Dynamic Axle Force and Road Profile Identification Using a Moving Vehicle

In the interaction between vehicles, pavements and bridges, it is essential to aim towards a reduction of vehicle axle forces to promote longer pavement life spans and to prevent bridges loads becoming too high. Moreover, as the road surface roughness affects the vehicle dynamic forces, an efficient monitoring of pavement condition is also necessary to achieve this aim. This paper uses a novel algorithm to identify the dynamic interaction forces and pavement roughness from vehicle accelerations in both theoretical simulations and a laboratory experiment; moving force identification theory is applied to a vehicle model for this purpose. Theoretical simulations are employed to evaluate the ability of the algorithm to predict forces over a range of bridge spans and to evaluate the influence of road roughness level on the accuracy of the results. Finally, in addressing the challenge for the real-world problem, the effects of vehicle configuration and speed on the predicted road roughness are also investigated in a laboratory experiment.

The use of an instrumented vehicle in a wavelet based damage detection approach for bridge structures

Periodic monitoring of structures such as bridges is necessary as their condition can deteriorate due to environmental conditions and ageing, causing the bridge to become unsafe. This monitoring - so called Structural Health Monitoring (SHM) - can give an early warning if a bridge becomes unsafe. This paper investigates an alternative wavelet-based approach for the monitoring of bridge structures which consists of the use of a vehicle fitted with accelerometers on its axles. A simplified vehicle-bridge interaction model is used in theoretical simulations to examine the effectiveness of the approach in detecting damage in the bridge. The accelerations of the vehicle are processed using a continuous wavelet transform, allowing a time-frequency analysis to be performed. This enables the identification of both the existence and location of damage from the vehicle response. Based on this analysis, a damage index is established. A parametric study is carried out to investigate the effect of parameters such as the bridge span length, vehicle speed, vehicle mass, damage level, signal noise level and road surface roughness on the accuracy of results. In addition, a laboratory experiment is carried out to validate the results of the theoretical analysis and assess the ability of the approach to detect changes in the bridge response.

Theoretical investigation of the use of a moving vehicle to identify bridge dynamic parameters

Pavements and bridges are subject to a continuous degradation due to traffic aggressiveness, ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure in order to provide adequate maintenance and guarantee the required levels of transport service and safety. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamics of bridges. A simplified quarter carbridge interaction model is used in theoretical simulations and the natural frequency of the bridge is extracted from the spectra of the vehicle accelerations. The accuracy is better at lower speeds and for smooth road profiles. The structural damping of the bridge was also monitored for smooth and rough road profiles. The magnitude of peaks in the power spectral density of the vehicle accelerations decreased with increasing bridge damping and this decrease was easier to detect the smoother the road profile.

Wavelet Based Damage Detection Approach for Bridge Structures Utilising Vehicle Vibration

This paper investigates a wavelet-based damage detection approach for bridge structures. By analysing the continuous wavelet transform of the vehicle response, the approach aims to identify changes in the bridge response which may indicate the existence of damage. A numerical vehicle-bridge interaction model is used in simulations as part of a sensitivity study. Furthermore, a laboratory experiment is carried out to investigate the effects of varying vehicle configuration, speed and bridge damping on the ability of the vehicle to detect changes in the bridge response. The accelerations of the vehicle and bridge are processed using a continuous wavelet transform, allowing time-frequency analysis to be carried out on the responses of the laboratory vehicle-bridge interaction system. Results indicate the most favourable conditions for successful implementation of the approach.

First-order characteristics of the person-to-vehicle channel at 5.8 GHz

In this paper we investigate the first order characteristics of the radio channel between a moving vehicle and a stationary person positioned by the side of a road at 5.8 GHz. The experiments considered a transmitter positioned at different locations on both the body and receivers positioned on the vehicle. The transmitter was alternated between positions on the central chest region, back and the wrist (facing the roadside) of the body, with the receivers placed on the outside roof, the outside rear window and the inside dashboard of the vehicle. The Rice fading model was applied to the measurement data to assess its suitability for characterizing this emerging type of wireless channel. The Ricean K factors calculated from the data suggest that a significant dominant component existed in the majority of the channels considered in this study.

SHEPARD: Scheduling on heterogeneous platforms using application resource demands

Heterogeneous computing technologies, such as multi-core CPUs, GPUs and FPGAs can provide significant performance improvements. However, developing applications for these technologies often results in coupling applications to specific devices, typically through the use of proprietary tools. This paper presents SHEPARD, a compile time and run-time framework that decouples application development from the target platform and enables run-time allocation of tasks to heterogeneous computing devices. Through the use of special annotated functions, called managed tasks, SHEPARD approximates a task's performance on available devices, and coupled with the approximation of current device demand, decides which device can satisfy the task with the lowest overall execution time. Experiments using a task parallel application, based on an in-memory database, demonstrate the opportunity for automatic run-time task allocation to achieve speed-up over a static allocation to a single specific device. © 2014 IEEE.

Autonomic scheduling of tasks from data parallel patterns to CPU/GPU core mixes

We propose a methodology for optimizing the execution of data parallel (sub-)tasks on CPU and GPU cores of the same heterogeneous architecture. The methodology is based on two main components: i) an analytical performance model for scheduling tasks among CPU and GPU cores, such that the global execution time of the overall data parallel pattern is optimized; and ii) an autonomic module which uses the analytical performance model to implement the data parallel computations in a completely autonomic way, requiring no programmer intervention to optimize the computation across CPU and GPU cores. The analytical performance model uses a small set of simple parameters to devise a partitioning-between CPU and GPU cores-of the tasks derived from structured data parallel patterns/algorithmic skeletons. The model takes into account both hardware related and application dependent parameters. It computes the percentage of tasks to be executed on CPU and GPU cores such that both kinds of cores are exploited and performance figures are optimized. The autonomic module, implemented in FastFlow, executes a generic map (reduce) data parallel pattern scheduling part of the tasks to the GPU and part to CPU cores so as to achieve optimal execution time. Experimental results on state-of-the-art CPU/GPU architectures are shown that assess both performance model properties and autonomic module effectiveness. © 2013 IEEE.

Vehicle-barrier tracking of a scaled crash test for roadside barrier design

In this paper the tracking system used to perform a scaled vehicle-barrier crash test is reported. The scaled crash test was performed as part of a wider project aimed at designing a new safety barrier making use of natural building materials. The scaled crash test was designed and performed as a proof of concept of the new mass-based safety barriers and the study was composed of two parts: the scaling technique and of a series of performed scaled crash tests. The scaling method was used for 1) setting the scaled test impact velocity so that energy dissipation and momentum transferring, from the car to the barrier, can be reproduced and 2) predicting the acceleration, velocity and displacement values occurring in the full-scale impact from the results obtained in a scaled test. To achieve this goal the vehicle and barrier displacements were to be recorded together with the vehicle accelerations and angular velocities. These quantities were measured during the tests using acceleration sensors and a tracking system. The tracking system was composed of a high speed camera and a set of targets to measure the vehicle linear and angular velocities. A code was developed to extract the target velocities from the videos and the velocities obtained were then compared with those obtained integrating the accelerations provided by the sensors to check the reliability of the method.

Compiler and Runtime Support for Hybrid Static/Dynamic Scheduling

One of the outstanding issues in parallel computing is the selection of task granularity. This work proposes a solution to the task granularity problem by lowering the overhead of the task scheduler and as such supporting very fine-grain tasks. Using a combination of static (compile-time) scheduling and dynamic (run-time) scheduling, we aim to make scheduling decisions as fast as with static scheduling while retaining the dynamic load- balancing properties of fully dynamic scheduling. We present an example application and discuss the requirements on the compiler and runtime system to realize hybrid static/dynamic scheduling.

Multiuser Scheduling for Cognitive MIMO with Channel Estimation Errors and Feedback Delay

A multiuser scheduling multiple-input multiple-output (MIMO) cognitive radio network (CRN) with space-time block coding (STBC) is considered in this paper, where one secondary base station (BS) communicates with one secondary user (SU) selected from K candidates. The joint impact of imperfect channel state information (CSI) in BS → SUs and BS → PU due to channel estimation errors and feedback delay on the outage performance is firstly investigated. We obtain the exact outage probability expressions for the considered network under the peak interference power IP at PU and maximum transmit power Pm at BS which cover perfect/imperfect CSI scenarios in BS → SUs and BS → PU. In addition, asymptotic expressions of outage probability in high SNR region are also derived from which we obtain several important insights into the system design. For example, only with perfect CSIs in BS → SUs, i.e., without channel estimation errors and feedback delay, the multiuser diversity can be exploited. Finally, simulation results confirm the correctness of our analysis.

In situ diagnostics and prognostics of solder fatigue in IGBT modules for electric vehicle drives

This paper proposes an in situ diagnostic and prognostic (D&P) technology to monitor the health condition of insulated gate bipolar transistors (IGBTs) used in EVs with a focus on the IGBTs' solder layer fatigue. IGBTs' thermal impedance and the junction temperature can be used as health indicators for through-life condition monitoring (CM) where the terminal characteristics are measured and the devices' internal temperature-sensitive parameters are employed as temperature sensors to estimate the junction temperature. An auxiliary power supply unit, which can be converted from the battery's 12-V dc supply, provides power to the in situ test circuits and CM data can be stored in the on-board data-logger for further offline analysis. The proposed method is experimentally validated on the developed test circuitry and also compared with finite-element thermoelectrical simulation. The test results from thermal cycling are also compared with acoustic microscope and thermal images. The developed circuitry is proved to be effective to detect solder fatigue while each IGBT in the converter can be examined sequentially during red-light stopping or services. The D&P circuitry can utilize existing on-board hardware and be embedded in the IGBT's gate drive unit.