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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.

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.

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.

The ignition quality of a fuel is described by its cetane number. Experimental methods used to determine cetane number employ Co-operative fuel research (CFR) engine and Ignition quality tester (IQT) which are expensive, have less repeatability and require skilled operation, and hence least preferred. There are many prediction models reported, which involve number of double bonds and number of carbon atoms whose determination is not direct. Using models that relate biodiesel composition to its cetane number is limited by the range of esters involved. Hence, a model to predict cetane number of biodiesels that addresses the limitations of the existing models, without ignoring the influence of factors such as degree of unsaturation and number of carbon atoms, is needed. Fourier transform infrared spectroscopy (FTIR) could be one such method.

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.

This paper presents the experimental investigation of combustion stability and nano-particle emissions from the CNG-diesel RCCI engine. A modified automotive diesel engine is used to operate in RCCI combustion mode. An open ECU is used to control the low and high reactivity fuel injection events. The engine is tested for fixed engine speed and two different engine load conditions. The tests performed for various port-injected CNG masses and diesel injection timings, including single and double diesel injection strategy. Several consecutive engine cycles are recorded using in-cylinder combustion pressure measurement system. Statistical and return map techniques are used to investigate the combustion stability in the CNG-diesel RCCI engine. Differential mobility spectrometer is used for the measurement of particle number concentration and particle-size and number distribution. It is found that advanced diesel injection timing leading to higher cyclic combustion variations.

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.

Today, homogenous charge compression ignition (HCCI) engines are becoming very popular because of their potential to reduce soot and nitric oxides (NOx) emissions simultaneously. But, their performance and emission characteristics are very much dependent upon fuel injection strategy and parameters. However, they also have many challenges viz., improper combustion phasing, high rate of pressure rise and narrow operating range. Therefore, addressing them is very essential before making them a commercial success. This study focuses on evaluating the effect of fuel injection strategy and parameters on the performance and emission characteristics of a HCCI engine by computational fluid dynamics (CFD) analysis. In this study, a four-stroke engine operating in the HCCI mode is considered and the CFD analysis is carried out by using the CONVERGE.

Fuel atomization and air-fuel mixing processes play a dominant role on engine performance and emission characteristics in a direct injection compression ignition engine. Understanding of microscopic spray characteristics is essential to predict combustion phenomena. The present work investigated near nozzle flow and atomization characteristics of biodiesel fuels in a constant volume chamber. Waste cooking oil, Jatropha, and Karanja biodiesels were applied and the results were compared with those of conventional diesel fuel. The tested fuels were injected by a solenoid injector with a common-rail injection system. A high-speed camera with a long distance microscopic lens was utilized to capture the near nozzle flow. Meanwhile, Sauter mean diameter (SMD) was measured by a phase Doppler particle analyzer to compare atomization characteristics.

Biodiesel is a renewable, carbon neutral alternative fuel to diesel for compression ignition engine applications. Biodiesel could be produced from a large variety of feedstocks including vegetable oils, animal fats, algae, etc. and thus, vary significantly in their composition, fuel properties and thereby, engine characteristics. In the present work, the effects of biodiesel compositional variations on engine characteristics are captured using a multi-linear regression model incorporated with two new biodiesel composition based parameters, viz. straight chain saturation factor (SCSF) and modified degree of unsaturation (DUm). For this purpose, biodiesel produced from seven vegetable oils having significantly different compositions are tested in a single cylinder diesel engine at varying loads and injection timings. The regression model is formulated using 35 measured data points and is validated with 15 other data points which are not used for formulation.

Minimum weight and high-efficiency gearboxes with the maximum service life are the prime necessity of today’s high-performance power transmission systems such as automotive and aerospace. Therefore, the problem to optimize the gearboxes is subjected to a considerable amount of interest. To accomplish these objectives, in this paper, two generalized objective functions for two stage spur-gearbox are formulated; first objective function aims to minimize the volume of gearbox material, while the second aims to maximize the power transmitted by the gearbox. For the optimization purpose, regular mechanical and critical tribological constraints (scuffing and wear) are considered. These objective functions are optimized to obtain a Pareto front for the two-stage gearbox using a specially formulated discrete version of non-dominated sorting genetic algorithm (NSGA-II) code written MATLAB. Two cases are considered, in the first with the regular mechanical constraints.

In commercial vehicles, exhaust system is normally mounted on frame side members (FSM) using hanger brackets. These exhaust system hanger brackets are tested either as part of full vehicle durability testing or as a subsystem in a rig testing. During initial phases of product development cycle, the hanger brackets are validated for their durability in rig level testing using time domain signals acquired from mule vehicle. These signals are then used in uni-axial, bi-axial or tri-axial rig facilities based on their severity and the availability of test rigs. This paper depicts the simulation method employed to replicate the bi-directional rig testing through modal transient analysis. Finite Element Method (FEM) is applied for numerical analysis of exhaust system assembly using MSC/Nastran software with the inclusion of rubber isolator modeling, meshing guidelines etc. Finite Element Analysis (FEA) results are in good agreement with rig level test results.