Structural analysis of a stone arch bridge under incremental railway static loading

This paper reports on the modelling strategies used to represent the structural behaviour of a masonry single-arch railway bridge. The bridge structural behaviour is simulated by a 3D finite element model, in which the different bridge components are represented by homogeneous materials. The material nonlinear behaviour is simulated using a Drucker-Prager model. The assigned material properties are based on material testing, performed in similar stone masonry structures. The load-carrying capacity is evaluated using a 3D Ansys model and with a RING model of the bridge under incremental static loading representing normal railway traffic with appropriate configurations on the bridge deck, and the results compared.Part of this work reports to research financially supported by Project POCI-01-0145-FEDER-007457—CONSTRUCT, Institute of R&D in Structures and Construction, funded by FEDER funds through COMPETE2020 and by national funds through Fundação para a Ciência e a Tecnologia (FCT). It also includes research supported by the FCT project PTDC/ECM-EST_1691/2012 – Experimental and Numerical Characterization of Structural Behaviour of Stone Masonry Arch Bridges under Railway Traffic Loading, Application to Existing Portuguese Bridges and by FCT PhD programme PD/BD/127812/2016 (iRail)

Flood Disaster Resilient Bridge Structures For Sustainable Bridge Management Systems

Extreme weather events are occurring at an increasing ferocity and frequency. Floods are the most comand damaging natural disaster. More than 4,400 occurrences of flood disasters have been reported globally between 1900 and 2016. As a result, around seven million people were killed and millions more were displaced. Climate impacts are expected to intensify weather related flooding events, and sea level rise expected worldwide will increase the risk of coastal disasters. Transportation infrastructure, vital to the economy and society of every country, is especially prone to the inland and coastal floods. Bridge structures are under the constant threat of these natural disasters. Superstructures can be washed away due to lateral forces generated by floodwater. Floodwater can also accelerate scouring around bridge piers, which often contributes to bridge failures. This research used the results of an extreme flood simulation conducted by the Center for Advanced Infrastructure Technology at the University of Mississippi. A flood inundation model was implemented for an extreme flood scenario at a floodplain site of Little Tallahatchie River in Northern Mississippi that featured surface transportation corridor sites and other infrastructure assets. Geospatial analysis of flood inundation mapping and simulation results shothat total flood inundation covered an area of 22.46 sq mi2 (58.16 sq km2) in the floodplain, where maximum floodwater depth reached up to 34.19 ft (10.42 m) within the inundation area. The results of the extreme flood simulation were used for assessing structural integrity of a bridge structure subject to lateral floodwater forces, with primary focus on the superstructure. A Three Dimensional-Finite Element model of US-51 Highway bridge, located in the floodplain site, was developed for flood impact analysis considering bridge girder-deck superstructure, bearings, pile caps and piers. The numerical results of finite element simulation shothat the bridge superstructure displaced 2.42 m under the lateral hydrodynamic force of floodwater. The dowel bars inserted at the bottom of each girder end through bearing to the top end of pile cap, failed in shear against lateral floodwater forces. This would lead to the failure of US-51 Highway bridge superstructure if an extreme flood event occurs in real life. A framework for structural integrity assessment of bridge structures is presented with Flood Resiliency Index. Recommendations for design enhancements and hardening of bridges are discussed for flood disaster resilience. An enhanced geospatial decision support system is recommended considering “vertical underclearance” criteria for bridge superstructure height above the channel and “flood probability” related to flood occurrence in 10, 50, 100, 500 and 1,000 years. These flood resilience parameters are missing from the traditional bridge management system (BMS) framework. Enhancing the current practice of BMS is proposed using optimization based prioritization of flood disaster vulnerable bridges, which considers vertical underclearance criteria, flood disaster risk probability and life cycle cost analysis. For this purpose, a Flood Vulnerability Rating (FVR) is proposed on a scale of 1 (catastrophic risk) to 6 (very low risk). The FVR scale was used for a case study of 270 bridges on major rivers in the state of Mississippi, which were analyzed using an optimization objective function to maximize benefits considering reconstruction/hardening costs and indirect benefits (cost avoidance from traffic disruption and economic loss related to bridge failure). Based on the present-worth life cycle analysis, total life cycle costs for the agency’s pre-planned bridge hardening for flood resilience was 59.3% less than the case of no hardening of the same bridge. This dissertation advances flood risk assessment and resilience management methodologies for transportation infrastructure in the United States and across the globe

Campaign Monitoring of Railroad Bridges in High-Speed Rail Shared Corridors using Wireless Smart Sensors

This report describes research results using wireless smart sensors to develop a cost-effective, practical, and portable structural health monitoring system for railroad bridges in North America. The system is designed for periodic inspection rather than as a permanent installation to enable campaign-style bridge response monitoring under in-service conditions. The system described herein measured bridge responses from a 310 feet long steel truss bridge using wireless sensors and calibrated a finite element (FE) model using the measured data to obtain global and local (at elements level) bridge responses under varied train loads and speeds. Additionally, this project developed a new simple beam model that can predict critical speeds and resonances based on train traffic properties. The results from this pilot project provide a technological foundation to develop campaign monitoring sensor technology as an important tool with which to manage railroad bridge assets.Financial support for this research was provided in part by the Federal Railroad Administration under Grant No. BAA-2010-1 No. DTFR53-13-C-00047, entitled “Campaign Monitoring of Railroad Bridges in High-Speed Rail Shared Corridors Using Wireless Smart Sensors” (Cameron Stuart, Program Manager).Ope

System identification of constructed civil engineering structures and uncertainty

Characterization of constructed civil engineering structures through system identification has gained increasing attention in recent years due to its tremendous potential for optimum infrastructure asset management and performance-based engineering. However, the lack of reliability in system identification, especially when applied to large-scale complex constructed systems, poses a major challenge for its widespread implementation. It is believed that this primarily stems from epistemic uncertainty associated with identification processes, due to unknown or less understood structural behaviors as well as the interaction of the system with its environment. The objective of this thesis is to investigate the effects of epistemic uncertainty on the reliability of identification and to develop solutions to recognize and mitigate these uncertainties. The research which was undertaken included laboratory and field investigation as the primary components. First, a cantilever beam with two test configurations was designed and constructed in the laboratory as a test bed. By comparing different identification scenarios, the impact of modeling uncertainty with epistemic mechanism on the field-calibrated analytical model was evaluated. Feasible techniques were developed to recognize and mitigate significant epistemic modeling uncertainty which controls the test-analysis discrepancy. In applications of system identification on real-life structural systems, the tempo, frequency and spatial incompatibility between detailed finite element model and information contained in test measurements often further complicates the identification process. It was demonstrated through the Henry Hudson Bridge that it was possible to characterize the fundamental behaviors of largescale complex structures by integrating heuristics and conventional techniques. Measurements to assess the adequacy of the field-calibrated models were proposed to ensure that significant epistemic modeling uncertainty was efficiently reduced and critical physical mechaisms was properly conceptualized.Ph.D., Structural Engineering -- Drexel University, 200