Gabriel Antonio del Pozo Alarcon

About

Structures close to reaching their design service life, such as a significant proportion of European bridges, require careful and continuous control and supervision to ensure safe usage. As bridges age, they can become increasingly vulnerable to damage and failure because of degradation mechanisms and increasing load requirements. Structural Health Monitoring (SHM) of bridges is the process of using various sensors and measurement techniques to monitor the condition of a bridge and detect any changes or damage that may occur over time. This can include monitoring the structural integrity of the bridge, as well as monitoring the environment around the bridge, such as temperature, humidity, and wind. The data collected by the sensors is then analyzed to identify any potential issues or problems and to help engineers make decisions about maintenance and repairs. SHM can help to increase the safety and longevity of bridges and can also help to reduce the costs associated with maintenance and repairs.

Machine learning has a significant role in vibration-based data-based SHM systems. It can be used to analyze the large amounts of data collected by the sensors, identify patterns, and detect anomalies. Machine learning algorithms can also be used to develop statistical models of a bridge's normal dynamic response, which can then be used to detect when the response deviates from this baseline, indicating a problem or damage. In short, sensors are used to measure the vibrations of a bridge, whereas machine learning algorithms are used to analyze the data and identify patterns and anomalies. This approach can provide a powerful tool for monitoring the condition of bridges and ensuring their safety and integrity over time.

Publications

Full-scale tests of a lightweight footbridge: The Folke Bernadotte Bridge

In Current Perspectives and New Directions in Mechanics, Modelling and Design of Structural Systems

Optimization and automatization of end-bearing pile groups

MSc thesis on the application of a Genetic Algorithm for automation and optimization of end-bearing pile groups.

The Effects of an Extended Sensitivity Analysis of Sensor Configurations for Bridge Damage Detection Using Experimental Data

The damage detection capabilities of sensor setups are essential for any structural health monitoring (SHM) system. In this chapter, the performance of different subsets of sensor configurations selected from a set of 40 accelerometers is evaluated.

Implementation of decision analysis on a structural health monitoring system applied to a bridge benchmark study

This paper presents an investigation into the connection between SHM and decision-making via Bayesian decision theory and the value of information (VoI) obtained from SHM.

2024

Dederichs, Anno Christian; del Pozo Alarcon, Gabriel Antonio; Svendsen, Bjørn Thomas; Øiseth, Ole Andre. (2024) A new damage detector for bridges based on natural frequencies with missing data. Structural Health Monitoring
Academic article

2023

del Pozo Alarcon, Gabriel Antonio; Svendsen, Bjørn Thomas; Øiseth, Ole Andre. (2023) Implementation of Decision Analysis on a Structural Health Monitoring System Applied to a Bridge Benchmark Study.
Academic chapter/article/Conference paper
del Pozo Alarcon, Gabriel Antonio; Svendsen, Bjørn Thomas; Øiseth, Ole Andre. (2023) The Effects of an Extended Sensitivity Analysis of Sensor Configurations for Bridge Damage Detection Using Experimental Data. Springer
Academic chapter/article/Conference paper

Journal publications

Dederichs, Anno Christian; del Pozo Alarcon, Gabriel Antonio; Svendsen, Bjørn Thomas; Øiseth, Ole Andre. (2024) A new damage detector for bridges based on natural frequencies with missing data. Structural Health Monitoring
Academic article

Part of book/report

del Pozo Alarcon, Gabriel Antonio; Svendsen, Bjørn Thomas; Øiseth, Ole Andre. (2023) Implementation of Decision Analysis on a Structural Health Monitoring System Applied to a Bridge Benchmark Study.
Academic chapter/article/Conference paper
del Pozo Alarcon, Gabriel Antonio; Svendsen, Bjørn Thomas; Øiseth, Ole Andre. (2023) The Effects of an Extended Sensitivity Analysis of Sensor Configurations for Bridge Damage Detection Using Experimental Data. Springer
Academic chapter/article/Conference paper

Språkvelger

Gabriel Antonio del Pozo Alarcon