Relevant bibliographies by topics / Structural damage to bridges

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Structural damage to bridges'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Structural damage to bridges"

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Murakami, Keisuke, Yoshiko Sakamoto, and Tetsuya Nonaka. "ANALYTICAL INVESTIGATION OF SLAB BRIDGE DAMAGES CAUSED BY TSUNAMI FLOW." Coastal Engineering Proceedings 1, no. 33 (October 25, 2012): 42. http://dx.doi.org/10.9753/icce.v33.structures.42.

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Tsunami caused by Tohoku earthquake in 2011 had brought fatal damages on many kinds of infrastructures such as ports, roads, bridges, lifelines and other important structures. Among those damages, we have found many bridges whose superstructure was flooded away by tsunami flow. This study proposes a composite simulation method in order to investigate the damage on bridges caused by tsunami action. The numerical method consists of a hydraulic analysis and a structural one. The proposed method is applied to the damaged bridge whose superstructure was flooded away by Tohoku earthquake tsunami. Based on the structural analysis, this study discusses the mechanism of damage caused by tsunami flow. Furthermore, this study confirms the validity of hydraulic analysis through physical experiment.
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Kawashima, Kazuhiko, and Ian Buckle. "Structural Performance of Bridges in the Tohoku-Oki Earthquake." Earthquake Spectra 29, no. 1_suppl (March 2013): 315–38. http://dx.doi.org/10.1193/1.4000129.

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Including minor nonstructural damage, over 1,500 highway bridges and numerous rail bridges were damaged during the Tohoku-oki earthquake of 11 March 2011. The causes of this damage can be broadly classified in two categories: ground shaking, including ground failure (liquefaction); and tsunami inundation. Damage included span unseating, column shear and flexural failures, approach fill erosion, liquefaction induced settlement, and failed steel and elastomeric bearings. Since many bridges in the north Miyagi-ken and south Iwate-ken suffered extensive damage during the 1978 Miyagi-ken-oki earthquake, bridge performance during the 2011 earthquake is of particular interest. Advances in design and retrofit may be assessed by looking at the performance of bridges designed to post-1990 codes and those retrofitted since the Kobe earthquake in 1995. In both categories, bridge damage due to ground shaking was minor, thus validating the provisions in the post-1990 codes and the Japan bridge retrofit program. Damage that did occur due to ground shaking was mainly to bridges not yet retrofitted or only partly so. Tsunami-related damage included complete loss of span and erosion of backfills. However, many bridges survived, despite being totally submerged, and their performance gives insight into the potential design of tsunami-resistant bridges.
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Svendsen, Bjørn T., Gunnstein T. Frøseth, and Anders Rönnquist. "Damage Detection Applied to a Full-Scale Steel Bridge Using Temporal Moments." Shock and Vibration 2020 (February 27, 2020): 1–16. http://dx.doi.org/10.1155/2020/3083752.

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The most common damages in existing highway and railway steel bridges are related to fatigue and are, as reported in the literature, found in the structural system of the bridge deck. This paper proposes a methodology for detecting damaged joint connections in existing steel bridges to improve the quality of bridge inspections. The methodology combines the use of temporal moments from response measurements with an appropriate instrumentation setup. Damaged joint connections are identified by comparing statistical parameters based on temporal moments to a baseline, where the baseline data are established from statistical parameters evaluated for all considered joint connections. Localization of damaged joint connections is performed by utilizing the instrumentation setup. The feasibility of the proposed methodology is demonstrated through an experimental study on a full-scale steel riveted truss bridge with two known damages below the bridge deck, where both damages are identified and localized. The proposed methodology can improve the identification of critical structural damage during bridge inspections and is applicable to open-deck steel bridges.
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Fitriani, Heni, M. Ade Surya Pratama, Yakni Idris, and Gunawan Tanzil. "Determination of prioritization for maintenance of the upper structure of truss bridge." MATEC Web of Conferences 276 (2019): 01036. http://dx.doi.org/10.1051/matecconf/201927601036.

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Bridge maintenance is one of the major issues of infrastructure problems. Deterioration of a bridge’s structure will continuously increase without proper maintenance. This condition will adversely affect the service life of a bridge. Moreover, the damage will also have a direct impact on structural and functional failure of the bridge. This paper aims at identifying the damages of truss bridges and determining the most significant criteria and sub-criteria used in prioritizing bridge maintenance. Analytical Hierarchy Process (AHP) was used to assess the most important criteria that give significant weight to bridge maintenance analysis. The objects of research were nine truss bridges with a wide range of types and levels of damage. It was found that there were approximately 900 m' of components damaged at the railing of Baruga Bridge and 227 m' truss damages due to poor quality of the galvanized paint. Furthermore, based on the analysis, the most significant criteria were the level of damage (27.6%), the technical aspects (25.7%), the finance (21%), the vehicle load (13.6%) and the resources (12%). The results of this research showed important findings in determining the priority scales for bridge repair and maintenance systems.
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Hu, Zhi Jian, and Chao Liu. "Blast Loads on Concrete Bridges." Advanced Materials Research 217-218 (March 2011): 445–50. http://dx.doi.org/10.4028/www.scientific.net/amr.217-218.445.

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Nowadays few current studies on blast effects are executed with real bridge structures for economic and social reasons. This paper analyzes the blast loadings on concrete bridges and offers five characteristics: uncertainty, significant structural response, mechanic differences, rapid overpressure decay, and confinement effects. Then with the further study for blast loads fundamentals and real bridge inspection, the damage forms for concrete bridges under blast loadings have been obtained, i.e. localized damage are the main structural damages and fragmentation loads can be neglected when explosions detonated above deck. Furthermore, due to the collapse or fallen of the structural components or segments secondary damages, like collisions and restraining blocks destruction, must be kept an eye on.
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Xiao, Xiang, Yu Yan, and Zhijian Hu. "Effect of random structural damage on vehicle–track–bridge coupled response." International Journal of Damage Mechanics 29, no. 1 (June 27, 2019): 103–25. http://dx.doi.org/10.1177/1056789519860203.

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With the rapid development of high-speed railway construction around the world, the structural damage problem of tracks and bridges has attracted more and more attention. In this paper, considering the random structural damages of tracks and bridges, an efficient computational procedure is developed based on the probability density evolution method to systematically investigate the random characteristics of the dynamic responses varying with the damages in vehicle–track–bridge time-dependent systems. Firstly, a vehicle–track–bridge dynamic model with random structural damage parameters is established, and the random motion equations are derived based on the generalized energy principle. Then, the probability density evolution equation for each random response is established and the random feature is investigated by the proposed computational procedure. Finally, the representative numerical examples are applied and some conclusions for the effects of the random structural damages on the dynamic responses of the vehicle–track–bridge systems are presented.
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Zhang, Yunkai, Qingli Xie, Guohua Li, and Yali Liu. "Multi-Damage Identification of Multi-Span Bridges Based on Influence Lines." Coatings 11, no. 8 (July 28, 2021): 905. http://dx.doi.org/10.3390/coatings11080905.

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The framework security of a bridge is essential as a critical component of traffic engineering. Even though the bridge structure is damaged to various degrees due to various reasons, the bridge will be wrecked when the damage reaches a particular level, suggesting a negative influence on people’s lives. Based on the current situation and existing problems of structural damage identification of bridges, a structural damage identification technology of continuous beam bridges based on deflection influence lines is proposed in this paper in order to keep track of and always detect broken bridge elements, thereby extending the bridge’s service life and reducing the risk of catastrophic accidents. The line function expression of deflection impact on a multi-span continuous beam bridge was first obtained using Graphic Multiplication theory. From the theoretical level, the influence line function of the continuous beam bridge without extensive damage was computed, and a graph was generated. The photographs of the DIL as well as the first and second derivatives, the deflection influence line distinction and its first and second derivatives, and the DIL distinction and its first and second derivatives of a continuous beam bridge in a single position and multi-position destruction were fitted in this paper. Finally, after comparing multiple work conditions and multiple measuring points, it was found that the first derivative of deflection influence line difference had the best damage identification effect. The design was completed and tested, which had verified the feasibility of this theory.
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Chun, Qing, and Lan Xiang Sun. "Structural Performance Analysis and Repair Design of Wenxing Lounge Bridge." Advanced Materials Research 778 (September 2013): 1014–19. http://dx.doi.org/10.4028/www.scientific.net/amr.778.1014.

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Lounge bridges in Taishun are a special type of Chinese traditional timber structure. Wenxing Lounge Bridge is a famous bridge of them. The analysis of structural performance and damages for Wenxing Lounge Bridge is the foundation of its repair and reinforcement. The performance degradation of wood material and the action of strong external force and the effect of environmental changing and the factor of unfavorable human-activity have continuously accelerated the damage of the bridge. After visiting local craftsmen, building technics and detailed conformations of the bridge are researched. The FEM analyses on the structure before damaged and after damaged are carried out respectively. Damages reasons of the bridge are then generally analyzed and repair design of the bridge is also presented.
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Buckle, Ian, Matias Hube, Genda Chen, Wen-Huei Yen, and Juan Arias. "Structural Performance of Bridges in the Offshore Maule Earthquake of 27 February 2010." Earthquake Spectra 28, no. 1_suppl1 (June 2012): 533–52. http://dx.doi.org/10.1193/1.4000031.

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Of the nearly 12,000 highway bridges in Chile, approximately 300 were damaged in this earthquake, including 20 with collapsed spans. Typical failure modes include damage to connections between super- and substructures, unseating of spans in skewed bridges due to in-plane rotation, and unseated spans with some column damage due to permanent ground movement. Unusual failure modes include unseating of spans in straight bridges due to in-plane rotation, plate girder rupture due to longitudinal forces, scour and pier damage due to tsunami action, and collapse of a historic masonry bridge. The most common damage mode was the failure of super-to-substructure connections (shear keys, steel stoppers, and seismic bars), which is the most likely reason for the low incidence of column damage. Whereas the fuse-like behavior of these components is believed to have protected the columns, the lack of adequate seat widths led to the collapse, or imminent collapse, of many superstructures.
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Pipinato, Alessio, Carlo Pellegrino, and Claudio Modena. "Structural Analysis of Historical Metal Bridges in Italy." Advanced Materials Research 133-134 (October 2010): 525–30. http://dx.doi.org/10.4028/www.scientific.net/amr.133-134.525.

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In this paper different studies on the structural analysis, the fatigue assessment and the damage evaluation of metal bridges are reported. These work examples are related to a widespread amount of works conducted since the first of 2000 in the research area of bridge design and assessment. The most part of these researches are related to railway bridges and historical metal bridges, because of their particular vulnerability to damage decay during their life. The main research topics are presented and discussed.
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Dissertations / Theses on the topic "Structural damage to bridges"

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Neild, S. A. "Using non-linear vibration techniques to detect damage in concrete bridges." Thesis, University of Oxford, 2001. http://ora.ox.ac.uk/objects/uuid:f116c6f1-3179-463b-9ff6-b83e48a71aaf.

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There has been much work published in recent years on the use of vibration characteristics to detect damage in bridges. Almost all of this work has been based on the assumption that the vibration is linear, i.e. the natural frequencies are not dependent on the amplitude of oscillation. The aim of the work presented here was to investigate the possibility of using changes in the non-linear vibration characteristics to detect damage in reinforced concrete bridges. These changes in the non-linear vibration characteristics were studied by conducting impact excitation vibration tests o reinforced concrete beams. The non-linearities were detected by examining the changes in fundamental frequency over time (and hence over amplitude of vibration). Several time-frequency distribution estimation tools are discussed including the discrete Fourier Transform moving window, the auto-regressive model moving window, harmonic wavelets and examples of the Cohen class of bilinear time-frequency distributions. A detailed investigation into these various distribution predictors was conducted to assess which is most suitable for analysing the vibration signals to detect changes in frequency with time. To understand the non-linearities in the vibration characteristics, a time-stepping model was described. The model is capable of including damage in the form of a moment-rotation relationship over the cracked region. It was validated for linear vibrations against theoretical values and the representation of a non-linear mechanism using the model was compared with experimental data. Static load tests were also conducted on the beams at various damage levels. They involved the use of vibrating wire strain gauges to investigate the moment-rotation behaviour over the cracked region. Several possible non-linear crack mechanisms are discussed and two of them are assessed using the vibration and the static load tests. Future experimental work is proposed to study the possible non-linear mechanisms further. The beam tests demonstrated that there is a change in non-linear vibration behaviour with damage. The change is greatest at low levels of damage and after the beam has been loaded to 30% of the failure load in three-point loading there is a reversal in the trend and a slight reduction in non-linearity with further damage.
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Neves, Cláudia. "Structural Health Monitoring of Bridges : Model-free damage detection method using Machine Learning." Licentiate thesis, KTH, Bro- och stålbyggnad, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-205616.

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This is probably the most appropriate time for the development of robust and reliable structural damage detection systems as aging civil engineering structures, such as bridges, are being used past their life expectancy and beyond their original design loads. Often, when a significant damage to the structure is discovered, the deterioration has already progressed far and required repair is substantial. This is both expensive and has negative impact on the environment and traffic during replacement. For the exposed reasons the demand for efficient Structural Health Monitoring techniques is currently extremely high. This licentiate thesis presents a two-stage model-free damage detection approach based on Machine Learning. The method is applied to data gathered in a numerical experiment using a three-dimensional finite element model of a railway bridge. The initial step in this study consists in collecting the structural dynamic response that is simulated during the passage of a train, considering the bridge in both healthy and damaged conditions. The first stage of the proposed algorithm consists in the design and unsupervised training of Artificial Neural Networks that, provided with input composed of measured accelerations in previous instants, are capable of predicting future output acceleration. In the second stage the prediction errors are used to fit a Gaussian Process that enables to perform a statistical analysis of the distribution of errors. Subsequently, the concept of Damage Index is introduced and the probabilities associated with false diagnosis are studied. Following the former steps Receiver Operating Characteristic curves are generated and the threshold of the detection system can be adjusted according to the trade-off between errors. Lastly, using the Bayes’ Theorem, a simplified method for the calculation of the expected cost of the strategy is proposed and exemplified.

QC 20170420

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Brown, Graham. "A study of the effect of damage on the dynamic response of masonry arch bridges." Thesis, University of Reading, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246045.

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Gonzalez, Ignacio. "Application of monitoring to dynamic characterization and damage detection in bridges." Doctoral thesis, KTH, Bro- och stålbyggnad, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-150804.

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The field of bridge monitoring is one of rapid development. Advances in sensor technologies, in data communication and processing algorithms all affect the possibilities of Structural Monitoring in Bridges. Bridges are a very critical part of a country’s infrastructure, they are expensive to build and maintain, and many uncertainties surround important factors determining their serviceability and deterioration state. As such, bridges are good candidates for monitoring. Monitoring can extend the service life and avoid or postpone replacement, repair or strengthening works. The amount of resources saved, both to the owner and the users, by reducing the amount of non-operational time can easily justify the extra investment in monitoring. This thesis consists of an extended summary and five appended papers. The thesis presents advances in sensor technology, damage identification algorithms, Bridge Weigh-In-Motion systems, and other techniques used in bridge monitoring. Four case studies are presented. In the first paper, a fully operational Bridge Weigh-In-Motion system is developed and deployed in a steel railway bridge. The gathered data was studied to obtain a characterization of the site specific traffic. In the second paper, the seasonal variability of a ballasted railway bridge is studied and characterized in its natural variability. In the third, the non-linear characteristic of a ballasted railway bridge is studied and described stochastically. In the fourth, a novel damage detection algorithm based in Bridge Weigh-In-Motion data and machine learning algorithms is presented and tested on a numerical experiment. In the fifth, a bridge and traffic monitoring system is implemented in a suspension bridge to study the cause of unexpected wear in the bridge bearings. Some of the major scientific contributions of this work are: 1) the development of a B-WIM for railway traffic capable of estimating the load on individual axles; 2) the characterization of in-situ measured railway traffic in Stockholm, with axle weights and train configuration; 3) the quantification of a hitherto unreported environmental behaviour in ballasted bridges and possible mechanisms for its explanation (this behaviour was shown to be of great importance for monitoring of bridges located in colder climate) 4) the statistical quantification of the nonlinearities of a railway bridge and its yearly variations and 5) the integration of B-WIM data into damage detection techniques.

QC 20140910

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Li, Zhe. "Soft computing for damage prediction and cause identification in civil infrastructure systems." Diss., Connect to online resource - MSU authorized users, 2008.

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Thesis (Ph.D.)--Michigan State University. Dept. of Civil and Environmental Engineering, 2008.
Title from PDF t.p. (viewed on July 21, 2009) Includes bibliographical references (p. 218-225). Also issued in print.
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Kapitan, Jacob G. "Structural assessment of bridge piers with damage similar to alkali silica reaction and/or delayed ettringite formation." Full-text Adobe Acrobat (PDF) file, 2006. http://www.engr.utexas.edu/research/fsel/FSEL_reports/Thesis/Kapitan,%20Jacob.pdf.

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Bayissa, Wirtu Lemessa. "Damage identification and condition assessment of civil engineering structures through response measurement /." Connect to thesis, 2007. http://eprints.unimelb.edu.au/archive/00003631.

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ZAURIN, RICARDO. "STRUCTURAL HEALTH MONITORING WITH EMPHASIS ON COMPUTER VISION, DAMAGE INDICES, AND STATISTICAL ANALYSIS." Doctoral diss., University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3530.

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Structural Health Monitoring (SHM) is the sensing and analysis of a structure to detect abnormal behavior, damage and deterioration during regular operations as well as under extreme loadings. SHM is designed to provide objective information for decision-making on safety and serviceability. This research focuses on the SHM of bridges by developing and integrating novel methods and techniques using sensor networks, computer vision, modeling for damage indices and statistical approaches. Effective use of traffic video synchronized with sensor measurements for decision-making is demonstrated. First, some of the computer vision methods and how they can be used for bridge monitoring are presented along with the most common issues and some practical solutions. Second, a conceptual damage index (Unit Influence Line) is formulated using synchronized computer images and sensor data for tracking the structural response under various load conditions. Third, a new index, Nd , is formulated and demonstrated to more effectively identify, localize and quantify damage. Commonly observed damage conditions on real bridges are simulated on a laboratory model for the demonstration of the computer vision method, UIL and the new index. This new method and the index, which are based on outlier detection from the UIL population, can very effectively handle large sets of monitoring data. The methods and techniques are demonstrated on the laboratory model for damage detection and all damage scenarios are identified successfully. Finally, the application of the proposed methods on a real life structure, which has a monitoring system, is presented. It is shown that these methods can be used efficiently for applications such as damage detection and load rating for decision-making. The results from this monitoring project on a movable bridge are demonstrated and presented along with the conclusions and recommendations for future work.
Ph.D.
Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil Engineering PhD
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Kelly, Brendan T. "A Newly Proposed Method for Detection, Location, and Identification of Damage in Prestressed Adjacent Box Beam Bridges." Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1339520527.

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Waltering, Markus. "Damage assessment of civil engineering structures and bridges using nonlinear dynamic characteristics." Aachen Shaker, 2009. http://d-nb.info/998626988/04.

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Books on the topic "Structural damage to bridges"

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Feng, Maria Q. Long-term structural performance monitoring of bridges: Development of baseline model and methodology for health monitoring and damage assessment. Sacramento, Calif: California Dept. of Transportation, Division of Research and Innovation, 2008.

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Larsen, Ole Damgaard. Ship collision with bridges. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 1993. http://dx.doi.org/10.2749/sed004.

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<p>Any struoture in navigable waters constitutes a hazard to shipping and is itself vulnerable to damage or destruction in the event of vessel collision. Worldwide vessel traffic and the average size of vessels continue to lncrease. At the same time, ever more bridges crossing navigable waterways are being planned and constructed, sometimes with inadequate navigation clearance and/or lnadequate protection.<p> The objective of this publication is to provide information and guidelinesfor engineers charged with the planning and design of new bridges, navlgation channels, and prevention and protection measures. Lt offers advice on up­grading and retrofrtting existing bridges and navigation channels. And lt provides the means to evaluate the safety of bridges, vessels, persons and the environment. <p>After reviewing some basics o! navigatlon and vessel traffic, and consider­ing risk acceptance and collision risk, the publication examines vessel impact forces on bridges and proposes appropriate bridge design criteria. Prevention measures, such as regulations and management systems. And protectlon measures and systems are also described. Major international research projects have provided the analytical basis for the publication, including the development of vessel collision guide specifi­c-atrons for the Federal Highway Administration in the USA and the vessel colllsion design crrteria developed for the Great Bell Crossing in Oenmark. <p>Prepared by Ole Damgaard LARSEN, Chairman of the IABSE Working Group "Ship Collision with Bridges'', lhis 132 page publlcation is a must for any engineer dealing with structures in navigable waters.
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Wood, Michael George. Damage analysis of bridge structures using vibrational techniques. Birmingham: Aston University. Department of Mechanical Engineering, 1992.

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Koutský, Jaroslav. Radiation damage of structural materials. Amsterdam: Elsevier, 1994.

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Koutsk'y, Jaroslav. Radiation damage of structural materials. Amsterdam: Elsevier, 1994.

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Nichols, Jonathan Michael. Modeling and estimation of structural damage. Chichester, UK: John Wiley & Sons, 2016.

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Nichols, Jonathan M., and Kevin D. Murphy. Modeling and Estimation of Structural Damage. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118776995.

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Eftekhar Azam, Saeed. Online Damage Detection in Structural Systems. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02559-9.

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Deng, Yang, and Aiqun Li. Structural Health Monitoring for Suspension Bridges. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3347-7.

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Wolfgang, Kauschke, ed. Structural bearings. Berlin: Ernst & Sohn, 2002.

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Book chapters on the topic "Structural damage to bridges"

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Deng, Yang, and Aiqun Li. "Modal Frequency-Based Structural Damage Detection." In Structural Health Monitoring for Suspension Bridges, 63–103. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-3347-7_4.

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Deng, Yang, and Aiqun Li. "Measurement-Based Damage Detection for Expansion Joints." In Structural Health Monitoring for Suspension Bridges, 47–61. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-3347-7_3.

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Zaurín, Ricardo, and F. Necati Catbas. "Computer Vision for Structural Health Monitoring and Damage Detection of Bridges." In Dynamics of Bridges, Volume 5, 125–35. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9825-5_13.

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Zonta, Daniele, Matteo Pozzi, and Paolo Zanon. "Bayesian Approach to Condition Monitoring of PRC Bridges." In Damage Assessment of Structures VII, 227–32. Stafa: Trans Tech Publications Ltd., 2007. http://dx.doi.org/10.4028/0-87849-444-8.227.

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Wang, Chun Sheng, Yue Xu, Ai Rong Chen, and Wei Zhen Chen. "System Fatigue Damage Reliability Assessment of Railway Riveted Bridges." In Damage Assessment of Structures VII, 173–78. Stafa: Trans Tech Publications Ltd., 2007. http://dx.doi.org/10.4028/0-87849-444-8.173.

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Nussbaumer, A., J. Oliveira Pedro, C. A. Pereira Baptista, and M. Duval. "Fatigue Damage Factor Calibration for Long-Span Cable-Stayed Bridge Decks." In Structural Integrity, 369–76. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13980-3_47.

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Ventura, Carlos E., and Juan C. Carvajal. "Structural Assessment of Damaged Bridges Using Ambient Vibration Testing." In Dynamics of Bridges, Volume 5, 41–47. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9825-5_5.

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Zhang, Haiping, Yang Liu, and Naiwei Lu. "Probabilistic Fatigue Damage of Orthotropic Steel Deck Details based on Structural Health Monitoring Data." In Reliability and Safety of Cable-Supported Bridges, 125–45. First edition. | Boca Raton : CRC Press, 2021. | Series: Resilience and sustainability: CRC Press, 2021. http://dx.doi.org/10.1201/9781003170594-7.

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Silva, Moisés, Adam Santos, and Elói Figueiredo. "Damage Detection for Structural Health Monitoring of Bridges as a Knowledge Discovery in Databases Process." In Data Mining in Structural Dynamic Analysis, 1–24. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0501-0_1.

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Aggarwal, Vasvi, and Lakshmy Parameswaran. "Effect of Overweight Trucks on Fatigue Damage of a Bridge." In Advances in Structural Engineering, 2483–91. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2187-6_190.

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Conference papers on the topic "Structural damage to bridges"

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SANTOS, ADAM, ELOI FIGUEIREDO, and JOAO COSTA. "Clustering Studies for Damage Detection in Bridges: A Comparison Study." In Structural Health Monitoring 2015. Destech Publications, 2015. http://dx.doi.org/10.12783/shm2015/146.

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ALAMDARI, MEHRISADAT, VAN VU NGUYEN, PETER RUNCIE, and SAMIR MUSTAPHA. "Damage Characterization in Concrete Jack Arch Bridges Using Symbolic Time Series Analysis." In Structural Health Monitoring 2015. Destech Publications, 2015. http://dx.doi.org/10.12783/shm2015/284.

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MI, JIANAN, YIXIAO ZHANG, WEIFENG LIU, and LIJUN LIU. "Seismic Damage Identification for Bridges Based on Transmissibility Function and Support Vector Machine." In Structural Health Monitoring 2019. Lancaster, PA: DEStech Publications, Inc., 2019. http://dx.doi.org/10.12783/shm2019/32399.

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Doornink, J. D., B. M. Phares, T. J. Wipf, and D. L. Wood. "Damage detection in bridges through fiber optic structural health monitoring." In Optics East 2006, edited by Michael A. Marcus, Brian Culshaw, and John P. Dakin. SPIE, 2006. http://dx.doi.org/10.1117/12.686011.

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Oura, Ryoga, Takashi Yamaguchi, and Kentaro Arimura. "Analytical study on repair method for steel I-girder bridges with corrosion damage considering its structural system behavior." In IABSE Congress, Christchurch 2021: Resilient technologies for sustainable infrastructure. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2021. http://dx.doi.org/10.2749/christchurch.2021.0382.

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<p>Bridges are composed by many structural members which interact with each other to resist against various load combinations. Considering damage repair of one of its structural members, the relationship between the recovery of the individual load-carrying capacity due to the repair of a single member and the improvement of the load-carrying capacity of the structural system is not clear. In the present study, a full-scale FE analysis has been conducted for a steel I-girder bridge system with corrosion damages which have been repaired. The analysis considered, the structural system behavior, varying the repaired areas and the type of patch members. From the analytical results, it was found that, compared to the method in which the damaged portion is completely repaired, the amount of repair can be reduced by taking into account the structural system behavior and partially repair both the damaged and the adjacent intact girders.</p>
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Xu, Yang, Shujin Laima, Hui Li, Na Li, Yao Jin, and Feiyang Han. "Machine Learning-based Structural Health Monitoring and Condition Assessment for Long-span Bridges." In IABSE Conference, Seoul 2020: Risk Intelligence of Infrastructures. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2020. http://dx.doi.org/10.2749/seoul.2020.033.

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<p>Machine learning (ML) provides a promising paradigm for discovering and modeling structural performances and conditions through the deep mining of structural health monitoring data. This paper exhibits recent progress of ML-based structural health monitoring and condition assessment for long-span bridges. A series of novel algorithms for bridge condition assessment via correlation modeling between structural responses, computer vision-assisted structural damage detection, and data mining for wind effects are introduced. First, correlation modeling between different bridge responses is investigated by both the time series data and probability distribution, further assisting bridge condition assessment. Second, several novel CNN architectures and a few-shot meta-learning framework are also established for CV-assisted bridge damage detection. Third, wind-induced vibrations of the bridge in site are identified and modeled to predicate structural responses and evaluate operation conditions. Results show that ML techniques indeed improve the state of the art in structural health monitoring and condition assessment for long-span bridges.</p>
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KUMAR, VIVEK, LEVENT E. AYGUN, NAVEEN VERMA, JAMES C. STURM, and BRANKO GLIŠIĆ. "Large Area Electronics Based Sensing Sheet for Strain Monitoring and Damage Detection of Bridges." In Structural Health Monitoring 2019. Lancaster, PA: DEStech Publications, Inc., 2019. http://dx.doi.org/10.12783/shm2019/32292.

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Wheat, Harovel G., James O. Jirsa, David W. Fowler, and Emily Berver. "Corrosion Damage in Composite-Wrapped Structures." In International Conference on High Performance Materials in Bridges. Reston, VA: American Society of Civil Engineers, 2003. http://dx.doi.org/10.1061/40691(2003)9.

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Smith, Frank J. "Smart Bridge: Autonomous Structural Integrity Monitor for Railroad Bridges." In 2020 Joint Rail Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/jrc2020-8062.

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Abstract This paper provides an introduction to Smart Bridge; a railroad bridge structural integrity monitoring system based on Continuous Fiber Optic Strain Sensing (CFOSS) technology. This design concept allows for the real time observation of how a bridge responds to dynamic loading and provides for autonomous reporting of abnormal structural conditions. The CFOSS technology can monitor the entire bridge and observe changes in the behavure of its structural elements. The structure is constantly monitored, both when the structure is at static load and when the bridge is supporting the load of a train. When significant changes are observed they can be defined by location and the degree of deviation from normal. A Smart Bridge provides automatic notification of sudden changes to the structure in real time. These changes may be an indication of bridge impact damage. It also provides a graphical map of the changes in structural behavure over time. In both circumstances the technology will identify the specific structural element that is degrading. Smart Bridge is based on Continuous Fiber Optic Strain Sensing technology. This technology manifests in the form of a cable that is bonded along the entire length of the structural elements of the bridge. The cable senses strain in both the axial and transverse directions. Unlike conventional strain gauge elements that are bonded to a single location, CFOSS cables run continuously along the beam, plate or tendon. The technology is able to observe the changes in the concentration of strain along a structure and identify the origin of the change. CFOSS technology is currently under development as part of the Smart Rail project. The underlying fiber optic strain sensing cable technology is in commercial use in the oil well and petrochemical pipeline industry. The adoption of Smart Bridge provides enhanced operational safety because it monitors the structural integrity of the bridge continuously and provides automatic status annunciations. This monitoring is active during times when the bridge is in dead load and when it is supporting the load of a passing train. Smart Bridge also improves the working safety of bridge inspectors by providing a map of structural changes that may indicate hazardous conditions. The use of Smart Bridge improves the inspection process by identifying potential structural problems that may require visual confirmation. And it provides autonomous warnings when sudden changes in the bridge structural integrity are detected.
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Zhang, Chaobo, and Chih-Chen Chang. "Surface damage detection for concrete bridges using single-stage convolutional neural networks." In Health Monitoring of Structural and Biological Systems XIII, edited by Paul Fromme and Zhongqing Su. SPIE, 2019. http://dx.doi.org/10.1117/12.2513571.

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Reports on the topic "Structural damage to bridges"

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Rahmani, Mehran, and Manan Naik. Structural Identification and Damage Detection in Bridges using Wave Method and Uniform Shear Beam Models: A Feasibility Study. Mineta Transportation Institute, February 2021. http://dx.doi.org/10.31979/mti.2021.1934.

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This report presents a wave method to be used for the structural identification and damage detection of structural components in bridges, e.g., bridge piers. This method has proven to be promising when applied to real structures and large amplitude responses in buildings (e.g., mid-rise and high-rise buildings). This study is the first application of the method to damaged bridge structures. The bridge identification was performed using wave propagation in a simple uniform shear beam model. The method identifies a wave velocity for the structure by fitting an equivalent uniform shear beam model to the impulse response functions of the recorded earthquake response. The structural damage is detected by measuring changes in the identified velocities from one damaging event to another. The method uses the acceleration response recorded in the structure to detect damage. In this study, the acceleration response from a shake-table four-span bridge tested to failure was used. Pairs of sensors were identified to represent a specific wave passage in the bridge. Wave velocities were identified for several sensor pairs and various shaking intensities are reported; further, actual observed damage in the bridge was compared with the detected reductions in the identified velocities. The results show that the identified shear wave velocities presented a decreasing trend as the shaking intensity was increased, and the average percentage reduction in the velocities was consistent with the overall observed damage in the bridge. However, there was no clear correlation between a specific wave passage and the observed reduction in the velocities. This indicates that the uniform shear beam model was too simple to localize the damage in the bridge. Instead, it provides a proxy for the overall extent of change in the response due to damage.
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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, May 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-consuming and expensive. The main objective of this study is to develop methods and algorithms to automate the post-processing of the visual sensor data towards the extraction of three main categories of information: 1) object information such as object identity, shapes, and spatial relationships - a novel heuristic-based method is proposed to automate the detection and recognition of main structural elements of steel girder bridges in both terrestrial and unmanned aerial vehicle (UAV)-based laser scanning data. Domain knowledge on the geometric and topological constraints of the structural elements is modeled and utilized as heuristics to guide the search as well as to reject erroneous detection results. 2) structural damage information, such as damage locations and quantities - to support the assessment of damage associated with small deformations, an advanced crack assessment method is proposed to enable automated detection and quantification of concrete cracks in critical structural elements based on UAV-based visual sensor data. In terms of damage associated with large deformations, based on the surface normal-based method proposed in Guldur et al. (2014), a new algorithm is developed to enhance the robustness of damage assessment for structural elements with curved surfaces. 3) three-dimensional volumetric models - the object information extracted from the laser scanning data is exploited to create a complete geometric representation for each structural element. In addition, mesh generation algorithms are developed to automatically convert the geometric representations into conformal all-hexahedron finite element meshes, which can be finally assembled to create a finite element model of the entire bridge. To validate the effectiveness of the developed methods and algorithms, several field data collections have been conducted to collect both the visual sensor data and the physical measurements from experimental specimens and in-service bridges. The data were collected using both terrestrial laser scanners combined with images, and laser scanners and cameras mounted to unmanned aerial vehicles.
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Varma, Amit H., Jan Olek, Christopher S. Williams, Tzu-Chun Tseng, Dan Huang, and Tom Bradt. Post-Fire Assessment of Prestressed Concrete Bridges in Indiana. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317290.

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This project focused on evaluating the effects of fire-induced damage on concrete bridge elements, including prestressed concrete bridge girders. A series of controlled heating experiments, pool fire tests, material tests, and structural loading tests were conducted. Experimental results indicate that the portion of concrete subjected to temperatures higher than 400°C loses significant amounts of calcium hydroxide (CH). Decomposition of CH increases porosity and causes significant cracking. The portion of concrete exposed to temperatures higher than 400°C should be repaired or replaced. When subjected to ISO-834 standard fire heating, approximately 0.25 in. and 0.75 in. of concrete from the exposed surface are damaged after 40 minutes and 80 minutes of heating, respectively. Prestressed concrete girders exposed to about 50 minutes of hydrocarbon fire undergo superficial concrete material damage with loss of CH and extensive cracking and spalling extending to the depth of 0.75–1.0 in. from the exposed surface. These girders do not undergo significant reduction in flexural strength or shear strength. The reduction in the initial stiffness may be notable due to concrete cracking and spalling. Bridge inspectors can use these findings to infer the extent of material and structural damage to prestressed concrete bridge girders in the event of a fire and develop a post-fire assessment plan.
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Heckman, James. Building Bridges Between Structural and Program Evaluation Approaches to Evaluating Policy. Cambridge, MA: National Bureau of Economic Research, June 2010. http://dx.doi.org/10.3386/w16110.

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Charles R. Farrar, Phillip J. Cornwell, Scott W. Doebling, and Michael B. Prime. Structural Health Monitoring Studies of the Alamosa Canyon and I-40 Bridges. Office of Scientific and Technical Information (OSTI), July 2000. http://dx.doi.org/10.2172/766805.

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Banovic, Stephen W., and Timothy Foecke. Damage and failure modes of structural steel components. Gaithersburg, MD: National Institute of Standards and Technology, 2005. http://dx.doi.org/10.6028/nist.ncstar.1-3cv1.

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Roach, Dennis P., Raymond Bond, and Doug Adams. Structural Health Monitoring for Impact Damage in Composite Structures. Office of Scientific and Technical Information (OSTI), August 2014. http://dx.doi.org/10.2172/1154712.

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Cha, Hun, Boyuan Liu, Arun Prakash, and Amit Varma. Efficient Load Rating and Quantification of Life-Cycle Damage of Indiana Bridges Due to Overweight Loads. Purdue University, February 2017. http://dx.doi.org/10.5703/1288284316329.

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Bhattcharya, B., and B. Ellingwood. A damage mechanics based approach to structural deterioration and reliability. Office of Scientific and Technical Information (OSTI), February 1998. http://dx.doi.org/10.2172/573315.

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Kacprzynski, Gregory J. Sensor/Model Fusion for Adaptive Prognosis of Structural Corrosion Damage. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada448747.

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