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In addition to the traditional benefits associated with the installation of structural health monitoring systems, reductions in construction, operational and maintenance costs, and improved performance and quality can be achieved by effectively using the acquired data. However, considered in isolation, the raw data are of little use and value. They must be processed and put into a geometric context within the infrastructure asset, which facilitates the interpretation and analysis of the data. This supports informed decision making, which in turn leads to effective actions. This study outlines a new approach that enables the modelling of structural performance monitoring systems in a Building Information Modelling (BIM) environment and hence permits sensor data to be visualised directly on BIM models. The paper addresses aspects related to: (a) interoperability and standard data models; (b) management and visualisation of monitoring data; and (c) data interpretation and analysis. A prestressed concrete bridge, with a comprehensive built-in structural performance monitoring system, has been used as a case study. The case study demonstrates that by including and visualising monitoring data directly on BIM models the acquired data gain geometrical context within the built asset, which facilitates better interpretation, analysis and all the data-sharing benefits associated with the BIM approach.

This study investigates integrating fibre optic sensing technology into the production process of concrete railway sleepers. Robust fibre Bragg grating (FBG) strain and temperature sensor arrays were developed specifically for this application and were designed for long-term monitoring of sleeper performance. The sensors were used to monitor sleeper production and to help gain a deeper understanding of their early-age behaviour which can highly influence long-term performance. Twelve sleepers were instrumented and strain data were collected during the entire manufacturing process including concrete casting and curing, prestressing strand detensioning, and qualification testing. Following the production process, sleepers were stored temporarily and monitored for four months until being placed in service. The monitoring results highlight the intrinsic variability in strain development among identical sleepers, despite high levels of production quality control. Using prestress loss as a quality control indicator, the integrated sensing system demonstrated that sleepers were performing within Eurocode-based design limits prior to being placed in service. A 3D nonlinear finite element (FE) model was developed to provide additional insight into the sleepers' early-age behaviour. Based on the FBG-calibrated FE model, more realistic estimates for the creep coefficient were provided and found to be 48% of the Eurocode-predicted values.

Numerous methods are available for the assessment of masonry arch bridges at the ultimate limit state, however there is a lack of suitable methods for assessing behaviour at service levels of loading. To address this, nonlinear three dimensional finite element models which consider constitutive material models enabling progressive cracking and failure of the complete structural system were used to investigate the development of damage for three masonry arch bridges at both service levels and at the ultimate capacity. All of the elements contributing to the strength of structure were represented in the models including the arch barrel, spandrel, abutments, fill and surrounding soil. This allowed for consideration of the longitudinal and transverse capacities, the stiffening effects of the spandrel walls, the restraint and load distribution provided by the fill, the frictional behaviour between the masonry and fill, movement at the abutments and multiple causes of failure. While complex nonlinear finite element models are able to identify the ultimate load capacity there are alternate simpler approaches available for this, and it is the investigation of damage and crack propagation at service level loads where their use is of greatest benefit. Notation: c cohesion f1 ultimate compressive strength for a state of biaxial compression superimposed on the ambient hydrostatic stress state f2 ultimate compressive strength for a state of uniaxial compression superimposed on the ambient hydrostatic stress state fc ultimate uniaxial compressive strength fcb ultimate biaxial compressive strength ft ultimate uniaxial tensile strength E Young's modulus βt shear transfer coefficient for an open crack βc shear transfer coefficient for a closed crack µ coefficient of friction ν Poisson's ratio ρ density σh hydrostatic stress state σh a ambient hydrostatic stress state σxp, σyp, σzp principal stresses in principal directions ϕ angle of internal friction ϕf angle of dilatancy