Damage analysis of bridge structures using vibrational techniques

Much research is currently centred on the detection of damage in structures using vibrational data. The work presented here examined several areas of interest in support of a practical technique for identifying and locating damage within bridge structures using apparent changes in their vibrational response to known excitation. The proposed goals of such a technique included the need for the measurement system to be operated on site by a minimum number of staff and that the procedure should be as non-invasive to the bridge traffic-flow as possible. Initially the research investigated changes in the vibrational bending characteristics of two series of large-scale model bridge-beams in the laboratory and these included ordinary-reinforced and post-tensioned, prestressed designs. Each beam was progressively damaged at predetermined positions and its vibrational response to impact excitation was analysed. For the load-regime utilised the results suggested that the infuced damage manifested itself as a function of the span of a beam rather than a localised area. A power-law relating apparent damage with the applied loading and prestress levels was then proposed, together with a qualitative vibrational measure of structural damage. In parallel with the laboratory experiments a series of tests were undertaken at the sites of a number of highway bridges. The bridges selected had differing types of construction and geometric design including composite-concrete, concrete slab-and-beam, concrete-slab with supporting steel-troughing constructions together with regular-rectangular, skewed and heavily-skewed geometries. Initial investigations were made of the feasibility and reliability of various methods of structure excitation including traffic and impulse methods. It was found that localised impact using a sledge-hammer was ideal for the purposes of this work and that a cartridge `bolt-gun' could be used in some specific cases.

Activity streets as economic opportunity generators: Case study of the Langa Township, Cape Town, South Africa

The Republic of South Africa since the 1948 inception of Apartheid policies has experienced economic problems resulting from spatially dispersed growth. The election of President Mandela in 1994, however, eliminated the last forms of Apartheid as well as its discriminatory spatial, social, and economic policies, specially toward black Africans. In Cape Town, South Africa, several initiatives to restructure and to economically revitalize blighted and abandoned township communities, like Langa, have been instituted. One element of this strategy is the development of activity streets. The main questions asked in this study are whether activity streets are a feasible solution to the local economic problems left by the apartheid system and whether activity streets represent an economically sustainable approach to development. An analysis of a proposed activity street in Langa and its potential to generate jobs is undertaken. An Employment Generation Model used in this study shows that many of the businesses rely on the local purchasing power of the residents. Since the economic activities are mostly service oriented, a combination of manufacturing industries and institutionally implemented strategies within the township will have to be developed in order to generate sustainable employment. The result seem to indicate that, in Langa, the activity street depend very much on an increase in sales, pedestrian and vehicular traffic flow. ^

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

An automatic tuning strategy for local fuzzy logic ramp metering algorithm using Particle Swarm Optimization (PSO)

Freeway systems are becoming more congested each day. One contribution to freeway traffic congestion comprises platoons of on-ramp traffic merging into freeway mainlines. As a relatively low-cost countermeasure to the problem, ramp meters are being deployed in both directions of an 11-mile section of I-95 in Miami-Dade County, Florida. The local Fuzzy Logic (FL) ramp metering algorithm implemented in Seattle, Washington, has been selected for deployment. The FL ramp metering algorithm is powered by the Fuzzy Logic Controller (FLC). The FLC depends on a series of parameters that can significantly alter the behavior of the controller, thus affecting the performance of ramp meters. However, the most suitable values for these parameters are often difficult to determine, as they vary with current traffic conditions. Thus, for optimum performance, the parameter values must be fine-tuned. This research presents a new method of fine tuning the FLC parameters using Particle Swarm Optimization (PSO). PSO attempts to optimize several important parameters of the FLC. The objective function of the optimization model incorporates the METANET macroscopic traffic flow model to minimize delay time, subject to the constraints of reasonable ranges of ramp metering rates and FLC parameters. To further improve the performance, a short-term traffic forecasting module using a discrete Kalman filter was incorporated to predict the downstream freeway mainline occupancy. This helps to detect the presence of downstream bottlenecks. The CORSIM microscopic simulation model was selected as the platform to evaluate the performance of the proposed PSO tuning strategy. The ramp-metering algorithm incorporating the tuning strategy was implemented using CORSIM's run-time extension (RTE) and was tested on the aforementioned I-95 corridor. The performance of the FLC with PSO tuning was compared with the performance of the existing FLC without PSO tuning. The results show that the FLC with PSO tuning outperforms the existing FL metering, fixed-time metering, and existing conditions without metering in terms of total travel time savings, average speed, and system-wide throughput.

An improved framework for dynamic origin-destination (O-D) matrix estimation

This dissertation aims to improve the performance of existing assignment-based dynamic origin-destination (O-D) matrix estimation models to successfully apply Intelligent Transportation Systems (ITS) strategies for the purposes of traffic congestion relief and dynamic traffic assignment (DTA) in transportation network modeling. The methodology framework has two advantages over the existing assignment-based dynamic O-D matrix estimation models. First, it combines an initial O-D estimation model into the estimation process to provide a high confidence level of initial input for the dynamic O-D estimation model, which has the potential to improve the final estimation results and reduce the associated computation time. Second, the proposed methodology framework can automatically convert traffic volume deviation to traffic density deviation in the objective function under congested traffic conditions. Traffic density is a better indicator for traffic demand than traffic volume under congested traffic condition, thus the conversion can contribute to improving the estimation performance. The proposed method indicates a better performance than a typical assignment-based estimation model (Zhou et al., 2003) in several case studies. In the case study for I-95 in Miami-Dade County, Florida, the proposed method produces a good result in seven iterations, with a root mean square percentage error (RMSPE) of 0.010 for traffic volume and a RMSPE of 0.283 for speed. In contrast, Zhou's model requires 50 iterations to obtain a RMSPE of 0.023 for volume and a RMSPE of 0.285 for speed. In the case study for Jacksonville, Florida, the proposed method reaches a convergent solution in 16 iterations with a RMSPE of 0.045 for volume and a RMSPE of 0.110 for speed, while Zhou's model needs 10 iterations to obtain the best solution, with a RMSPE of 0.168 for volume and a RMSPE of 0.179 for speed. The successful application of the proposed methodology framework to real road networks demonstrates its ability to provide results both with satisfactory accuracy and within a reasonable time, thus establishing its potential usefulness to support dynamic traffic assignment modeling, ITS systems, and other strategies.

Optimization of waiting time at toll plazas

Toll plazas have several toll payment types such as manual, automatic coin machines, electronic and mixed lanes. In places with high traffic flow, the presence of toll plaza causes a lot of traffic congestion; this creates a bottleneck for the traffic flow, unless the correct mix of payment types is in operation. The objective of this research is to determine the optimal lane configuration for the mix of the methods of payment so that the waiting time in the queue at the toll plaza is minimized. A queuing model representing the toll plaza system and a nonlinear integer program have been developed to determine the optimal mix. The numerical results show that the waiting time can be decreased at the toll plaza by changing the lane configuration. For the case study developed an improvement in the waiting time as high as 96.37 percent was noticed during the morning peak hour.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Effect of wind on operating cost based cruise speed reduction for delay absorption

En route speed reduction can be used for air traffic flow management (ATFM), e.g., delaying aircraft while airborne or realizing metering at an arrival fix. In previous publications, the authors identified the flight conditions that maximize the airborne delay without incurring extra fuel consumption with respect to the nominal (not delayed) flight. In this paper, the effect of wind on this strategy is studied, and the sensitivity to wind forecast errors is also assessed. A case study done in Chicago O’Hare airport (ORD) is presented, showing that wind has a significant effect on the airborne delay that can be realized and that, in some cases, even tailwinds might lead to an increase in the maximum amount of airborne delay. The values of airborne delay are representative enough to suggest that this speed reduction technique might be useful in a real operational scenario. Moreover, the speed reduction strategy is more robust than nominal operations against fuel consumption in the presence of wind forecast uncertainties.

Improvement of Longitudinal Joints in Asphalt Pavement, HR-215, Construction Report, 1981

One significant benefit of asphalt concrete pavement construction is that it may be opened to traffic within one hour after being laid. Therefore, road closure and detour are not necessary, but only temporary lane closure and control of traffic. This one lane construction, even though desirable in regard to maintaining traffic flow, does pose an additional problem. The longitudinal joint at centerline often becomes a maintenance problem. The objective of this research project is to identify construction procedures that will provide an improved centerline joint.

DEVELOPMENT OF A DECISION/DEPLOYMENT SUPPORT TOOL FOR VARIABLE SPEED LIMITS IN RECURRENT CONGESTION

Traffic demand increases are pushing aging ground transportation infrastructures to their theoretical capacity. The result of this demand is traffic bottlenecks that are a major cause of delay on urban freeways. In addition, the queues associated with those bottlenecks increase the probability of a crash while adversely affecting environmental measures such as emissions and fuel consumption. With limited resources available for network expansion, traffic professionals have developed active traffic management systems (ATMS) in an attempt to mitigate the negative consequences of traffic bottlenecks. Among these ATMS strategies, variable speed limits (VSL) and ramp metering (RM) have been gaining international interests for their potential to improve safety, mobility, and environmental measures at freeway bottlenecks. Though previous studies have shown the tremendous potential of variable speed limit (VSL) and VSL paired with ramp metering (VSLRM) control, little guidance has been developed to assist decision makers in the planning phase of a congestion mitigation project that is considering VSL or VSLRM control. To address this need, this study has developed a comprehensive decision/deployment support tool for the application of VSL and VSLRM control in recurrently congested environments. The decision tool will assist practitioners in deciding the most appropriate control strategy at a candidate site, which candidate sites have the most potential to benefit from the suggested control strategy, and how to most effectively design the field deployment of the suggested control strategy at each implementation site. To do so, the tool is comprised of three key modules, (1) Decision Module, (2) Benefits Module, and (3) Deployment Guidelines Module. Each module uses commonly known traffic flow and geometric parameters as inputs to statistical models and empirically based procedures to provide guidance on the application of VSL and VSLRM at each candidate site. These models and procedures were developed from the outputs of simulated experiments, calibrated with field data. To demonstrate the application of the tool, a list of real-world candidate sites were selected from the Maryland State Highway Administration Mobility Report. Here, field data from each candidate site was input into the tool to illustrate the step-by-step process required for efficient planning of VSL or VSLRM control. The output of the tool includes the suggested control system at each site, a ranking of the sites based on the expected benefit-to-cost ratio, and guidelines on how to deploy the VSL signs, ramp meters, and detectors at the deployment site(s). This research has the potential to assist traffic engineers in the planning of VSL and VSLRM control, thus enhancing the procedure for allocating limited resources for mobility and safety improvements on highways plagued by recurrent congestion.

Mapeamento acústico como ferramenta para predição de ruído urbano na área de influência do estádio Arena das Dunas, Natal/ RN

The Noise Pollution causes degradation in the quality of the environment and presents itself as one of the most common environmental problems in the big cities. An Urban environment present scenario and their complex acoustic study need to consider the contribution of various noise sources. Accordingly to computational models through mapping and prediction of acoustic scene become important, because they enable the realization of calculations, analyzes and reports, allowing the interpretation of satisfactory results. The study neighborhood is the neighborhood of Lagoa Nova, a central area of the city of Natal, which will undergo major changes in urban space due to urban mobility projects planned for the area around the stadium and the consequent changes of urban form and traffic. Thus, this study aims to evaluate the noise impact caused by road and morphological changes around the stadium Arena das Dunas in the neighborhood of Lagoa Nova, through on-site measurements and mapping using the computational model SoundPLAN year 2012 and the scenario evolution acoustic for the year 2017. For this analysis was the construction of the first acoustic mapping based on current diagnostic acoustic neighborhood, physical mapping, classified vehicle count and measurement of sound pressure level, and to build the prediction of noise were observed for the area study the modifications provided for traffic, urban form and mobility work. In this study, it is concluded that the sound pressure levels of the year in 2012 and 2017 extrapolate current legislation. For the prediction of noise were numerous changes in the acoustic scene, in which the works of urban mobility provided will improve traffic flow, thus reduce the sound pressure level where interventions are expected

The study of the sedimentation mechanism in channels under the impact of tidal currents

The purpose of this research is to study sedimentation mechanism by mathematical modeling in access channels which are affected by tidal currents. The most important factor for recognizing sedimentation process in every water environment is the flow pattern of that environment. It is noteworthy that the flow pattern is affected by the geometry and the shape of the environment as well as the type of existing affects in area. The area under the study in this thesis is located in Bushehr Gulf and the access channels (inner and outer). The study utilizes the hydrodynamic modeling with unstructured triangular and non-overlapping grids, using the finite volume, From method analysis in two scale sizes: large scale (200 m to 7.5km) and small scale (50m to 7.5km) in two different time durations of 15 days and 3.5 days to obtain the flow patterns. The 2D governing equations used in the model are the Depth-Averaged Shallow Water Equations. Turbulence Modeling is required to calculate the Eddy Viscosity Coefficient using the Smagorinsky Model with coefficient of 0.3. In addition to the flow modeling in two different scales and the use of the data of 3.5 day tidal current modeling have been considered to study the effects of the sediments equilibrium in the area and the channels. This model is capable of covering the area which is being settled and eroded and to identify the effects of tidal current of these processes. The required data of the above mentioned models such as current and sediments data have been obtained by the measurements in Bushehr Gulf and the access channels which was one of the PSO's (Port and Shipping Organization) project-titled, "The Sedimentation Modeling in Bushehr Port" in 1379. Hydrographic data have been obtained from Admiralty maps (2003) and Cartography Organization (1378, 1379). The results of the modeling includes: cross shore currents in northern and north western coasts of Bushehr Gulf during the neap tide and also the same current in northern and north eastern coasts of the Gulf during the spring tide. These currents wash and carry fine particles (silt, clay, and mud) from the coastal bed of which are generally made of mud and clay with some silts. In this regard, the role of sediments in the islands of this area and the islands made of depot of dredged sediments should not be ignored. The result of using 3.5 day modeling is that the cross channels currents leads to settlement places in inner and outer channels in tidal period. In neap tide the current enters the channel from upside bend of the two channels and outer channel. Then it crosses the channel oblique in some places of the outer channel. Also the oblique currents or even almost perpendicular current from up slope of inner channel between No. 15 and No. 18 buoys interact between the parallel currents in the channel and made secondary oblique currents which exit as a down-slope current in the channel and causes deposit of sediments as well as settling the suspended sediments carried by these currents. In addition in outer channel the speed of parallel currents in the bend of the channel which is naturally deeper increases. Therefore, it leads to erosion and suspension of sediments in this area. The speed of suspended sediments carried by this current which is parallel to the channel axis decreases when they pass through the shallower part of the channel where it is in the buoys No.7 and 8 to 5 and 6 are located. Therefore, the suspended sediment settles and because of this process these places will be even shallower. Furthermore, the passing of oblique upstream leads to settlement of the sediments in the up-slope and has an additional effect on the process of decreasing the depth of these locations. On the contrary, in the down-slope channel, as the results of sediments and current modeling indicates the speed of current increases and the currents make the particles of down-slope channel suspended and be carried away. Thus, in a vast area of downstream of both channels, the sediments have settled. At the end of the neap tide, the process along with circulations in this area produces eddies which causes sedimentation in the area. During spring some parts of this active location for sedimentation will enter both channels in a reverse process. The above mentioned processes and the places of sedimentation and erosion in inner and outer channels are validated by the sediments equilibrium modeling. This model will be able to estimate the suspended, bed load and the boundary layer thickness in each point of both channels and in the modeled area.

Mejoras en los proyectos de simulación de flujo de tráfico en tiempo acelerado

Se han desarrollado cuatro mejoras en los proyectos de simulación de flujo de tráfico en tiempo acelerado. Los proyectos [1] y [2] realizan una simulación de flujo de tráfico en un CAS, Maxima, y usan Java, para realizar la GUI. Ambos usan Jacomax para realizar la comunicación Java-Maxima. La primera ha sido implementar un algoritmo Dijkstra difuso en [2] que simule (de forma más real que el algoritmo Dijkstra), el camino que sigue un vehículo entre un origen y un destino, dentro de un mapa (un grafo) que representa una zona de Málaga. Además, se ha personalizado el grafo inicial asociando uno ponderado a cada vehículo, en el cual, las aristas (las calles) tienen un peso calculado con una uniforme o una normal. Para ganar en rendimiento en [1] y [2], se ha permitido al usuario decidir cada cuantos pasos en Maxima se comunica con Java, eliminando así muchas comunicaciones que resultaban lentas. Además, se ha creado un programa con Java, el cual crea un paquete Maxima con las funciones de distribución, densidad, masa, variables aleatorias, que el usuario desee, dando la posibilidad de elegir entre las más usuales ya implementadas. Este paquete puede ser cargado en [1] y [2] permitiendo al usuario elegir la función de distribución que más se asemeje al fenómeno que se desea simular. La última ha sido conseguir que funcionen los proyectos [1] y [2] en una máquina Mac.

Un modelo de predicción de tráfico en la ciudad de Ambato

Este artículo contiene el estudio inicial de un modelo de predicción de tráfico, que intenta mostrar cómo puede complementarse la toma de decisiones que afecten a la ciudad a través de una buena planificación vial. Esto permitirá dar alternativas posibles de solución mediante la predicción de flujos de tráfico y determinando las intersecciones de mayor influencia dentro de la red vial, lo que por consecuencia reduciría costes en tiempo, combustible, contaminación, etc., obteniendo así una herramienta de ayuda en la toma de decisiones respecto del tráfico. Específicamente, se utiliza modelos dinámicos lineales para predecir el tráfico en distintos puntos de una ciudad y, en consecuencia, pronosticar su eventual saturación. Se puede así predecir puntos de la ciudad en la que es necesario actuar para aliviar los problemas de tráfico antes de que éstos lleguen a manifestarse.

Collaborative Management of Intermodal Mobility

Part 21: Mobility and Logistics