Search Results

A twist beam rear suspension system is modeled, analyzed and optimized in this paper. An ADAMS model is established based on the REC (Rigid-Elastic Coupling) Theory, which is verified by FEM (Finite Element Method) approach, the effects of the geometric parameters on the twist beam suspension performance are investigated. In order to increase the calculation efficiency and improve the simulation accuracy, a neural network model and NSGA II (Non-dominated Sorting Genetic Algorithm II) are adopted to conduct a multi-objective optimization on a twist beam rear suspension system.

Two models are presented for the long life (107 cycles) axial fatigue strength of four ferrous powder metal (PM) material series: sintered and heat-treated iron-carbon steel, iron-copper and copper steel, iron-nickel and nickel steel, and pre-alloyed steel. The materials are defined at ranges of carbon content and densities using the broad data available in the Metal Powder Industries Federation (MPIF) Standard 35 for PM structural parts. The first model evaluates 107 cycles axial fatigue strength as a function of ultimate strength and the second model as a function of hardness. For all 118 studied materials, both models are found to have a good correlation between calculated and 107 cycles axial fatigue strength with a high Pearson correlation coefficient of 0.97. The article provides details on the model development and the reasoning for selecting the ultimate strength and hardness as the best predictors for 107 cycles axial fatigue strength.

This work presents a method for estimating human body orientation using a combination of convolutional neural network (CNN) and stereo camera in real time. The approach uses the CNN model to predict certain human body keypoints then transforms these points into a 3D space using the stereo vision system to estimate the body orientations. The CNN module is trained to estimate the shoulders, the neck and the nose positions, detecting of three points is required to confirm human detection and provided enough data to translate the points into 3D space.

Scuffing is a failure mechanism which can occur in various engineering components, such as engine cylinder kits, gears and cam/followers. In this research, the scuffing behavior of 4140 steel and ductile iron was investigated and compared through ball-on-disk scuffing tests. A step load of 22.2 N every two minutes was applied with a light mineral oil as lubricant to determine the scuffing load. Both materials were heat treated to various hardness and tests were conducted to compare the scuffing behavior of the materials when the tempered hardness of each material was the same. Ductile iron was found to have a consistently high scuffing resistance before tempering and at tempering temperatures lower than 427°C (HRC ≻45). Above 427°C the scuffing resistance decreases. 4140 steel was found to have low scuffing resistance at low tempering temperatures, but as the tempering temperature increases, the scuffing resistance increased.

One of the major problems that the automotive industry faces is reducing friction to increase efficiency. Researchers have shown that 30% of the fuel energy was consumed to overcome the friction forces between the moving parts of any automobile, Holmberg et al. [1]. The interface of the piston pin and pin bore is one of the areas that generate high friction under severe working conditions of high temperature and lack of lubrication. In this research, experimental investigation and theoretical simulation have been carried out to analyze the motion of the floating pin against pin bore. In the experimental study, the focus was on analyzing the floating pin motion by using a bench test rig to simulate the floating pin motion in an internal combustion engine. A motion data acquisition system was developed to capture and record the pin motion. Thousands of images were recorded and later analyzed by a code written by MATLAB.

In this research, ball-on-plate reciprocating sliding wear tests were utilized on austempered and quench-tempered gray cast iron samples with and without shot-peening treatment. The wear volume loss of the gray cast iron samples with different heat treatment designs was compared under equivalent hardness. The phase transformation in the matrix was studied using metallurgical evaluation and hardness measurement. It was found that thin needle-like ferrite became coarse gradually with increasing austempering temperature and was converted into feather-like shape when using the austempering temperatures of 399°C (750°F). The residual stress on the surface and sub-surface before and after shot-peening treatment was analyzed using x-ray diffraction. Compressive residual stress was produced after shot-peening treatment and showed an increasing trend with austempering temperature.

This paper describes the scuffing tests performed to understand the effect of surface roughness and lubrication on scuffing behavior for austempered ductile iron (ADI) material. As the scuffing tendency is increased, metal-to-metal interaction between contacting surfaces is increased. Lubrication between sliding surfaces becomes the boundary or mixed lubrication condition. Oil film breakdown leads to scuffing failure with the critical load. Hence, the role of surface roughness and lubrication becomes prominent in scuffing study. There are some studies in which the influence of the surface roughness and lubrication on scuffing was evaluated. However, no comprehensive scuffing study has been found in the literature regarding the effect of surface roughness and lubrication on scuffing behavior of ADI material. The current research took into account the inferences of surface roughness and lubrication on scuffing for ADI.

An existing challenge in current state-of-the-art autonomous vehicles is the process of safely transferring control from autonomous driving mode to manual mode because the driver may be distracted with secondary tasks. Such distractions may impair a driver’s situational awareness of the driving environment which will lead to fatal outcomes during a handover. Current state-of-the-art vehicles notify a user of an imminent handover via auditory, visual, and physical alerts but are unable to improve a driver’s situational awareness before a handover is executed. The overall goal of our research team is to address the challenge of providing a driver with relevant information to regain situational awareness of the driving task. In this paper, we introduce a novel approach to estimating a driver’s visual focus of attention using a 2D RGB camera as input to a Multi-Input Convolutional Neural Network with shared weights. The system was validated in a realistic driving scenario.

This particular study focuses on four specific gear steels: SAE 4320, SAE 8822, PS18, and 20MnCr5. Notched specimens are manufactured from the four materials. Three point bending experiments were conducted which include ultimate tests and fatigue tests. Part I is on ultimate test only. Part II will concentrate on fatigue testing. In order to see how the carburization affected the fatigue performance of these steels, a residual stress test was performed on one sample of each steel by mean of the incremental hole drilling method. The compressive stresses were found in all four steels with minimum and maximum stress approximately equal. This suggests that the residual stresses are biaxial in the carburized steel case. The difference between the maximum and minimum stresses is within 37% for all steels. The residual stress after the carburization process were found to be highest in the 4320 steel and SAE 8822, followed by PS 18 and then MnCr.

High-fidelity finite element (FE) tire-snow interaction models have the advantage of better understanding the physics of the tire-snow system. They can be used to develop semi-analytical models for vehicle design as well as to design and interpret field test results. For off-terrain conditions, there is a high level of uncertainties inherent in the system. The FE models are computationally intensive even when uncertainties of the system are not taken into account. On the other hand, field tests of tire-snow interaction are very costly. In this paper, dynamic metamodels are established to interpret interaction forces from FE simulation and to predict those forces by using part of the FE data as training data and part as validation data. Two metamodels are built based upon the Krieging principle: one has principal component analysis (PCA) taken into account and the other does not.

The hole stretchability of two Aluminum Alloys (AA6111 and AA6022) are studied by using a two stages integrated finite element framework where the edge geometry and edge damages from the hole piercing processes were considered in the subsequent hole expansion processes. Experimentally it has been found that AA6022 has higher hole expansion ratios than those of AA6111. This observation has been nicely captured by finite element simulations. The main cause of differences have been identified to the volume fractions of the random distributed second phase hard particles which play a critical role in determining the fracture strains of the materials.

Advanced high-strength steel (AHSS) is gaining popularity in the automotive industry due to its higher final part strength with the better formability compares to the conventional steel. However, the edge fracture occurs during the forming procedure for the pre-strained part. To avoid the edge fracture that happens during the manufacturing, the effect of pre-strain on edge cracking limit needs to be studied. In this paper, digital image correlation (DIC), as an accurate optical method, is adopted for the strain measurement to determining the edge cracking limit. Sets of the wide coupons are pre-strained to obtain the samples at different pre-strain level. The pre-strain of each sample is precisely measured during this procedure using DIC. After pre-straining, the half dog bone samples are cut from these wide coupons. The edge of the notch in the half dog bone samples is created by the punch with 10% clearance for the distinct edge condition.

Vehicle weight reduction is a significant challenge for the modern automotive industry. In recent years, the amount of vehicular components constructed from aluminum alloy has increased due to its light weighting capabilities. Automotive manufacturing processes, predominantly those utilizing various stamping applications, require a thorough understanding of aluminum fracture predictions methods, in order to accurately simulate the process using Finite Element Method (FEM) software or use it in automotive engineering manufacture. This paper presents the strain distribution of A5182 aluminum samples after punch impact under various conditions by Digital Image Correlation (DIC) system, its software also measured the complete strain history, in addition to sample curvature after it was impacted; therefore obtaining the data required to determine the amount of side-wall-curl (Aluminum sheet springback) present after formation.

In recent years, dual phase (DP) Advanced High Strength Steels (AHSS) and Ultra High Strength Steels (UHSS) are considered as prominent materials in the automotive industry due to superior structural performance and vehicle weight reduction capabilities. However, these materials are often sensitive to trimmed edge cracking if stretching along sheared edge occurs in such processes as stretch flanging. Another major issue in the trimming of UHSS is tool wear because of higher contact pressures at the interface between cutting tools and sheet metal blank caused by UHSS’s higher flow stresses and the presence of a hard martensitic phase in the microstructure. The objective of the current paper is to study the influence of trimming conditions and tool wear on quality and stretchability of trimmed edge of DP980 steel sheet. For this purpose, mechanically trimmed edges were characterized for DP980 steel and compared with other steels such as HSLA 350 and BH210.

Advanced high strength steels (AHSS) are increasingly used in automotive industry. A major issue for AHSS stamping is edge cracking. This failure mode is difficult to predict by conventional forming limit curve (FLC). The material edge stretchability is mainly evaluated using the hole expansion test. In this study, digital Image Correlation (DIC) is applied for strain measurement. DIC is a non-contact, full field, high accuracy and direct measurement technique that provides more detailed information for the evolution of strains on the sheet surface. Tests were conducted for five AHSS and nine cases. This paper will explain in detail the DIC technique and its results.

Scuffing is one of the major problems that influence the life cycle and reliability of several auto components, including engine cylinder kits, flywheels, camshafts, crankshafts, and gears. Ferrous casting materials, such as gray cast iron, ductile cast iron and austempered ductile cast iron (ADI) are widely applied in these components due to their self-lubricating characteristics. The purpose of this research is to determine the scuffing behavior of these three types of cast iron materials and compare them with 1050 steel. Rotational ball-on-disc tests were conducted with white mineral oil as the lubricant under variable sliding speeds and loads. The results indicate that the scuffing initiation is due to either crack propagation or plastic deformation. It is found that ADI exhibits the highest scuffing resistance among these materials.

An application of variation simulation for predicting vehicle interior driveline vibration is presented. The model, based on a “Monte Carlo”-style approach, predicts the noise, vibration and harshness (NVH) response of the vehicle driveline based on distributions of imbalance and runout derived from manufacturing production variation (the forcing function) and the vehicle's sensitivity to the forcing function. The model is used to illustrate the change in vehicle interior vibration that results when changes are made to production variation for runout and imbalance of driveline components, and how those same changes result in different responses based on vehicle sensitivity.

Selecting the right transportation platform is challenging, whether it is at a personal level or at an organizational level. In settings where predominantly the functional aspects rule the decision making process, defining the mobility of a vehicle is critical for comparing different offerings and making acquisition decisions. With the advent of intelligent vehicles, exhibiting partial to full autonomy, this challenge is exacerbated. The same vehicle may traverse independently and with greater tolerance for acceleration than human occupied vehicles, while, at the same time struggle with obstacle avoidance. The problem presents itself at the individual vehicle sensing level and also at the vehicle/fleet level. At the sensing and information level, one can be looking at issues of latency, bandwidth and optimal information fusion from multiple sources including privileged sensing. At the overall vehicle level, one focuses more on the ability to complete missions.

A multi-sensor Digital Image Correlation (DIC) system is employed to measure the deformation of metal specimens during tensile tests. The multi-sensor DIC system is capable of providing high quality contour and deformation data of a 3D object. Methodology and advantages of the multi-sensor DIC system is introduced. Tests have been done on steel and aluminum specimens to prove the performance of the system. With the help of the multi-sensor DIC system, we proposed our approaches to determine the forming limit based on shape change around the necking area instead of calculate the FLD based on the in-plane strains. With the employed system, all measurements are done post-deformation, no testing controlling mechanism, such as load force control or touching control, is required. The extracted data is analyzed and the result shows a possibility that we may be able to improve current technique for Forming Limit Diagram (FLD) measurement.

In this work, a multi-camera Digital Image Correlation (DIC) system is applied to measure the material properties of aluminum (5754) specimens. Such tests are usually done using 2D (one-camera) or 3D (two-camera) DIC systems. A multi-camera DIC system includes three or more cameras and inherits all the advantages of a conventional 3D DIC system (with two cameras) such as, full-field measurement, high accuracy and high speed. In addition, this system further improves the measured results by including redundant data. In this work, we will show the potential of this system to measure a variety of material properties at one time.