Search Results

Abstract Diesel engines include systems for cooling, lubrication, and fuel injection and contain a variety of components. A malfunction in any of the engine systems or the presence of any faulty element influences engine performance and deteriorates its components. This research is concerned with the untimely appearance of vital cracks in the liners of a turbocharged heavy-duty Diesel engine. To find the root causes for premature failure, rigorous examinations through visual observations, material characterization, and metallographic investigations are performed. These include Scanning Electron Microscope (SEM) and Energy-Dispersive Spectroscopy (EDS), fracture mechanics analysis, and performance examination, which are also followed by Finite Element Moldings. To find the proper remedy to resolve the problem, drawing a precise and reliable picture of the engine’s operating conditions is required.

Abstract The frequency of video-capturing collision events from surveillance systems are increasing in reconstruction analyses. The video that has been provided to the investigator may not always include a clear perspective of the relevant area of interest. For example, surveillance video of an incident may have captured a pre- or post-incident perspective that, while failing to capture the precise moment when the pedestrian was struck by a vehicle, still contains valuable information that can be used to assist in reconstructing the incident. When surveillance video is received, a quick and efficient technique to place the subject object or objects into a three-dimensional environment with a known rate of error would add value to the investigation.

Abstract The causes of failure due to cracking in the resistance spot welding of the advanced high-strength steels dual-phase 590 (DP590) were investigated using scanning electron microscopy (SEM), optical microscopy, and the tensile-shear test. The results showed that by increasing the current amount, the formation of the melting zone occurred in the heat-affected zone, leading to the cracking in this area, reducing the tensile strength and decreasing the mechanical properties; the initiation and growth of cracking and failure in this region also happened. In the heat-affected zone, by increasing the current amount with the softening phenomenon, the recrystallized coarse grains also occurred, eventually resulting in the loss of mechanical properties. The results of the tensile-shear test also indicated that by increasing the current up to 12 kA, the strength was raised, but the ductility was reduced.

Abstract This study implements Flame Image Velocimetry (FIV), a diagnostic technique based on post-processing of high-speed soot luminosity images, to show the in-flame flow field development impacted by after-injection in a single-cylinder, small-bore optical diesel engine. Two after-injection cases with different dwell times between the main injection and after-injection, namely, close-coupled and long-dwell, as well as a main-injection-only case are compared regarding flow fields, flow vector magnitude, and turbulence intensity distribution. For each case, high-speed soot luminosity movies from 100 individual combustion cycles are recorded at a high frame rate of 45 kHz for FIV processing. The Reynolds decomposition using a spatial filtering method is applied to the obtained flow vectors so that bulk flow structures and turbulence intensity distributions can be discussed.

Abstract Although tread block deformation analysis is important, the deformation measurement is difficult because fast-rotating tires maintain a continuous contact with the road surface. Furthermore, capturing small displacements near the edge of tread blocks using a high-speed camera is difficult because of the particularly limited resolution. Additionally, the tread blocks being significantly deformed at the edge and susceptible to wear powder, the state change of the feature points, is highly probable. To overcome these problems, a system that obtains high-resolution images and measures the deformation of a fast-rotating body (tire) is proposed herein. The developed system captures the deformation behavior through intermittent imaging. To further measure the strain distribution, fine tracking markers are drawn on the tread block using a laser processing machine. The displacement of the marker is calculated using the particle mask correlation method.

Abstract In the present study, the mechanical performances of plain carbon steel were explored based on the grain growth behavior. In the first step, the samples were normalized at different temperatures ranging from 900°C to 1100°C for 30, 60, 100, 150, and 200 min, respectively. In order to measure the grain size, the planimetric technique of Jeffries was used based on the optical micrographs taken for each sample. The mechanical properties of each grain such as hardness, elongation, yield, and tensile strength were studied, depending on the conventional methods. Experimental results showed that the increase in both heating temperature and holding time enhances grain growth, while the growth rate decreases with increasing time. The initial grain size and proportionality constant were calculated at 950°C, where K = 2.26 μm2/min and D 0 = 25.09 μm. Moreover, a significant increase in strength and hardness was observed with a decrease in grain size.

Abstract In this article, Al-Mg-Si-Mn alloy (AA6082) is butt joined by employing friction stir welding (FSW). The mechanical and metallurgical properties of joints are analyzed by conducting tensile and microhardness testing, respectively. To measure the temperature at different locations, eight thermocouples (L-shaped k-type) are placed at equal distance from the centerline. Least square method attempts to calculate the temperature at the centerline of joints. The process parameters are also optimized using Taguchi’s five-level experimental design. The optimum process parameters are determined, employing ultimate tensile strength (UTS) as a response parameter. A statistical test “analysis of variance” is used to check the adequacy of the model. It has been observed that rotational speed and feed rate are the predominant factors for UTS and microhardness.

Abstract An aeroengine exhaust plume is one of the important sources of infrared (IR) signature in the 3-5 μm and the 2-3 μm bands. Analysis, characterization, and modeling of the exhaust plume IR emission are needed for insight into its role in aircraft survivability against IR-guided missiles. The IR signature estimation of aeroengine exhaust needs estimation of radiative properties of absorbing-emitting exhaust gases, e.g., carbon dioxide (CO2) and water vapor (H2O). The radiative properties of the gases can be estimated by a mathematical model with a spectroscopic database of these gases. Low-Resolution Transmission (LOWTRAN), Moderate-Resolution Transmission (MODTRAN), High-Resolution Transmission (HITRAN), and High-Temperature Transmission (HITEMP) are some commonly used spectroscopic databases. This study compares Statistical Narrowband (SNB) models with the various other mathematical models used for the estimation of radiative properties of exhaust gases.

Abstract An ongoing challenge with Gasoline engines is achieving rapid activation of the three-way catalyst during cold starts in order to minimize pollutant emissions. Retarded combustion is an effective way in achieving rapid light-up of the three-way catalyst and can be facilitated by stratified charge using late fuel injection. This, however, provides insufficient time for fuel entrainment with air, resulting in locally fuel-rich diffusion combustion. Employing a split injection strategy can help tackle these issues. The effects of a split injection strategy, using a high-pressure Solenoid injector, on the in-cylinder charge formation are investigated in the current study. The studies are performed inside an optical Gasoline engine using high-speed particle image velocimetry (PIV) in the central tumble and Omega tumble planes, by means of a high-speed laser and camera operating at a repetition rate of 10 kHz.

Abstract This research involves the study of the different properties of aluminum alloy (AA) 2024 in the presence of carbon nanotubes (CNTs) and Silicon (Si) nanoparticles. Structural morphology, elemental composition, mechanical properties (density, tensile strength, elongation, and hardness), and tribological properties (wear rate and coefficient of friction) of AA 2024 in the presence of CNTs, Si, and its combinations at various proportions were evaluated using a Scanning Electron Microscope (SEM), Energy Dispersive X-Ray Analyzer (EDX), Universal Testing Machine (UTM), Model HMV-2T Vickers hardness test machine, and pin-on-disk friction-and-wear test rig. The Hybrid Metal Matrix Composite (HMMC) material is prepared by a two-stage stir casting method. It was found that the density of the AA 2024 + 4%CNT + 2%Si is 2.22 g/cm3, ultimate tensile strength is 308 N/mm2, elongation is 15.5%, and Vickers hardness is 187.5 Vickers Hardness Number (VHN).

Abstract Reliable detection of obstacles around an autonomous vehicle is essential to avoid potential collision and ensure safe driving. However, a vast majority of existing systems are mainly focused on detecting large obstacles such as vehicles, pedestrians, and so on. Detection of small obstacles such as road debris, which pose a serious potential threat are often overlooked. In this article, a novel stereo vision-based road debris detection algorithm is proposed that detects debris on the road surfaces and estimates their height accurately. Moreover, a collision warning system that could warn the driver of an imminent crash by using 3D information of detected debris has been studied.

Abstract High fuel injection pressure systems for Gasoline Direct Injection (GDI) engines have become widely used in passenger car engines to reduce emissions of particulates and pollutant gases. Current commercial systems operate at pressures of up to 450 bar, but several studies have examined the use of injection pressures above 600 bar, and some have even used pressures around 1500 bar. These works revealed that high injection pressures have numerous benefits including reduced particulate emissions, but there is still a need for more data on the possible benefits of injection pressures above 1000 bar. This article presents spray and engine data from a comprehensive study using several measurement techniques in a spray chamber and optical and metal engines. Shadowgraph imaging and Phase Doppler Interferometry (PDI) were used in a constant volume chamber to interpret spray behavior. Particle Image Velocimetry (PIV) was used to capture near-nozzle air entrainment.

Abstract Various feedstocks can be employed for biodiesel production, leading to considerable variation in composition and engine fuel characteristics. Using biodiesels originating from diverse feedstocks introduces notable variations in engine characteristics. Therefore, it is imperative to scrutinize the composition and properties of biodiesel before deployment in engines, a task facilitated by predictive models. Additionally, the international commercialization of biodiesel fuel is contingent upon stringent regulations. The traditional experimental measurement of biodiesel properties is laborious and expensive, necessitating skilled personnel. Predictive models offer an alternative approach by estimating biodiesel properties without depending on experimental measurements. This research is centered on building models that correlate mid-infrared spectra of biodiesel and critical fuel properties, encompassing kinematic viscosity, cetane number, and calorific value.

Abstract Previous studies have shown that injector aging adversely affects the diesel engine spray formation and combustion. It has also been shown that the oxygenated fuel additive tripropylene glycol monomethyl ether (TPGME) can lower soot emissions. In this study, the effects of injector aging and TPGME on the late-cycle oxidation of soot were investigated using laser diagnostic techniques in a light-duty optical diesel engine at two load conditions. The engine was equipped with a quartz piston with the same complex piston geometry as a production engine. Planar laser-induced incandescence (LII) was used to obtain semiquantitative in-cylinder two-dimensional (2D) soot volume fraction (fv ) distributions using extinction measurements. The soot oxidation rate was estimated from the decay rate of the in-cylinder soot concentration for differently aged injectors and for cases with and without TPGME in the fuel.

Abstract KL extinction measurements are an attractive soot measurement method common in the literature concerning soot-producing sprays because of their nonintrusiveness and 2D or 3D results. Unfortunately, these measurements often rely on bold assumptions of uniform and monodisperse spherical soot particles. In this work, a Spray A case is simulated using a highly detailed 3D stochastic soot model capable of predicting soot particle morphology. The measured and simulated soot volume fraction are compared, and although the simulated volume fraction magnitudes are approximately correct, the simulated volume fraction lacks a core of high volume fraction that the measured data shows. Optical models based on simulated particle size and shape are applied to the simulated data to find the local optical thickness.

Abstract Today, as the spread of vehicles equipped with autonomous driving functions increases, accidents caused by autonomous vehicles are also increasing. Therefore, issues regarding safety and reliability of autonomous vehicles are emerging. Various studies have been conducted to secure the safety and reliability of autonomous vehicles, and the application of the International Organization for Standardization (ISO) 26262 standard for safety and reliability improvement and the importance of verifying the safety of autonomous vehicles are increasing. Recently, Mobileye proposed an RSS model called Responsibility Sensitive Safety, which is a mathematical model that presents the standardization of safety guarantees of the minimum requirements that all autonomous vehicles must meet. In this article, the RSS model that ensures safety and reliability was derived to be suitable for variable focus function cameras that can cover the cognitive regions of radar and lidar with a single camera.

Abstract In this work, we present a lightweight pipeline for robust behavioral cloning of a human driver using end-to-end imitation learning. The proposed pipeline was employed to train and deploy three distinct driving behavior models onto a simulated vehicle. The training phase comprised of data collection, balancing, augmentation, preprocessing, and training a neural network, following which the trained model was deployed onto the ego vehicle to predict steering commands based on the feed from an onboard camera. A novel coupled control law was formulated to generate longitudinal control commands on the go based on the predicted steering angle and other parameters such as the actual speed of the ego vehicle and the prescribed constraints for speed and steering. We analyzed the computational efficiency of the pipeline and evaluated the robustness of the trained models through exhaustive experimentation during the deployment phase.

Abstract A major reduction of greenhouse gas emissions, as well as other toxic emissions, is required to reduce the environmental impact of transportation systems. Renewable fuels, in combination with new internal combustion processes, such as reactivity controlled compression ignition (RCCI), are promising measures to enable this reduction. By combining two fuels with different reactivity, RCCI offers high efficiency and low emissions through homogeneous low-temperature combustion. However, a two-fuel RCCI approach leads to an increased number of adjustable operation parameters, such as injection timing. Optimizing these operation parameters to ensure homogenous combustion is challenging. To that end, optical methods provide temporally and spatially resolved information on mixture formation and combustion to analyze the homogeneity of the process. However, established methods, such as OH* imaging, cannot differentiate between multiple fuels.

Abstract With the sustainable development of the social economy and the continuous maturity of science and technology, urban rail transit has developed rapidly. It solved the problems of urban road load and people’s travel and brought about the problem of rail transit passenger congestion. The image detection algorithm for rail transit congestion is established based on the convolutional neural networks (CNN) structure to realize intelligent video image monitoring. The CNN structure is optimized through the backpropagation (BP) algorithm so that the model can detect and analyze the riding environment through the monitoring camera and extract the relevant motion characteristics of passengers from the image. Furthermore, the crowding situation of the riding environment is analyzed to warn the rail transit operators. In practical application, the detection accuracy of the algorithm reached 91.73%, and the image processing speed met the second-level processing.

Abstract The aim of this work is to quantify three different antioxidants in biodiesel - Santoflex, baynox, and tocopherol-using Middle Infrared (MIR) spectroscopy and chemometrics. For the construction of the models, 28 samples containing an antioxidant in the range of 0.1 to 500 mg/kg in biodiesel were used. We developed three models based on PLS 1 multivariate calibration method to quantify each of the three antioxidants separately and a model based on PLS 2 method to quantify simultaneously all the antioxidants. All models were compared to the values of root mean square error of calibration (RMSEC) and validation (RMSEP). For the baynox, santoflex, and tocopherol antioxidants quantification using PLS 1, the values of RMSEC and RMSEP were 37.2, 18.8, 9.0 mg/kg, and 26.7, 21.1, 68.6 mg/kg, respectively.