Nonlinear Temperature Distributions in Bridges at Different Locations in the United States

Potgieter, I C; Gamble, William L.

doi:10.15554/pcij.07011989.80.103

Cited by 39 publications

(28 citation statements)

References 4 publications

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“…Temperatures at the top chord of the truss are up to 10°C higher than that of the bottom chord. This vertical temperature gradient is similar to those observed in other test-beds [21] and full-scale structures [26].…”

Section: Simulated Scenariossupporting

confidence: 88%

“…Variations in environmental conditions and in particular temperatures have a major influence on the structural response of bridges. Real-life bridges experience complex temperature distributions that can vary nonlinearly in all three spatial dimensions [24]- [26]. Potgieter and Gamble [26] showed using measurements from an existing box girder bridge that stresses and forces due to nonlinear temperature distributions are often of magnitudes comparable to those due to live loads.…”

Section: Thermal Response Of Bridgesmentioning

confidence: 99%

“…Real-life bridges experience complex temperature distributions that can vary nonlinearly in all three spatial dimensions [24]- [26]. Potgieter and Gamble [26] showed using measurements from an existing box girder bridge that stresses and forces due to nonlinear temperature distributions are often of magnitudes comparable to those due to live loads. These are also confirmed by real measurements from full-scale structures wherein time-series of response measurements often resemble those of measured ambient temperatures.…”

Section: Thermal Response Of Bridgesmentioning

confidence: 99%

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SHM of bridges: characterising thermal response and detecting anomaly events using a temperature-based measurement interpretation approach

Kromanis

Kripakaran

2016

J Civil Struct Health Monit

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Abstract:A major bottleneck preventing widespread use of Structural Health Monitoring (SHM) systems for bridges is the difficulty in making sense of the collected data. Characterising environmental effects in measured bridge behaviour, and in particular the influence of temperature variations, remains a significant challenge. This paper proposes a novel data-driven approach referred to as Temperature-Based Measurement Interpretation (TB-MI) approach to solve this challenge. The approach is composed of two key steps -(i) characterisation of thermal effects in bridges using a methodology referred to as Regression-Based Thermal Response Prediction (RBTRP) methodology, and (ii) detection of anomaly events by analysing differences between measured and predicted structural behaviour. Measurements from a laboratory truss structure that is setup to simulate a range of structural scenarios are employed to evaluate the performance of the TB-MI approach. The study examines how the predictive capability of the RBTRP methodology is influenced by dimensionality reduction and measurement down-sampling, which are common pre-processing techniques used to deal with high spatial and temporal density in measurements. It also proposes a novel anomaly detection technique referred to as signal subtraction method that detects anomaly events from timeseries of prediction errors, which are computed as the difference between in-situ measurements and predictions obtained using the RBTRP methodology. Results demonstrate that the TB-MI approach has potential for integration within data interpretation frameworks of SHM systems of full-scale bridges. Keywords: structural health monitoring; thermal effects; data-driven methods; anomaly detection; measurement interpretation. Rolands AcknowledgmentsThe authors would like to express their gratitude to Bill Harvey Associates and Pembrokshire County Council for providing access to the measurements of the Cleddau Bridge, and to Elena Barton (National Physical Laboratory) for providing the data from the National Physical Laboratory Footbridge project.

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Section: Simulated Scenariossupporting

confidence: 88%

Section: Thermal Response Of Bridgesmentioning

confidence: 99%

Section: Thermal Response Of Bridgesmentioning

confidence: 99%

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SHM of bridges: characterising thermal response and detecting anomaly events using a temperature-based measurement interpretation approach

Kromanis

Kripakaran

2016

J Civil Struct Health Monit

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“…Temperature distributions across full-scale structures could be very complex depending upon various factors such as their geographic location, their shape and orientation, and the surrounding environment. Temperature gradients in bridges are often non-linear [18] such that they introduce thermal stresses even in bridge girders with simple supports. Potgieter and Gamble [18] showed using measurements from an existing box girder bridge that stresses and forces due to nonlinear temperature distributions are often of magnitudes comparable to those due to live loads.…”

Section: Temperature Effects In Bridgesmentioning

confidence: 99%

“…Temperature gradients in bridges are often non-linear [18] such that they introduce thermal stresses even in bridge girders with simple supports. Potgieter and Gamble [18] showed using measurements from an existing box girder bridge that stresses and forces due to nonlinear temperature distributions are often of magnitudes comparable to those due to live loads. Bridge engineers therefore give significant importance to thermal effects and consequently, bridge designs either incorporate ways of accommodating thermal movements (e.g.…”

Section: Temperature Effects In Bridgesmentioning

confidence: 99%

Predicting thermal response of bridges using regression models derived from measurement histories

Kromanis

Kripakaran

2014

Computers & Structures

107

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This study investigates the application of novel computational techniques for structural performance monitoring of bridges that enable quantification of temperature-induced response during the measurement interpretation process. The goal is to support evaluation of bridge response to diurnal and seasonal changes in environmental conditions, which have widely been cited to produce significantly large deformations that exceed even the effects of live loads and damage. This paper proposes a regression-based methodology to generate numerical models, which capture the relationships between temperature distributions and structural response, from distributed measurements collected during a reference period. It compares the performance of various regression algorithms such as multiple linear regression (MLR), robust regression (RR) and support vector regression (SVR) for application within the proposed methodology. The methodology is successfully validated on measurements collected from two structures -a laboratory truss and a concrete footbridge. Results show that the methodology is capable of accurately predicting thermal response and can therefore help with interpreting measurements from continuous bridge monitoring.

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Thermal Loads and Moments in Reinforced Concrete Integral Bridges

Skorpen

Kearsley

2023

Lecture Notes in Civil Engineering

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Nonlinear Temperature Distributions in Bridges at Different Locations in the United States

Cited by 39 publications

References 4 publications

SHM of bridges: characterising thermal response and detecting anomaly events using a temperature-based measurement interpretation approach

SHM of bridges: characterising thermal response and detecting anomaly events using a temperature-based measurement interpretation approach

Predicting thermal response of bridges using regression models derived from measurement histories

Thermal Loads and Moments in Reinforced Concrete Integral Bridges

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