors. Because the established grinding technique makes it possible to determine the ideal cutting settings for decreasing surface roughness, it has potential applications in the machining industries. This could result in tool steel machining procedures that are more productive and of higher quality.
Emergency Message Transmission in Vehicular Ad-Hoc Networks and its Performance Analysis using AODV, OLSR and VGEO Protocols
Due to the ability to change people's lifestyle, communication systems are of great importance in the development of societies. Thanks to the variability of applications, today, communications are necessary for the evolution of relationships between individuals, groups and institutions in a society. Communication systems between vehicles are not ruled out in the connection process. One of the main applications that arouses interest in the industry is the study and development of vehicular communication networks Vehicular Ad-Hoc Networks (VANET). These networks enable vehicles to act as communication devices to provide information with the aim of offering comfort and safety to all users of the network. The transfer of emergency messages in a VANET is of great importance when providing medical assistance in a situation where a catastrophe has occurred. However, the sending of information in these networks presents a real technological challenge due to the dynamism they present, which has led to the implementation of different protocols for the containment of the different problems and inconveniences that they show. This final degree project aims to study the definition of VANETs, as well as their characteristics, categorization and description of protocols commonly used by them. An investigation is carried out through a simulation of the network behaviour, to finally observe and analyse the performance of the Ad hoc On-Demand Distance Vector (AODV), Optimized Link State Routing Protocol (OLSR) and Vehicle Geographic Routing Protocol (VGEO) protocols in the transmission of emergency message packets over a VANET network. For the analysis of the research, the free software NS-3 and SUMO were used. Through SUMO, a vehicular mobility environment was set up on an area that emulates a layout of streets and intersections through the obtaining of tcl files. Through this software, the simulation and network parameters are built for the evaluation of the efficiency and scalability of each protocol.
Corrosion Study on AZ80/91 Mg-Alloys Processed at Different Temperatures during the ECAE Process
Magnesium (Mg) alloys have emerged as promising materials for lightweight vehicle structural applications due to their high strength-to-weight ratio, contributing to enhanced fuel efficiency and reduced emissions. However, their susceptibility to corrosion has been a significant obstacle to their widespread adoption. This study investigates the corrosion behavior of AZ80/91 Mg alloys processed through Equal Channel Angular Extrusion (ECAE) at varying temperatures. ECAE is a powerful deformation technique that refines the microstructure and enhances the mechanical properties of materials. The influence of processing temperature on corrosion resistance in these alloys has been relatively unexplored, making it a critical area of investigation. As a concluding remark, the electrochemical corrosion of AZ80/91 Mg alloys showed better corrosion resistance after ECAP at a higher processing temperature of 663K compared to a lower processing temperature of 533K, this revealed a 71% and 90% improved corrosion resistance for AZ80 and AZ91 Mg alloy respectively.
Investigation for Thermal Relation Between Connecting Rod and Fins through Thermal Analysis of a Triangular Fin Made of Various Materials
This paper explores the analysis of heat transfer through non-uniform geometries, specifically focusing on an I section and triangular fin configurations. Boundary conditions, such as constant temperature or uniform heat flux at the base and fully insulated or convective conditions at the tip, were applied to both the I section and the fin. Thermal analysis utilized the Fourier law, the first law of thermodynamics and Newton's law of cooling for both the I section and triangular fin. Analytical solutions were derived for conduction and convection, with the latter employing Bessel functions for the triangular fin. The study considered materials such as copper, aluminium, brass, cast iron and steel and various parameters such as heat flux, temperature distribution, fin effectiveness and fin efficiency were analysed. To present the findings, graphs depicting the analysed parameters were generated using Microsoft Office Excel 2016. The material properties were assumed to be isotropic throughout the analysis.
Dynamic Characteristics Determination of Viscoelastic Sandwich Beam using Finite Element Method
With the aim of reducing the various structural vibrations, the numerical methods have been developed with the structural damping capacity. The use of passive control in viscoelastic materials has been proven too much of effective to all the methods. The reason being the ability of the materials to exhibit low bearing capacity, when subjected to cyclic deformations makes them more sustainable and justifies the reason for using stiff elastic materials sandwiched between the viscoelastic materials. Viscoelastic sandwich beams were developed to fulfil the need for lightweight beams with excellent compression strength, good stiffness-to-mass and strength-to-mass ratios, alongside excellent damping properties. An investigation of the free vibration analysis of a three-layered viscoelastic sandwich beam is performed, both numerically and experimentally, under the assumption of linear viscoelasticity as per the Maxwell model. Three boundary conditions, namely cantilever, fixed-fixed and simply supported, were applied on the beam in order to study its vibrational behaviour under these conditions. The numerically obtained results are compared against the investigated results. A strong correlation is found between the investigations and the numerical results. The graphs presenting the identification of the natural frequencies through experimental impact hammer testing have been shown and the mode shapes for the corresponding natural frequencies have been presented.
PID and ANFIS based Control of Semi-Active Suspension System using Different Membership Functions
This study considers proportional-integral-derivative (PID) and adaptive neuro fuzzy inference system (ANFIS) controllers for stabilizing extremely dynamic semi-active suspension of quarter-car model. The free-body-diagram analysis was conducted and system was then simulated in Matlab-Simscape using PID controller. The results of PID were acquired as inputs for ANFIS controller. The ANFIS controller was trained via three different membership functions (MFs) namely triangular, trapezoidal and Gauss. The results clearly demonstrate that MF shape effects the learning of ANFIS. The fallouts highlight superior responses of ANFIS technique then PID. Moreover, ANFIS controller designed using Gauss shape MF performed better than other shaped MFs.
Performance and Analysis of RCCI Combustion using Gasoline and Jatropha Curcas Biodiesel for Enhanced Efficiency and Reduced Emissions in CI Engines
This research focuses on reduce Nitrous oxide (NOx) and soot emissions while enhancing the efficiency of Compression Ignition (CI) engines by implementing the Reactivity Controlled Compression Ignition (RCCI) approach, which incorporates the use of low-reactive gasoline as a fuel source. The highly reactive biodiesel (BD) derived from Jatropha Curcas (JC) feedstock served as an ignition source for RCCI combustion. According to the research, when compared to BD blends, the combustion of RCCI resulted in improvements of about 0.2-1.2% for Brake Thermal Efficiency (BTE), 11.3-44.6% for Net Heat Release Rate (NHRR) at full load and 4.9-13.6% for maximum in-cylinder combustion pressure. Similarly, the RCCI method effectively decreases NOx and soot emissions by 24.40-43.74% and 31.28%-52.57% under max loads. However, the emissions of carbon monoxide (CO) and hydrocarbons (HC) are more than those of biodiesel at all levels of usage. Nevertheless, increasing the gasoline injection duration from 3ms to 5ms (milli second) in RCCI mode results in a drop in Pmax, NHRR, BTE, as well as NOx and soot emissions. The primary reason for this is mostly due to the superior cooling properties of gasoline and the longer period of time it takes for ignition to occur. The process of multi-response optimization is carried out utilizing VIKOR, B15 + 2ms GF and it is determined that operating at 80% load is the most optimal condition.
Optimization of Underwater Friction Stir Welding Parameters for AA5128 and AA 7075 Aluminum Alloy using Response Surface Methodology
The lower melting points and inherent welding difficulties of aluminium alloys make the process of joining them a formidable obstacle. This is why FSW solid-state friction stir welding (FSW) has become so popular in the industrial sector. To improve ultimate tensile strength, yield tensile strength and microhardness, this study uses the FSW process to combine two different aluminium alloys of AA7075 and AA5128. The experimental plans were developed utilizing a central composite design based on response surface methodology. The four input factors that were considered were tool pin profile (TPP), tool rotational speed (TRS), tool traverse speed (TTS) and axial force (AF). The experimental results demonstrate that all of the outputs are significantly affected by the input variables that were taken into account. The optimal conditions, which include a TRS of 1007 rpm, a TTS of 32 mm/min and an AF of 7.7 kN with a triangular pin profile, were derived from a multi-objective optimization technique utilizing the desirability approach. The outputs of the confirmation experiment show a max variance of 9.13% with investigative results under ideal conditions and the second-order regression model predicted values for these responses with reduced residuals. There are no holes, oxides, or fractures visible in the micrographs taken from the heat-affected zone area. Base metals and other components appear in the nugget zone.
Fuel Efficiency Analysis using Machine Learning Approach
In this modern era, vehicular improvements in terms of cost, effective utilization of fuel saving, power has become a necessary and prime task. The applications of predicting fuel efficiency (FE) are investigated by wide group of research community using several methods. From improving vehicle design and fleet management to supporting environmental initiatives and consumer applications, predictive models can drive innovation and efficiency across multiple sectors. By leveraging the power of deep learning (DL), organizations can make data-driven decisions that lead to significant economic, environmental and societal benefits. Predicting FE using Tensor Flow in Python with DL presents a powerful and efficient approach to addressing the challenges associated with fuel consumption and vehicle emissions. The combination of Tensor Flow’s robust framework and the capabilities of DL allows for the development of highly accurate predictive models that can significantly impact various sectors. The continuous advancements in DL and the expanding capabilities of Tensor Flow promise further improvements in predictive accuracy and efficiency. As more data becomes available and computational power increases, the potential for even more sophisticated and impact applications of FE prediction will grow. Using Tensor Flow in Python with DL for predicting FE represents a significant step forward in the quest for more sustainable and efficient transportation solutions. By harnessing the power of advanced machine learning techniques, organizations can make data-driven decisions that lead to tangible benefits for the economy, the environment and society as a whole. This methodology not only enhances our ability to predict FE accurately but also opens up new avenues for innovation and improvement in various sectors, driving progress towards a more efficient and sustainable future.
Investigation of Surface Roughness during Machining of Al-Composite on EDM using Regression Analysis and Genetic Algorithm
Al-composites have several applications in lightweight structures. But due to the high hardness particulates reinforced in the Al matrix, it isn't easy to machine it via conventional machining. Therefore, a non-conventional machining method was used to process the aluminium matrix composite (AMC). Out of all the available methods, electric discharge machining (EDM) was considered one of the viable options for processing Al-composite. Thus, EDM was used to machine the AMC at different machining parameters and with different tool electrodes. Brass and copper electrodes of 12 mm diameters were used. The other machining parameters were pulse on-time (Pon), pulse off-time (Poff) and voltage (V). A Taguchi-based L18 mixed array was used for the planning of experiments. The mean roughness value (Ra) was measured for the corresponding experimental setting. The regression coefficients were computed using regression analysis and finally empirical model has been developed. The developed empirical model was solved using a genetic algorithm. The optimization was completed using an integrated approach of Regression and Genetic algorithms. The optimized setting suggested by Regression-GA is tool: brass, Pon: 30µs, Poff: 90 µs and V: 8V and the corresponding value of Ra is 2.99 µm. The confirmation experiments were conducted on the suggested optimized setting and a close agreement has been found between the predicted value (predicted by integrated approach of regression analysis and genetic algorithm) and experimental value.
Consequences of Modification in Interface Angles of the Plates in Friction Stir Welding of Different Aluminium Alloys
Because of their low weight and good strength, AA6101-T6 and AA1350 aluminium alloys are extensively utilized in the electrical and automotive industries. A number of compelling benefits of friction stir welding (FSW) include the capability to weld metals that are challenging to weld using typical welding techniques. This one is carried out in the solid-phase and as a result, weldments do not experience solidification related problems. Hence, the joining of these alloys is conducted by FSW process. The primary goal of this research is to look into the effects of angular variation between aluminium alloys at the interface region. Here, the interface angle means the angle at which end surfaces of two plates mate each other. To evaluate the properties of weldments, tensile and hardness tests, macro and microstructural analyses were conducted. When compared to various interface angles, the results showed that a 90° interface angle results in enough heat input, plastic flow of materials, dynamic recrystallization and fine grain structure which leads to a defect-free weld and better tensile (69 MPa), hardness (57.1 VHN) and wear (7.69 % weight loss) properties. Whereas 150° interface angle at retreating side yields poor tensile (46 MPa), hardness (41.3 VHN) and wear (10.40 % weight loss) properties. This is attributed with insufficient heat generation and lack of plasticization at lower portion which produces poor flow properties of materials, cracks and volume defects.
Enhancement of Corrosion and Wear Resistance in Maritime Propeller Systems through Copper Electroplating on Nickel based Superalloys
Thin coatings applied to surfaces are extremely important in industrial applications because they protect base materials against wear, corrosion and other surface-related hazards. Extensive study has been performed in the field of maritime engineering, where standard steel propellers are highly prone to corrosion, to investigate improved alternatives such as nickel-based superalloys. These superalloys are notable for their lightweight qualities and outstanding corrosion resistance, making them a possible replacement for ordinary steel propellers. Electroplating, specifically the deposition of a copper coating onto nickel-based superalloy substrates, is the primary focus of this research effort. The goal is to build a protective copper covering that is up to 10 microns thick. The primary purpose of this research is to improve the ability of the nickel-based superalloy to endure wear, corrosion and general surface deterioration by methodically altering process parameters during electroplating. The key objective is to improve the copper coating process in order to achieve maximum efficiency. A complete set of experiments was performed to evaluate the performance of the coated surfaces. The resistance to wear was examined using the pin-on- disc method, while the resistance to corrosion was investigated using salt spray testing in a controlled environment with an ASTM B-117-compliant NaCl solution. Brinell hardness testing was also used to determine the hardness of the coated samples. Furthermore, the microstructure of the coated surfaces was painstakingly studied using Scanning Electron Microscopy (SEM) to gain vital insights into the structural properties and integrity of the copper-coated nickel-based super alloy.
Experimental Investigation to Mitigate Environmental Pollutants by using Emulsified Biodiesel
This experimental study explores the potential of emulsified biodiesel blends, comprising 20% palmyra methyl ester and 80% diesel (B20), in reducing environmental pollutants in a single-cylinder, four-stroke diesel engine. The blends were emulsified using Span80 and Tween 80 as surfactants, with 5%, 10% and 15% water content. The emulsification process, employing a Mech method, yielded blends labelled B20W5 (90% B20, 5% water, 5% surfactant), B20W10 (85% B20, 10% water, 5% surfactant) and B20W15 (80% B20, 15% water, 5% surfactant). The study focuses on evaluating the engine's performance, emissions and combustion characteristics under various engine loads, from no load to full load conditions. Results indicate that although emulsified biodiesel blends exhibited lower Brake Thermal Efficiency (BTE) than diesel, B20W10 showed the highest BTE, approximately 4% higher than B20W15. Additionally, there was a substantial reduction in nitrogen oxide (NOX) emissions with increasing water content, with B20W15 demonstrating a 30.61% reduction compared to neat diesel operation. These findings suggest that emulsified biodiesel blends, especially B20W10 and B20W15, could serve as sustainable alternatives to diesel fuel, with reduced environmental impact in terms of NOX emissions.
Research on CNN and Phase Correlation Fusion Algorithm for Vehicle Stopping State Detection in VINS System with Dynamic Scenarios
Vehicle stopping state detection in dynamic scenes is a key technology for autonomous driving and Intelligent Transportation Systems (ITSs), playing a crucial role in enhancing vehicle localization accuracy and safety. This paper proposes a vehicle stopping state detection method based on a fusion algorithm combining Convolutional Neural Networks (CNN) and phase correlation, aiming to address the challenges of detection accuracy degradation caused by moving object interference and complex environmental changes in dynamic scenes. The method extracts static background features and filters out dynamic objects using a lightweight CNN model, while leveraging the Phase Correlation Algorithm (PCA) to compute global Motion Vectors (MVs) between consecutive frames, thereby achieving high-precision detection of vehicle stopping states. The experimental outcomes reveal that the suggested technique shows outstanding efficacy on both public datasets and real-world scenarios, achieving a dynamic object detection accuracy of over 75% with the computational load greatly reduced to 2.3 Floating Point Operations (FLOPs). The entire fusion algorithm can improve the accuracy of vehicle stopping state detection to 95.6%, while meeting real-time requirements (inference time of 22 ms per frame). Additionally, the method maintains strong robustness under low-light and adverse weather conditions, providing a new solution for optimizing Visual-Inertial Navigation Systems (VINS) in dynamic environments. The research outcomes of this paper not only provide theoretical support for stopping state detection in autonomous driving systems and lay a technical foundation for the realization of ITSs.