11 research outputs found

    Structural Performance Monitoring Using a Dynamic Data-Driven BIM Environment

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    Structural health monitoring data has not been fully leveraged to support asset management due to a lack of effective integration with other datasets. A Building Information Modelling (BIM) approach is presented to leverage structural monitoring data in a dynamic manner. The approach allows for the automatic generation of parametric BIM models of structural monitoring systems that include time-series sensor data; and it enables data-driven and dynamic visualisation in an interactive 3D environment. The approach supports dynamic visualisation of key structural performance parameters, allows for the seamless updating and long-term management of data, and facilitates data exchange by generating Industry Foundation Classes (IFC) compliant models. A newly-constructed bridge near Stafford, UK, with an integrated fibre-optic sensor based monitoring system was used to test the capabilities of the developed approach. The case study demonstrated how the developed approach facilitates more intuitive data interpretation, provides a user-friendly interface to communicate with various stakeholders, allows for the identification of malfunctioning sensors thus contributing to the assessment of monitoring system durability, and forms the basis for a powerful data-driven asset management tool. In addition, this project highlights the potential benefits of investing in the development of data-driven and dynamic BIM environments

    Real-time statistical modelling of data generated from self-sensing bridges

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    Instrumentation of infrastructure is changing the way engineers design, construct, monitor and maintain structures such as roads, bridges and underground structures. Data gathered from these instruments have changed the hands-on assessment of infrastructure behaviour to include data processing and statistical analysis procedures. Engineers wish to understand the behaviour of the infrastructure and detect changes – for example, degradation – but are now using high-frequency data acquired from a sensor network. Presented in this paper is a case study that models and analyses in real time the dynamic strain data gathered from a railway bridge which has been instrumented with fibre-optic sensor networks. The high frequency of the data combined with the large number of sensors requires methods that efficiently analyse the data. First, automated methods are developed to extract train passage events from the background signal and underlying trends due to environmental effects. Second, a streaming statistical model which can be updated efficiently is introduced that predicts strain measurements forward in time. This tool is enhanced to provide anomaly detection capabilities in individual sensors and the entire sensor network. These methods allow for the practical processing and analysis of large data sets. The implementation of these contributions will be essential for demonstrating the value of self-sensing structures. </jats:p

    Centrifuge modelling of the initiation of cracks in a clay liner subjected to differential settlement with and without overburden pressure

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    Compacted clay liners are used in the basal and capping layers of landfills to separate the waste material from the environment. These liners are subjected to differential settlement through degradation of the waste or compression of the subgrade. This differential settlement induces cracking in the liner, and reduces the effectiveness of the clay as an environmental protection barrier. Physical model tests were conducted in the geotechnical centrifuge to study the influence of differential settlement on clay liners and observe the crack mechanism using a consolidated kaolin clay to model the clay liner. Differential settlement was imposed on the clay beam by means of a trapdoor. Cracking in the clay was monitored through digital analysis of images taken as the tests were conducted using particle image velocimetry. The test investigated the orientation and types of cracks formed with varying void dimensions and with and without overburden pressure. The unconfined clay over the small trapdoor was able to support itself across the void; a punching shear failure occurred in the case of a wider trapdoor or greater overburden pres sure

    Pile defect assessment using distributed temperature sensing: fundamental questions examined

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    Thermal integrity testing has been successfully used to assess the quality of cast-in-place piles for the past decade. It employs temperature data measured during concrete curing to identify defects along the piles’ length. However, the uptake of this technology has been rather limited in the piling industry. The main concerns are that the method is not standardised and its reliability is not well understood. In order to address these, there are a number of fundamental questions that need to be explored in more detail, including (a) the optimum time to conduct the assessment, (b) the defect thermal impact, (c) the zone of influence on temperature sensors, (d) the minimum detectable size of a defect and (e) the associated optimum sensor location required. In this paper, experimental and numerical studies were conducted to examine these questions. Fibre optic sensors were employed on model concrete piles in laboratory tests to provide fully distributed temperature data throughout the curing process. The test results showed that the optimum time to assess the defects is approximately at 60% of the time to reach peak temperature and the minimal detectable defect size, using the currently available optical fibre sensor technology, is 4% of the cross-sectional area. In addition, the thermal influence of different defect sizes is presented. Following this, it is shown in the paper that the minimum numbers of sensor cables required to identify defects with cross-sectional areas of 4%, 5% and 8% are eight, six and four cables, respectively. The optimum layout of these sensor cables within a pile cross-section has also been discussed. When specifying pile instrumentation for integrity assessment, the findings of this paper enable practising engineers to make informed judgements in relation to the size of defects they would like to detect (and hence the associated risk this entails) together with the corresponding instrumentation layout required.</p
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