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Abstract Real-time reconstruction of 3D environment attributed with semantic information is significant for a variety of applications, such as obstacle detection, traffic scene comprehension and autonomous navigation. The current approaches to achieve it are mainly using stereo vision, Structure from Motion (SfM) or mobile LiDAR sensors. Each of these approaches has its own limitation, stereo vision has high computational cost, SfM needs accurate calibration between a sequences of images, and the onboard LiDAR sensor can only provide sparse points without color information. This paper describes a novel method for traffic scene semantic segmentation by combining sparse LiDAR point cloud (e.g. from Velodyne scans), with monocular color image. The key novelty of the method is the semantic coupling of stereoscopic point cloud with color lattice from camera image labelled through a Convolutional Neural Network (CNN).

Abstract Additive manufacturing (AM) technologies can produce lighter parts; reduce manual assembly processes; reduce the number of production steps; shorten the production cycle; significantly reduce material consumption; enable the production of prostheses, implants, and artificial organs; and produce end-user products since it is used in many sectors for many reasons; it has also started to be used widely, especially in the field of aerospace. In this study, polylactic acid (PLA) was preferred for the antenna substrate because it is environmentally friendly, easy to recycle, provides convenience in production design with a three-dimensional (3D) printer, and is less expensive compared to other available materials. Copper (Cu) tape and graphene filament were employed for the antenna patch component due to their benefits.

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 Autonomous Racing is gaining increasing publicity as an attractive showcase of state-of-the-art technologies and the enhanced algorithms used for autonomous driving. The Indy Autonomous Challenge (IAC) tackled autonomous high-speed wheel-to-wheel racing at the famous Indianapolis Motor Speedway (IMS) in October 2021. To solve this problem, advanced autonomous driving algorithms were developed by each team. In this article, we display a multi-sensor localization approach developed for usage in the IAC. To decouple the lateral and longitudinal position of the ego vehicle, a trackbound coordinate system is used that can be transformed to conventional Cartesian coordinates. The longitudinal motion of the car is tracked via a modified version of the OpenVSLAM that outputs the progress of the already driven distance.

Abstract With the introduction of advanced lightweight materials with complex microstructures and behaviors, more focus is put on the accurate determination of their forming limits, and that can only be possible through experiments as the conventional theoretical models for the forming limit curve (FLC) prediction fail to perform. Despite that, CAE engineers, designers, and toolmakers still rely heavily on theoretical models due to the steep costs associated with formability testing, including mechanical setup, a large number of tests, and the cost of a stereo digital image correlation (DIC) system. The international standard ISO 12004-2:2021 recommends using a stereo DIC system for formability testing since two-dimensional (2D) DIC systems are considered incapable of producing reliable strains due to errors associated with out-of-plane motion and deformation.

Abstract A modular, stationary IC engine blow rig for differential and integral flow field measurements using particle image velocimetry (PIV) has been developed. Unlike conventional PIV blow rigs, the given design is capable of operating under near-reality charge air conditions, that is, highly pressurized, hot intake air supply at high flow rates. Its conceptual flexibility as well as peripheral infrastructure allow for comprehensive and wide-ranging flow field analysis. Because of a modular architecture, it is neither confined to a specific cylinder head design nor limited solely to the application of PIV for differential flow field analysis. It also already accounts for direct inlet flow determination through an additional PIV access point upstream of the cylinder head. The inlet and outlet ducts have been designed with regular shapes and smooth walls, such that a digital twin-type CFD model of the blow rig is conveniently feasible.

Abstract Effective circumstance perception technology is the prerequisite for the successful application of autonomous driving, especially the detection technology of traffic objects that affects other tasks such as driving decisions and motion execution in autonomous vehicles. However, recent studies show that a single sensor cannot perceive the surrounding environment stably and effectively in complex circumstances. In the article, we propose a multi-scale feature fusion framework that exploits a dual backbone network to extract camera and radar feature maps and performs feature fusion on three different feature scales using a new fusion module. In addition, we introduce a new generation mechanism of radar projection images and relabel the nuScenes dataset since there is no other suitable autonomous driving dataset for model training and testing.

Abstract Autonomy is a key enabling factor in uncrewed aircraft system (UAS) and advanced air mobility (AAM) applications ranging from cargo delivery to structure inspection to passenger transport, across multiple sectors. In addition to guiding the UAS, autonomy will ensure that they stay safe in a large number of off-nominal situations without requiring the operator to intervene. While the addition of autonomy enables the safety case for the overall operation, there is a question as to how we can assure that the autonomy itself will work as intended. Specifically, we need assurable technical approaches, operational considerations, and a framework to develop, test, maintain, and improve these capabilities. We make the case that many of the key autonomy functions can be realized in the near term with readily assurable, even certifiable, design approaches and assurance methods, combined with risk mitigations and strategically defined concepts of operations.

Abstract The following work presents a new concept for optical accessibility of a single-cylinder medium-speed large-bore marine engine from the concept development to the implementation and feasibility investigation in a test bench observing the flame chemiluminescence of dual-fuel (DF) combustion. The design’s feasibility is verified using conjugated heat transfer (CHT) and finite element method (FEM) simulation during the whole design process presented herein. Assumptions made for the simulation, e.g., of the mount between the optical component and the steel engine parts, are evaluated in pretesting setups presented and described as follows. The optical access is made to withstand steady-state full-load operating conditions and is proofed so. The optical access is designed for an engine with a bore of 350 mm and a stroke of 440 mm.

Abstract This article presents a novel approach to optimize the placement of light detection and ranging (LiDAR) sensors in autonomous driving vehicles using machine learning. As autonomous driving technology advances, LiDAR sensors play a crucial role in providing accurate collision data for environmental perception. The proposed method employs the deep deterministic policy gradient (DDPG) algorithm, which takes the vehicle’s surface geometry as input and generates optimized 3D sensor positions with predicted high visibility. Through extensive experiments on various vehicle shapes and a rectangular cuboid, the effectiveness and adaptability of the proposed method are demonstrated. Importantly, the trained network can efficiently evaluate new vehicle shapes without the need for re-optimization, representing a significant improvement over classical methods such as genetic algorithms.

Abstract The demand for contactless, rapid manufacturing has increased over the years, especially during the COVID-19 pandemic. Additive manufacturing (AM), a type of rapid manufacturing, is a computer-based system that precisely manufactures products. It proves to be a faster, cheaper, and more efficient production system when integrated with cloud-based manufacturing (CBM). Similarly, the need for semiconductors has grown exponentially over the last five years. Several companies could not keep up with the increasing demand for many reasons. One of the main reasons is the lack of a workforce due to the COVID-19 protocols. This article proposes a novel technique to manufacture semiconductor chips in a fast-paced manner. An algorithm is integrated with cloud, machine vision, sensors, and email access to monitor with live feedback and correct the manufacturing in case of an anomaly.

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 Electromagnetic forming (EMF) is a high-speed impulse forming process developed during the 1950s and 1960s to acquire shapes from sheet metal that could not be obtained using conventional forming techniques. In order to attain required deformation, EMF process applies high Lorentz force for a very short duration of time. Due to the ability to form aluminum and other low-formability materials, the use of EMF of sheet metal for automobile parts has been rising in recent years. This review gives an inclusive survey of historical progress in EMF of continuum sheet metals. Also, the EMF is reviewed based on analytical approach, finite element method (FEM) simulation-based approach and experimental approach, on formability of the metals.

Abstract Tailored blanks offer great lightweighting opportunities for automotive industry and were applied on the front rails of a sedan in this research. To achieve the most efficient material usage, all the front rail parts were tailored into multiple sheets with the gauge of each sheet defined as a design variable for optimization. The equivalent static loads (ESL) method was adopted for linear optimization and the Insurance Institute for Highway Safety (IIHS) moderate overlap frontal crash as the nonlinear analysis load case. The torsion and bending stiffness of the sedan body in white (BIW) were set as design constraints. The occupant compartment intrusion in IIHS moderate overlap front crash was set as design objective to be minimized. The optimal thickness configuration for the tailored front rail designs was obtained through ESL optimization for multiple mass saving targets.

Abstract Improving the aerodynamics of heavy trucks is an important consideration in the strive for more energy-efficient vehicles. Cooling drag is one part of the total aerodynamic resistance acting on a vehicle, which arises as a consequence of air flowing through the grille area, the heat exchangers, and the irregular under-hood area. Today cooling packages of heavy trucks are dimensioned for a critical cooling case, typically when the vehicle is driving fully laden, at low speed up a steep hill. However, for long-haul trucks, mostly operating at highway speeds on mostly level roads, it may not be necessary to have all the cooling airflow from an open-grille configuration. It can therefore be desirable for fuel consumption purposes, to shut off the entire cooling airflow, or a portion of it, under certain driving conditions dictated by the cooling demands. In Europe, most trucks operating on the roads are of cab-over-engine type, as a consequence of the length legislations present.

Abstract In this article, a methodology is presented to assess the influence of time-averaged deformations on a production car of the 2018 A-class due to wind load. Exemplary, the deformations of the front and rear bumper are investigated. The aerodynamic development of vehicles at Mercedes-Benz is divided into several phases. When comparing, force coefficients differences can be observed between these distinct hardware stages as well as when comparing steady-state simulations to wind tunnel measurements. In early phases when prototype vehicles are not yet available, so-called aero foam models are used. These are well-defined full-sized vehicle models as the outer skin is milled from Polyurethane. Important aerodynamic characteristics such as an engine compartment with a cooling module, deflecting axles with rotatable wheels, and underbody covers are represented.

Abstract The fuel injection pressures used in gasoline direct injection (GDI) engines have increased in recent years to improve fuel efficiency and reduce emissions. Current GDI engines use injection pressures of up to 350 bar, and there is evidence that even higher fuel injection pressures could yield further improvements in atomization. Higher injection pressures could also improve mixture formation by increasing the spray velocity; however, the research with higher injection pressures over 1000 bar is limited due to a limit of mechanical components. This manuscript summarizes experimental investigations into the effect of injection pressure, injection mass, and nozzle shape on spray-induced air motion with ultrahigh injection pressure over 1000 bar.

Abstract This research was initiated with the goal of developing a significantly stronger aircraft transparency design that would reduce transparency failures from bird strikes. The objective of this research is to demonstrate the fact that incorporating high-strength tempered glass into cockpit window constructions for commercial aircraft can produce enhanced safety protection from bird strikes and weight savings. Thermal glass tempering technology was developed that advances the state of the art for high-strength tempered glass, producing 28 to 36% higher tempered strength. As part of this research, glass probability of failure prediction methodology was introduced for determining the performance of transparencies from simulated bird impact loading. Data used in the failure calculation include the total performance strength of highly tempered glass derived from the basic strength of the glass, the temper level, the time duration of the load, and the area under load.

Abstract In subsonic aircraft design, the aerodynamic performance of aircraft is compared meaningfully at a system level by evaluating their range and endurance, but cannot do so at an aerodynamic level when using lift and drag coefficients, CL and CD , as these often result in misleading results for different wing reference areas. This Part I of the article (i) illustrates these shortcomings, (ii) introduces a dimensionless number quantifying the induced drag of aircraft, and (iii) proposes an aerodynamic equation of state for lift, drag, and induced drag and applies it to evaluate the aerodynamics of the canard aircraft, the dual rotors of the hovering Ingenuity Mars helicopter, and the composite lifting system (wing plus cylinders in Magnus effect) of a YOV-10 Bronco. Part II of this article applies this aerodynamic equation of state to the flapping flight of hovering and forward-flying insects.

Abstract Part I introduced the aerodynamic equation of state. This Part II introduces the aerodynamic equation of state for lift and induced drag of flapping wings and applies it to a hovering and forward-flying bumblebee and a mosquito. Two- and three-dimensional graphical representations of the state space are introduced and explored for engineered subsonic flyers, biological fliers, and sports balls.