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Aluminum alloy AA2024 stands out as a widely utilized age-hardening alloy in aircraft applications worldwide. Despite its superior weldability in comparison to its 6000-series counterparts, AA2024 still reveals vulnerability in the welded joint. Specifically, in the T6 condition, the joint strength is only about 40% of the strength exhibited by the base metal. Faced with this challenge, design engineers often resort to selecting thicker base metal plates due to notable disparities in strength values, particularly concerning yield strength. AA2024 alloy is welded using low heat input electron beam welding. This weld is eliminated all demerits in other fusion welding process. However, heat affected zone is always a weaker region in all the fusion welding process. Post weld heat treatment process, namely, solution treatment and artificial ageing was performed to dimmish the width of weaker region.

The development of ramjet engines has experienced a significant increase in response to the growing demand for supersonic speed capabilities in contemporary propulsion systems and missile weaponry. Their efficient operation at supersonic speeds has garnered increased attention. The study focuses on designing a diffuser and ram cone for decelerating supersonic flow in the combustion chamber. Performance tests for hydrogen and ethanol fuels are conducted at Mach values of 3.5, 3, and 2.5. Injectors are positioned asymmetrically in parallel, perpendicular, and at a 45-degree angle to the flow. Effects of injector orifice diameters (0.8mm, 1mm, 1.2mm) on atomization and penetration length distribution are investigated. SolidWorks is used for design, and Ansys with a coupled implicit second-order upwind solver analyzes the Reynolds-averaged Navier-Stokes equation. Eddy dissipation handles combustion. Hydrogen and ethanol are modeled and injected, reacting with atmospheric oxygen.

Effect of Lanthanum addition on mechanical properties of LA93 along with its microstructural evolution has been analysed using optical microscopy, scanning electron microscope (SEM) and energy dispersive spectroscopy (EDS). The phases of this alloy were identified by X-ray diffraction (XRD). La addition has resulted in a reformed semi continuous structure with a decrease in grain volume along the boundary. The morphology shows the formation of Al2La and Al3La phase while the AlLi in LA93 has decreased. At 1.5 wt% La addition, the maximum grain refinement is obtained. In LA93+xLa, the Al2La and Al3La appear as a white long stripy phase and a white large blocky phase, respectively, and contribute to the increased strength of the alloy. There is a clear distribution of intermetallic compounds along the grain boundary of α-Mg and inside the matrix. The ultimate tensile strength increases by 60% to 112 MPa and hardness increases by 48% when the La content is 1.5 wt%.

The requirement for lightweight, high-performance materials with higher wear resistance, which is critical in industries such as aerospace, automotive, and consumer-related sectors, has fueled the development of particle reinforced metal matrix composites (PRMCs). These materials are an appealing alternative for a broad variety of scientific and technological applications due to their remarkable mechanical qualities and low cost. The primary goal of developing metal matrix composite materials is to combine the favorable properties of metals and ceramics. This study included several experimental experiments to explore the behavior of stir-cast composites made of aluminum grade 6063 with varying amounts of SiC, Al2O3, and TiO2 reinforcements.

Additive manufacturing (AM) is a common way to make things faster in manufacturing era today. A mix of polypropylene (PP) and carbon fiber (CF) blended filament is strong and bonded well. Fused deposition modeling (FDM) is a common way to make things. For this research, made the test samples using a mix of PP and CF filament through FDM printer by varying infill speed of 40 meters per sec 50 meters per sec and 60 meters per sec in sequence. The tested these samples on a tribometer testing machine that slides them against a surface with different forces (from 5 to 20 N) and speeds (from 1 to 4 meters per sec). The findings of the study revealed a consistent linear increase in both wear rate and coefficient of friction across every sample analyzed. Nevertheless, noteworthy variations emerged when evaluating the samples subjected to the 40m/s infill speed test.

Aluminum alloys are employed in agricultural equipment, aerospace sectors, medical instruments, machinery, automobiles, etc. due to their physical and mechanical characteristics. The geometrical shape and size of the parts are modified in turning operation by using a single-point cutting tool. A356 aluminum alloy is widely used in various engineering sectors, hence there is a necessity to produce A-356 components with quality. The inappropriate cutting parameters used in turning operation entail high production costs and reduce tool life. Box–Behnken design (BBD) based on response surface methodology (RSM) was used to design the experiments such that the experiment trials were conducted by varying cutting parameters like N-spindle speed (rpm), f-feed rate (mm/rev), and d-depth of cut (mm). The multi-objective responses, such as surface roughness (SR) and metal removal rate (MRR) were analyzed with the desirability method.

This article explores the impact of friction stir processing (FSP) on the surface modification of magnesium alloy AZ91D. The purpose is to enhance the alloy’s surface qualities and, consequently, improve its performance in various applications. Using FSP, the microstructure and mechanical characteristics of the magnesium alloy are improved through solid-state joining. The study assesses the impact of FSP parameters on the alloy’s surface properties. Researchers adjust parameters such as tool rotation speed and traverse speed to achieve accurate FSP conditions for the intended surface alterations. The surface characteristics of FSP-treated magnesium alloy AZ91D are evaluated through detailed analyses, including microstructure, surface roughness, hardness, and wear resistance. The study considers the effect of FSP on grain development and microhardness, which reflect the immediate impact on surface properties.

The focus on driver and occupant safety as well as comfort is increasing rapidly while designing commercial vehicles in India. Improvements in the road network have enhanced road transport for commercial vehicles. Apart from the cost of operation and fuel economy, the commercial vehicles must deliver goods within stipulated time. These factors resulted in higher speed of operation for commercial vehicles. The design should not compromise the safety of the vehicle at these higher speeds of operation. The vehicle should obey the driver’s intended direction at all speeds and the response of the vehicle to driver input must be predictable without much larger surprises which can lead to accidents. The commercial vehicles are designed with rigid axle and RCB type steering system. This suspension and steering design combination introduce steering errors when vehicle travel over bump, braked and while cornering.

Closed crankcase ventilation prevent harmful gases from entering atmosphere thereby reducing hydrocarbon emissions. Ventilation system usually carries blowby gases along with oil mist generated from Engine to Air intake system. Major sources of blowby occurs from leak in combustion chamber through piston rings, leakage from turbocharger shafts & leakage from valve guides. Oil mist carried by these blowby gases gets separated using separation media before passing to Air Intake. Fleece separation media has high separation efficiency with lower pressure loss for oil aerosol particles having size above 10 microns. However, efficiency of fleece media drops drastically if size of aerosol particles are below 10 microns. Aerosol mist of lower particle size (>10 microns) generally forms due to flash boiling on piston under crown area and from shafts of turbo charger due to high speeds combined with elevated temperatures. High power density diesel engine is taken for our study.

Driving dynamics performance is one of the key customer attributes to be developed during product development. In the vehicle development process, freezing the hardware of the chassis aggregates is one of the major priorities to kick off the other vehicle development activities. The current work involves the development of a multilink suspension for an SUV class vehicle. Typically, each OEM performs several product development loops for maturing the vehicle design. The driving dynamics performance evaluation and tuning happens on a physical vehicle with the driver in Loop. Tuning of suspension parameter on the physical vehicle entails actual replacement of parts/components. This encompasses multiple tuning cycles in product development associated with increased cost and test time. To reduce the product development time and cost while delivering first time right chassis configuration, we took an approach of getting driver-in-loop through driving simulator in the concept phase.

In automotive world role of suspension system is to absorb vibrations from the road, and to provide stability while vehicle is going over bumps or uneven roads, cornering, acceleration and braking etc. For body on frame SUVs which are typically characterized by high center of gravity, it is quite critical to find best balance in ensuring stability of the vehicle and having comfortable ride performance. Rigid axle rear suspension is quite a typical choice in such vehicles, wherein lower and upper control links are two important components subjected to lateral, longitudinal, and vertical loads. These links allow the vehicle to move smoothly throughout the entire range of suspension travel. Kinematics and compliance optimization of these links is a major factor in definition of ride-handling performance of the vehicle.

For any two wheeler vehicle development, rider and pillion comfort while driving the vehicles over different kinds of road perturbations holds high importance. Designing a vehicle for comfort starts at the very beginning of its layout definition through vehicle geometric parameters, key hardpoints, mass-inertia distribution of subsystems and suspension characteristics. There is a need for highly reliable simulation models for comfort predictions as any change in layout during subsequent design stages is a very costly affair. Accurately predicting comfort using a full vehicle model is a challenging task though as it depends on how realistic the Simulation Model is to that of actual vehicle. While suspension stiffness and damping characteristics remain critical parameters for the comfort, selection of tyres are known to hold equal importance in vehicle comfort.

Potholes are a major cause of discomfort for riders and vehicle damage. The passive suspension systems which are used in the passenger vehicles are primarily reaction based. These can’t adapt to the changing road conditions which means the best ride quality and handling characteristics cannot be ensured for different driving situations. Passive suspension system also needs more maintenance due to its inability to reduce the impact of the road irregularities. In recent years, semi-active suspension systems have been developed to improve ride comfort and vehicle safety. This paper covers the integration of a semi-active suspension system with a road preview mechanism with a TATA car model to investigate its impact on ride comfort, handling characteristics and component loads in digital domain. A quarter car vehicle model is used to compare different active damping control strategies.

Heavy Commercial Road Vehicles (HCRVs) may be more susceptible to rollover incidents due to their higher centre of gravity position than passenger vehicles, and rollover is one of the significant causes of HCRV accidents. Therefore, variation in vehicle roll behaviour becomes crucial to the safety of an HCRV. Toe misalignment is a commonly observed phenomenon in HCRVs, and studying its impact on roll behaviour is important. In this study, the impact of the symmetric toe and thrust misalignment on the roll behaviour of an HCRV is analysed using IPG TruckMaker®, a vehicle dynamics simulation software. A ramp steer manoeuvre was used for the simulations, and the toe misalignment on a wheel was chosen from the range [-0.21°, 0.21°]. Variation in roll behaviour was quantified using the steering wheel angle at which one-wheel lift-off (OWL) occurred (SWAL).

Automated parking systems for cars have become the need of the hour globally, gaining wide acceptance from customers, and hence OEMs are working towards achieving precise/accurate automated parking. Various algorithms are being developed to plan the trajectory of the vehicle to be moved in/out of the desired parking slot. Most of these algorithms assume a static environment and don’t account for highly dynamic objects. Accounting for such objects is vital especially when autonomously exiting a parking slot and merging with traffic. This paper summarizes our initial efforts in addressing dynamic objects, specifically the ‘right of way’ aspects, while autonomously exiting a parking slot. In this study, we propose a novel approach for generating linear and angular velocity profiles using Deep Reinforcement Learning (DRL) in conjunction with Hybrid A* path planning for autonomous vehicles (AVs) navigating parking maneuvers.

Vehicle design necessarily involves tuning various parameters to optimize automotive performance metrics like ride and handling. The tuning process is iterative and involves a trial-and-error approach to understand the influence of the input parameters on various output metrics. We develop tuning models and run many simulations to optimize various parameters, followed by validation. This process is computationally expensive and contingent on the output metrics. Alternatively, data-driven modelling could overcome shortcomings but requires extensive data sets to train, which may not be feasible in the initial design phase. In this work, we demonstrate how we can use Dynamic Mode Decomposition, commonly used in Fluid Mechanics, to create Reduced Order Single Parameter Tuning Models, which are computationally lightweight and can provide the output metrics as a function of one tuning parameter. It reduces the tuning time and also helps to understand the system better.

Motorcycles are a preferred means of transportation in most of the countries due to its economic factor and ease in travelling. Rider comfort is an important aspect while designing a vehicle. Rider comfort is often compromised by unwanted vibrations experienced at human interface points also called as tactile points. These unwanted vibrations also affect rider’s motorcycle control and overall health. There are two major source of vibrations in a motorcycle that is engine & road inputs. In current study, a method is being explored to predict engine induced vibrations. Engine induced vibrations at various locations are simulated through multi body dynamics (MBD) and finite element (FE) simulation methods at vehicle level. Motorcycle model comprising of engine, frame and subassemblies are modeled in FE tool and then condensed to be used in MBD tool. Piston assembly, connecting rod, bearings and engine mounts are modeled in MBD tool.

With the advancement of automotive industries, the need for wireless connectivity between vehicle and smartphone is increasing. To meet the demand for wireless connectivity, Bluetooth plays a vital role. Testing Bluetooth systems is challenging and complex when development cycles of the system involve multiple partners. The system under test must fulfil consumers expectation of Bluetooth functionality paired with their personal devices. Despite many advances and existence of a few reliable systems, hardware limitation, and lack of standardization in Bluetooth test system are some of the prolonged issues. Throughout the course, various capabilities and existing traditional Bluetooth testing system practice were researched, which majorly at a system level (Black box). The gap of such testing is the escape of defect which involves the interoperability of multiple profiles like AVRCP, HFP, and A2DP.

The Indian automotive industry is striving towards more safe and durable vehicles. A need was felt to study the effect of changes in axle static loads on fatigue life of the axle components. Also, there was a need to develop generic test method, as there are no test standards or generic methods available in public domain for fatigue testing of commercial vehicle axles. The study was carried out to check direct effect of change in axle loads on various connections on axle, effect of suspension configuration and force distribution, Vehicle dynamics, etc. In this paper, an India specific generic load spectra was evaluated for accelerated laboratory validation. Paper discusses the methodology as; study of heavy commercial vehicle systems, road load data collection on identified test vehicles w.r.t. test matrix finalized, India specific test loads and load spectra development, normalization of axle load spectra w.r.t to static axle weights and arriving at test guidelines.

Tyre wear is of significant concern for the automotive industry due to multiple reasons including vehicle performance, safety, economy, environmental (particulate matter emission) aspects, etc. Therefore, ensuring enhanced tyre tread wear resistance is one of the most important criteria while developing a new tyre. Tyre wear phenomenon is influenced by various factors, such as road conditions, driving habits, maintenance practices and tyre design parameters (construction, geometry and material). The wear assessment through the classical field-testing approach consumes significant time and resources. Therefore, digital predictive tools are very useful in predicting wear characteristics at the early stage of the tyre development process. In this study, an attempt has been made to capture the impact of tread geometry, tread material, vehicle geometry, vehicle speed, test track geometry, etc. on tyre wear.