• Smart Structures and Systems
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• v.32 no.1
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• pp.49-59
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• 2023

A bridge transportation network supplies products from various source nodes to destination nodes through bridge structures in a target region. However, recent frequent earthquakes have caused damage to bridge structures, resulting in extreme direct damage to the target area as well as indirect damage to other lifeline structures. Therefore, in this study, a surrogate model-based comprehensive framework to estimate the seismic resilience of bridge transportation networks is proposed. For this purpose, total system travel time (TSTT) is introduced for accurate performance indicator of the bridge transportation network, and an artificial neural network (ANN)-based surrogate model is constructed to reduce traffic analysis time for high-dimensional TSTT computation. The proposed framework includes procedures for constructing an ANN-based surrogate model to accelerate network performance computation, as well as conventional procedures such as direct Monte Carlo simulation (MCS) calculation and bridge restoration calculation. To demonstrate the proposed framework, Pohang bridge transportation network is reconstructed based on geographic information system (GIS) data, and an ANN model is constructed with the damage states of the transportation network and TSTT using the representative earthquake epicenter in the target area. For obtaining the seismic resilience curve of the Pohang region, five epicenters are considered, with earthquake magnitudes 6.0 to 8.0, and the direct and indirect damages of the bridge transportation network are evaluated. Thus, it is concluded that the proposed surrogate model-based framework can efficiently evaluate the seismic resilience of a high-dimensional bridge transportation network, and also it can be used for decision-making to minimize damage.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.3
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• pp.43-52
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• 2004

This paper describes a method of evaluating seismic system performance of highway transportation network in California. The basic element that plays a crucial role in this study is the fragility information of highway bridges in Caltrans' (California Department of Transportation) freeway network. The bridge fragility information is expressed as a function of the ground motion intensity, such as peak ground acceleration (PGA) or peak ground velocity (PGV). Network damage was evaluated under the 1994 Northridge earthquake and scenario earthquakes. A probabilistic model was developed to determine the effect of repair of bridge damage on the improvement of the network performance as days passed after the event. As an example, the system performance degradation measured in terms of an index, “Drivers Delay”, is calculated for the Los Angeles area transportation system, and losses due to Drivers Delay with and without retrofit were estimated.

• Smart Structures and Systems
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• v.15 no.3
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• pp.543-553
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• 2015

The condition of the vehicular bridge network in New York City, as represented by ratings obtained during biennial inspections is reviewed over a period of three decades. Concurrently, the bridges comprising the network are considered as networks of structural elements whose condition defines the overall bridge condition according to New York State assumptions. A knowledge-based matrix of assessments is used in order to determine each element's vulnerability and impact within the network of an individual structure and the network of City bridges. In both networks expansion deck joints emerge as the weak link. Typical joint failures are illustrated. Bridge management options for maintenance, preservation, rehabilitation and replacement are examined in the context of joint performance.

• International Journal of Concrete Structures and Materials
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• v.2 no.2
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• pp.91-98
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• 2008

Curved bridges are important components of a highway transportation network for connecting local roads and highways, but very few data have been collected in terms of their field performance. This paper presents two-years monitoring and system identification results of a curved concrete box-girder bridge, the West St. On-Ramp, under ambient traffic excitations. The authors permanently installed accelerometers on the bridge from the beginning of the bridge life. From the ambient vibration data sets collected over the two years, the element stiffness correction factors for the columns, the girder, and boundary springs were identified using the back-propagation neural network. The results showed that the element stiffness values were nearly 10% different from the initial design values. It was also observed that the traffic conditions heavily influence the dynamic characteristics of this curved bridge. Furthermore, a probability distribution model of the element stiffness was established for long-term monitoring and analysis of the bridge stiffness change.

• Structural Monitoring and Maintenance
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• v.9 no.4
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• pp.359-371
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• 2022

Bridges are critical to the civil engineering infrastructure network as they facilitate movement of people, the transportation of goods and services. Given the aging of bridge infrastructure, federal officials mandate visual inspections biennially to identify necessary repair actions which are time, cost, and labor-intensive. Additionally, the expansion joints of bridges are rarely monitored due to cost. However, expansion joints are critical as they absorb movement from thermal effects, loadings strains, impact, abutment settlement, and vehicle motion movement. Thus, the need to monitor bridge expansion joints efficiently, at a low cost, and wirelessly is desired. This paper addresses bridge joint monitoring needs to develop a cost-effective, real-time wireless system that can be validated in a full-scale bridge structure. To this end, a wireless expansion joint monitoring was developed using commercial-off-the-shelf (COTS) sensors. An in-service bridge was selected as a testbed to validate the performance of the developed system compared with traditional displacement sensor, LVDT, temperature and humidity sensors. The short-term monitoring campaign with the wireless sensor system with the internet protocol version 6 over the time slotted channel hopping mode of IEEE 802.15.4e (6TiSCH) network showed reliable results, providing high potential of the developed system for effective joint monitoring at a low cost.

• Smart Structures and Systems
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• v.32 no.5
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• pp.297-308
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• 2023

Dynamic deflection is important for evaluating the performance of a long-span cable-stayed bridge, and its continuous measurement is still cumbersome. This study proposes a dynamic deflection monitoring method for cable-stayed bridge based on Bi-directional Long Short-term Memory (BiLSTM) neural network taking advantages of the characteristics of spatial variation of cable acceleration response (CAR) and main girder deflection response (MGDR). Firstly, the relationship between the spatial and temporal variation of the CAR and the MGDR is described based on the geometric deformation of the bridge. Then a data-driven relational model based on BiLSTM neural network is established using CAR and MGDR data, and it is further used to monitor the MGDR via measuring the CAR. Finally, numerical simulations and field test are conducted to verify the proposed method. The root mean squared error (RMSE) of the numerical simulations are less than 4 while the RMSE of the field test is 1.5782, which indicate that it provides a cost-effective and convenient method for real-time deflection monitoring of cable-stayed bridges.

• Earthquakes and Structures
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• v.26 no.2
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• pp.87-96
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• 2024

This paper proposes a logistic multinomial regression approach to model the spatial cross-correlation of damage probabilities among different damage states in an expanded transportation network. Utilizing Bayesian theory and the multinomial logistic model, we analyze the damage states and probabilities of bridges while incorporating damage correlation. This correlation is considered both between bridges in a network and within each bridge's damage states. The correlation model of damage probabilities is applied to the seismic assessment of a portion of Tehran's transportation network, encompassing 26 bridges. Additionally, we introduce extra daily traffic time (EDTT) as an operational parameter of the transportation network and employ the shortest path algorithm to determine the path between two nodes. Our results demonstrate that incorporating the correlation of damage probabilities reduces the travel time of the selected network. The average decrease in travel time for the correlated case compared to the uncorrelated case, using two selected EDTT models, is 53% and 71%, respectively.

• Computational Structural Engineering : An International Journal
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• v.2 no.1
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• pp.11-17
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• 2002

Cost-effectiveness in design is considered for determining the target reliability of concrete bridges under seismic actions. This objective can be achieved based on the economic optimization of the expected life-cycle cost of a bridge, which includes initial cost, direct losses, and indirect losses of a bridge due to strong earthquakes over its lifetime. A separating factor is defined to consider the redundancy of a transportation network. The Park-Ang damage model is employed to define the damage of a bridge under seismic action, and a Monte Carlo method based on the DRAIN-2DX program is developed to assess the failure probability of a bridge. The results for an example bridge analyzed in this paper show that the optimal target failure probability depends on the traffic volume carried by the bridge and is between 1.0×10/sup -3/ to 3.0×10/sup -3/ over a life of 50 years.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.415-426
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• 2013

Condition assessment and monitoring of bridges is critical for safe passenger travel, public transportation, and efficient freight. In monitoring, displacement measurement capability is important to keep track of performance of bridge, in part or as whole. One of the most important parts of a bridge is the expansion joint, which accommodates continuous cyclic thermal expansion of the whole bridge. Though expansion joint is critical for bridge performance, its inspection and monitoring has not been considered significantly because the monitoring requires long-term data using cost intensive equipment. Recently, a wireless smart sensor network (WSSN) has drawn significant attention for transportation infrastructure monitoring because of its merits in low cost, easy installation, and versatile on-board computation capability. In this paper, a rapid wireless displacement monitoring system, wireless hybrid sensor (WHS), has been developed to monitor displacement of expansion joints of bridges. The WHS has been calibrated for both static and dynamic displacement measurement in laboratory environment, and deployed on an in-service highway bridge to demonstrate rapid expansion joint monitoring. The test-bed is a continuous steel girder bridge, the Founders Bridge, in East Hartford, Connecticut. Using the WHS system, the static and dynamic displacement of the expansion joint has been measured. The short-term displacement trend in terms of temperature is calculated. With the WHS system, approximately 6% of the time has been spent for installation, and 94% of time for the measurement showing strong potential of the developed system for rapid displacement monitoring.

• Computers and Concrete
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• v.32 no.4
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• pp.411-423
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• 2023

The rapid development of road transport has increased the number of bridges that require widening. A critical issue in the construction of bridge widening is the influence of vibrations of the old bridge on the casting of wet joint concrete between the old and new bridges owing to the running traffic. Typically, the bridge is closed to traffic during the pouring of wet joint concrete, which negatively affects the existing transportation network. In this study, a newly developed microscopic traffic load modeling approach and the vehicle-bridge interaction theory are incorporated to develop a refined numerical framework for the analysis of random traffic-bridge coupled dynamics. This framework was used to investigate traffic-induced vibrations at the wet joint of a widened bridge. Based on an experimental study on the vibration resistance of wet joint concrete, traffic control strategies were proposed to ensure the construction performance of cast-in-site wet joint concrete under random traffic without interruption. The results show that the vibration displacement and frequency of the old bridge, estimated by the proposed framework, were comparable with those obtained from field measurements. Based on the target peak particle velocity and vibration amplitude of the wet joint concrete, it was found that traffic control measures, such as limiting vehicle gross weight and limiting traffic volume by closing an additional traffic lane, could ensure the construction performance of the wet joint concrete.