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Severe problem of aerodynamic heating and drag force are inherent with any hypersonic space vehicle like space shuttle, missiles etc. For proper design of vehicle, the drag force measurement become very crucial. Ground based test facilities are employed for these estimates along with any suitable force balance as well as sensors. There are many sensors (Accelerometer, Strain gauge and Piezofilm) reported in the literature that is used for evaluating the actual aerodynamic forces over test model in high speed flow. As per previous study, the piezofilm also become an alternative sensor over the strain gauges due to its simple instrumentation. For current investigation, the piezofilm and strain gauge sensors have mounted on same stress force balance to evaluate the response time as well as accuracy of predicted force at the same instant. However, these force balance need to be calibrated for inverse prediction of the force from recorded responses.

The study of aerodynamic forces in hypersonic environments is important to ensure the safety and proper functioning of aerospace vehicles. These forces vary with the angle of attack (AOA) and there exists an optimum angle of attack where the ratio of the lift to drag force is maximum. In this paper, computational analysis has been performed on a blunt cone model to study the aerodynamic characteristics when hypersonic flow is allowed to pass through the model. The flow has a Mach number of 8.44 and the angle of attack is varied from 0º to 20º. The commercial CFD solver ANSYS FLUENT is used for the computational analysis and the mesh is generated using the ICEM CFD module of ANSYS. Air is selected as the working fluid. The simulation is carried out for a time duration of 1.2 ms where it reaches a steady state and the lift and drag forces and coefficients are estimated. The pressure, temperature, and velocity contours at different angles of attack are also observed.

Modern combat aircraft demands efficient maintenance strategies to ensure operational readiness while minimizing downtime and costs. Innovative approaches using Digital Twining models are being explored to capture inter system behaviours and assessing health of systems which will help maintenance aspects. This approach employs advanced deep learning protocols to analyze the intricate interactions among various systems using the data collected from various systems. The research involves extensive data collection from sensors within combat aircraft, followed by data preprocessing and feature selection, using domain knowledge and correlation analysis. Neural networks are designed for individual systems, and hyper parameter tuning is performed to optimize their performance. By combining the outputs of these during the model integration phase, an overall health assessment of the aircraft will be generated.

In-cylinder fluid dynamics enhance performance and emission characteristics in internal combustion (IC) engines. Techniques such as helical ports, valve shrouding, masking, and modifications to piston profiles or vanes in ports are employed to achieve the desired in-cylinder flows in these engines. However, due to space constraints, modifications to the cylinder head are typically minimal. The literature suggests that introducing baffles into the combustion chamber of an IC engine can enhance in-cylinder flows, air-fuel mixing, and, subsequently, stratification. Studies have indicated that the height of the baffles plays a significant role in determining the level of improvement in in-cylinder flow and air-fuel mixing. Therefore, this study employs Computational fluid dynamics (CFD) analysis to investigate the impact of baffle height on in-cylinder flow and air-fuel mixing in a four-stroke, four-valve, spray-guided gasoline direct injection (GDI) engine.

The current research focuses on enhancing the performance of Si solar cells by using Er2O3 (Erbium Oxide) in cubic crystalline nature serves as an anti-reflection coating material. An anti-reflective coating aims to improve the Efficient Power Conversion (EPC) of polycrystalline silicon wafers solar cells (PSSC) utilised in solar roof panels of the automotive sector. It also exhibits superior light transmittance and least light reflectance, which eventually leads to the increase EPC. Erbium oxide helps to convert low energy photons into high energy photons. The incident photons, which lies on the solar cell, gradually losses its energy to travel in a denser medium and dissipate in the form of heat energy. In order to overcome the rate of reflection, current research aims in synthesis of erbium oxide nanosheets using electrospinning deposition technique for varying deposition timings such as 1, 1.5 and 2 hours.

This research paper focuses on the modelling and analysis of a flywheel energy storage system (FESS) specifically designed for electric vehicles (EVs) with a particular emphasis on the flywheel rotor system associated with active magnetic bearings. The methodology used simulation approaches to investigate the dynamics of the flywheel system. The objective of this study is to explore the effects of implementing the flywheel energy storage system on the performance of the EV. The paper presents a comprehensive model of the flywheel energy storage system, considering the mechanical and electrical aspects. The mechanical model accounts for the dynamic behaviors of the flywheel, including parameters such as rotational speed, inertia, and friction. The electrical model describes the interaction between the flywheel and the power electronics, such as the converter and motor/generator. To evaluate the benefits of the flywheel energy storage system, simulations are conducted.

For the foreseeable future, On-Board Charging will be a critical feature for all EVs, as it allows greater flexibility when charging vehicles from common power points and dedicated EVSEs. The OBC (On-Board Charger) has no function while the vehicle is moving; at the same time, heavy or large OBC reduces range. So, designers must design OBCs that are both energy efficient and lightweight. In addition to surviving the rigors of the automotive environment, such as heat and vibrations, they must also be cost-competitive. Designing OBCs encapsulating multiple objectives thus becomes a necessity. However, current methods often use the “most important” objective and transform other objectives into constraints that do not truly reflect the tradeoffs among all possible designs. Simulating Multi-Objective Optimization methods allow for an in-depth exploration of the solution and tradeoffs.

Automotive crash data analysis and reconstruction is vital for ensuring automotive safety. The objective of vehicle crash reconstruction is to determine the vehicle's motion before, during, and after the crash, as well as the impact on occupants in terms of injuries. Simulation approaches, such as PC CrashTM, have been developed to understand pre-crash and post-crash vehicle motion, rather than the crash phase behavior. Over the past few decades, crash phase simulations have utilized vehicle finite element models. While multibody simulation tools are suitable for crash simulations, they often require detailed crash test data to accurately capture vehicle behavior, which is not always readily available. This paper proposes a solution to this limitation by incorporating crash test data from databases, such as NHTSA, Global NCAP, consumer rating reports, and videos, along with a multibody-based approach, to conduct crash phase simulations.

Metallic particles in brake-friction materials (FMs) play a vital role in improving mainly strength, friction level, thermal conductivity and hence resistance to fade during braking operations. Although Copper was the most efficient and popular metallic ingredient in FMs, it is being phased out because of its proven threat to the aquatic life in the form of wear debris. Hardly any successful efforts are reported in open literature barring few on in the authors’ laboratory. It is well-known that the size and shape of particles affect the performance of composites apart from their type, concentration, etc. In this paper, Ferritic stainless steel (SS 434) particles were selected as a theme ingredient in two forms, first particulate (SSP) with two sizes, larger (30-45 micron) and smaller (10-20 micron) and also in the form of swarf. The aim was to investigate the size and shape effect of these ingredients when used to manufacture the brake-pads on the performance properties.

Graphite plays a crucial role in friction materials, since it has good thermal conductivity, lubricity and act as a friction modifier. The right type, amount, shape, and size of the particles control the performance of the brake-pads. The theme of the study was investigating the influence of size of graphite particles (having all other specifications identical) on performance properties of brake-pads containing graphite particles in the average size of 60 μm, 120 μm, 200 μm and 400 μm. Physical, mechanical and chemical characterization of the developed brake-pads was done. The tribological performance was studied using a full- scale inertia brake dynamometer following a Japanese automobile testing standard (JASO C406). Tribo-performance in terms of fade resistance, friction stability and wear resistance were observed best for smaller graphite particles. It was concluded that smaller size serves best for achieving best performance properties barring compressibility.

Flow variations from one cycle to the next significantly influence the mixture formation and combustion processes in engines. Therefore, it is important to understand the fluid motion and its cycle-to-cycle variations (CCVs) inside the engine cylinder. Researchers have generally investigated the cycle-to-cycle flow variations in moderate- to large-sized engines. In the present work, we have performed the flow measurement and analysis in a small spark-ignition engine. Experiments are conducted in an optically accessible, single-cylinder, port-fuel-injection engine with displacement volume of 110 cm3 at different throttle openings (i.e. 50% and WOT) using particle image velocimetry. Images are captured at different crank angle positions during both intake and compression strokes over a tumble measurement plane, bisecting the intake and exhaust valves and passing through the cylinder axis.

Stringent emission regulations on one hand and increasing demand for better fuel economy along with lower noise levels on the other hand require adoption of advanced common-rail direct-injection technologies in diesel engines. In the present work, a small 0.9-l, naturally aspirated, two-cylinder, common-rail direct-injection diesel engine is used for the analysis of combustion noise at different engine operating conditions. Experiments are conducted at different loads and engine speeds, incorporating both single and multiple (i.e. pilot and main) injections along with different injection timings. In the case of multiple injections, the influence of pilot injection quantity is also evaluated on the combustion noise while maintaining the same load. In-cylinder pressure was recorded with the resolution of 0.1 crank angle degree, and it was used for the quantitative analysis of noise assessed from the resulting cylinder pressure spectra, and sound pressure level.

In a direct-injection (DI) engine, charge motion and mixture preparation are among the most important factors deciding the performance and emissions. This work was focused on studying the effect of injector positioning on fuel-air mixture preparation and fuel impingement on in-cylinder surfaces during the homogeneous mode of operation in a naturally aspirated, small bore, 0.2 l, light-duty, air-cooled, four-stroke, spark-ignition engine modified to operate under the DI mode. A commercially available, six-hole, solenoid-operated injector was used. Two injector locations were identified based on the availability of the space on the cylinder head. One location yielded the spray-guided (SG) configuration, with one of the spray plumes targeted towards the spark plug. In the second location, the spray plumes were targeted towards the piston top in a wall-guided (WG) configuration so as to minimize the impingement of fuel on the liner.

In this work methanol was port injected while diesel was injected using a common rail system in a single cylinder non-road CI engine. Experiments were conducted with single (SPI) and double (DPI - pilot and main) injection of the directly injected diesel at 75% load and at a constant speed of 1500 rpm. The effects of methanol to diesel energy share (MDES) and injection scheduling on combustion stability, efficiency and emissions were evaluated. Initially, in the SPI mode, the methanol to diesel Energy Share (MDES) was varied, while the injection timing of diesel was always fixed for best brake thermal efficiency (BTE). Increase in the MDES resulted in a reduction in NOx and smoke emissions because of the high latent heat of vaporization of methanol and the oxygen available. Enhanced premixed combustion led to a raise in brake thermal efficiency (BTE). Coefficient of variation of IMEP, peak pressure and BTE were deteriorated which limited the usable MDES to 43%.

Vertical takeoff and landing vehicle platforms with many small rotors are gaining importance for small UAVs as well as distributed electric propulsion for larger vehicles. To predict vehicle performance, it must be possible to gauge interaction effects. These rotors operate in the less-known regime of low Reynolds number, with different blade geometry. As a first step, two identical commercial UAV rotors from a flight test program are studied in isolation, experimentally and computationally. Load measurements were performed in Georgia Tech’s 2.13 m × 2.74 m wind tunnel. Simulations were done using the RotCFD solver which uses a Navier-Stokes wake computation along with rotor-disc loads calculation using low-Reynolds number blade section data. It is found that in hover, small rotors available in the market vary noticeably in performance at low rotor speeds, the data converging at higher RPM and Reynolds number.

Application of advance composites in place of the various conventional materials such as steel can give significant weight and performance advantages. The application of composites is now finding it’s way in the automotive industry due to the growing requirement of the lightweight solutions and high strength to weight ratio. However, their low mechanical properties have limited their application in automotive structural components. The study presented here is focused on the explicit dynamic analysis of a bumper beam and advance composites are used for the study. Different configurations and designs of the bumper are considered to be able to make a comparative study of the stress and deformation levels. The analysis was done in coherence to the Euro NCAP tests and the offset frontal impact analysis was done. The boundary conditions were aligned with the real time impact conditions for proper prediction of the results.

Biodiesel makes an attractive option to replace fossil diesel owing to its applicability in diesel engines without major modifications. An increase in NO emissions with biodiesel compared to diesel is a major concern for its wider use. Blending alcohols, such as methanol, with biodiesel is a potential remedy to mitigate NO formation, as suggested by experiments. However, computational investigations studying the effect of biodiesel-methanol blends on NO formation are scarce. A combined experimental and computational approach is adopted here to investigate the NO formation mechanism with neat biodiesel and biodiesel-methanol blend fueled light duty diesel engine. Firstly, a new compact kinetic model is utilized consisting of oxidation reactions for methyl butanoate and n-dodecane as a surrogate for biodiesel. A surrogate is defined to represent biodiesel based on a combined property and functional group based approach.

Predicting the brake performance and characteristics is a crucial task in the vehicle development activity. Performance prediction is a challenge because of the involvement of various parts in the brake assembly like booster, master cylinder, calipers, disc and drum brakes. Determination of these characteristics through vehicle level tests requires a lot of time and money. This performance prediction is achieved by theoretical calculations involving vehicle dynamics. The final output must satisfy the regulations. This project involves the creation of a standalone application using MATLAB to predict the various brake performances such as: booster characteristics, adhesion curves, deceleration and pedal effort curves, behavior of brakes during brake and booster failed conditions and braking force diagrams based on the given user inputs. Previously, MS Excel and an application developed in the TK Solver environment was used to predict the brake performance curves.

Gasoline direct injection (GDI) engines have gained popularity in the recent times because of lower fuel consumption and exhaust emissions compared to that of the conventional port fuel injection (PFI) engine. But, in these engines, the mixture formation plays an important role which affects combustion, performance and emission characteristics of the engine. The mixture formation, in turn, depends on many factors of which fuel injector location and orientation are most important parameters. Therefore, in this study, an attempt has been made to understand the effect of fuel injector location and nozzle-hole orientation on the mixture formation, performance and emission characteristics of a GDI engine. The mixture stratification inside the combustion chamber is characterized by a parameter called “stratification index” which is based on average equivalence ratio at different zones in the combustion chamber.

Alcohols are potential blending agents for diesel that can be effectively used in compression ignition engines. This work investigates the use of n-butanol as a blending component for diesel fuel using experiments and simulations. Dodecane was selected as a surrogate for diesel fuel and various concentrations of n-butanol were added to study ignition characteristics. Ignition delay times for different n-butanol/dodecane blends were measured using the ignition quality tester at KAUST (KR-IQT). The experiments were conducted at pressure of 21 and 18 bar, temperature ranging from 703-843 K and global equivalence ratio of 0.85. A skeletal mechanism for n-dodecane and n-butanol blends with 203 species was developed for numerical simulations. The mechanism was developed by combining n-dodecane skeletal mechanism containing 106 species and a detailed mechanism for all the butanol isomers.