Review of Elastic Analysis of Box Girder Bridges

The importance of thin-walled box girder bridges has attracted the attention of researchers since the last five decades. A lot of literature has dealt with the analytical formulations as well as experimental investigations. Field studies have increased tremendously in the last decade. So far the agreement between the analytical and experimental results has been excellent and, therefore, has made it possible to augment a limited number of experimental tests with hundreds of analytical studies. Highlights of research efforts in published literature regarding the analysis methods and experimental studies related to the elastic analysis of box girder bridges have been presented in this review. Subjects discussed include: (1) Thin –Walled Curved Beam Theory; (2) BEF/EBEF Method; (3) Finite Segment Method; (4) Folded Plate Method; (5) Finite Difference Method; (6) Energy Variational Principle; (7) Grillage Analogy and Space Frame Methods; (8) Finite Element Method; (9) Finite Strip Method; (10) Simplified/Miscellaneous Methods; (11) Experimental  Studies.http://dx.doi.org/10.4314/njt.v34i1.1

Steel-Concrete Composite Bridges: Design, Life Cycle Assessment, Maintenance, and Decision-Making

[EN] Steel-concrete composite bridges are used as an alternative to concrete bridges because of their ability to adapt their geometry to design constraints and the possibility of reusing some of the materials in the structure. In this review, we report the research carried out on the design, behavior, optimization, construction processes, maintenance, impact assessment, and decision-making techniques of composite bridges in order to arrive at a complete design approach. In addition to a qualitative analysis, a multivariate analysis is used to identify knowledge gaps related to bridge design and to detect trends in research. An additional objective is to make visible the gaps in the sustainable design of composite steel-concrete bridges, which allows us to focus on future research studies. *eresults of this work show how researchers have concentrated their studies on the preliminary design of bridges with a mainly economic approach, while at a global level, concern is directed towards the search for sustainable solutions. It is found that life cycle impact assessment and decision-making strategies allow bridge managers to improve decision-making, particularly at the end of the life cycle of composite bridges.This study was funded by the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (DIMALIFE Project BIA2017-85098-R).Martínez-Muñoz, D.; Martí Albiñana, JV.; Yepes, V. (2020). Steel-Concrete Composite Bridges: Design, Life Cycle Assessment, Maintenance, and Decision-Making. Advances in Civil Engineering. 2020:1-13. https://doi.org/10.1155/2020/8823370S113202

Reliability-Calibrated ANN-Based Load and Resistance Factor Load Rating for Steel Girder Bridges

This research aimed to develop a supplemental ANN-based tool to support the Nebraska Department of Transportation (NDOT) in optimizing bridge management investments when choosing between refined modeling, field testing, retrofitting, or bridge replacement. ANNs require an initial investment to collect data and train a network, but offer future benefits of speed and accessibility to engineers utilizing the trained ANN in the future. As the population of rural bridges in the Midwest approaching the end of their design service lives increases, Departments of Transportation are under mounting pressure to balance safety of the traveling public with fiscal constraints. While it is well-documented that standard code-based evaluation methods tend to conservatively overestimate live load distributions, alternate methods of capturing more accurate live load distributions, such as finite element modeling and diagnostic field testing, are not fiscally justified for broad implementation across bridge inventories. Meanwhile, ANNs trained using comprehensive, representative data are broadly applicable across the bridge population represented by the training data. The ANN tool developed in this research will allow NDOT engineers to predict critical girder distribution factors (GDFs), removing unnecessary conservativism from approximate AASHTO GDFs, potentially justifying load posting removal for existing bridges, and enabling more optimized design for new construction, using ten readily available parameters, such as bridge span, girder spacing, and deck thickness. A key drawback obstructing implementation of ANNs in bridge rating and design is the potential for unconservative ANN predictions. This research provides a framework to account for increased live load effect uncertainty incurred from neural network prediction errors by performing a reliability calibration philosophically consistent with AASHTO Load and Resistance Factor Rating. The study included detailed FEA for 174 simple span, steel girder bridges with concrete decks. Subsets of 163 and 161 bridges within these available cases comprised the ANN design and training datasets for critical moment and shear live load effects, respectively. The reliability calibration found that the ANN live load effect prediction error with mean absolute independent testing error of 3.65% could be safely accommodated by increasing the live load factor by less than 0.05. The study also demonstrates application of the neural network model validated with a diagnostic field test, including discussion of potential adjustments to account for noncomposite bridge capacity and Load Factor Rating instead of Load and Resistance Factor Rating. Advisor: Joshua S. Steelma

Wireless Monitoring Systems for Long-Term Reliability Assessment of Bridge Structures based on Compressed Sensing and Data-Driven Interrogation Methods.

The state of the nation’s highway bridges has garnered significant public attention due to large inventories of aging assets and insufficient funds for repair. Current management methods are based on visual inspections that have many known limitations including reliance on surface evidence of deterioration and subjectivity introduced by trained inspectors. To address the limitations of current inspection practice, structural health monitoring (SHM) systems can be used to provide quantitative measures of structural behavior and an objective basis for condition assessment. SHM systems are intended to be a cost effective monitoring technology that also automates the processing of data to characterize damage and provide decision information to asset managers. Unfortunately, this realization of SHM systems does not currently exist. In order for SHM to be realized as a decision support tool for bridge owners engaged in performance- and risk-based asset management, technological hurdles must still be overcome. This thesis focuses on advancing wireless SHM systems. An innovative wireless monitoring system was designed for permanent deployment on bridges in cold northern climates which pose an added challenge as the potential for solar harvesting is reduced and battery charging is slowed. First, efforts advancing energy efficient usage strategies for WSNs were made. With WSN energy consumption proportional to the amount of data transmitted, data reduction strategies are prioritized. A novel data compression paradigm termed compressed sensing is advanced for embedment in a wireless sensor microcontroller. In addition, fatigue monitoring algorithms are embedded for local data processing leading to dramatic data reductions. In the second part of the thesis, a radical top-down design strategy (in contrast to global vibration strategies) for a monitoring system is explored to target specific damage concerns of bridge owners. Data-driven algorithmic approaches are created for statistical performance characterization of long-term bridge response. Statistical process control and reliability index monitoring are advanced as a scalable and autonomous means of transforming data into information relevant to bridge risk management. Validation of the wireless monitoring system architecture is made using the Telegraph Road Bridge (Monroe, Michigan), a multi-girder short-span highway bridge that represents a major fraction of the U.S. national inventory.PhDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116749/1/ocosean_1.pd

Evaluation and Damage Detection of Highway Bridges with Distinct Vulnerabilities

Bridge failures over the past few decades have shown conventional bridge monitoring is insufficient to effectively evaluate the safety of this important piece of infrastructure. Therefore, new methods for bridge monitoring and special considerations in bridge design are needed to ensure the health of these structures as they continue to age and prevent the possibility of catastrophic collapses. The objective of this research is to explore new means for detecting damage in bridge members during normal operations that are both accurate and affordable at the same time. However, to make any damage detection method effective and efficient, the behavior of intact and damaged bridges needs to be investigated, preferably using simple analytical models. Therefore, to achieve the objective of this research, a two-fold investigation was performed. One was to study the bridge behavior subjected to various damage scenarios and identify possible failure mechanisms. Achieving this objective leads to a method for bridge evaluation after damage and determines its level of vulnerability to such damage; in other words, it defines the redundancy and reliability of the structure. The other was to develop an effective non-destructive method for damage detection based on the bridge behavior after the damage. vii Two types of bridges were selected and studied for this purpose, twin steel box girder bridges (TSBG) that are classified as fracture critical and prefabricated bridge systems containing cast-in-place joints. These bridges are designed with distinct vulnerabilities that make them susceptible to certain types of damages. The results of the current study confirmed that concrete deck failure is the dominant failure mode of the TSBG bridge after the occurrence of a fracture in one of the girders. Therefore, an improved simple and unified yield line analysis method was developed to determine the bridge deck capacity. An extensive analytical evaluation and availability of a simple model for load-carrying capacity developed in this study facilitated a comprehensive and coherent reliability approach to assess the safety of TSBG bridges after the complete fracture of one steel girder. Although the results of this research cannot readily be generalized for all TSBG bridges without further evaluation, this study shows that simply supported twin steel box girder bridges could indeed be safe and potentially removed from the fracture critical list. Moreover, the TSBG bridge dynamic analysis after damage showed that bridge frequencies are sufficiently sensitive for identifying partial or full-depth girder fracture in the simple span bridges. However, these significant damages may cause very small changes in the natural frequencies of continuous span bridges. The results show a significant change in the vibration mode shapes after damage in both simple and continuous span bridges. The mode shapes are sensitive enough to detect damage at the inflicted locations, in most cases providing better resolution when compared to the frequency changes. Investigation on the performance of the full-depth precast-prestressed voided slab bridge shows the vulnerability of such bridge decks to damage at the deck longitudinal joints. Using the FE analysis and load testing results, a new damage detection method for viii structural health monitoring of bridges with precast deck panels was also introduced. This method, applicable to all bridges with modular precast deck units, can effectively identify locations and significance of potential deck joint damage based on the measured changes in bridge response and model updating. A damage detection software tool was also developed in this case that is patent pending

Stainless Steel Corrugated Web Girders for Composite Road Bridges: Concept Evaluation and Flange Buckling Resistance

Achieving a sustainable bridge design requires careful consideration of economic viability and environmental impact over the entire lifespan of the structure. While stainless steel is recognized for its excellent life cycle performance, its high cost prevents it from being used to a larger extent in bridges. In this thesis work, a new solution is investigated to mitigate this issue. The new solution comprises the use of corrugated webs in stainless steel girders which is expected to result in reduced material consumption and cost. The work in this thesis focuses on two problem areas in this field. First, a study is performed to examine the competitiveness of the new concept in relation to conventional designs of steel-concrete composite road bridges. The second part of the work focuses on the problem of flange buckling in girders with corrugated webs. Previous research has shown that the design models developed\ua0for flange buckling resistance, including the one in EN 1993-1-5, frequently result in unsafe design. Furthermore, these models were developed for carbon steel and have not been updated for stainless steel. To explore the economic and environmental benefits of the new concept, two studies have been conducted. Firstly, three design solutions are examined on a case study bridge with three continuous spans. These design solutions include carbon steel flat web, stainless steel flat web, and stainless steel corrugated web girder bridges. A genetic algorithm is used to optimize each design solution in terms of weight. The three optimal solutions are then assessed in terms of investment costs, life cycle costs (LCC), and environmental life cycle impact. Secondly, two of the considered design solutions, namely carbon steel flat web and stainless-steel corrugated web girders, are employed to conduct multiple parametric studies using a simply supported reference bridge. For both design solutions, the effects of optimization targets on weight, investment cost, life cycle cost, and environmental life cycle impact are initially investigated. Following that, the focus is put on the life cycle cost (LCC) as an optimization target, and the impact of various design input parameters is investigated. These parameters include span length, girder depth, average daily traffic (ADT) with the associated number of heavy vehicles per slow lane (Nobs), and time intervals and expenses for maintenance activities. Furthermore, a sensitivity analysis is conducted to study the influence of the inflation rate and discount rate. The results indicate that the new concept offers considerable potential saving in weight, life cycle costs, and life cycle impacts for both simply supported and continuous bridges. The saving is more apparent with deeper girders, higher ADT, and more intense maintenance activities. Saving is also larger when inflation is high and discount rate is low.After studying the potential of corrugated web girders to reduce costs and environmental impacts in the case of employing stainless steel, a study of the flange buckling behaviour in duplex stainless-steel girders is conducted in this work. A parametric finite element model is developed and validated with tests conducted on beams made of carbon steel. The material is then changed to EN1.4162, and linear buckling analysis (LBA) and geometrically and materially nonlinear analysis with imperfections (GMNIA) are carried out on 410 girders with typical bridge girder dimensions. The results are compared to previously developed models for carbon steel, and a new buckling curve and flange local buckling design procedure for duplex stainless-steel girders with corrugated webs are proposed. The study shows that the new proposed design model generates more accurate estimates of flange buckling resistance than previous proposed models

System identification of bridge and vehicle based on their coupled vibration

Most current techniques used for system identification of bridges and vehicles are static-test-based methods. Methodologies that can use bridge dynamic responses or modal information are highly desirable and under development. This dissertation aims to develop new identification methodologies for bridge-vehicle systems using the bridge dynamic responses and modal information. A new bridge model updating method using the response surface method (RSM) was proposed in this dissertation. The RSM was used to design experiments in order to find out the relationships between the bridge responses and parameters to be updated. Results from numerical simulations and a field study show that the proposed methodology can effectively update bridge models with reasonable explanations available. A new methodology of identifying dynamic vehicle wheel loads was developed using only the measured bridge responses. The proposed methodology has demonstrated its ability to successfully identify dynamic vehicle loads by both numerical simulations and field tests conducted. This methodology can be used to improve the existing weigh-in-motion techniques which usually require slow vehicle movement or good road surface conditions. A new methodology of identifying the parameters of vehicles traveling on bridges was proposed in this dissertation. The proposed methodology uses the genetic algorithm to search the optimal vehicle parameter values in order to produce satisfactory agreements between the measured bridge responses and predicted bridge responses from the identified vehicle parameters. This methodology can also be used to improve the existing weigh-in-motion techniques with the ability to identify the static axle weights of vehicles. The dynamic impact factors for multi-girder concrete bridges were investigated in this dissertation. Relationships between the dynamic impact factor and bridge length, vehicle velocity, and road surface condition were investigated. Statistical properties of the impact factor were obtained. Simple expressions for dynamic impact factor were proposed, which can be used as modifications to the LRFD code regarding short bridges and bridges with poor road surface conditions

Structural health monitoring and bridge condition assessment

Thesis (Ph.D.) University of Alaska Fairbanks, 2016This research is mainly in the field of structural identification and model calibration, optimal sensor placement, and structural health monitoring application for large-scale structures. The ultimate goal of this study is to identify the structure behavior and evaluate the health condition by using structural health monitoring system. To achieve this goal, this research firstly established two fiber optic structural health monitoring systems for a two-span truss bridge and a five-span steel girder bridge. Secondly, this research examined the empirical mode decomposition (EMD) method’s application by using the portable accelerometer system for a long steel girder bridge, and identified the accelerometer number requirements for comprehensively record bridge modal frequencies and damping. Thirdly, it developed a multi-direction model updating method which can update the bridge model by using static and dynamic measurement. Finally, this research studied the optimal static strain sensor placement and established a new method for model parameter identification and damage detection.Chapter 1: Introduction -- Chapter 2: Structural Health Monitoring of the Klehini River Bridge -- Chapter 3: Ambient Loading and Modal Parameters for the Chulitna River Bridge -- Chapter 4: Multi-direction Bridge Model Updating using Static and Dynamic Measurement -- Chapter 5: Optimal Static Strain Sensor Placement for Bridge Model Parameter Identification by using Numerical Optimization Method -- Chapter 6: Conclusions and Future Work