Extracting statistically dominant modes of a steel truss bridge from vehicle-induced vibrations

This study is intended to investigate the validity of the stability diagram (SD) aided multivariate autoregressive (MAR) analysis for identifying modal parameters of a real truss bridge. The MAR models are adopted to fit the time series of the dynamic accelerations recorded from a number of observation points on the bridge; then the modal parameters are extracted from the MAR model coefficient matrix. The SD is adopted to determine statistically dominant modes. In plotting the SD, a number of stability criteria are further adopted for filtering out those modes with unstable modal parameters. By the present method, the first five modal frequencies and mode shapes are identified with very high precision, while the damping ratios are identified with high precision for the 1st mode but with poorer precision for higher modes. Moreover, the ability of the SD in selecting structural modes without getting involved in any model-order optimization problem is highlighted through a comparison study.

A Conventional Internal Combustion Engine Versus a Range Extended Electric Vehicle Under the Current Regulatory Regime in the United Kingdom

Transport accounts for 22% of greenhouse gas emissions in the United Kingdom and cars are expected tomore than double by 2050. Car manufacturers are continually aiming for a substantially reduced carbonfootprint through improved fuel efficiency and better powertrain performance due to the strict EuropeanUnion emissions standards. However, road tax, not just fuel efficiency, is a key consideration of consumerswhen purchasing a car. While measures have been taken to reduce emissions through stricter standards, infuture, alternative technologies will be used. Electric vehicles, hybrid vehicles and range extended electricvehicles have been identified as some of these future technologies. In this research a virtual test bed of aconventional internal combustion engine and a range extended electric vehicle family saloon car were builtin AVL’s vehicle and powertrain system level simulation tool, CRUISE, to simulate the New EuropeanDrive Cycle and the results were then soft-linked to a techno-economic model to compare the effectivenessof current support mechanisms over the full life cycle of both cars. The key finding indicates that althoughcarbon emissions are substantially reduced, switching is still not financially the best option for either theconsumer or the government in the long run.

Development of a Vehicle-Bridge-Soil Dynamic Interaction Model for Scour Damage Modelling

Damage detection in bridges using vibration-based methods is an area of growing research interest. Improved assessment
methodologies combined with state-of-the-art sensor technology are rapidly making these approaches applicable for real-world
structures. Applying these techniques to the detection and monitoring of scour around bridge foundations has remained
challenging; however this area has gained attraction in recent years. Several authors have investigated a range of methods but
there is still significant work required to achieve a rounded and widely applicable methodology to detect and monitor scour.This
paper presents a novel Vehicle-Bridge-Soil Dynamic Interaction (VBSDI) model which can be used to simulate the effect of scour
on an integral bridge. The model outputs dynamic signals which can be analysed to determine modal parameters and the variation
of these parameters with respect to scour can be examined.The key novelty of this model is that it is the first numerical model for
simulating scour that combines a realistic vehicle loadingmodel with a robust foundation soil responsemodel.This paper provides a
description of the model development and explains the mathematical theory underlying themodel. Finally a case study application
of the model using typical bridge, soil, and vehicle properties is provided.

Determining the Presence of Scour around Bridge Foundations Using Vehicle-Induced Vibrations

Bridge scour is the number one cause of failure in bridges located over waterways. Scour leads to rapid losses in foundation stiffness and can cause sudden collapse. Previous research on bridge health monitoring has used changes in natural frequency to identify damage in bridge beams. The possibility of using a similar approach to identifying scour is investigated in this paper. To assess if this approach is feasible, it is necessary to establish how scour affects the natural frequency of a bridge, and if it is possible to measure changes in frequency using the bridge dynamic response to a passing vehicle. To address these questions, a novel vehicle–bridge–soil interaction (VBSI) model was developed. By carrying out a modal study in this model, it is shown that for a wide range of possible soil states, there is a clear reduction in the natural frequency of the first mode of the bridge with scour. Moreover, it is shown that the response signals on the bridge from vehicular loading are sufficient to allow these changes in frequency to be detected.

Selection of the most appropriate roadside vehicle restraint system – the SAVeRS project

Run Off Road (ROR) crashes are road accidents that often result in severe injuries or fatalities. To reduce the severity of ROR crashes, “forgiving roadsides” need to be designed and this includes identifying situations where there is a need for a Vehicle Restraint System (VRS) and what appropriate VRS should be selected for a specific location and traffic condition. Whilst there are standards covering testing, evaluation and classification of VRS within Europe (EN1317 parts 1 to 8), their selection, location and installation requirements are typically based upon national guidelines and standards, often produced by National Road Authorities (NRA) and/or overseeing organisations. Due to local conditions, these national guidelines vary across Europe.
The European SAVeRS project funded by CEDR has developed a practical and readily understandable VRS guidance document and a user-friendly software tool which allow designers and road administrations to select the most appropriate solution in different road and traffic conditions.
This paper describes the main outcomes of the project, the process to select the most appropriate roadside barrier, and the user friendly SAVeRS tool.

Effect of vehicle characteristics on safety, fuel use and emissions

Nos últimos anos, o número de vítimas de acidentes de tráfego por milhões de habitantes em Portugal tem sido mais elevado do que a média da União Europeia. Ao nível nacional torna-se premente uma melhor compreensão dos dados de acidentes e sobre o efeito do veículo na gravidade do mesmo. O objetivo principal desta investigação consistiu no desenvolvimento de modelos de previsão da gravidade do acidente, para o caso de um único veículo envolvido e para caso de uma colisão, envolvendo dois veículos. Além disso, esta investigação compreendeu o desenvolvimento de uma análise integrada para avaliar o desempenho do veículo em termos de segurança, eficiência energética e emissões de poluentes. Os dados de acidentes foram recolhidos junto da Guarda Nacional Republicana Portuguesa, na área metropolitana do Porto para o período de 2006-2010. Um total de 1,374 acidentes foram recolhidos, 500 acidentes envolvendo um único veículo e 874 colisões. Para a análise da segurança, foram utilizados modelos de regressão logística. Para os acidentes envolvendo um único veículo, o efeito das características do veículo no risco de feridos graves e/ou mortos (variável resposta definida como binária) foi explorado. Para as colisões envolvendo dois veículos foram criadas duas variáveis binárias adicionais: uma para prever a probabilidade de feridos graves e/ou mortos num dos veículos (designado como veículo V1) e outra para prever a probabilidade de feridos graves e/ou mortos no outro veículo envolvido (designado como veículo V2). Para ultrapassar o desafio e limitações relativas ao tamanho da amostra e desigualdade entre os casos analisados (apenas 5.1% de acidentes graves), foi desenvolvida uma metodologia com base numa estratégia de reamostragem e foram utilizadas 10 amostras geradas de forma aleatória e estratificada para a validação dos modelos. Durante a fase de modelação, foi analisado o efeito das características do veículo, como o peso, a cilindrada, a distância entre eixos e a idade do veículo. Para a análise do consumo de combustível e das emissões, foi aplicada a metodologia CORINAIR. Posteriormente, os dados das emissões foram modelados de forma a serem ajustados a regressões lineares. Finalmente, foi desenvolvido um indicador de análise integrada (denominado “SEG”) que proporciona um método de classificação para avaliar o desempenho do veículo ao nível da segurança rodoviária, consumos e emissões de poluentes.Face aos resultados obtidos, para os acidentes envolvendo um único veículo, o modelo de previsão do risco de gravidade identificou a idade e a cilindrada do veículo como estatisticamente significativas para a previsão de ocorrência de feridos graves e/ou mortos, ao nível de significância de 5%. A exatidão do modelo foi de 58.0% (desvio padrão (D.P.) 3.1). Para as colisões envolvendo dois veículos, ao prever a probabilidade de feridos graves e/ou mortos no veículo V1, a cilindrada do veículo oposto (veículo V2) aumentou o risco para os ocupantes do veículo V1, ao nível de significância de 10%. O modelo para prever o risco de gravidade no veículo V1 revelou um bom desempenho, com uma exatidão de 61.2% (D.P. 2.4). Ao prever a probabilidade de feridos graves e/ou mortos no veículo V2, a cilindrada do veículo V1 aumentou o risco para os ocupantes do veículo V2, ao nível de significância de 5%. O modelo para prever o risco de gravidade no veículo V2 também revelou um desempenho satisfatório, com uma exatidão de 40.5% (D.P. 2.1). Os resultados do indicador integrado SEG revelaram que os veículos mais recentes apresentam uma melhor classificação para os três domínios: segurança, consumo e emissões. Esta investigação demonstra que não existe conflito entre a componente da segurança, a eficiência energética e emissões relativamente ao desempenho dos veículos.

Review of state government motor vehicle resources

The LAC was requested to review state motor vehicle resources and make recommendations. It focused on three statewide objectives posed by the committees: (1) Determine if any wasteful duplication exists among state-owned vehicle maintenance facilities. (2) Identify any waste or inefficiency in the use of state owned vehicles. (3) Identify unnecessary or personal use of state-owned vehicles.

Improving energy efficiency in the road freight transport sector: the application of a vehicle approach

Several approaches can be used to analyse performance, energy consumption and CO2 emissions in freight transport. In this paper we define and apply a vehicle-oriented, bottom up survey approach, the so called ‘vehicle approach’, in contrast to a ‘supply chain approach’. The main objective of the approach is to assess the impacts of various freight transport operations on efficiency and energy use. We apply the approach, comparing official statistics on freight transport and energy efficiency in Britain and France. Results on freight intensity, vehicle utilisation, fuel use, fuel efficiency and CO2 intensity are compared for the two countries. The results indicate comparable levels of operational and fuel efficiency in road freight transport operations in the two countries. Issues that can be addressed with the vehicle approach include: the impacts of technology innovations and logistics decisions implemented in freight companies, and the quantification of the effect of policy measures on fuel use at the national level.

Internalising the external costs of light goods vehicle transport in Britain

Report produced as part of the Green Logistics project (EPSRC and Department for Transport funded). To what extent do the taxes paid by the light goods vehicles (LGVs) users in Britain cover their allocated infrastructural, environmental and congestion costs? This report is a continuation of a study on the internalisation of the external costs of heavy goods vehicle activity. Research undertaken jointly by the Transport Studies Group at University of Westminster and Logistics Research Centre at Heriot-Watt University has attempted to answer this question using official government transport statistics and monetary valuations for the external costs.

Internalising the external costs of light and heavy goods vehicle transport in London

Report produced as part of the Green Logistics project (EPSRC and Department for Transport funded). This report provides estimates of the total external costs of LGV and HGV operations in London. In 2006, total LGV and HGV activity imposed external costs of approximately £1.75-£1.8 billion using low, medium and high emission cost values. About 27 per cent of these costs were internalised by duties and taxes paid by LGV operators, compared with 26% in the case of HGVs. If congestion costs are excluded, taxes and duties paid by LGV operators are estimated to be 155% of LGVs' allocated infrastructural and environmental costs, compared with 85% in the case of HGVs. When using the medium emission cost values, LGVs accounted for 56% of these external costs in London and HGVs for 44%.

Internalising the external costs of light goods vehicle transport in Britain

To what extent do the taxes paid by the light goods vehicles (LGVs) users in Britain cover their allocated infrastructural, environmental and congestion costs? This report is a continuation of a study on the internalisation of the external costs of heavy goods vehicle activity. Research undertaken jointly by the Transport Studies Group at University of Westminster and Logistics Research Centre at Heriot-Watt University has attempted to answer this question using official government transport statistics and monetary valuations for the external costs.

Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Modelling and aerodynamic simulation of a vehicle and failure analysis of a laminated front fender

Master Thesis in Mechanical Engineering field of Maintenance and Production

Geostatistical Prediction of Ocean Outfall Plume Characteristics Based on an Autonomous Underwater Vehicle

Geostatistics has been successfully used to analyze and characterize the spatial variability of environmental properties. Besides giving estimated values at unsampled locations, it provides a measure of the accuracy of the estimate, which is a significant advantage over traditional methods used to assess pollution. In this work universal block kriging is novelty used to model and map the spatial distribution of salinity measurements gathered by an Autonomous Underwater Vehicle in a sea outfall monitoring campaign, with the aim of distinguishing the effluent plume from the receiving waters, characterizing its spatial variability in the vicinity of the discharge and estimating dilution. The results demonstrate that geostatistical methodology can provide good estimates of the dispersion of effluents that are very valuable in assessing the environmental impact and managing sea outfalls. Moreover, since accurate measurements of the plume’s dilution are rare, these studies might be very helpful in the future to validate dispersion models.