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Abstract AISI H13 hot work tool steel is commonly used for applications such as hot forging and hot extrusion in mechanical working operations that face thermal and mechanical stress fluctuations, leading to premature failures. Cryogenic treatment was applied for AISI H13 steel to improve the surface hardness and thereby fatigue resistance. This work involves failure analysis of H13 steel specimens subjected to cryogenic treatment and gas nitriding. The specimens were heated to 1020°C, oil quenched followed by double tempering at 550°C for 2 h, and subsequently, deep cryogenically treated at −185°C in the cryochamber. Gas nitriding was carried out for 24 h at 500°C for 200 μm case depth in NH3 surroundings. The specimens were subjected to rotating bending fatigue at constant amplitude loading at room temperature.

Abstract Super duplex stainless steel (SDSS) is a type of stainless steel made of chromium (Cr), nickel (Ni), and iron (Fe). In the present work, a 1.6 mm wide thin sheet of SDSS is joined using gas tungsten arc welding (GTAW). The ideal parameter for a bead-on-plate trial is found, and 0.216 kJ/mm of heat input is used for welding. As an outcome of the welding heating cycle and subsequent cooling, a microstructural study revealed coarse microstructure in the heat-affected zone and weld zone. The corrosion rate for welded joints is 9.3% higher than the base metal rate. Following the corrosion test, scanning electron microscope (SEM) analysis revealed that the welded joint’s oxide development generated a larger corrosive attack on the weld surface than the base metal surface. The percentages of chromium (12.5%) and molybdenum (24%) in the welded joints are less than those in the base metal of SDSS, as per energy dispersive X-ray (EDX) analysis.

Abstract The emerging use of rechargeable batteries in electric and hybrid electric vehicles and distributed energy systems, and accidental fires involving batteries, has heightened the need for a methodology to determine the root cause of the fire. When a fire involving batteries takes place, investigators and engineers need to ascertain the role of batteries in that fire. Just as with fire in general, investigators need a framework for determining the role that is systematic, reliant on collection and careful analysis of forensic evidence, and based on the scientific method of inquiry. This article presents a systematic scientific process to analyze batteries that have been involved in a fire. It involves examining Li-ion cells of varying construction, using a systematic process that includes visual inspection, x-ray, CT scan, and possibly elemental analysis and testing of exemplars.

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Abstract Composite ceramic brake discs are made of ceramic material reinforced with carbon fibers and offer exceptional advantages that translate directly into higher vehicle performance. In the case of an electric vehicle, it could increase the range of the vehicle, and in the case of conventional internal combustion engine vehicles, it means lower fuel consumption (and consequently lower CO2 emissions). These discs are typically characterized by complex internal geometries, further complicated by the presence of drilling holes on both friction surfaces. To estimate the aerothermal performance of these discs, and for the thermal management of the vehicle, a reliable model for predicting the air flowing across the disc channels is needed. In this study, a real carbon-ceramic brake disc with drilling holes was investigated in a dedicated test rig simulating the wheel corner flow conditions experimentally using the particle image velocimetry technique and numerically.

Abstract To address the challenge of directly measuring essential dynamic parameters of vehicles, this article introduces a multi-source information fusion estimation method. Using the intelligent front camera (IFC) sensor to analyze lane line polynomial information and a kinematic model, the vehicle’s lateral velocity and sideslip angle can be determined without extra sensor expenses. After evaluating the strengths and weaknesses of the two aforementioned lateral velocity estimation techniques, a fusion estimation approach for lateral velocity is proposed. This approach extracts the vehicle’s lateral dynamic characteristics to calculate the fusion allocation coefficient. Subsequently, the outcomes from the two lateral velocity estimation techniques are merged, ensuring rapid convergence under steady-state conditions and precise tracking in dynamic scenarios.

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Abstract Single point incremental forming (SPIF) is a robust and new technique. In the recent research scenario, materials properties such as microstructure, micro-texture analysis, and crystal structure can be accessed through characterization non-destructive techniques, e.g., scanning electron microscope (SEM), electron backscattered diffraction (EBSD), and X-ray diffraction (XRD). XRD is a non-destructive method for analyzing the fine structure of materials. This study explores how process variables such as wall angle, step size, feed rate, and forming speed affect the parts of large-, medium-, and small-sized truncated cones of aluminum alloy AA3003-O sheet. Several cone parts of truncated cones are used in this investigation to implement Scherrer’s method. The two primary determining factors peak height and crystallite size are assessed for additional analysis in the present research.

Abstract This study investigated the influence of high-strength low-alloy steel on the fatigue life of a load-bearing member with a non-load-bearing transverse welded attachment (T-joint). It compared high cycle fatigue data to two fatigue design codes, namely BS 7608 and Eurocode EN 1993-1-9. Different base and filler material combinations of varying material strengths were investigated, resulting in a total of three different specimen configurations. Two material combinations had a high-strength steel (Strenx® 700 MC D) for the base material, with one combination having a matched filler material and the other having an undermatched filler material. The third material combination had a lower-strength steel (S 355 JR AR) for the base material, with a matched filler material. Tensile tests were performed to confirm the base material mechanical properties and weld quality of the manufactured specimens.

Abstract This study investigates the use of a road weather model (RWM) as a virtual sensing technique to assist autonomous vehicles (AVs) in driving safely, even in challenging winter weather conditions. In particular, we investigate how the AVs can remain within their operational design domain (ODD) for a greater duration and minimize unnecessary exits. As the road surface temperature (RST) is one of the most critical variables for driving safety in winter weather, we explore the use of the vehicle’s air temperature (AT) sensor as an indicator of RST. Data from both Road Weather Information System (RWIS) stations and vehicles measuring AT and road conditions were used. Results showed that using only the AT sensor as an indicator of RST could result in a high number of false warnings, but the accuracy improved significantly with the use of an RWM to model the RST.

Abstract The closet in-path vehicle (CIPV) is recognized relying on the detection results for road lane lines in most current ACC system, which may not work well in the poor conditions, for example, unclear road lane lines, low light level, bad weather, and so on. To solve this problem, the article proposes a sensor fusion-based CIPV recognition algorithm independent of road lane lines. First, a robust Kalman filter based on the global coordinate system is designed to fuse the millimeter-wave radar and camera targets. The fusion algorithm can dynamically adjust the covariance matrix of sensor observations to avoid the influence of anomalous observations on the fusion results. Stable detection of targets by the fusion algorithm is the basis of the CIPV recognition algorithm.

Abstract In this article, the effect of heat treatment on the microstructure and mechanical behavior of medium-carbon steel wire intended for the spring mattress is investigated using scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), X-ray diffraction, Vickers hardness (Hv), and tensile strength. The results indicate that the microstructure elongation along the wire axis is observed with the bending and kinking lamellae at the deformation level of 57.81%, this change appears as a fracture in the microstructure and leads to an increase in hardness, tensile strength, and intensities of diffraction patterns. After heat treatment, we observed a redistribution in the grain, which is almost the same in the wire rod and drawn wires; indeed, this led to a decrease in hardness, tensile strength, and augmentation in intensities of peaks. The EBSD pole figures reveal the development of texture in the cementite slip plane (001).

Abstract The ASTM D130 was first issued in 1922 as a tentative standard for the detection of corrosive sulfur in gasoline. A clean copper strip was immersed in a sample of gasoline for three hours at 50°C with any corrosion or discoloration taken to indicate the presence of corrosive sulfur. Since that time, the method has undergone many revisions and has been applied to many petroleum products. Today, the ASTM D130 standard is the leading method used to determine the corrosiveness of various fuels, lubricants, and other hydrocarbon-based solutions to copper. The end-of-test strips are ranked using the ASTM Copper Strip Corrosion Standard Adjunct, a colored reproduction of copper strips characteristic of various degrees of sulfur-induced tarnish and corrosion, first introduced in 1954. This pragmatic approach to assessing potential corrosion concerns with copper hardware has served various industries well for a century.

Abstract Rib fractures are associated with high rates of morbidity and mortality. Improved methods to assess rib bone quality are needed to identify at-risk populations. Quantitative computed tomography (QCT) can be used to calculate volumetric bone mineral density (vBMD) and bone mineral content (BMC), which may be related to rib fracture risk. The objective of this study was to determine if vBMD and BMC from QCT predict human rib structural properties. 127 mid-level (5th–7th) ribs were obtained from adult female (n = 67) and male (n = 60) postmortem human subjects (PMHS). Isolated rib QCT scans were performed to calculate vBMD and BMC.

Abstract In this study, a parametric thoracic spine (T-spine) model was developed to account for morphological variations among the adult population. A total of 84 CT scans were collected, and the subjects were evenly distributed among age groups and both sexes. CT segmentation, landmarking, and mesh morphing were performed to map a template mesh onto the T-spine vertebrae for each sampled subject. Generalized procrustes analysis (GPA), principal component analysis (PCA), and linear regression analysis were then performed to investigate the morphological variations and develop prediction models. A total of 13 statistical models, including 12 T-spine vertebrae and a spinal curvature model, were combined to predict a full T-spine 3D geometry with any combination of age, sex, stature, and body mass index (BMI). A leave-one-out root mean square error (RMSE) analysis was conducted for each node of the mesh predicted by the statistical model for every T-spine vertebra.

Abstract Pre-chamber jet ignition technologies have been garnering significant interest in the internal combustion engine field, given their potential to deliver shorter burn durations, increased combustion stability, and improved dilution tolerance. However, a clear understanding of the relationship between pre-chamber geometry, operating condition, jet formation, and engine performance in light-duty gasoline injection engines remains under-explored. Moreover, research specifically focusing on high dilution levels and passive pre-chambers with optical accessibility is notably scarce. This study serves to bridge these knowledge gaps by examining the influence of passive pre-chamber nozzle diameter and dilution level on jet formation and engine performance.

Abstract Speckle noise degrades the visual appearance and the quality of a synthetic aperture radar (SAR) image. The reduction of speckle noise is the first step in any remote-sensing device. To improve the noisy SAR images, a variety of adaptive and nonadaptive noise reduction filters were used. In order to eliminate speckle noise present in SAR images, an adaptive cuckoo search optimization-based speckle reduction bilateral filter has been designed in this article. To test the ability to eliminate multiplicative noise, the suggested filter’s effectiveness was compared to that of several de-speckling approaches. It has been measured with different assessment metrics such as PSNR, EPI, SSIM, and ENL. When compared to conventional de-noising filters, the proposed filter shows promising results for lowering speckle noise and retaining edge properties.

Abstract Currently, there is a growing tendency to incorporate natural fibers in composites due to their affordability, lightweight nature, and eco-friendliness. Researchers are continuously exploring new materials that offer improved mechanical properties for a broader range of applications. In this work, an experimental investigation on tensile and fatigue behavior of jute-wool felt-reinforced epoxy hybrid laminate is carried, in addition to an E-glass fiber-reinforced epoxy laminate that helps in comparison. Constant amplitude tensile fatigue test is conducted for 80%, 70%, and 60% of the ultimate load of respective composites at a stress ratio of 0.1 and frequency of 7 Hz for both laminates. The jute-wool felt composite showed good fatigue resistance. Though glass fiber composite showed higher tensile strength, jute-wool felt composite exhibits higher fatigue performance than glass fiber composites at higher stress levels.

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 A rapid compression and expansion machine (RCEM) was used to experimentally investigate the ignition phenomena of dielectric-barrier discharge (DBD) in engine conditions. The effect of elevated pressure and temperature on ignition phenomena of a methane/air premixed mixture was investigated using a DBD igniter. The equivalence ratio was changed to elucidate the impact of DBD on flame kernel development. High-speed imaging of natural light and OH* chemiluminescence enabled visualization of discharges and flame kernel. According to experimental findings, the discharges become concentrated and the intensity increases as the pressure and temperature rise. Under different equivalence ratios, the spark ignition (SI) system has a shorter flame development time (FDT) as compared with the DBD ignition system.