Maximum Probabilistic Traffic Load Effects on Large Bridges Based on Long-term Traffic Monitoring Data

With the steadily growing of global transportation market, the traffic load has increased dramatically over the past decades, which may develop into a risk source for existing bridges. The simultaneous presence of heavy trucks that are random in nature governs the serviceability limit for large bridges. This study investigated probabilistic traffic load effects on large bridges under actual heavy traffic load. Initially, critical stochastic traffic loading scenarios were simulated based on millions of traffic monitoring data in a highway bridge in China. A methodology of extrapolating maximum traffic load effects was presented based on the level-crossing theory. The effectiveness of the proposed method was demonstrated by probabilistic deflection investigation of a suspension bridge. Influence of traffic density variation and overloading control on the maximum deflection was investigated as recommendations for designers and managers. The numerical results show that the congested traffic mostly governs the critical traffic load effects on large bridges. Traffic growth results in higher maximum deformations and probabilities of failure of the bridge in its lifetime. Since the critical loading scenario contains multi-types of overloaded trucks, an effective overloading control measure has a remarkable influence on the lifetime maximum deflection. The stochastic traffic model and corresponding computational framework is expected to be developed to more types of bridges.

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Probabilistic evaluation of maximum dynamic traffic load effects on cable-supported bridges under actual heavy traffic loads

Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability ◽

10.1177/1748006x20938491 ◽

2020 ◽

pp. 1748006X2093849

Author(s):

Yang Liu ◽

Qinyong Wang ◽

Naiwei Lu

Keyword(s):

Heavy Traffic ◽

Suspension Bridge ◽

Traffic Monitoring ◽

Traffic Load ◽

Dynamic Traffic ◽

Type Distribution ◽

Cable Stayed Bridge ◽

Weigh In Motion ◽

Load Effects ◽

Motion Measurements

The traffic load has grown significantly in recent years, which might be a threat for the service safety of existing bridges. Thus, it is an urgent task to assess the actual traffic load effects on bridges, considering actual heavy traffic load instead of design traffic load. This study presents a framework for extrapolating maximum dynamic traffic load effects on large bridges using site-specific traffic monitoring data. The framework involves vehicle–bridge interaction analysis and probabilistic modelling of extreme values. The weigh-in-motion measurements of a busy highway in China were collected for stochastic traffic load modelling. Case studies of two long-span cable-supported bridge based on the weigh-in-motion measurements were conducted to demonstrate the effectiveness of the proposed framework. It is demonstrated that Rice’s level-crossing approach can capture both dynamic and probabilistic characteristics of the traffic load effects. The root-mean-square displacement of the cable-stayed bridge follows a C-type distribution, and the one for the suspension bridge follows an M-type distribution, which is associated with the first-order mode shapes of the two types of bridges. The amplification factors for the cable-stayed bridge and the suspension bridge are 5.9% and 3.6%, respectively. The numerical analysis indicates that the dynamic effect for extrapolation is weaker with the increase in bridge span length, but the effect of traffic volume growth will be more significant.

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Damage Detection Based on Structural Responses Induced by Traffic Load: Methodology and Application

International Journal of Structural Stability and Dynamics ◽

10.1142/s0219455416400265 ◽

2016 ◽

Vol 16 (04) ◽

pp. 1640026 ◽

Cited By ~ 10

Author(s):

Shouwang Sun ◽

Limin Sun ◽

Lin Chen

Keyword(s):

Damage Detection ◽

Traffic Load ◽

Monitoring Data ◽

Random Disturbance ◽

Influence Line ◽

Structural Deterioration ◽

Structural Responses ◽

Long Term Monitoring ◽

Term Monitoring

In consideration of the important role that bridges play in transportation system, their safety, durability and serviceability have always been deeply concerned. Recently, many long-span bridges have been instrumented with Structural Health Monitoring Systems (SHMS) to provide bridge engineers with the information needed for decisions-making in management and maintenance. However, efficient use of monitoring data remains a challenge confronted before engineers. Recently, methodologies based on monitoring data while robust to random disturbance and sensitive to damage have received worldwide attention. In this context, this study proposes an innovative damage detection methodology based on structural responses induced by traffic load. First, vehicle-induced strain responses are found to be separable from the strain induced by operational loads, owing to their unique characteristics. This is achieved by a detailed investigation on the relationship between strain measurements and operational loads including temperature, wind as well as vehicles based on long-term monitoring data. From the vehicular load and pertinent strain response, the strain influence line (SIL) can be further identified. As a structural signature, SIL can be used to provide a reasonable assessment of the bridge health condition at least in the vicinity of strain monitoring point. Two damage indexes are therefore derived from the identified SIL, which are promising for damage evaluation because they are: (a) capable of revealing structural deterioration; (b) immune to influences of environmental changes; (c) adaptable to the random characteristic exhibited by long-term monitoring data. Besides, the SIL identification procedure and its theoretical basis are elaborated to respectively handle the case where the vehicle load is available or not, which is also applicable to identify the influence line of other measurements such as stresses. The proposed damage methodology is applied to the cable-stayed bridge spanning the main navigation channel of Shanghai Yangtze River Bridge, and the result shows its effectiveness.

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