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In this paper, the local stress intensity factors for kinked cracks in spot weld cup specimens are investigated by finite element analyses. Based on the experimental observations of kinked crack growth mechanisms in square-cup specimens under cyclic loading conditions, axisymmetric finite element models are established to investigate the local stress intensity factor solutions for kinked cracks emanating from the main crack. Both circular and rectangular shaped notch tip and a sharp crack tip are considered for the main crack. Various kink lengths are considered. The local stress intensity factor solutions for kinked cracks are obtained. The results show that the local stress intensity factors for kinked cracks with finite kink lengths are much higher than those based on the closed-form solutions for kinked cracks with vanishing kink length. Finally, the implications of the local stress intensity factor solutions for kinked cracks on fatigue life prediction are discussed.

Limited room temperature formability hinders the wide-spread use of high strength aluminum alloys in body parts. Forming at warm temperatures or from softer tempers are the current solutions. In this work, our approach is to start with age-hardened sheets from 7xxx and 6xxx family of alloys and improve their formability using local thermomechanical processing only in the regions demanding highest ductility in the forming processes. We achieved local formability improvements with friction stir processing and introduce another process named roller bending-unbending as a concept and showed its feasibility through finite element simulations. Initial results from FSP indicated significant deformation in the processed zones with minimal sheet distortion. FSP also resulted in dynamically recrystallized, fine grained (d < 5 μm) microstructures in the processed regions with textures significantly different from the base material.

Intelligent driving is an important research direction in the field of artificial intelligence. The fourth industrial revolution represented by the Internet of things provides more prospects for the development of intelligent vehicles. Trajectory planning and tracking control is one of the key technologies of intelligent driving vehicle. This paper takes intelligent driving vehicle as the starting point and establishes a research method of intelligent vehicle trajectory planning based on particle swarm optimization, based on the vehicle kinematics and dynamics model, a model predictive control algorithm is built for trajectory tracking control, the simulation scene is built by Prescan, the vehicle dynamics parameters are set in Carsim, and then the joint simulation is carried out with Simulink.

The objective of this study was to investigate the local change of PV value on the end faces of rocker pins driven by a high-performance chain under transmitting torque conditions. A test bench system was prepared to evaluate the behavior of the chain belt under driven state. Local contact force of the pin was measured by strain gauges attached to a specific modified pin for which the thickness was partly reduced by machine work. Change of PV value on the end face of the pin was also calculated by considering the change of pressure generated by contact force and sliding velocity of rocker pin. Autorotation angles of the rocker pins in the groove of driving and driven sheaves were investigated by replacing the normal pulleys with visibly transparent sheaves made with acrylic resin. The representative loading points were also calculated assuming that the pin was regarded as a simple beam where an eccentric compressive load was applied.

In the multi-link mechanism of a variable compression ratio engine, the stiffness of the end of the housing increase by adopting the slit structure, this eventually led to an increase in pressure concentrate locally at a certain contact point at the end of the sliding surface of the lower link bearing. As a design solution, this is a report of how to disperses/reduces the generated axial pressure by optimizing the shape of the sliding surface based on FEM/EHD, which are estimated by considering the deformation characteristics of lower link mechanism.

Valve covers are a primary source of radiated engine noise. In this paper, we discuss an analytical approach that captures the complicated nonlinear response of the cam cover gaskets and grommets without the need for a prohibitively large finite-element model of the cam cover system. We utilize a detailed local analysis of the gasket and grommet components and abstract their isolation characteristics for later use in a global NVH (Noise-Vibration-Harshness) system analysis.

This paper presents the design and experimental validation of a localization method for autonomous driving. The investigated method proposes and compares the application of the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) to the sensor fusion of onboard data streaming from a Global Positioning System (GPS) sensor and an Inertial Navigation System (INS). In the paper, the design of the hardware layout and the proposed software architecture is presented. The method is experimentally validated in real time by using a properly instrumented all-wheel-drive electric racing vehicle and a compact Sport Utility Vehicle (SUV). The proposed algorithm is deployed on a high-performance computing platform with an embedded Graphical Processing Unit that is mounted on board the considered vehicles.

Future SAE Level 4 and Level 5 autonomous vehicles will require novel applications of localization, perception, control and artificial intelligence technology in order to offer innovative and disruptive solutions to current mobility problems. This paper concentrates on low speed autonomous shuttles that are transitioning from being tested in limited traffic, dedicated routes to being deployed as SAE Level 4 automated driving vehicles in urban environments like college campuses and outdoor shopping centers within smart cities. The Ohio State University has designated a small segment in an underserved area of campus as an initial autonomous vehicle (AV) pilot test route for the deployment of low speed autonomous shuttles. This paper presents initial results of ongoing work on developing solutions to the localization and perception challenges of this planned pilot deployment.

A three-dimensional (3D) sound intensity probe is used to identify the trim components generating buzz, squeak, and rattle (BSR) noise in a vehicle interior. The 3D intensity probe has the advantages of compact overall size, small number of microphones, and low-frequency detection capability. Although the 3D sound intensimetry has been not popularly applied in practical problems due to various bias errors, a new error compensation method is adopted in this work, substantially improving the estimate’s precision. Linearization of the phase function of the cross-spectral density function between a set of two microphones is used to calculate the intensity avoiding spectral bias error, and an error map for spatial angles is used to compensate for the difference in directivity index around the microphone array. An intensity probe with an even microphone spacing of 30 mm in tetrahedral arrangement is used for the source localization.

The recent research on location approaches of the intelligent vehicle based on Light Detection and Ranging (LiDAR) is analyzed in this paper. According to the features of these approaches, it can be divided into three categories: simultaneous localization and mapping (SLAM), offline mapping and online localization (OMOL) and fusion localization (FL). Past research and applications of the main algorithms and critical research scenarios in each localization approaches are reviewed. Three aspects of the current trend in location approaches of the intelligent vehicle based on LiDAR are discussed. Based on object detection, object recognition and object analysis algorithms in the field of deep learning, semantic SLAM and real-time three-dimensional reconstruction are important research trends for SLAM. The performance of robustness and real-time performance of localization algorithm of intelligent vehicles based on LiDAR need to be improved.

The exploitation of full load capabilities of DI gasoline engines requires at least the same degree of effort as in MPFI engine development. An optics based sensor and sensing technique is presented, which together with conventional pressure indicating provides identification of self ignition centers as the engine is operated under knock or borderline knock conditions. The knock location sensor is configured as a spark plug providing the relevant spark plug properties together with the multichannel optical access into the upper part of the combustion chamber. Functionality and sensitivity of this sensing technique are demonstrated and results for combustion system development are shown.

Structure-born vibrations are often required to be localized in a complex structure, but in such dispersive medium, the vibration wave propagates with speed dependent on frequency. This property of solid materials causes an adverse effect for localization of vibrational events. The cause behind such phenomenon is that the propagating wave envelope changes its phase delay and amplitude in time and space as it travels in dispersive medium. This problem was previously approached by filtering a signal to focus on frequencies of the wave propagating with a similar speed, with improved accuracy of cross-correlation results. However, application of this technique has not been researched for localization of vibrational sources. In this work we take advantage of filtering prior to cross-correlation calculation while using multiple sensors to indicate an approximate location of vibration sources.

Acoustic beamforming was used to visualize the sound radiation of trucks under test track passby and actual highway operating conditions. The purpose of these measurements was to obtain an understanding of which sources contribute to the overall passby noise level and to determine the vertical distribution of noise sources. For trucks, drive axle tires were found to be the major contributor to passby noise at highway speeds, followed by powertrain noise to a much less degree, and very occasionally, exhaust stack outlet noise. For medium and heavy trucks, the acoustic mean source height was found to be about 0.5m and about 0.3m for light vehicles.

Traditional vehicle air conditioning systems condition the entire cabin to a comfortable range of temperature and humidity regardless of the number of passengers in the vehicle. The A/C system is designed to have enough capacity to provide comfort for transient periods when cooling down a soaked car. Similarly for heating, the entire cabin is typically warmed up to achieve comfort. Localized heating and cooling, on the other hand, focuses on keeping the passenger comfortable by forming a micro climate around the passenger. This is more energy efficient since the system only needs to cool the person instead of the entire cabin space and cabin thermal mass. It also provides accelerated comfort for the passenger during the cooling down periods of soaked cars. Additionally, the system adapts to the number of passengers in the car, so as to not purposely condition areas that are not occupied.

Plastic air induction system (AIS) has been widely used in vehicle powertrain applications for reduced weight, cost, and improved engine performance. Physical design validation (DV) tests of an AIS, as to meet durability and reliability requirements, are usually conducted by employing the frequency domain vibration tests, either sine sweep or random vibration excitations, with a temperature cycling range typically from -40°C to 120°C. It is well known that under high vibration loading and large temperature range, the plastic components of the AIS demonstrate much higher nonlinear response behaviors as compared with metal products. In order to implement a virtual test for plastic AIS products, a practical procedure to model a nonlinear system and to simulate the frequency response of the system, is crucial. The challenge is to model the plastic AIS assembly as a function of loads and temperatures, and to evaluate the dynamic response and fatigue life in frequency domain as well.

There are numerous component applications that would benefit from localized austempering (heat treating only a portion of the component) for either improved wear properties or fatigue strength. Currently available methods for “surface austempering” of ductile iron are often expensive and not as well controlled as would be desired. This study was undertaken to find a better process. Locally Austempered Ductile Iron (LADI) is the result of those efforts. LADI is a surface hardening heat treatment process that will produce a localized case depth of an ausferrite microstructure (ADI) in a desired area of a component. This process has been jointly developed by Ajax Tocco Magnethermic Corporation (ATM) and Applied Process, Inc.- Technologies Division (AP) with support and collaboration from ThyssenKrupp Waupaca, Inc. (TKW). This paper describes the outcome of using this patent pending process (US #65/195,131).

Laser-based measurements of charge temperature and exhaust gas recirculation (EGR) ratio in an homogeneous charge compression ignition (HCCI) engine are demonstrated. For this purpose, the rotational coherent anti-Stokes Raman spectroscopy technique (CARS) was used. This technique allows temporally and locally resolved measurements in combustion environments through only two small line-of-sight optical accesses and the use of standard gasoline as a fuel. The investigated engine is a production-line four-cylinder direct-injection gasoline engine with the valve strategy modified to realize HCCI-operation. CARS-measurements were performed in motored and fired operation and the results are compared to polytropic calculations. Studies of engine speed, load, valve timing, and injection pressure were conducted showing the strong influence of charge temperature on the combustion timing.

Ultrasonic transducers are widely used in automotive and industrial applications for surround sensing. Anisotropic directivity patterns with a narrow-angled beam in the vertical plane and a wide-angled beam in the horizontal plane are needed in automotive applications particularly. Today’s ultrasonic transducers for automotive applications are mainly metal based, pot-like ultrasonic transducers. The anisotropic directivity pattern is achieved by increasing the thickness of the vibrating plate-like part of the structure locally. Composites with locally structured fiber reinforcements open up the possibility to design the dynamical behavior of components without changing its contour. Using this new dimension of design to modify the directivity pattern of sound radiating components is less examined in literature.

This paper presents an experimental technique for locating engine cooling system hot spots by using a Magnesium Borate water solution for the engine coolant. In doing so, Magnesium Borate is deposited wherever local boiling occurs thus indicating the high temperature areas. This technique was applied to a large V-8 engine and provided visual results of high temperature areas in the water jacket. Color photographs show the results, which correlate with measured metal temperatures and measured coolant flow velocities. The extension of the technique to include estimation of metal temperatures results from additional test data reported. The procedure is useful for locating unsuspected hot-spots in any passage in the engine cooling system. The severity of the temperature may be determined by knowing the Boiling Point of the solution.

A model based approach is developed to track and trace multiple incoherent sound sources in 3D space in real time. This technology is capable of handling continuous, random, transient, impulsive, narrowband and broadband sounds over a wide frequency range (20 to 20,000 Hz). The premise of this technology is that the sound field is generated by point sources located in a free field. To locate these sound sources, iterative triangulations are used based on the signals measured by a microphone array. These signals are preprocessed through de-noising techniques to enhance signal to noise ratios (SNR). Unlike the conventional beamforming, the present technology enables one to pinpoint the exact locations of multiple incoherent sound sources simultaneously by using the Cartesian coordinates, including sources behind measurement microphones. In other words, the microphone array need not face a test object, which is required in the beamforming.