Performance Measures to Assess Resiliency and Efficiency of Transit Systems

Transit agencies are interested in assessing the short-, mid-, and long-term performance of infrastructure with the objective of enhancing resiliency and efficiency. This report addresses three distinct aspects of New Jersey’s Transit System: 1) resiliency of bridge infrastructure, 2) resiliency of public transit systems, and 3) efficiency of transit systems with an emphasis on paratransit service. This project proposed a conceptual framework to assess the performance and resiliency for bridge structures in a transit network before and after disasters utilizing structural health monitoring (SHM), finite element (FE) modeling and remote sensing using Interferometric Synthetic Aperture Radar (InSAR). The public transit systems in NY/NJ were analyzed based on their vulnerability, resiliency, and efficiency in recovery following a major natural disaster

Importance and applications of robotic and autonomous systems (RAS) in railway maintenance sector: a review

Maintenance, which is critical for safe, reliable, quality, and cost-effective service, plays a dominant role in the railway industry. Therefore, this paper examines the importance and applications of Robotic and Autonomous Systems (RAS) in railway maintenance. More than 70 research publications, which are either in practice or under investigation describing RAS developments in the railway maintenance, are analysed. It has been found that the majority of RAS developed are for rolling-stock maintenance, followed by railway track maintenance. Further, it has been found that there is growing interest and demand for robotics and autonomous systems in the railway maintenance sector, which is largely due to the increased competition, rapid expansion and ever-increasing expense

Measuring and modeling moisture environment in underground metro stations during commissioning stage: A case study

Due to the humid underground environment, underground metro stations often have internal condensation issues, especially during the commissioning and initial operation phases, and these issues will have a negative impact on the equipment operation and building life. This study aims to solve the issue by 1) identifying common areas with condensation risks based on on-site measurements and numerical simulation methods, and 2) proposing effective dehumidification solutions for the moisture control of stations. By on-site investigating the characteristics of the station’s moisture environment and numerical assessing the effects of two different dehumidification strategies, it has been found that 1) for Tianjin, during most times in summer, the air temperature of the station in the commissioning phase was maintained relatively stable, but with significantly changing humidity; 2) the relative humidity on the platforms was higher than 80% for almost 30% of the testing time, and the surface of the upper structure of platform doors having a high risk of condensation; 3) the dehumidification effect of industrial dehumidifiers was found to be better than that of increasing exhaust air volume. The authors hope that the research could aid the decision on dehumidification strategies and provide guidance for further moisture control in underground stations

Innovative Modelling Approaches for the Design, Operation and Control of Complex Energy Systems with Application to Underground Infrastructures

The ventilations systems play a key role in underground infrastructures for health and safety of occupants during normal operation as well as during accidents. Their performances are affected by selection of the optimal design, operation and control that is investigated by predicting air flow. The calculation of ventilation flows and their interaction with fires can be done with different modelling approaches that differ in the accuracy and in the required resources. The 3D computational fluid dynamics (CFD) tools approximate the flow behaviour with a great accuracy but they require high computational resources. The one dimensional (1D) models allow a compact description of the system with a low computational time but they are unsuitable to simulate thermal fluid-dynamic scenarios characterized by turbulence and gradients. Innovative tools are necessary in order to make the analysis and optimization of these systems possible and accurate in a reasonable time. This can be achieved both with appropriate numerical approaches to the full domain as the model order reduction techniques and with the domain decompositions methods as the multiscale physical decomposition technique. The reduced order mode techniques as the proper orthogonal decomposition (POD) is based on the snapshots method provides an optimal linear basis for the reconstruction of multidimensional data. This technique has been applied to non-dimensional equations in order to produce a reduced model not depending on the geometry, source terms, boundary conditions and initial conditions. This type of modelling is adapted to the optimization strategies of the design and operation allowing to explore several configuration in reduced times, and for the real time simulation in the control algorithms. The physical decomposition achieved through multiscale approaches uses the accuracy of the CFD code in the near field e.g. the region close to the fire source, and takes advantage of the low computational cost of the 1-D model in the region where gradients in the transversal direction are negligible. In last years, the multiscale approach has been proposed for the analysis of tunnel ventilation. Among the several CFD codes used in this field, the Fire Dynamic Simulator (FDS) is suitable for the multiscale modelling. This is an open source CFD package developed by NIST and VTT and presents the HVAC routine in which the conservation equations of mass, energy and momentum are implemented. Currently, the HVAC module does not allow one to consider heat and mass transfer, which significanltly limits the applications. For these reasons a multiscale simulator has been created through the fully integration of a 1D continuity, momentum, energy and mass transport equation in FDS modifying its source codes. The multiscale simulator thus obtained, is based on a direct coupling by means of a Dirichlet-Neumann strategy. At each 1-D-CFD interface, the exchange flow information occurs prescribing thermo-fluid dynamic boundary conditions. The 1-D mass transport equation computes the diffusion of the exhaust gas from the CFD domain and the relative concentration that is particularly interesting in the case of back layering of smoke. The global convergence of the boundary conditions at each 1-D-CFD interface has been analyzed by monitoring the evolution of thermo-fluid dynamic variables (temperature, velocity, pressure and concentration. The multiscale simulator is suitable for parametric and sensitivity studies of the design and the operation ventilation and fire safety systems. This new tool will be available for all the scientific community. In this thesis, Chapter 1 provides a general introduction to the role of the system ventilation in underground infrastructures and to the innovative modelling strategies proposed for these systems. Chapter 2 offers a description of the 1D network modelling, its fluid-dynamic application to the Frejus tunnel and its thermal application to ground heat exchangers. In Chapter 3, the proper orthogonal decomposition method is presented and its application to the optimal control of the sanitary ventilation for the Padornelo Tunnel is discussed. To demonstrate the applicability of POD method in other fields, boreholes thermal energy storage systems have been considered in same chapter. In particular, a multi-objective optimization strategy is applied to investigate the optimal design of these system and an optimization algorithm for the operation is proposed. Chapter 4 describes the multiscale approach and the relative simulator. The new open tool is used for modeling the ventilation system of the Monte Cuneo road tunnel in case of fire. Results show that in the case of the current configuration of the ventilation system, depending on the atmospheric conditions at portals, smoke might not be fully confined. Significant improvements in terms of safety conditions can be achieved through increase of in smoke extraction, which requires the installation of large dumpers and of deflectors on the jet fans. The developed tool shows to be particularly effective in such analysis, also concerning the evaluation of local conditions for people evacuation and fire-brigades operation

The effect of short-term changes in air pollution on respiratory and cardiovascular morbidity in Nicosia, Cyprus.

Presented at the 6th International Conference on Urban Air Quality, Limassol, March, 2007. Short-paper was submitted for peer-review and appears in proceedings of the conference.This study investigates the effect of daily changes in levels of PM10 on the daily volume of respiratory and cardiovascular admissions in Nicosia, Cyprus during 1995-2004. After controlling for long- (year and month) and short-term (day of the week) patterns as well as the effect of weather in Generalized Additive Poisson models, some positive associations were observed with all-cause and cause-specific admissions. Risk of hospitalization increased stepwise across quartiles of days with increasing levels of PM10 by 1.3% (-0.3, 2.8), 4.9% (3.3, 6.6), 5.6% (3.9, 7.3) as compared to days with the lowest concentrations. For every 10μg/m3 increase in daily average PM10 concentration, there was a 1.2% (-0.1%, 2.4%) increase in cardiovascular admissions. With respects to respiratory admissions, an effect was observed only in the warm season with a 1.8% (-0.22, 3.85) increase in admissions per 10μg/m3 increase in PM10. The effect on respiratory admissions seemed to be much stronger in women and, surprisingly, restricted to people of adult age

A Safety Risk Management Database for Metro Construction Project

This research focuses on the build of a new kind of database, named metro safety risk database(MSRD), which integrates the accident case library and engineering information library to provide more practical and valuable safety information for the project participants, so that we can take effective measures to prevent the tragic accident from happening again. The use of modern database technology with powerful project data processing capability has aroused the attention of the builders, but there are still many things have to be done to improve the database. Therefore, it is extremely important to analyses the database composition, the data acquisition process and the database functional design. In this research, an effective tool to improve on-site safety performance has been developed from historical data and project engineering information

Integrated Condition Assessment of Subway Networks Using Computer Vision and Nondestructive Evaluation Techniques

Subway networks play a key role in the smart mobility of millions of commuters in major metropolises. The facilities of these networks constantly deteriorate, which may compromise the integrity and durability of concrete structures. The ASCE 2017 Report Card revealed that the condition of public transit infrastructure in the U.S. is rated D-; hence a rehabilitation backlog of $90 billion is estimated to improve transit status to good conditions. Moreover, the Canadian Urban Transit Association (CUTA) reported 56.6 billion CAD in infrastructure needs for the period 2014-2018. The inspection and assessment of metro structures are predominantly conducted on the basis of Visual Inspection (VI) techniques, which are known to be time-consuming, costly, and qualitative in nature. The ultimate goal of this research is to develop an integrated condition assessment model for subway networks based on image processing, Artificial Intelligence (AI), and Non-Destructive Evaluation (NDE) techniques. Multiple image processing algorithms are created to enhance the crucial clues associated with RGB images and detect surface distresses. A complementary scheme is structured to channel the resulted information to Artificial Neural Networks (ANNs) and Regression Analysis (RA) techniques. The ANN model comprises sequential processors that automatically detect and quantify moisture marks (MM) defects. The RA model predicts spalling/scaling depth and simulates the de-facto scene by developing a hybrid algorithm and interactive 3D presentation. In addition, a comparative analysis is performed to select the most appropriate NDE technique for subway inspection. This technique is applied to probe the structure and measure the subsurface defects. Also, a novel model for the detection of air voids and water voids is proposed. The Fuzzy Inference System (FIS), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Monte Carlo Simulation (MCS) are streamlined through successive operations to create the integrated condition assessment model. To exemplify and validate the proposed methodology, a myriad of images and profiles are collected from Montréal Metro systems. The results ascertain the efficacy of the developed detection algorithms. The attained recall, precision, and accuracy for MM detection algorithm are 93.2%, 96.1%, and 91.5% respectively. Whereas for spalling detection algorithm, are 91.7%, 94.8%, and 89.3% respectively. The mean and standard deviation of error percentage in MM region extraction are 12.2% and 7.9% respectively. While for spalling region extraction, they account for 11% and 7.1% respectively. Subsequent to selecting the Ground Penetrating Radar (GPR) for subway inspection, attenuation maps are generated by both the amplitude analysis and image-based analysis. Thus, the deteriorated zones and corrosiveness indices for subway elements are automatically computed. The ANN and RA models are validated versus statistical tests and key performance metrics that indicated the average validity of 96% and 93% respectively. The air/water voids model is validated through coring samples, camera images, infrared thermography and 3D laser scanning techniques. The validation outcomes reflected a strong correlation between the different results. A sensitivity analysis is conducted showing the influence of the studied subway elements on the overall subway condition. The element condition index using neuro-fuzzy technique indicated different conditions in Montréal subway systems, ranging from sound concrete to very poor, represented by 74.8 and 35.1 respectively. The fuzzy consolidator extrapolated the subway condition index of 61.6, which reveals a fair condition for Montréal Metro network. This research developed an automated tool, expected to improve the quality of decision making, as it can assist transportation agencies in identifying critical deficiencies, and by focusing constrained funding on most deserving assets