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Copyright of Japanese Journal of JSCE / Doboku Gakkai Ronbunshu is the property of Japan Society of Civil Engineers and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The hybrid cable-stayed suspension bridge is used to combine the advantages of cable-stayed and suspension bridges and hence has a broad prospect for application. The conventional simplified analytical models of the hybrid bridge are usually developed based on a schematic with the cable-stayed and suspension systems working separately without any overlapping zone, which cannot represent the modern hybrid bridge system. In this study, a novel analytical model is proposed based on the modified suspension–elastic foundation beam theory to estimate the mechanical performance and deflection of the hybrid bridge system with the consideration of the overlapped section between the suspension and stayed cables. The governing equations of the hybrid bridge system are developed based on the elastic foundation beam theory and the deflection theory, which are derived separately in the hybrid section, the pure suspension section and the cable-stayed section. The general solution of each section is presented. The Transfer Matrix Method is then employed to solve the unknowns from one end to the other, which are in turn used to solve the internal forces of the hybrid bridge system caused by the concentrated load. In addition, in view of no variation in the unstressed length of the main cable, the compatibility equation of the main cable is established with consideration of the longitudinal displacement of the main tower, which is used to derive the formulas for the internal force and deflection of the hybrid system. The model can be easily complied in any programming platform, such as Matlab, with simple input parameters, which can eliminate the complex finite element modeling process. Hence, it can be easily used in the preliminary design stage to determine the optimal size and layout of the bridge. Then, a case study is presented for the verification of the proposed model under a vertical load, which is simplified from the Xihoumen Bridge, a combined highway and railway bridge with a main span of 1488 m. Good agreement is obtained between the proposed model and the finite element method. Meanwhile, it is found that there exists a negative deflection zone for the main beam at a distance from the concentrated vertical load, which is mainly caused by the deflection of the main cables, leading to the cambering of the beam. [ABSTRACT FROM AUTHOR]

Visual inspection and hammering tests are the standard methods for inspecting shield tunnels. They can provide a comprehensive judgment based on the engineer's past experience and conditions, such as cracking, water leakage, and structural details. However, one problem with this method is that the inspection results are highly dependent on the skills of the inspector. To overcome this limitation, it is necessary to develop an easy and quantitative inspection method for shield tunnels. The influence line (IL), which is the response at a specific point due to a unit load that is moved along the target structure, can be used for evaluating the soundness of the infrastructure. Therefore, in this study, we propose a method for determining the IL that can be applied when the speed of a passing train changes. The IL is determined by measuring the displacement due to the train load using a MEMS accelerometer. Finally, to verify the validity of the determined IL, a finite element analysis is performed. Good agreement is found between the ILs determined experimentally and analytically when the soil spring constant is 18 times higher than the nominal value, with a correlation coefficient of 0.98. [ABSTRACT FROM AUTHOR]

Bridge bending stiffness, related to bridge material and geometric properties, is considered an important indicator of bridge performance. Accurately identifying bridge bending stiffness is essential for evaluating the condition of the bridge. The bridge influence line (IL), which can reflect the bending stiffness, is widely used for bending stiffness identification. The most frequently employed IL is deflection IL, which is typically extracted from the deflection response of the midspan section. In practice, a fixed reference point below the midspan section is usually unavailable, thus limiting the application of deflection measurements. Furthermore, existing methods primarily focus on simply supported girder bridges, which are not applicable to continuous girder bridges. This paper proposes a method for identifying the bending stiffness of continuous girder bridges by using multiple rotation influence lines (RILs) of the section near the bearing. The rotation responses of the section near the bearing are measured for RIL extraction since the bearing has a platform for sensor fixation and overcomes the limitation of deflection measurements. The distribution functions are introduced for simulating bending stiffness, and their parameters are estimated by an optimization algorithm using multiple RILs. This approach leverages multiple measurement points and is more accurate than the method using a single RIL. The effectiveness of the proposed method for identifying bridge bending stiffness is verified by both numerical simulations and laboratory experiments. A comparison between the identified bending stiffness using multiple RILs and that using a single RIL assesses the applicability of the proposed method. [ABSTRACT FROM AUTHOR]

A smart concrete girder bridge usually has various sensors, based on which several physical properties can be measured, and hence, the health condition can be evaluated. Cracks are always observed on a smart concrete girder bridge. In particular, some of the cracks are induced by overloaded vehicles, which is dangerous to its safe operation. However, due to the crack opening and closing effect, it exhibits nonlinear responses, posing challenges for accurately assessing its health condition. Influence lines (ILs) are a promising indicator for bridge damage. However, there is limited research on the effect of cracks on the ILs of a smart concrete girder bridge. A digital twin is commonly used to accompany the smart sensing system to accurately evaluate the health condition, where the finite element (FE) model is of great importance. Therefore, this study proposes an element size–independent FE model construction method based on the concrete damage plasticity (CDP) model to investigate the changes of displacement and strain ILs of different types of smart concrete girder bridges with bending cracks, which is helpful to guide how to use the ILs to identify the cracks and evaluate the health condition. Initially, a concrete constitutive model based on crushing/fracture energy is proposed, and the evolution law of tensile damage based on fracture energy is derived to construct the element size–independent FE model. Subsequently, experiments on a reinforced concrete (RC) simply supported beam and a prestressed concrete (PC) simply supported bridge subjected to bending failure are used to verify the FE models constructed by the proposed method. Finally, the FE models of a smart RC T‐beam bridge and a smart three‐span PC continuous bridge are established to study the changes in ILs caused by bending cracks. The change of displacement IL at the midspan due to cracks for the smart RC bridge exceeds 10% when the reinforcements yield, while it is less than 10% for the smart PC bridge even if the bridge is in the failure state. The change of both displacement and strain ILs becomes greater when the measurement point approaches the cracks, and the change of strain IL is only detectable when the measurement is close to the cracks. Due to the crack opening and closing effect, the displacement and strain ILs of a smart concrete girder bridge with bending cracks are inconsistent when different loads are applied. The findings can also be used as a pre‐IL‐based crack detection using the passing inspection vehicle‐induced dynamic response on a selection of type of ILs, determination of layout of sensors, and mass of inspection vehicle. [ABSTRACT FROM AUTHOR]

The hybrid cable-stayed suspension bridge is used to combine the advantages of cable-stayed and suspension bridges and hence has a broad prospect for application. The conventional simplified analytical models of the hybrid bridge are usually developed based on a schematic with the cable-stayed and suspension systems working separately without any overlapping zone, which cannot represent the modern hybrid bridge system. In this study, a novel analytical model is proposed based on the modified suspension–elastic foundation beam theory to estimate the mechanical performance and deflection of the hybrid bridge system with the consideration of the overlapped section between the suspension and stayed cables. The governing equations of the hybrid bridge system are developed based on the elastic foundation beam theory and the deflection theory, which are derived separately in the hybrid section, the pure suspension section and the cable-stayed section. The general solution of each section is presented. The Transfer Matrix Method is then employed to solve the unknowns from one end to the other, which are in turn used to solve the internal forces of the hybrid bridge system caused by the concentrated load. In addition, in view of no variation in the unstressed length of the main cable, the compatibility equation of the main cable is established with consideration of the longitudinal displacement of the main tower, which is used to derive the formulas for the internal force and deflection of the hybrid system. The model can be easily complied in any programming platform, such as Matlab, with simple input parameters, which can eliminate the complex finite element modeling process. Hence, it can be easily used in the preliminary design stage to determine the optimal size and layout of the bridge. Then, a case study is presented for the verification of the proposed model under a vertical load, which is simplified from the Xihoumen Bridge, a combined highway and railway bridge with a main span of 1488 m. Good agreement is obtained between the proposed model and the finite element method. Meanwhile, it is found that there exists a negative deflection zone for the main beam at a distance from the concentrated vertical load, which is mainly caused by the deflection of the main cables, leading to the cambering of the beam.

The reasonable expression of live load and its accuracy are important to the safety and design rationality of highway bridge structures. In this study, the optimization issue of the traffic load model for the suspenders of large-scale suspension bridges is studied. Taking a 2300-m main span suspension bridge as an example, a method for suspender classification based on the geometric feature of the influence lines is proposed, and the extreme traffic load effect scenarios are analyzed and used as an optimization reference. Multi-objective optimization based on a genetic algorithm is used to explore the improvement of the traffic load model of the suspender. The traffic load model of the suspender is optimized with three objectives, i.e., accuracy, convenience, and improvement, and the optimization results regarding the load value and loading length are obtained. The value of the uniformly distributed load of the optimized model ranges from 6.4 kN/m to 8.9 kN/m, and the maximum value of the concentrated force could reach 1433 kN. By comparing the obtained optimized model with the current specification model and the extreme load effect scenario model, the improved applicability of the optimized model in the analysis of the load effect of the suspender can be verified. The optimized method and relevant conclusions can provide useful references for the improved design and operation management of similar bridge structures. [ABSTRACT FROM AUTHOR]

Steel truss girder suspension bridges are gradually applied to long-span railway bridges. The fatigue damage correction factor is an important parameter for fatigue calculation, however the research on the coefficient is limited to small-span bridges. This paper analyzes force characteristics of main truss members, calculates the fatigue damage correction coefficient of truss members, and studies the influences of train loading length, annual traffic level of fatigue damage correction coefficient. The main conclusions are as follows: (1) The influence line and fatigue stress characteristics of the main truss members were studied; the stress range of members under tension or mainly under tension is analyzed, and the stress ranges and ratios between dead and live loads in main truss members are investigated. The results show that the maximum stress range of the bottom chord is 182 MPa, the ratios of dead to live loads of about 90 % of bottom chords and diagonal web members exceed the current specifications, and stress ratios of about 10 % of bottom chords and diagonal web members exceed the current specifications. (2) The fatigue damage correction coefficients of main truss members under different train loading lengths and annual traffic levels are calculated and recommended. The research results provide a basis for updating and supplementing the railway steel bridge code.

During operation, a variety of factors, including earthquakes, wind, fatigue, the environment, and many others, can always cause damage to structures and the characteristics of the structure change as a result of the damage. The availability of low-cost methods for detecting damage in truss bridges makes it possible to examine a greater number of operating bridges and ultimately reduces future losses and risks. As a result, researchers' pursuit of suitable methods for detecting damage in structures has grown significantly over time. Bridges have always been the focus of researchers' efforts to comprehend their behavior and develop methods for identifying damage because of their significance as the infrastructure of every nation. In this study, an eight-span truss bridge was subjected to a moving load in a laboratory process, and the vertical displacement response of only one desired point of the truss lower chord is measured, in the damaged and intact condition. On the other hand, the influence line diagrams of all truss members have been extracted during the modeling in finite element software. The efficacy of this method in detecting damage in truss bridge screw connections has been evaluated using fourteen distinct damage scenarios. The results show that if damage occurs in the bridge connections, the difference diagram of displacement responses of two healthy and damaged states and the influence line diagram of the member whose connections are damaged will match in terms of shape and can be an indicator to identify the damage. This method works for all of the truss bridge's members, and it has worked even when more than one member was damaged. Considering that this method has been numerically validated in the previous study, using a more accurate displacement sensor with less noise and using conditions closer to those of the numerical analysis improves the accuracy of the results.

Influence lines are indispensable tools for visualizing and analyzing the dynamic variations in force factors induced by external loads within structural systems. Among these methods, the energetic approach stands as a widely employed technique, rooted in the fundamental principle of work done by changing forces. It enables engineers to transform intricate structural analysis problems into manageable ones by exploring the first derivatives of the radius vector, which represent infinitesimal velocity or displacement. This methodology seamlessly interweaves concepts such as carrier motion, relative motion, and the construction of mechanisms, bringing fresh perspectives to the analysis of influence lines. In this article, we explore the nuances of these novel methods within the domain of mechanism theory. Through comprehensive elaboration and analysis, we elucidate the underlying principles and practical applications of Jacobian contours. Crucially, we introduce a straightforward, rapid, and programmable approach, promising to revolutionize influence line determination in structural engineering. This method bridges the gap between theory and practice, offering the potential to elevate the accuracy, efficiency, and adaptability of influence line analysis. As such, it represents a significant advancement in the field of structural and applied mechanics, with broad-reaching implications for engineering practice.

Steel truss girder suspension bridges are gradually applied to long-span railway bridges. The fatigue damage correction factor is an important parameter for fatigue calculation, however the research on the coefficient is limited to small-span bridges. This paper analyzes force characteristics of main truss members, calculates the fatigue damage correction coefficient of truss members, and studies the influences of train loading length, annual traffic level of fatigue damage correction coefficient. The main conclusions are as follows: (1) The influence line and fatigue stress characteristics of the main truss members were studied; the stress range of members under tension or mainly under tension is analyzed, and the stress ranges and ratios between dead and live loads in main truss members are investigated. The results show that the maximum stress range of the bottom chord is 182 MPa, the ratios of dead to live loads of about 90 % of bottom chords and diagonal web members exceed the current specifications, and stress ratios of about 10 % of bottom chords and diagonal web members exceed the current specifications. (2) The fatigue damage correction coefficients of main truss members under different train loading lengths and annual traffic levels are calculated and recommended. The research results provide a basis for updating and supplementing the railway steel bridge code. [ABSTRACT FROM AUTHOR]

Many damage identification methods are based on a comparison of structure response between healthy and damaged states. However, the healthy state response of especially old bridges is rarely available. In this paper, a new output-only damage identification approach is proposed to locate damage in multi-span bridges. In this method, only the damaged state strain and displacement influence lines are required. This approach is theoretically explained for a three-span girder. The middle span, the health condition of which is in quest, is modeled as a single-span beam, supported by rotational springs with unknown stiffness. A new algorithm is proposed to estimate the healthy state displacement influence line of the middle point of the span. In this algorithm, the ratio of the flexural stiffness of the girder to the spring's rotational stiffness is determined in such a way that the estimated displacement, is as close to the measured response, as possible. Then, the estimated displacement is scaled based on two constraints. First, it is expected to be lower than the pseudo-static component of measured displacement because damage increases the response globally. Second, the difference between the scaled and pseudo-static component of the measured response is minimized. Eventually, damage is located using a novel damage index based on the local deviation of pseudo-static component of measured displacement from the estimated scaled response. The proposed method is numerically evaluated in a three-span girder. The damage is successfully identified in all different scenarios. Also, its application to Powder Mill Pond Bridge is numerically investigated which yielded promising results. [ABSTRACT FROM AUTHOR]

Copyright of Transportation Science & Technolgy is the property of Transportation Science & Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Influence lines are indispensable tools for visualizing and analyzing the dynamic variations in force factors induced by external loads within structural systems. Among these methods, the energetic approach stands as a widely employed technique, rooted in the fundamental principle of work done by changing forces. It enables engineers to transform intricate structural analysis problems into manageable ones by exploring the first derivatives of the radius vector, which represent infinitesimal velocity or displacement. This methodology seamlessly interweaves concepts such as carrier motion, relative motion, and the construction of mechanisms, bringing fresh perspectives to the analysis of influence lines. In this article, we explore the nuances of these novel methods within the domain of mechanism theory. Through comprehensive elaboration and analysis, we elucidate the underlying principles and practical applications of Jacobian contours. Crucially, we introduce a straightforward, rapid, and programmable approach, promising to revolutionize influence line determination in structural engineering. This method bridges the gap between theory and practice, offering the potential to elevate the accuracy, efficiency, and adaptability of influence line analysis. As such, it represents a significant advancement in the field of structural and applied mechanics, with broad-reaching implications for engineering practice. [ABSTRACT FROM AUTHOR]

Conventional methods to identify influence lines, which are essential in design and evaluation of bridges, use contact sensors involving high upfront and operational costs. This paper presents an approach to identifying influence lines based on computer vision measurements. The approach integrates vision-based identification of vehicle types, estimation of vehicle loads, bridge displacement measurement, and Bayesian parametric estimation. A you only look once version 4 (YOLOv4)—a real-time object detector—with a convolutional block attention module is trained to identify vehicle types and estimate vehicle loads. Bridge displacement measurements provide dynamic deflections, which are then used to analyze the influence line through Bayesian parametric estimation. The performance of this approach was evaluated through laboratory and field experiments with different types of vehicles and driving speeds. The results show that the errors were up to 4.88% for laboratory experiments and up to 11.48% for field experiments. This research provides findings that will help with the practices of condition monitoring and assessment of highway bridges. [ABSTRACT FROM AUTHOR]

Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bridge influence lines (BILs) and bridge influence surfaces (BISs) are inherent static parameters of bridges which can be extracted from moving vehicle-induced bridge responses. Compared with dynamic parameters, these parameters are directly related to the stiffness and internal forces in each cross-section of a bridge therefore can be considered as an effective bridge metamodel. To accelerate the engineering practice of BIL- and BIS-based bridge evaluation, this paper first briefly reviews the current BIL and BIS field test and identification methods. Then, the bridge evaluation guidelines of China and the United States are introduced as the basis of the evaluation methods. Engineering application scenarios for bridge evaluation, including permit load verification, performance degradation checking, and load carrying capacity evaluation, are summarized, and a multiple-scenario bridge evaluation method is established. At the end of this paper, an evaluation example of a four-span continuous bridge is presented to illustrate the application procedure and verify the effectiveness of the proposed method. The outcomes of this paper provide a promising application method of field test BILs and BISs, which may help bridge engineers more effectively use these parameters in engineering practice. [ABSTRACT FROM AUTHOR]

Simply supported bridges are the main bridge types in many transportation systems, and their damage can significantly reduce their load-carrying capacity. To detect possible damage, the time history and spatial distribution of the static responses of bridges (deflection, rotation, and strain influence lines/deformation curves) have recently been proposed as important indicators due to their good local damage detection ability and low testing cost. This paper attempts to establish connections between different static curve-based damage indicators through the various forms of Maxwell-Betti's law. Damage indicators related to seven static curves are then rewritten as a unified framework. The framework states that all these static curves are directly related to the flexural stiffness distribution of the main girder for the simply supported bridge. Then, the theoretical formulations for the difference between the static curves of bridges in intact and damaged states are derived, and the response difference surfaces (RDSs) are plotted to visualize the sensitivity of different static curves to damage. Sensor placement suggestions for stiffness degradation evaluation are presented based on the damage sensitivity analysis at the end of this paper. The results of this study provide comprehensive theoretical support for static response-based damage identification of simply supported bridges. [ABSTRACT FROM AUTHOR]

The reasonable expression of live load and its accuracy are important to the safety and design rationality of highway bridge structures. In this study, the optimization issue of the traffic load model for the suspenders of large-scale suspension bridges is studied. Taking a 2300-m main span suspension bridge as an example, a method for suspender classification based on the geometric feature of the influence lines is proposed, and the extreme traffic load effect scenarios are analyzed and used as an optimization reference. Multi-objective optimization based on a genetic algorithm is used to explore the improvement of the traffic load model of the suspender. The traffic load model of the suspender is optimized with three objectives, i.e., accuracy, convenience, and improvement, and the optimization results regarding the load value and loading length are obtained. The value of the uniformly distributed load of the optimized model ranges from 6.4 kN/m to 8.9 kN/m, and the maximum value of the concentrated force could reach 1433 kN. By comparing the obtained optimized model with the current specification model and the extreme load effect scenario model, the improved applicability of the optimized model in the analysis of the load effect of the suspender can be verified. The optimized method and relevant conclusions can provide useful references for the improved design and operation management of similar bridge structures.

The bridge weigh-in-motion (BWIM) technique uses the instrumented bridge on a large scale to identify the axle weight of a passing vehicle. Vehicle configurations, e.g., axle number and wheelbase, are crucial for the BWIM system, which require additional axle detectors. Free of axle (FAD) sensors are often used to obtain vehicle information, but they are only suitable for specific bridge types, such as slab-girder bridges. The concept of a virtual-axle-based algorithm, without requiring axle detectors, has been developed, and the validity of this algorithm has been verified numerically and experimentally. However, this algorithm assumes the vehicle speed as a known input, indicating that additional speed sensors/devices are still required in the BWIM system. Using this virtual-axle-based algorithm in a field test, it is found that the identification accuracy of the BWIM system is sensitive to the vehicle speed, and it shows poor recognition of vehicle configuration. To improve the recognition accuracy and remove vehicle speed detectors from the BWIM system, an extended BWIM system is proposed using the regularization technique and iterative approach. Both vehicular virtual axles and speeds are assumed in this approach. An error function based on the measured responses and theoretical ones is built to evaluate these assumed vehicle configurations and speeds. The effectiveness of the proposed approach is verified by the field tests. The results show that the proposed approach can obtain high recognition accuracy, which is close to Moses's algorithm using FAD sensors. Compared with the previous virtual-axle-based algorithm, the recognition accuracy and robustness of the proposed approach are greatly improved. The proposed approach is still challenged by real-world traffic because this paper only considers the case when a single vehicle passes over the bridge. Nevertheless, the proposed extended BWIM system shows potential practical applications as it can further reduce costs and be applicable to more bridge types. [ABSTRACT FROM AUTHOR]

Prestressed concrete bridges built between 1960 and 1990 no longer meet today's requirements due to loads and increasing mileage of higher loads that have increased since the bridges were designed. Prestressed concrete bridges are representative of Germany's existing bridges. In order to deal with the large number of ageing bridges, recalculations and measurements for control as well as bridge monitoring are an important means of support. For both, it is important to find features that are damage-sensitive as well as robust against measurement noise, vehicle parameters (dynamics, geometry, weight, etc.) and environmental influences (temperature, wind, etc.). In this paper, we present features for damage detection based on the influence line, which are investigated with respect to the above requirements by using the analytical solution of the Euler–Bernoulli beam and more complex numerical bridge simulations. In this context, we restrict ourselves to the damage caused by bending stress. The features are calculated on the basis of single vehicle crossings over the bridge for the strain in the longitudinal direction as well as for the deflection of the bridge at different sensor positions. The ratio-based features are compared with raw data and natural frequencies in a classification. Additionally, the sensor positioning is considered. The investigations shows that the ratio-based integrated influence lines are equivalent to or better than the modal parameters, especially when noise and temperature changes are taken into account. [ABSTRACT FROM AUTHOR]

In the last few decades, structural health monitoring (SHM) has proven a helpful tool to support the maintenance and management of civil infrastructure. However, typical measurement networks are expensive and require considerable initial efforts. The user-friendliness and interpretability of the outcome of SHM systems are crucial factors in motivating infrastructure owners and decision-makers to sustain their costs. For this reason, simple algorithms that provide structural parameters with direct physical interpretability for professionals familiar with the typical quantities involved in structural engineering are still the most used in field applications. This paper proposes an original method to identify curvature influence lines of bridges and viaducts only using the structural acceleration response induced by vehicular loads. Acceleration time histories collected at sparse locations through standard accelerometers are employed. In contrast to SHM approaches based on modal parameters, the proposed method does not need strict synchronization, thus being suitable for wireless and low-cost monitoring solutions. Identified influence lines are used to define a spatially dense damage indicator for accurate localization of structural anomalies with a clear physical meaning. Experimental results obtained for a steel truss bridge analyzed in different damage conditions prove the efficacy of the proposed method for situations where modal-based approaches may fail. [ABSTRACT FROM AUTHOR]

The bridge influence line (IL) reflects the response of a certain section due to varying load positions. As a result, IL has a wide application prospect in damage identification and condition assessment. Up to date, studies regarding IL have been focused on the structure condition evaluation. A feasible and practical method for damage identification is still not yet available. The present paper proposes a comprehensive damage identification methodology based on IL under a moving vehicle is composed of data pre-processing, IL extraction, and damage detection. Firstly, a thorough review of existing IL identification methods based on signal processing is provided. Then three quasi-static IL identification methods based on measured data are discussed. Consequently, the study proposes a two-stage damage identification approach for simply supported bridges with equal span length. Also, the effectiveness of this approach is verified through field tests on a real girder bridge. At last, conclusions are drawn, and potential issues for the application of the proposed method in practice are discussed.

Influence line (IL)–based damage indices for long-span bridges are investigated in this study. Their effectiveness is experimentally validated for the first time through the scaled physical model of the Tsing Ma Bridge (TMB). First, the IL mechanism for damage detection and its corresponding damage indices are briefly introduced. Subsequently, the scaled TMB model instrumented with different types of sensors, including displacement sensors, strain gauges, and accelerometers, is introduced. The IL characteristics of different bridge components are compared. Two different damage cases with single- and double-damage locations at the bottom chord were tested. In the single-damage case, different ILs extracted from the nearby components were used for damage identification. These ILs can successfully locate damage visually. The strain IL (SIL) is more sensitive to local damage than deflection IL, but its detection performance degrades rapidly with the increasing distance between sensor and force locations. In the double-damage case, the SIL extracted from a single sensor cannot identify both damage cases because of the limited detectable range of each SIL; therefore, using multiple sensor information becomes necessary. For comparison, the modal parameters were also employed for damage detection. These experimental results validated the merits of the IL–based methods proposed for long-span bridges, indicating that IL–based damage indices are good indicators of local damage detection in long-span bridges. This finding contributes to the development of real-time techniques for damage localization in long-span bridges equipped with a structural health monitoring system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Architecture & Civil Engineering is the property of Chang'an Daxue Zazhishe and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study introduces a novel method to determine apparent profile of the track and detect railway bridge condition using sensors on in-service trains. The concept uses a type of Inverse Newmark-β integration scheme on data from a batch of trains. In a self-calibration process, an optimization algorithm is used to find vehicle dynamic properties and speed. For bridge health monitoring, the apparent profile of the bridge is first determined, i.e., the true profile plus components of ballast and bridge deflection under the moving train. The apparent profile is used, in turn, to calculate the moving reference deflection influence line, i.e., the deflection due to a moving (static) unit load. The moving reference influence line is shown to be a good indicator of bridge stiffness. This numerical approach is assessed using an elaborate finite element model operated by an independent research group. The results show that the moving reference influence line can be found accurately and that it constitutes an effective indicator of the condition of a bridge. [ABSTRACT FROM AUTHOR]

Load testing is usually used to evaluate the load-carrying capacity of long-span bridges in their service life. However, a large number of calibration trucks should be arranged in complicated loading patterns to deform bridges during load testing, which is labor-intensive and time-consuming. Aiming to solve this problem, this paper proposes a rapid bridge load-carrying capacity evaluation method using limited testing vehicles. The methodology includes three steps: influence line identification from limited vehicle exciting responses; influence line correction based on prior information of the bridge; and influence line–based bridge load-carrying capacity evaluation. To apply this method in engineering practice, standardized truck passage routines are designed. An application example involving a 1,280-m long-span suspension bridge is presented at the end of this paper. The truck routines, extracted bridge influence lines, and predicted load-carrying capacity of that bridge are presented based on the proposed methods. The testing results are also compared with standard load testing conducted 12 years ago to evaluate bridge performance changes. The outcomes of this paper provide a workable and economical method for long-span bridge load-carrying capacity evaluation. [ABSTRACT FROM AUTHOR]

Prestressed concrete bridges built between 1960 and 1990 no longer meet today’s requirements due to loads and increasing mileage of higher loads that have increased since the bridges were designed. Prestressed concrete bridges are representative of Germany’s existing bridges. In order to deal with the large number of ageing bridges, recalculations and measurements for control as well as bridge monitoring are an important means of support. For both, it is important to find features that are damage-sensitive as well as robust against measurement noise, vehicle parameters (dynamics, geometry, weight, etc.) and environmental influences (temperature, wind, etc.). In this paper, we present features for damage detection based on the influence line, which are investigated with respect to the above requirements by using the analytical solution of the Euler–Bernoulli beam and more complex numerical bridge simulations. In this context, we restrict ourselves to the damage caused by bending stress. The features are calculated on the basis of single vehicle crossings over the bridge for the strain in the longitudinal direction as well as for the deflection of the bridge at different sensor positions. The ratio-based features are compared with raw data and natural frequencies in a classification. Additionally, the sensor positioning is considered. The investigations shows that the ratio-based integrated influence lines are equivalent to or better than the modal parameters, especially when noise and temperature changes are taken into account.

This paper presents a method of developing digital twins (DTs) of road bridges directly from field measurements taken under random traffic loading. In a physics-based approach, the full three-dimensional behavior of the bridge is represented using response functions and distribution factors. In contrast to conventional finite-element analysis, this approach focuses on the relationship between the applied loads and the measured responses, given the limitations on the information about the applied loads due to random passing traffic. At the same time, it takes advantage of some key features of bridge traffic loading that are consistent, regardless of the weights of the passing vehicles. The nature of traffic loading is that axles travel from one end of a bridge to the other and the response is a linear combination of axle weights and ordinates of the same influence line function, adjusted for relative axle locations. Small/medium span concrete slab–girder decks are the target structures of the study. The three-dimensional nature of such structures is a particular challenge, especially in the case of multiple vehicle presence. While these bridges are strongly orthotropic, there is a significant degree of load distribution between the girders immediately under the passing vehicle and girders under adjacent lanes. This is addressed using an iterative approach that uses transverse distribution factors. The proposed DT model is verified using both numerical simulation and field tests. [ABSTRACT FROM AUTHOR]

With an increase in bridge service time, damage will inevitably occur. Accurately identifying damage is of great significance to the operation and maintenance of a bridge. To realize a frequent identification of local stiffness reduction caused by structural damage in operation, this paper proposes a new method for damage localization of short-span bridges based on the axle weight time history identified by bridge weigh-in-motion technology. This method is based on a least squares QR decomposition recursive algorithm, and the orthogonal matrix is updated by the newly added measured rotation response and the axle weight identified in the previous step to recursively obtain the current axle weight. Then, the axle weight time history is obtained and the damage is located according to the mutation of axle weight time history caused by the first axle passing through the damage. The accuracy and applicability of the proposed method are verified by a numerical model of a simply supported beam. The results show that the axle weight time history has a strong sensitivity to damage, and the average normalized axle weight time history can accurately locate the damage and significantly reduce the impact of environmental noise. This method can be used for long-term health monitoring of bridge structures. [ABSTRACT FROM AUTHOR]

The influence line is an important static property in bridges. The shape and magnitude of the girder bridge influence line contain stiffness information for the bridge supports and beam. This research sought to directly identify the rotational stiffness of bridge supports and the flexural stiffness of beams from extracted influence lines, which provides a quantification method for bridge damage and performance degradation. The paper first reviews the influence line identification method from vehicle-induced bridge responses. Then, the complete theoretical formulations of the deflection, rotation, and strain influence line for a general girder bridge are derived. Based on these derivations, the rotational stiffness at two supports and the equivalent flexural stiffness value of the beam are identified. Next, a certain span of a continuous girder bridge is converted to an equivalent simply supported system, and the flexural stiffness distribution of the beam is estimated based on the bending moment-curvature relationship and Betti's law. The paper then presents a three-span continuous girder bridge verification example. The stiffness estimation results under different test conditions combined with the bridge influence line identification algorithm are presented to verify the reliability of the proposed method. This stiffness estimation method can be applied to baseline-free bridge performance evaluations based on vehicle-induced bridge responses. [ABSTRACT FROM AUTHOR]

Bridge weigh-in-motion systems use instrumented bridges or culverts to weigh vehicles as they pass over the structures. They also provide data to allow the calculation of several bridge performance indicators. The article starts with the basics of a bridge weigh-in-motion system and briefly describes two key bridge performance indicators, girder distribution factor and dynamic amplification factor, which are also derived from B-WIM measurements. The central part of the article focuses on monitoring of influence lines, the third key parameter that characterises the bridge performance under traffic loads. First, the method of calculating the bending moment influence lines from random heavy traffic is described. A coefficient of rotational stiffness is introduced, which defines the shape of influence lines around the supports as a linear combination of the ideal simply supported and fixed supported influence lines, to allow quantifying the influence line changes. Then the long-term monitoring of influence lines is investigated on four different single-span test bridges. The initial focus is given on the examination of the effect of temperature on the shape of influence lines. Finally, two sets of influence lines are compared on one test bridge, one from before and the other from after replacing the expansion joints and bearings. The work done so far confirms that calculating of influence lines from random vehicles with a B-WIM system is entirely feasible and that differences in their shape can be detected on single-span bridges. What remains to be investigated is the comparison of these differences to the actual damages and under which circumstances the proposed procedure can compete with or better the routine bridge inspection and the conventional monitoring techniques. [ABSTRACT FROM AUTHOR]

A real-time vehicle monitoring is crucial for effective bridge maintenance and traffic management because overloaded vehicles can cause damage to bridges, and in some extreme cases, it will directly lead to a bridge failure. Bridge weigh-in-motion (BWIM) system as a high performance and cost-effective technology has been extensively used to monitor vehicle speed and weight on highways. However, the dynamic effect and data noise may have an adverse impact on the bridge responses during and immediately following the vehicles pass the bridge. The fast Fourier transform (FFT) method, which can significantly purify the collected structural responses (dynamic strains) received from sensors or transducers, was used in axle counting, detection, and axle weighing technology in this study. To further improve the accuracy of the BWIM system, the field-calibrated influence lines (ILs) of a continuous multi-girder bridge were regarded as a reference to identify the vehicle weight based on the modified Moses algorithm and the least squares method. In situ experimental results indicated that the signals treated with FFT filter were far better than the original ones, the efficiency and the accuracy of axle detection were significantly improved by introducing the FFT method to the BWIM system. Moreover, the lateral load distribution effect on bridges should be considered by using the calculated average ILs of the specific lane individually for vehicle weight calculation of this lane. [ABSTRACT FROM AUTHOR]

The article presents a technique that significantly reduces the number of calculations when plotting internal forces and influence lines in statically determined multi- span beams. The interaction scheme of the individual beams are not stored, but with the use of the axiom of constraints, it is presented in a more general form- in a straight line, without separation of the main and auxiliary beams. Given that in the case of vertical load to external forces the horizontal reaction or horizontal component is zero, unknown reactions can be easily determined from the conditions of equilibrium of parallel forces and construct a diagram of internal forces according to the general scheme. Influence lines can also be constructed for the required parameters using the appropriate reaction chain. [ABSTRACT FROM AUTHOR]

This article proposes a bridge damage detection method using direct rotation measurements. Initially, numerical analyses are carried out on a one-dimensional (1D) simply supported beam model loaded with a single moving point load to investigate the sensitivity of rotation as a main parameter for damage identification. As a result of this study, the difference in rotation measurements due to a single moving point load obtained for healthy and damaged states is proposed as a damage indicator. A relatively simple laboratory experiment is conducted on a 3-m long simply supported beam structure to validate the results obtained from the numerical analysis. The case of multi-axle vehicles is investigated through numerical analyses of a 1D bridge model and a theoretical basis for damage detection is presented. Finally, a sophisticated 3D dynamic finite element model of a 20-m long simply supported bridge structure is developed by an independent team of researchers and used to test the robustness of the proposed damage detection methodology in a series of blind tests. Rotations from an extensive range of damage scenarios were provided to the main team who applied their methods without prior knowledge of the extent or location of the damage. Results from the blind test simulations demonstrate that the proposed methodology provides a reasonable indication of the bridge condition for all test scenarios. [ABSTRACT FROM AUTHOR]

Summary: The bridge influence line can reflect the structural behavior under moving vehicle loads, which is becoming a proposing tool to study the bridge behavior during service life. A high‐speed vehicle will induce dynamic effect on the bridge, which will significantly change the shape of response curve. It is essential to consider the dynamic response for the accurate identification of the bridge influence line. This paper firstly summarizes current research activities for bridge influence line identification and components of the bridge dynamic responses. A dynamic fluctuation part elimination method based on empirical mode decomposition is proposed, based on which the bridge static influence line is identified by static bridge influence line identification method. Finally, a vehicle–bridge coupling model of a simply supported beam excited by passing vehicles with three different speeds is introduced to illustrate the effectiveness of the proposed identification method. The result of this study provides an effective identification method of the bridge static influence line, which can lead to a satisfactory identification results based on the dynamic responses induced by high‐speed vehicle loads. [ABSTRACT FROM AUTHOR]

Strain Energy of the structure can be changed with the damage at the damage location. The accurate detection of the damage location using this index in a force system is dependent on the degree of accuracy in determining the structure deformation function before and after damage. The use of modal-based methods to identify damage in complex bridges is always associated with problems due to the need to consider the effects of higher modes and the adverse effect of operational conditions on the extraction of structural modal parameters. In this paper, the deformation of the structure was determined by the concept of influence line using the Betti-Maxwell theory. Then two damage detection indicators were developed based on strain energy variations. These indices were presented separately for bending and torsion changes. Finite element analysis of a five-span concrete curved bridge was done to validate the stated methods. Damage was simulated by decreasing stiffness at different sections of the deck. The response regarding displacement of a point on the deck was measured along each span by passing a moving load on the bridge at very low speeds. Indicators of the strain energy extracted from displacement influence line and the strain energy extracted from the rotational displacement influence line (SERIL) were calculated for the studied bridge. The results show that the proposed methods have well identified the location of the damage by significantly reducing the number of sensors required to record the response. Also, the location of symmetric damages is detected with high resolution using SERIL. [ABSTRACT FROM AUTHOR]

A novel damage detection approach is proposed in this study for a continuous girder bridge in which support reaction influence lines (ILs) are adopted. First, the relationship between the local damage of a continuous girder bridge and a damage index, based on support reaction ILs, is established through analytical derivation. Subsequently, the sensitivity of a support reaction IL-based damage index is analyzed using Dempster-Shafer (D-S) evidence theory, and it shows that the support reaction IL-based damage index is more noise-resistant if more support reaction ILs from a variety of locations are used. Three case studies (a simple numerical study of a two-span continuous beam, a laboratory experimental study of a two-span aluminum beam, and a complicated numerical study of a continuous girder bridge in Xiamen) have been conducted to validate the effectiveness of the proposed method in different damage scenarios, including single damage and multiple damages. Satisfactory damage identification results can be obtained even in high-level measurement noise conditions, showing that the proposed approach offers a promising field detection technique for identifying local structural damages in continuous girder bridges.