Off-set crack propagation analysis under mixed mode loadings

An assessment was carried out herein to study the eccentricity of cracks subjected to mixed-mode loadings. Several loading locations relative to a central line were selected to induce mixed-mode loadings, which were computed using a finite element method. An adaptive meshing technique was adopted during the simulation of crack propagation to ensure the singularity of stress at the tip of the crack. The stress intensity failure criterion was used and programmed, and the node splitting technique was used when the stress intensity factor reached the fracture toughness of the material to simulate crack propagations. It was found that large variations in the stress intensity factor were observed when off-set cracks were used, and that K _II decreased when loading distance increased, but increased when the off-set crack distance was increased. Both crack eccentricity and loading distance played important roles in producing mixed-mode loading, compared to the influence of central cracks. Correction factors were introduced to modify the calculation of stress intensity factors under mixed-mode loadings. Simulations of crack propagation were also conducted to study the effects of crack eccentricities and loading distances. It was found that the crack length, the loading distance relative to the central crack and the crack eccentricity dominated calculations of the integrity of cracked structures.     

Sampling of alternatives for route choice modeling

This paper presents a new paradigm for choice set generation in the context of route choice model estimation. We assume that the choice sets contain all paths connecting each origin–destination pair. Although this is behaviorally questionable, we make this assumption in order to avoid bias in the econometric model. These sets are in general impossible to generate explicitly. Therefore, we propose an importance sampling approach to generate subsets of paths suitable for model estimation. Using only a subset of alternatives requires the path utilities to be corrected according to the sampling protocol in order to obtain unbiased parameter estimates. We derive such a sampling correction for the proposed algorithm.Estimating models based on samples of alternatives is straightforward for some types of models, in particular the multinomial logit (MNL) model. In order to apply MNL for route choice, the utilities should also be corrected to account for the correlation using, for instance, a path size (PS) formulation. We argue that the PS attribute should be computed based on the full choice set. Again, this is not feasible in general, and we propose a new version of the PS attribute derived from the sampling protocol, called Expanded PS.Numerical results based on synthetic data show that models including a sampling correction are remarkably better than the ones that do not. Moreover, the Expanded PS shows good results and outperforms models with the original PS formulation.     

Interval estimation in the calibration of certain trip distribution models

This paper argues for interval, rather than point, estimation when calibrating some variants of the trip distribution “gravity” models. Analytic expressions are derived for the approximate asymptotic covariances of least squares and maximum likelihood estimates of the parameters in the impedance function under a variety of conditions. A comparative numerical example, and an application using migration flows, are also presented.     

Development of a low-noise cooling fan for an alternator using numerical and doe methods

An alternator, which converts mechanical rotational energy into electrical energy, is an important component of a vehicle. Alternators operate over a broad range of rotational speeds, typically from 3,000 RPM to 18,000 RPM, which demands a cooling fan producing sufficient airflow, ideally with a minimum of noise. In the current study, an optimized alternator-cooling fan was developed through a linked DOE(Design OF Experiment) process and numerical analysis. The SC/Tetra and FlowNoise S/W programs were used to calculate flow rates and noise levels, respectively, for the newly developed fan. Compared with original model, the numerical results predicted a 3 dBA noise reduction; the measured reduction was 4 dBA.     

Model-based design of a variable nozzle turbocharger controller

Variable Nozzle Turbocharger (VNT) was invented to solve the problem of matching an ordinary turbocharger with an engine. VNT can harness exhaust energy more efficiently, enhance intake airflow response and reduce engine emissions, especially during transient operating conditions. The difficulty of VNT control lies in how to regulate the position of the nozzle at different engine working conditions. The control strategy designed in this study is a combination of a closed-loop feedback controller and an open-loop feed-forward controller. The gain-scheduled proportional-integral-derivative (PID) controller was implemented as the feedback controller to overcome the nonlinear characteristic. As it is difficult to tune the parameters of the gain-scheduled PID controller on an engine test bench, system identification was used to identify the plant model properties at different working points for a WP10 diesel engine on the test bench. The PID controller parameters were calculated based on the identified first-order-plus-dead-time (FOPDT) plant model. The joint simulation of the controller and the plant model was performed in Matlab/Simulink. The time-domain and frequency-domain performances of the entire system were evaluated. The designed VNT control system was verified with engine tests. The results indicated that the real boosting pressure traced the target boosting pressure well at different working conditions.     

Deflection test and transmission error measurement to identify hypoid gear whine noise

T-Hypoid gears are commonly used in rear-drive and 4WD (4 Wheel Drive) vehicle axles. Investigating their sensitivity to deflections is one of the most important aspects of their design and optimization procedures. Therefore, a deflection test was performed in this study in the actual gear mounting using completely processed gear. This test covered the full operating range of gear loads from “no load” to “peak load”. Under peak load, the contact pattern extended to the tooth boundaries without showing a concentration of the contact pattern at any point on the tooth surface. The transmission error was tested under an axle assembly triaxial-real-car-load condition.     

Development of a navigation algorithm with dead reckoning for unmanned ground vehicles

A navigation algorithm is indispensable for Unmanned Ground Vehicles (UGVs). During driving, UGVs follow a global path. In this study, we propose a navigation algorithm using Real Time Kinematic (RTK)-Differential Global Positioning System (DGPS) units and encoders to complement global path planning. Sometimes GPS systems lose their signals and receive inaccurate position data due to many factors, such as edifice and barrier obstructions. This paper shows that GPS deviations can be solved using a Dead Reckoning (DR) navigation method with encoders and that position errors can be decreased through the use of RTK-DGPS units. In addition to this method, we will introduce a new waypoint update algorithm and a steering algorithm using RTK-DGPS units.     

Modified lateral control of an autonomous vehicle by look-ahead and look-down sensing

This paper presents a modified lateral control method for an autonomous vehicle with both look-ahead and look-down sensing systems. To cope with sensor noise and modeling uncertainty in the lateral control of the vehicle, a modified LMI-based H lateral controller was proposed, which uses the look-ahead information of the lateral offset error measured at the front of vehicle and the look-down information of the vehicle yaw angle error between the reference lane and the centerline of the vehicle. To verify the safety and the performance of the lateral control, a scaled-down vehicle was developed, and the positioning of the vehicle was estimated with USAT. The proposed controller, which uses both look-ahead and look-down information, was tested for lane changing and reference lane tracking with both simulation and experiment. The simulation and experimental results show that the proposed controller has better tracking and handling performance compared with a controller that uses only the look-ahead information of the target heading angle error.     

License plate extraction method for identification of vehicle violations at a railway level crossing

The primary cause of most railroad accidents is vehicle entry into railway level crossings despite warning messages. To identify drivers who violate railway level crossing regulations, vehicle license plate recognition can be applied at railway level crossings. The purpose of this paper is to present an effective method for extracting the license plate region from vehicle images taken at railway level crossings. The method proposed in this paper uses the variation in the gray-level values across the image of a license plate. For license plate region extraction, the character region is first recognized by identifying the character width and the difference between the background region and the character region. The license plate region is then extracted by finding the inter-character distance in the plate region. In addition, the license plate type is identified by the difference in the gray-level value between the background region and the character region. The proposed method is effective in solving the current challenges in extracting the license plate region from the damaged frames of license plates issued for domestic use, including new types of license plates. According to the experimental results, the proposed method yields a high extraction rate of 99.5% for vehicle license plates.     

Design framework for FlexRay network parameter optimization

Because the FlexRay protocol has more than 70 configuration parameters and these parameters correlate with each other, designing a FlexRay network is a complex and difficult task. In this study, we propose a design framework that optimizes the two main FlexRay network parameters that are highly relevant to the application algorithm. The design process is composed of two steps for optimizing parameters. In the first step, the static slot length is optimized using a frame-packing algorithm. This algorithm binds network signals into static frames based on their periods and signal groups. In the second step, the communication cycle length is optimally designed with frame-scheduling algorithm and worst-case reponse time analysis. Based on the frame-scheduling algorithm, the response times are analyzed. The proposed design framework was applied to a unified chassis control system as a case study, and the analytical results were verified.