Location Of Bridge Research Articles

Time-Variant Chloride Ingress Models for Probabilistic Assessment of Concrete Bridge Decks with De-Icing Salt Attack

This study is to propose time-variant probabilistic models of surface chloride and diffusion coefficient based on the survey data of 16 concrete bridge decks with the attack of de-icing salts. These models are developed, because there is no study that simultaneously considers both time-variance and probabilistic descriptors in the model for concrete bridge decks. From the study, it can be found that long-term surface chloride and its time-variant development are fitted with Log-normal and Weibull distributions, respectively. In addition, the 28-day diffusion coefficient and age factor are fitted with Log-logistic and Triangular distributions, respectively. Considering only the mean value in the models, the corrosion-free residual life of concrete bridge decks is equal to 18.3 years based on the target value of critical chloride of 1.2 kg/m3, whereas their cracking-free residual life is equal to 29.5 years based on the target value of critical chloride of 2.0 kg/m3. In comparison with the probabilistic analysis, it was nevertheless found that at year 18.3, there are 38% and 20% probabilities to have rebar corrosion and concrete cracking, respectively. However, at year 29.5, there are 63% and 42% probabilities to have rebar corrosion and concrete. Specifically, there are 6 and almost 7 out of 16 bridge locations having rebar corrosion in the year 18.3 and concrete cracking in the year 29.5, respectively.

Estimating bridge stress histories at remote locations from vibration sparse monitoring

Structural health monitoring with accelerometers provides notable benefits over strain gauges, particularly in installation time and cost efficiency. However, effective local damage assessment necessitates access to local stress histories. This paper proposes a methodology that integrates two distinct approaches to identify and predict stress and strain across various bridge locations from sparse monitoring via acceleration data. The proposed model is validated using strain histories and accelerations collected from the composite railway Bryngeån Bridge in Sweden during its in-service conditions. Initially, a deep learning algorithm for sequence data is employed to forecast strain histories from acceleration data gathered across various bridge locations. Subsequently, the local response function method is implemented, utilizing experimental data collected from the bridge and employing localized models of its substructures, allowing predictions of the bridge’s local strain. By integrating these methods, the approach enables accurate prediction of stress ranges and cycles for critical non-instrumented parts, minimizing the need for extensive direct instrumentation and providing a cost-effective, efficient solution for operational structural health monitoring.

Directional effects on the nonlinear response of vehicle-bridge system under correlated wind and waves

Long-span railway sea-crossing bridges are subjected to strong winds and high waves. Due to variations in structural features, including stiffness and size across diverse orientations, the dynamic response of vehicles and bridges can exhibit significant differences under distinct wind and wave directions. Consequently, a novel approach for analyzing bridge and vehicle dynamic performance called the directional wind-wave-vehicle-bridge (DWWVB) model has been developed. To acquire the statistical characterization of the correlation between wind and wave conditions, a three-dimensional joint probability distribution of wind and wave characteristics derived from collected data at the bridge site is established. The wind loads are derived from wind tunnel tests and computational fluid dynamics simulations. The nonlinear wave loads are solved utilizing the hydrodynamic solver ANSYS-AQWA. Based on the finite element bridge model and a 23-degree-of-freedom mass-spring-damper vehicle model, the aerodynamic nonlinearity and initial geometric nonlinearity are considered during the iteration process. The Newmark-β method is employed to solve the dynamic response of bridges and vehicles. The calculation results reveal that the most unfavorable response occurs when the wind direction is 45° and the wave direction is 90°. The directional analysis provides valuable insights for selecting optimal bridge locations and reasonable design environmental parameters.

Application of regression and remote sensing technology for determining sufficiency of contact-based sensors in long-term SHM of civil structures

Long-span bridges are huge, complex, and vital civil engineering structures for every society. Due to the critical importance of such structures, structural health monitoring (SHM) systems utilizing both contact and non-contact sensor platforms are often considered to measure influential parameters, such as environmental/operational factors and various structural responses. In some circumstances, such as bridge locations, services, weather conditions, harsh environments, and budget constraints, it may not be practical or necessary to utilize all possible sensor systems and measure all parameters, especially environmental/operational (E/O) factors. To devise and implement an affordable SHM program for large-scale civil structures, it is necessary to develop more efficient sensing systems compared to state-of-the-art ones. Against this backdrop, this paper proposes a new methodology for verifying the sufficiency of contact-based E/O sensors installed in long-span bridges using spaceborne remote sensing and regression modeling. The main premise of the proposed methodology is that structural responses obtained from certain remote sensing products enable us to assess the sufficiency of contact sensors and the impacts of both measured and unmeasured E/O conditions. Utilizing structural displacement responses from remote sensing and measured E/O data from contact-based sensors, a supervised regression model using a feedforward artificial neural network is developed to reconstruct or predict displacement responses and to determine the regression accuracy using the R-squared measure. When the accuracy rate is high, one can infer that the contact-based E/O sensors are sufficient; otherwise, it may be essential to install additional E/O sensors and apply the proposed methodology with new information. Real-world long-span bridges are examined to validate the proposed methodology, using displacement responses and recorded temperature data from contact-based thermocouples. The results demonstrate that the methodology offers an effective but affordable system for long-term SHM programs.

Bridge decks under cold waves: Implications of concrete’s temperature-dependent CTE

Temperature fluctuations within a bridge deck during a cold wave event can cause severe continuity stresses in structures where movement is restrained. Thermal loads are accounted for using thermal gradients that vary depending on bridge location and cross-sectional geometry. However, the effect of temperature change on material properties, particularly on the coefficient of thermal expansion (CTE) is rarely accounted for in the analysis and design. A review of the literature indicates that the CTE of concrete materials can vary significantly with changes in temperature, especially under freezing conditions, whereas saturated or partly saturated concrete exhibits nonlinear expansion at temperatures below freezing, resulting from effective reversal of the CTE sign. This effect has not been considered in the literature, when investigating thermal actions on bridge decks in cold temperatures. The aim of this study is to analyze, using an advanced nonlinear F.E. platform, the structural response of a prestressed concrete box bridge structure subjected to cold wave events, when considering the effect of temperature on the nonlinearity, the magnitude and the sign of the CTE of concrete. Meteorological data from three historical cold events of different intensity is input in the thermal models to simulate the temperature distribution in the bridge deck; the estimated temperature field was then used in a structural model to determine the resulting thermal stresses. The temperature-dependence and nonlinearity of the CTE is modeled after calibration of the mathematical relationships against published data. The results indicate that this behavior has a significant influence on structural response, highlighting the need for pertinent consideration of its effect in the relevant sections of the bridge codes.

Landslide Risks to Bridges in Valleys in North Carolina

This research delves into the intricate dynamics of landslides, emphasizing their consequences on transportation infrastructure, specifically highways and roadway bridges in North Carolina. Based on a prior investigation of bridges in Puerto Rico after Hurricane Maria, we found that bridges above water and situated in valleys can be exposed to both landslide and flooding risks. These bridges faced heightened vulnerability to combined landslides and flooding events due to their low depth on the water surface and the potential for raised flood heights due to upstream landslides. Leveraging a dataset spanning more than a century and inclusive of landslide and bridge information, we employed logistic regression (LR) and random forest (RF) models to predict landslide susceptibility in North Carolina. The study considered conditioning factors such as elevation, aspect, slope, rainfall, distance to faults, and distance to rivers, yielding LR and RF models with accuracy rates of 76.3% and 82.7%, respectively. To establish that a bridge’s location is at the bottom of a valley, data including landform, slope, and elevation difference near the bridge location were combined to delineate a bridge in a valley. The difference between bridge height and the lowest river elevation is established as an assumed flooding potential (AFP), which is then used to quantify the flooding risk. Compared to traditional flood risk values, the AFP, reported in elevation differences, is more straightforward and helps bridge engineers visualize the flood risk to a bridge. Specifically, a bridge (NCDOT ID: 740002) is found susceptible to both landslide (92%) and flooding (AFT of 6.61 m) risks and has been validated by field investigation, which is currently being retrofitted by North Carolina DOT with slope reinforcements (soil nailing and grouting). This paper is the first report evaluating the multi-hazard issue of bridges in valleys. The resulting high-fidelity risk map for North Carolina can help bridge engineers in proactive maintenance planning. Future endeavors will extend the analysis to incorporate actual flooding risk susceptibility analysis, thus enhancing our understanding of multi-hazard impacts and guiding resilient mitigation strategies for transportation infrastructure.

Inovasi Metoda Pekerjaan Jembatan Rangka Baja Studi Kasus: Pembangunan Jembatan Ujung Tanah Ii, Kota Padang, November 1993

The bridge is one of the most important means of transportation for humans. The bridge also serves as a link between one area and another. Seeing the importance of the function of a bridge, the construction of a bridge must meet various existing standards. One of the requirements that must be met in making a bridge is the resilience of the bridge in accept the load of both humans and vehicles that cross the bridge and the static equilibrium conditions on the bridge. The construction of a Truss bridge is usually carried out at the place where the bridge will stand. But now the construction of the bridge can be done outside that location, to then be shifted to the actual location. And, that's not only for short bridges, but also for long bridges. But sometimes a condition does not allow conventional bridge construction, while on the other hand the construction of the bridge is something very important. For that we need an innovation, an alternative method so that the construction of the Truss bridge can be carried out. The 100 meter span Australian Truss bridge was assembled above the maintenance bridge at the Batang Arau flood control structure and then shifted downstream to the new bridge location which is 10 meters away. Before the shifting was carried out, rails were prepared as the shifting path and two bridgeheads as the placement of the Truss bridge on the left and right of the Batang Arau river. Currently the Ujung Tanah II Truss bridge has been functioning for 30 years with good maintenance.

Vehicle-Bridge Interaction Modelling Using Precise 3D Road Surface Analysis.

Uneven road surfaces are the primary source of excitation in the dynamic interaction between a bridge and a vehicle and can lead to errors in bridge weigh-in-motion (B-WIM) systems. In order to correctly reproduce this interaction in a numerical model of a bridge, it is essential to know the magnitude and location of the various roadway irregularities. This paper presents a methodology for measuring the 3D road surface using static terrestrial laser scanning and a numerical model for simulating vehicle passage over a bridge with a measured road surface. This model allows the evaluation of strain responses in the time domain at any bridge location considering different parameters such as vehicle type, lateral position and speed, road surface unevenness, bridge type, etc. Since the time domain strains are crucial for B-WIM algorithms, the proposed approach facilitates the analysis of the different factors affecting the B-WIM results. The first validation of the proposed methodology was carried out on a real bridge, where extensive measurements were performed using different sensors, including measurements of the road surface, the response of the bridge when crossed by a test vehicle and the dynamic properties of the bridge and vehicle. The comparison between the simulated and measured bridge response marks a promising step towards investigating the influence of unevenness on the results of B-WIM.

Research on Damage Identification of Arch Bridges Based on Deflection Influence Line Analytical Theory

There is no analytical solution to the deflection influence line of catenary hingeless arches nor an explicit solution to the deflection influence line difference curvature of variable section hingeless arches. Based on the force method equation, a deflection influence line analytical solution at any location before and after structural damage is obtained, and then an explicit solution of the deflection influence line difference curvature of the structural damage is obtained. The indexes suitable for arch structure damage identification are presented. Based on analytical theory and a finite element model, the feasibility of identifying damage at a single location and multiple locations of an arch bridge is verified. This research shows that when a moving load acts on a damaged area of an arch structure, the curvature of the deflection influence line difference will mutate, which proves theoretically that the deflection influence line difference curvature can be used for the damage identification of hingeless arch structures. This research has provided theoretical support for hingeless arch bridge design and evaluation. Combined with existing bridge monitoring methods, the new bridge damage identification method proposed in this paper has the potential to realize normal health status assessments of existing arch bridges in the future.

Quantitative Analysis of the Possible Sites of a New Danube Bridge to Bypass Budapest on Rail (Part 2)

Since 1920, almost all the traffic on rail crossing the Danube in Hungary, crosses it in Budapest via the Southern Railway Bridge which makes it overloaded. This is a very disadvantageous situation not only for commercial shipping but also for military uses as there is certain heavy military equipment that can only be transported via rail.In our two-part article, we examine the locations of new bridges that could be alternatives to bypass Budapest and thus to reduce the traffic load on the railway lines of the capital. In this second part, we examine the situation on the river Tisza by simulating the existence of several bridge alternatives, both newly built and developed existing ones. We also suggest a combined way of development to treat the capacity changes in the context of the whole network by building two new bridges, one on each river.

Quantitative Analysis of the Possible Sites of a New Danube Bridge to Bypass Budapest on Rail (Part 1)

Since 1920, almost all the traffic on rail crossing the Danube in Hungary, crosses it in Budapest via the Southern Railway Bridge which makes it heavily overloaded. This is a very disadvantageous situation not only for commercial shipping but also for military uses as there is certain heavy military equipment that can only be transported via rail.In our two-part article, we examine the locations of new bridges that could be alternatives to bypass Budapest and thus to reduce the traffic load on the railway lines of the capital. In this first part of our paper, we present the effect of a new Danube bridge as an alternative to the V0 railway line. We examine the possible sites of the bridge with several different route alternatives connecting it to the existing railway lines by using traffic simulation.

Probabilistic connectivity assessment of bridge networks considering spatial correlations associated with flood and seismic hazards

To estimate the connectivity of a road network, it is crucial to evaluate the correlation of hazard intensities among individual bridge locations since the probability of multiple bridges being damaged simultaneously depends on the degree of this correlation. However, research on connectivity assessment of bridge networks considering spatial correlations associated with flood intensities is scarce in the literature. When quantifying the spatial correlation of flood intensities, modeling based on the stream distance rather than the Euclidean distance is required, taking into account that river flow is restricted only within the stream network. To achieve this purpose, a novel methodology is proposed to evaluate the spatial correlation of a stream network based on a geostatistical linear model and stream network covariance models. In addition, this study considers the spatial correlation of seismic hazard intensity. With the proposed method, it is possible to identify which bridges play an important role in ensuring the connectivity of the road network under multiple hazards, i.e. flood and seismic. As an illustrative example, the proposed method is applied to a hypothetical bridge network in Kumamoto Prefecture, Japan. The results demonstrate that improved network connectivity can be achieved by implementing a relevant retrofitting strategy for important bridges.

Glacier as a source of novel polyethylene terephthalate hydrolases.

Polyethylene terephthalate (PET) is a major component of microplastic contamination globally, which is now detected in pristine environments including Polar and mountain glaciers. As a carbon-rich molecule, PET could be a carbon source for microorganisms dwelling in glacier habitats. Thus, glacial microorganisms may be potential PET degraders with novel PET hydrolases. Here, we obtained 414 putative PET hydrolase sequences by searching a global glacier metagenome dataset. Metagenomes from the Alps and Tibetan glaciers exhibited a higher relative abundance of putative PET hydrolases than those from the Arctic and Antarctic. Twelve putative PET hydrolase sequences were cloned and expressed, with one sequence (designated as GlacPETase) proven to degrade amorphous PET film with a similar performance as IsPETase, but with a higher thermostability. GlacPETase exhibited only 30% sequence identity to known active PET hydrolases with a novel disulphide bridge location and, therefore may represent a novel PET hydrolases class. The present work suggests that extreme carbon-poor environments may harbour a diverse range of known and novel PET hydrolases for carbon acquisition as an environmental adaptation mechanism.

Structural damage levels of bridges in vehicular collision fires: Predictions using an artificial neural network (ANN) model

Fire poses a major risk to the structural integrity of a bridge or progressively to the bridge’s failure. This study uses an Artificial Neural Network (ANN) to investigate the determining factors in bridge fire incidents. Implementation of this powerful model produces an estimation of the damage levels. The basis of the proposed model is determined by critical factors, including bridge location, materials, structural systems, annual average daily traffic (AADT), ignition source, combustible type, and bridge face exposed to fire. Results show that steel I-girder bridges are the most susceptible structural system in a fire. Moreover, a fire involving tankers containing hydrocarbon fuel and trucks with solid combustible cargo is the most dangerous to a bridge. The accuracy of the proposed model is verified, and its outcome can be utilized to determine fire risk based on discrete characteristics. Based on the proposed model, a combination of hazard prevention and protection measures may be utilized to improve structural integrity, human life safety, and durability, and to reduce maintenance costs.

Decision Support Model for Allocating Maintenance Budgets for Bridges

This paper introduces a newly developed decision support model for allocating a budget for bridge maintenance. The model is built based on capturing the experts’ knowledge for the prioritization of criteria for selecting a bridge maintenance plan. A literature review and interviews with a group of nine local experts were carried out to identify the criteria for bridge prioritization for maintenance. A questionnaire survey was then designed and administered, utilizing multi-criteria decision-making techniques through face-to-face meetings with local bridge maintenance managers to determine the weights of the identified criteria and develop the utility curves for each criterion. The developed model consists of four major modules: (1) bridge ranking module; (2) prioritization module of bridge structural elements; (3) optimization-based simulation module; and (4) the outputs module. The model was validated in a hypothetical network of four bridges. The validation reveals that the model can assist bridge maintenance managers in setting a bridge maintenance plan, with a high level of confidence using efficient frontier analysis technique. Utilizing frontier analysis enables comparisons of mean costs of different bridge maintenance plans against different levels of risk to enable decision-makers to make informed decisions. The result of this study indicated that bridge structural condition was the most important criterion amongst all the criteria influencing the decision of bridge prioritization for maintenance, followed by traffic and bridge location. Moreover, bridge deck and parapet, followed by bearing pads, were found to be the most important of the bridge’s structural elements.

Mapping the chloride-induced corrosion damage risks for bridge decks under climate change

Climate change is expected to alter the environmental factors that are known to influence the corrosion process, creating additional uncertainties in the long-term performance of reinforced concrete (RC) decks. With due consideration of site-specific exposure and environmental conditions, this study aims to investigate the degree to which projected climate change may impact corrosion-induced damage for RC bridges. A hierarchical two-tier framework was developed incorporating the material deterioration process simulation at the local element level, and a component level prediction of the corrosion-induced damage severity and extent over the bridge deck domain. The predictive accuracy of this framework was validated against the historical bridge inspection data. Case studies were performed for decks located in Toronto and Victoria to investigate the influence of climate data resolution and climate projection models on deck deterioration status. At last, ANN (artificial neural network) and SVM (support vector machine) approaches were used to generate a series of cartographic expressions to reveal how the corrosion-induced deck deterioration risk varies with the region due to the difference in the environmental conditions. These maps can serve as visual tools to express the corrosion damage risks for different bridge locations and to formulate region-based durability design requirements.

Engineering demand functions for medium-span RC bridges subjected to earthquake and scour actions

In Mexico, there are two broad areas where highway bridges are subjected to multi-hazard action due to the effects of scour induced by floods and the occurrence of earthquakes. This study aims to determine, for the first time in the country, analytical expressions to assess engineering demand parameters of the joint action of earthquakes and scour events. These expressions will be the basis to evaluate expected losses and the risk of bridges located in these regions, to prioritize rehabilitation and reinforcement actions. Initially, a statistical analysis of the bridges' typology in the regions of Mexico exposed to multi-hazard was carried out. Based on those analyses, the geometric characteristics of the numerical models were chosen. Spectral acceleration in the longitudinal and transverse directions of the bridges was selected as the seismic intensity measure (IM), whereas engineering demand parameter (EDP) was the curvature ductility demand in columns (μφ). On the other hand, the expected maximum scour depth (ys) was estimated by evaluating the maximum extraordinary flood at bridge locations. Finally, IM-EDP empirical functions that correlate μφ−ys−Sa(T), based on 25020 nonlinear time-history analyses, were proposed. The proposed equations can also be used in other sites with similar bridges’ typologies subjected to multi-hazard actions of scour and interplate and intraplate earthquakes.

Study on the Damage Mechanism of Bank Slope-Bridge Pile Foundation Interaction under Reservoir Water Level Cycle

The physical and mechanical properties of the reservoir bank slope deteriorate under the fluctuation of water level, causing bank debonding and slippage, which can produce different degrees of damage to the bridge foundation, piers, and superstructure, a condition that is difficult to treat. In this paper, for a Yangtze River Bridge bank slope instability problem in the Three Gorges reservoir area, a numerical model of the bank slope and bridge was established using the finite element-SPH conversion coupling algorithm, and the pile pier damage development law and damage mode (deformation and stress–strain curves of the bank slope and pile foundation) were obtained according to the geological conditions of the bridge location. Additionally, combined with the characteristics of bank destabilization in the reservoir area of the Three Gorges Yangtze River Bridge, landslide management is proposed by using soil drainage and anti-slip pile reinforcement measures. In addition, for the characteristics of bridge pier deflection, a comprehensive deflection correction reinforcement method of pushing deflection correction, adding pile foundation, expanding pile bearing, and increasing pier cross-sectional area is proposed, so as to provide a theoretical basis for the prevention and control of reservoir bank landslides, the service life of pile structure, and the disposal of diseases.

Magnetic Reconnection Rate in the M6.5 Solar Flare on 2015 June 22

Magnetic reconnection is regarded as the mechanism for the rapid release of magnetic energy stored in active regions during solar flares, and quantitative measurements of the magnetic reconnection rate are essential for understanding solar flares. In the context of the standard two-ribbon flare model, we derive the coronal magnetic reconnection rate of the M6.5 flare on 2015 June 22 in two terms, reconnection flux change rate and reconnection electric field, both of which can be obtained from observations of the flare morphology. Data used include a sequence of chromospheric Hα images with unprecedented resolution during the flare from the Visual Imaging Spectrometer of the Goode Solar Telescope (GST) at the Big Bear Solar Observatory and a preflare line-of-sight photospheric magnetogram from the GST Near-InfraRed Imaging Spectropolarimeter along with hard X-ray data from the Ramaty High Energy Solar Spectroscopic Imager. The temporal correlation between the magnetic reconnection rate and nonthermal emission is found, and the variation of the reconnection electric field is mainly determined by the ribbon speed, not by the local magnetic field encountered by the ribbon front. Spatially, the hard X-ray source overlaps with the location of the strongest electric field obtained at the same time. The ribbon motion shows abundant fine structures, including a local acceleration at the location of a light bridge with a weaker magnetic field.

A Roadmap for an Integrated Assessment Approach to the Adaptation of Concrete Bridges to Climate Change

Bridges play a crucial role in modern societies, regardless of their culture, geographical location, or economic development. The safest, most economical, and most resilient bridges are those that are well managed and maintained. Recently, climate change has been posed as one of the greatest concerns for the health of bridges. Although the uncertainty associated with the magnitude of the change is large, the fact that our climate is changing is unequivocal. As a result, making bridges resilient to climate change is a priority for the authorities. A well-planned early intervention may save lives and money. Until now, the focus of scientific research has mostly been on the climate science, but any practical plan for the adaptation of bridges has to be rooted in other disciplines, including physics, chemistry, engineering, economics, and finance. Therefore, the goal of this paper is to review the work already done from climate change to bridges and set a roadmap for an integrated assessment approach to the adaptation of bridges to climate change. This approach is grounded in a probabilistic- and physics-based framework able to prioritize bridge adaptation measures as a function of bridge location, climate scenario, impact, vulnerability, risk, and cost in order to assist the authorities in the decision-making process. Because adaptation to climate change is highly context-specific, this approach is mainly focused on concrete bridges. Structural health monitoring technology is proposed as a mechanism for assessing and continuously evaluating the structural condition of bridges and for triggering adaptation measures as a function of the predicted severity of climate change.