Bridge Model Research Articles

Random Fourier Surrogate for simulation calibration

In this paper we propose Random Fourier Surrogate (RFS) as a method for simulation calibration. Computer simulations are actively used in various fields to model and analyze complex real-world phenomena, enabling practitioners to explore situations inaccessible by other means. To create a simulation that accurately reflects the desired real-world scenario requires calibrating the simulation parameters, a non-trivial process that requires domain expertise and iterative trial-and-error. The model-bridge paradigm has been proposed to automatize this process, where a more computationally efficient surrogate model is used in lieu of the real simulation, and a bridge model is used to map the noninterpretable surrogate parameters to calibrated simulation parameters, which are physically interpretable. Recently an efficient solution called tangent slope-intercept (TSI) descriptors has been proposed, where tangent lines of a principal curve are used to represent the simulation in low dimensionality. However, we find that it has two key problems: it is prone to overfitting and is sensitive to initialization. We address these issues using Random Fourier Features to construct a surrogate model, thereby reducing calibration time by avoiding complex computations, while retaining high accuracy. We evaluate the effectiveness of our method with different experiments on synthetic signal simulations and physical simulations of turbulent flow dynamics.

Large-scale baseline model exploration from structural monitoring based on a novel information entropy-probability learning function

In this paper, an active learning framework for structural baseline model exploration is proposed based on the Kriging method. The framework is built to solve the problem that when the traditional Kriging approach needs to calibrate more structural parameters, the performance of Kriging predictors hinges very much upon the number of samples obtained from the finite element analysis. A novel information entropy-probability learning function is derived based on Bayesian inference and information entropy. To give a full picture, the uncertainties of different responses should also be quantified during the updating process. Then the effects of uncertainties are considered in both the learning function and objective function constructed from the posterior probabilities. The proposed algorithm is first verified experimentally by a two-span continuous beam considering different types of responses. The framework is then further improved for updating the baseline model of a cable-stayed bridge using field data. The active learning approach, as compared to the ordinary Kriging method, can achieve good performance without undue computational cost and the need for imposing weights on different responses. The proposed baseline model exploration method can be extensively applied to bridge engineering because it facilitates the calibration of numerical models using field measurements and response simulation of extreme loading with significant improvement in computational efficiency and performance of Kriging predictors.

Finite-Element Performance Degradation Behavior of a Suspension Prestressed Concrete Arch Bridge with Grouting Defects

In response to the difficulty in effectively dealing with grouting defects in corrugated pipes within a suspension prestressed concrete arch bridge, a method for assessing the deterioration in the performance of prestressed concrete girders afflicted with grouting defects was established in the present study. Specifically, a time-varying model of steel strand corrosion within grouting defects was constructed by investigating the corrosion theory of steel strands. In addition, a full-scale numerical simulation model of the long-span prestressed concrete bridge was established based on a practical project. Through the described means, the long-term impact of steel strand corrosion at various locations, lengths, and quantities on the vertical displacement and axial stress of girders was elucidated. The results reveal that in the presence of corrosion affecting 16 steel strands located in the midspan bottom plate, a vertical displacement alteration of 17.55 mm was observed in the midpoint region of the girder over a 30-year period following the bridge’s construction. Further, when considering the combined effects of concrete shrinkage, creep, and the corrosion of 16 steel strands in the midspan bottom plate, the axial compressive stress within the midpoint region of the girder decreased from an initial 6.30 MPa to 0.79 MPa over the same 30-year timeframe post-construction. It was observed that two indicators of vertical displacement and axial stress can be employed to evaluate the performance degradation of prestressed concrete bridge girders with grouting defects. The present findings may provide a reference for the operation and management of bridges with grouting defects.

Statistical moments for simulation calibration with model-bridge

Computer simulations are actively used for analyzing complex phenomena, especially in fields where access to their real-world counterparts is not feasible, such as physics, chemistry, material science, and others. The key to executing successful simulations is making sure that the parameters of a simulator reflect real-world scenarios, a tedious and error-prone effort addressed through simulation calibration. Recently, several methods have been proposed to automatize this task by learning from previously calibrated simulations using a model-bridge paradigm: a complex simulation is replaced by a simpler surrogate model, which can then be bridged to the calibrated simulation parameters. However, designing the surrogate model is a non-trivial problem involving trade-offs between simplicity of representation, interpretability and calibration accuracy, as well as the complexity of the bridge model required to map the surrogate to calibrated parameters. Further, while effective, such approaches can be non-intuitive for practitioners due to their distance from the simulation. In this paper, we view a simulation as a distribution of output variables, which can be easily represented by statistical moments. This yields a very simple and interpretable surrogate that can be bridged to calibrated parameters with a simple linear regression. We show that our method outperforms previous approaches, in terms of calibration accuracy and time, through experiments on simulations of turbulent flow dynamics and synthetic signals.

АНАЛИЗ НАПРЯЖЕННО-ДЕФОРМИРОВАННОГО СОСТОЯНИЯ КОСТНОЙ ТКАНИ ПРИ ОРТОПЕДИЧЕСКОМ ЛЕЧЕНИИ МОСТОВИДНЫМИ ПРОТЕЗАМИ С ОПОРОЙ НА ДЕНТАЛЬНЫЕ ИМПЛАНТАТЫ

Currently, structures based on dental implants are increasingly used for orthopedic treatment of partial and complete tooth loss, which can significantly improve the effectiveness of treatment and the quality of life of patients. To date, a large number of implantation systems are known, which are quite well studied, but so far, a number of issues remain unresolved, and the most important of them is the choice of the method of fixation of implantation prostheses. The main task in orthopedic treatment based on dental implants is to maintain a stable level of bone tissue, and, as a result, the long-term prospects for the functioning of the implant and the entire structure. There are two main types of fixations of such prostheses: screw and cement, but there is still no specificity in the choice of indications for them. In this study, based on mathematical modeling data, an analysis of the stress-strain state of bone tissue in the area of implants installed at different angles to each other was carried out. Mathematical models of screw-fixed bridges supported by two implants located strictly parallel to each other and at angles from 2о to 10о have been developed (conical and planar types of connection of implant platforms with abutments have been studied). The analysis of the maximum equivalent Mises stresses occurring inside the structure itself is also carried out. Stress localization zones under vertical load have been identified. The critical angles of implant divergence have been determined, which determine the indications for the use of screw-type fixation of bridges.

Modeling and vibration suppression based on Nussbaum function for beam bridge with unknown control directions and unknown nonlinear time-varying actuator faults

In this paper, the modeling of the beam bridge system with in-domain control and the vibration suppression under unknown control directions, unknown nonlinear time-varying actuator faults and external disturbances are studied. The beam bridge with fixed ends can be regarded as Euler Bernoulli beam, which is a typical distributed parameter system. Firstly, the partial differential equation (PDE) model of the beam bridge is established according to Hamilton principle. Then, an adaptive in-domain control scheme based on Nussbaum function is designed on the PDE model to eliminate the vibration of the beam bridge. It is proved theoretically that all closed-loop signals are uniformly bounded under this control law, and the vibration of the system asymptotically converges to zero. The simulation results also prove the effectiveness of the proposed control scheme. What’ more, the modeling and control scheme presented in this paper can be applied to a class of systems similar to beam bridges, such as vibration suppression of the main beam of an overhead crane bridge.

Characterizing Bridge Thermal Response for Bridge Load Rating and Condition Assessment: A Parametric Study

Temperature is the main driver of bridge response. It is continuously applied and may have complex distributions across the bridge. Daily temperature loads force bridges to undergo deformations that are larger than or equal to peak-to-peak traffic loads. Bridge thermal response must therefore be accounted for when performing load rating and condition assessment. This study assesses the importance of characterizing bridge thermal response and separating it from traffic-induced response. Numerical replicas (i.e., fine element models) of a steel girder bridge are generated to validate the proposed methodology. Firstly, a variety of temperature distribution scenarios, such as those resulting from extreme weather conditions due to climate change, are modelled. Then, nominal traffic load scenarios are simulated, and bridge response is characterized. Finally, damage is modelled as a reduction in material stiffness due to corrosion. Bridge response to applied traffic load is different before and after the introduction of damage; however, it can only be correctly quantified when the bridge thermal response is accurately accounted for. The study emphasizes the importance of accounting for distributed temperature loads and characterizing bridge thermal response, which are important factors to consider both in bridge design and condition assessment.

FE Analysis of Suspension Bridges Based on Extended Deflection Theories with Extensible Hangers and Floating Girders

This paper presents extended deflection theories of multi-span continuous suspension bridges and their FE formulations using the energy method. The proposed deflection theories take into account effects of hanger extensibility, free sliding of main cables at the saddle, and floating girders. Suspension bridge elements consisting of main girder, main cable, and tower elements are then introduced and simplified FE formulations are rigorously proposed to solve the extended deflection theories. In order to demonstrate the validity and accuracy of the presented formulation, three/four-span suspension bridge models having regular and floating support conditions of the main girder are analyzed using the simplified FEMs, and the analysis results are compared with those by the unstrained length method, which is a sophisticated FEM. Finally, three virtual earth-anchored suspension bridge models are analyzed to explore the effects of hanger extensibility.

Multiscale simulation of hygrothermal stress and mechanical properties degradation of carbon fiber reinforced polymers laminates

AbstractA mesoscopic representative volume element (RVE) model of carbon fiber reinforced polymers (CFRP) laminate with 15 plies was established based on the principle of fiber random disturbance. The RVE model was validated by comparing the elastic parameters calculated by the RVE model, Chamis model, and Bridge model. Wet stress and thermal stress were coupled using a sequential method. Macroscopic and microscopic subroutines were developed to calculate the stress–strain field of CFRP laminate and RVE model. A multiscale numerical simulation of three‐point bending of moisture‐saturated CFRP laminate was conducted. Failure process and failure modes of CFRP laminate were discussed based on the multiscale simulation and SEM observations. The results show that the RVE model and the multiscale simulation strategy presented in this work can predict the coupled hygrothermal stress and the strength degradation due to moisture absorption very well. The maximum error between the simulated and experimental averaged force of the moisture‐saturated CFRP laminate subjected to three‐point bending is about 3.4%. Multiscale simulation demonstrated that uneven distribution of fibers can result in the fiber/matrix interfaces bearing a larger transverse stress in the fiber's dense distribution area. It is the main reason that results in fiber/matrix interface failure of CFRP laminates working in hygrothermal environments.Highlights A RVE model of CFRP laminate was presented using fibers random disturbance. Coupled hygrothermal stress of single fiber and surrounded matrix was obtained. A multiscale simulation of the strength change of the CFRP plate due to wet‐thermal stress was conducted. Failure modes of CFRP laminate are discussed based on the multiscale simulation.

An evolutionary vehicle scanning method for bridges based on time series segmentation and change point detection

In this paper, the problem of bridge health monitoring is formulated as an unsupervised semantic segmentation where the aim is to identify the onset of structural damage by detecting unexpected irregularities in the time series data. In particular, the main objective of this study is to approach this problem through an indirect sensing framework based on the concept of vehicle-mounted scanning. Thus, the sole source of information is the acceleration responses of the moving vehicle passing over the bridge. This is achieved through automatic feature learning by adopting the concept of matrix profile to conduct an all-pair-similarity search for a given time series, where the location of the contextual change is determined by the corresponding Corrected Arc Crossings (CAC) profile. The performance of the method is first evaluated through numerical investigations for different damage cases where the effect of operational uncertainties such as road roughness, and variability in vehicle properties are considered. Further, the method is experimentally evaluated using a lab-scale bridge model with different damage cases. Through these investigations, it is consistently observed that the location of the change point always coincides with the minimum point of the CAC profile. The proposed framework has three major advantages making it more appealing compared to the competing techniques. First, it has been fully formulated in the context of unsupervised learning where no access to labeled data is required. Second, it is capable of working with a limited amount of data yet providing promising results. Finally, it can be easily applied to online settings where data is streaming in real-time. These successful results demonstrate the potential of the proposed method as a cost-effective and rigorous bridge inspection tool and open up opportunities in the field of indirect bridge health monitoring.

A multiscale FEM-MD coupling method for investigation into atomistic-scale deformation mechanisms of nanocrystalline metals under continuum-scale deformation

This study aims to develop a multiscale bridging method for investigating nanocrystalline metals based on macro-scale deformation. For this purpose, we propose a hierarchical multiscale computational method that can focus on some of the elements in a finite element model for scale bridging to atomistic-scale models. This method assumes that atomistic-scale nanocrystalline models are related to the integration points in a finite element and deform based on the macro-scale deformation. Nanocrystalline aluminum was chosen for the validation of the multiscale method. The finite element method (FEM) and the molecular dynamics (MD) method were used for continuum-scale and atomistic-scale simulations, respectively. We utilized the notion of the CauchyBorn rule (CBR) for communicating deformation information from the continuum scale to the atomistic scale. We studied three different cases with two nanocrystalline models and two loading cases to compare differences resulting from crystal structures and loading. Based on the crystal structure change during relaxation, nonequilibrium grain boundaries (NEGBs) were shown to play a role as deformation mechanisms in the plastic regime and induce the onset and migration of crystal defects, including deformation twins, as reported in the experiment. Furthermore, the crystal orientation dependence of the onset of crystal defects was confirmed by the comparison of the results from the two different nanocrystalline models. The qualitative agreement of the results with experimental observations is also confirmed. The proposed ‘FEM-MD’ method can bridge a large-scale gap, for example, from a nano-scale to a continuum-scale such that an MD model can be coupled to a millimeter or centimeter scale compared to other embedding methods. The present method is ideal for investigating the dislocation behavior of nanocrystalline materials, which contain multi-grained nanostructure at finite temperature, undergoing various loading scenarios at the macro-scale.

An Integrated Data-Driven System for Digital Bridge Management

Relational databases are established and widespread tools for storing and managing information. The efficient collection of information in a database appears to be a promising solution for bridge management (BM), thus facilitating the digital transition. The Italian regulatory framework on infrastructure operation and maintenance (O&M) is complex and is constantly being updated. The current plan for implementing its guidelines envisages that infrastructure managers, also on a regional scale, equip themselves with their own digital database for BM. Within this context, this research proposes an integrated methodology that collects information derived from project documentation, in situ inspections, digital surveys, and monitoring and field tests in a queryable database for digitalising, georeferencing, and creating models of many bridges. Structured query language (SQL) statements are used to efficiently export specific shared information, enabling network cross-analysis. Furthermore, the database represents the source of a geographic information system (GIS) catalogue and the basis for deriving models for building information modelling (BIM). The methodology focuses on the infrastructural context of the Lazio region, Italy, the first beneficiary of the research.

Construction Quality Control for Rutting Resistance of Asphalt Pavement Using BIM Technology

During the course of building asphalt pavement, a lack of quality control will lead to the abandonment of the asphalt mixtures. One of the most common problems with asphalt pavement is rutting. Improving the construction’s quality is an important measure to reduce rutting. The purpose is to ensure the high-temperature durability of asphalt mixtures during the construction workflow to reduce the waste of asphalt mixtures, as well as to provide a methodology for the current monitoring of the quality based on the building information modeling (BIM). Rutting resistance was appraised utilizing the static uniaxial creep examination. Oblique photography technology was used to obtain terrain data. The software of Revit 2016 was used to build the spatial model of highways and bridges. The results show that the size distribution of particles, the asphalt proportion, and the forming specimen’s temperature are the vital elements influencing the high-temperature behavior. The gradation was identified as the most important factor. The second was the asphalt binder content. Gradation variation should be given more consideration during paving using asphalt mixtures. Furthermore, the developed BIM platform can also monitor rutting resistance to reduce rework during construction.

On the effectiveness of sparse regularization for structural damage diagnosis using dynamic strain measurements

Strain measurement is considered inherently suitable for structural health monitoring due to the ease of extracting damage-sensitive features. However, the need for pre- and post-damage feature extraction, especially in the absence of baseline data for aging infrastructures in service, has engendered skepticism concerning the practical efficacy of strain-based damage diagnosis. To address this, this study incorporates limited prior information on structures and sparse regularization to ascertain the locations and severities of structural damages based on dynamic strain response data. A model-assisted approach is presented, including the typical three-step process of damage feature extraction, finite element modeling, and analytical sensitivity-based model updating. In particular, sparse regularization technique aids in robustly identifying structural damage by tackling the hindrance encountered during model updating, involving ill-posedness and the impact of measurement and modeling uncertainties. The approach’s effectiveness is substantiated through a numerical investigation of a Bailey truss bridge model exposed to operating loads and an experiment with a steel beam equipped with an array of fiber Bragg grating sensors. The results demonstrate that using the proposed damage diagnosis approach enables accurately locating and quantifying element-level damages, even when significant modeling errors or a lack of baseline features exist.

Dynamic mechanical response and damage constitutive model of end-jointed rock bridge with different water content states under impact load

In rock slope engineering, the dynamic mechanical behavior of rocks is significantly influenced by the length of rock bridges and their moisture content. This study explored the dynamic characteristics of defective rocks under impact loads through dynamic impact tests on specimens varying in rock bridge lengths and moisture states, conducted using a Split Hopkinson Pressure Bar (SHPB). The experimental results revealed that both moisture state and rock bridge length markedly affect the dynamic compressive strength and elastic modulus. Additionally, there is a significant correlation between the energy dissipation density and the specimen's moisture state and rock bridge length. The failure process, captured via a high-speed camera, exhibited a transition in fracture mode from predominantly tensile to tensile-shear failure with increasing rock bridge length. Moreover, an enhanced ZWT model was developed and validated for the dynamic damage constitutive model of defective rocks. This model, incorporating four parameters, precisely characterizes the stress–strain relationship of defective rocks under high strain rates and effectively demonstrates the dynamic response of rocks with varying rock bridge lengths and moisture states. The findings of this study are vital for advancing the understanding of rock dynamics in varying conditions and offer significant insights for geological and civil engineering applications, particularly in the design and assessment of rock structure stability in slopes.

Computationally-efficient high-fidelity nonlinear FEA of seismically isolated post-tensioned RC bridges

This study presents a novel computationally efficient high-fidelity nonlinear FEA (NLFEA) methodology for prestressed RC bridges constructed in the UAE and seismically isolated with elastomeric bearings. Specifically, the presented NLFEA methodology, using 3D solid brick elements, is shown to overcome traditional prohibitive numerical burdens. This is demonstrated without compromising accuracy or upscaling applicability and appropriateness. The proposed NLFEA approach is highlighted through detailed modeling of RC bridges’ non-traditional structural components and loading aspects (elastomeric bearings and post-tension prestressing cables). The mechanical behavior of elastomeric isolators and the RC continua, including cracking and other nonlinear phenomena, are captured via 3D solid brick elements. Moreover, the modeling procedure accurately represents the post-tension tendons’ prestressing forces and the associated effects on the RC elements. The prestressing forces are incorporated within the tendon elements via insightful manipulations of stepwise initial conditions and internal force adjustments. Additionally, load-carrying capacity determination for the elastomeric bearings was achieved by conducting a parametric investigation to capture their mechanical behavior adequately. Eventually, the analysis of a full-scale bridge is presented in this paper. The post-tensioned RC bridge understudy spans 100 m over eight elastomeric (natural rubber) seismic isolator bearings. Twelve post-tension prestressing cables are utilized to provide the bridge with continuous internal tension-balancing forces. A high-fidelity detailed FEA model of the complete bridge is developed and validated against a SAP2000 FEA model. It is shown that reasonable computational efforts can be expected without compromising the accuracy of the results.

Investigation of longitudinal movements of girder ends considering various longitudinal non-linear resistances in railway suspension bridges

The functionality of expansion joints, bearings, and dampers in suspension bridges is directly impacted by the longitudinal movement of the girder ends. The complex longitudinal resistance of the girder significantly influences this movement in railway suspension bridges. This study develops an analytical model of a railway suspension bridge using measured displacement. The model encompasses various longitudinal nonlinear resistances, including girder-rail interaction, bearing friction, and viscous dampers, enabling a detailed analysis of longitudinal motion characteristics and deformation patterns of girder ends under train loads. This study investigates the effects of various longitudinal resistances on the movement of the girder and stress within the connecting components. A novel central buckle design is proposed to reduce the stress amplitude of the central buckles in railway suspension bridges. Results show that the innovative analysis model can accurately assess the longitudinal movement of girder ends in railway suspension bridges, aligning closely with the measured. The girder displays minimal longitudinal movement under train loads, owing to the longitudinal nonlinear resistances. However, there is a significant relative longitudinal displacement between the cable and girder in short hangers, leading to a considerable increase in bending stress and vast stress in the central buckle. Consequently, when studying the longitudinal movement in railway suspension bridges, it is critical to comprehensively analyze the longitudinal displacement of girder ends and the stress across various bridge components. The novel central buckle effectively mitigates excessive stress on the central buckle during train passage and simultaneously alleviates bending stresses of the short hangers. The findings of this study offer invaluable theoretical direction and practical engineering insights for the rational design of railway suspension bridges.

Application of model updating to a large‐scale hybrid simulation

AbstractModel updating can enhance hybrid simulation by utilizing the experimental data from the physically tested substructure to update the parameters of like‐components in the numerical substructure throughout the test, improving the overall accuracy and reducing the extent of the experimental setup. Identifying and updating parameters can be challenging, especially when coupling between degrees of freedom (DOF) must be considered or the specimen experiences loading scenarios which result in newly observed behavior. To explore the performance of model updating under these challenging conditions, a large‐scale hybrid simulation was conducted using a model of a major toll bridge with seismic isolation lead rubber bearings (LRB). One LRB is physically tested considering axial, shear, and rotational loading, while the remainder of the bearings are simulated and updated with a phenomenological model within the numerical substructure. A weighted adaptive constrained unscented Kalman filter is applied as the online model updating algorithm. The study explored the effect of learning over different loading patterns, the selection of initial model parameters, and the selection of the physically tested substructure. The improvement of numerical model hysteresis performance accuracy of the force prediction demonstrates the benefits of model updating in large‐scale hybrid simulation.

A Novel Method for Full‐Field Scale Factor Calculation under Off‐Axis Measurements for Vision‐Based Structural Multipoint Displacement Measurement and Health Monitoring

For vision‐based structural displacement measurement and health monitoring, the scale factor (SF) calculation plays a pivotal role in converting the pixel displacement into the actual one. On the other hand, for the current SF calculation methods, the object distance, between the to‐be‐measured points on the object plane and the optical center of the shooting instrument, has to be measured in advance due to the existence of the pitch and horizontal angle under off‐axis measurement. Unfortunately, it is usually inefficient, difficult, and even impossible to obtain the object distances for all the to‐be‐measured points, especially for the full‐field displacement monitoring on huge scale structures. In this paper, a novel SF calculation method was proposed to calculate the full‐field scale factor of the host structure under off‐axis measurement by combining with the similarity relation of the camera imaging model. With the help of this method, all the scale factors of the to‐be‐measured points can be calculated accurately and highly efficiently, as long as the object distance of any one point or the geometric dimensions of any feature object on the object surface is provided. In addition, to quantitatively assess the SF calculation accuracy of the method, a static vision‐based measurement investigation was firstly conducted, and then, two experimental investigations about the multipoint and full‐field structural displacement measurement on a cable‐stayed bridge model and a simply supported beam model were conducted to validate the effectiveness and feasibility of the proposed method. Finally, all the results demonstrated that the proposed method exhibits an excellent performance on the SF calculation under off‐axis measurement and provides a great potential to be utilized for the vision‐based structural multipoint and full‐field displacement measurement and health monitoring.

The Benefits and Burdens of Being In-between. Discourses in European Parliament on Turkey’s Identity and Geopolitical Role in the Syrian Civil War

This article researches discursive practices of Members of European Parliament (MEPs) regarding Turkey’s identity and geopolitical role in the context of the Syrian Civil War from 2011 to 2016. It argues that MEPs struggled to accept Turkey’s in-betweenness: being European and Islamic/Asian simultaneously. This became particularly visible when Turkish foreign policy-behaviour in the region was colliding with European interests and authoritarianism in Turkey kept increasing. As a result, Turkey was framed more and more as non-European by referring to its religion, history and geography. However, MEPs believed cooperation with Turkey to be necessary due to its (growing) role in the conflict and the region in general. In that vein, parliamentary discourses shifted from EU membership to strategic partnership; perceiving Turkey as a key (regional) actor instead of a bridge and role model. Overall, the article gives valuable insights into the EU’s perception of its own identity and (normative) role, and tensions and challenges related to it.