Pervasive Fibre-optic sensor networks in bridges: A UK case study

© 2018 Taylor & Francis Group, London. Integrating fibre-optic sensor networks in a newly-constructed infrastructure assets enables datadriven performance assessment during its construction and throughout its operational life. As part of a multimillion pound railway infrastructure redevelopment project, two new railway bridges were instrumented with an extensive network of both discrete (fibre Bragg gratings or FBGs) and distributed (based on Brillouin optical time domain reflectometry or BOTDR) fibre optic sensors to measure both strain and temperature throughout construction and in-service. Completed in 2016 in Staffordshire UK, both ‘self-sensing’ bridges contain more than 500 fibre Bragg grating sensors and over 600 metres of distributed fibre optic sensor cabling. This paper describes the sensing technologies employed, installation techniques for improving sensing robustness, the monitoring programme and objectives, data processing methods and assumptions, and the primary monitoring findings of this project. Results related to measurements of prestress losses in prestressed concrete girders, estimates of steel girder deflection using FBGs and videogrammetry, and assessments of percentage utilization of critical superstructure elements are presented. In terms of future directions, BIM-based environments which incorporate sensor elements and an emerging field of research known as Data-Centric Engineering are introduced as tools to better manage, maintain and learn from the information generated from self-sensing infrastructure.EPSRC, Innovate UK and the Lloyd's Register Foundation for funding this research through the Centre for Smart Infrastructure and Construction (CSIC) Innovation and Knowledge Centre and the Alan Turing Institute

The response of embedded strain sensors in concrete beams subjected to thermal loading

A wide range of commercially available sensors are frequently used to record the response of civil engineering structures that may be subjected to unexpected loading scenarios, changes of environmental conditions or material deterioration. However, a common problem faced when using these sensors is to distinguish strain changes experienced by the structure due to a temperature change from strain changes that occur due to other causes. Temperature effects on strain sensors are usually accommodated by allowing for temperature effects (temperature compensation); however, there is limited research in the literature that investigates the performance of strain sensor measurements when subjected to temperature change. Understanding the temperature effect on strain sensors will greatly enhance the ability of civil engineers to monitor the performance of structural materials. In this paper, different types of commonly used and advanced strain sensors have been installed in a reinforced concrete beam to measure the thermal strain response of concrete under different temperature conditions. The experimental results demonstrated a 25-30% difference in strain measurements from the different sensors. It is shown in this paper that this difference is due to the combined effects of sensor inaccuracy, uncertainties related to the testing conditions and uncertainties associated with the temperature compensation methods.The authors would like to acknowledge Dr. Peter Long, Martin Touhey and the Engineering Structures Laboratory technical staff at University of Cambridge for their assistance through the experimental program. The authors are also grateful to the Cambridge Center for Smart Infrastructure and Construction for supporting this research project.This is the accepted manuscript. The final version is available from Elsevier at http://www.sciencedirect.com/science/article/pii/S0950061814008642

Implementing bridge model updating for operation and maintenance purposes: examination based on UK practitioners’ views

There has been a vision of creating bridge digital twins as virtual simulation models of bridge assets to facilitate remote management. Bridge model updating is one digital twin technology which can enable the continuous updating of the structural model as new monitoring data is collected. This paper examines why there is currently little industry uptake of monitoring, modelling and model updating for the operation and maintenance of bridges despite over two decades of research in these fields. The study analyses the findings from a series of semi-structured industry interviews with expert bridge professionals in the U.K. and from an extensive literature survey of bridge model updating studies to examine the disconnects between research and practice and the practical issues of implementing bridge model updating. In particular, the study found that localised damage resulting in local reduction in structural stiffness, a key assumption made in the majority of research, is subject to question by practitioners as many common types of bridge damage may not induce noticeable change in structural stiffness that existing model updating techniques would identify. Key recommendations for future research are proposed to drive adoption of bridge monitoring, modelling and model updating and thus realise their industrial value

Categories of SHM deployments: Technologies and capabilities

The findings of an extensive literature survey focusing on bridge structural health monitoring (SHM) deployments are presented. Conventional, maturing, and emerging technologies are reviewed as well as deployment considerations for new SHM endeavors. The lack of published calibration studies (and quantification of uncertainty studies) for new sensors is highlighted as a major concern and area for future research. There are currently very few examples of SHM systems that have clearly provided significant value to the owners of monitored structures. The results of the literature survey are used to propose a categorization system to better assess the potential outcomes of bridge SHM deployments. It is shown that SHM studies can be categorized as one (or a combination) of the following: (1) anomaly detection, (2) sensor deployment studies, (3) model validation, (4) threshold check, and (5) damage detection. The new framework aids engineers specifying monitoring systems to determine what should be measured and why, hence allowing them to better evaluate what value may be delivered to the relevant stakeholders for the monitoring investments.This work was partly funded by EPSRC Grant No. EP/K000314/1: Innovation Knowledge Centre for Smart Infrastructure and Construction.This is the final version of the article. It first appeared from American Society of Civil Engineers via http://dx.doi.org/10.1061/(ASCE)BE.1943-5592.000073

Detection of Structural Components in Point Clouds of Existing RC Bridges

The cost and effort for modelling existing bridges from point clouds currently outweighs the perceived benefits of the resulting model. Automating the point cloud-to-Bridge Information Models process can drastically reduce the manual effort and cost involved. Previous research has achieved the automatic generation of surfaces primitives combined with rule-based classification to create labelled construction models from point clouds. These methods work very well in synthetic dataset or idealized cases. However, real bridge point clouds are often incomplete, and contain unevenly distributed points. Also, bridge geometries are complex. They are defined with horizontal alignments, vertical elevations and cross-sections. These characteristics are the reasons behind the performance issues existing methods have in real datasets. We propose to tackle this challenge via a novel top-down method for major bridge component detection in this paper. Our method bypasses the surface generation process altogether. Firstly, this method uses a slicing algorithm to separate deck assembly from pier assemblies. It then detects pier caps using their surface normal, and uses oriented bounding boxes and density histograms to segment the girders. Finally, the method terminates by merging over-segments into individual labelled point clusters. Experimental results indicate an average detection precision of 99.2%, recall of 98.3%, and F1-score of 98.7%. This is the first method to achieve reliable detection performance in real bridge datasets. This sets a solid foundation for researchers attempting to derive rich IFC (Industry Foundation Classes) models from individual point clusters.SeeBridge, Trimbl

Social and private information influence the decision making of Australian meat ants (Iridomyrmex purpureus)

For social animals, decision-making is influenced by both social information provided by the group, and private information based on the individual’s personal experience. Social insects make excellent study systems for understanding how social and private information is used by individuals to influence their navigational route choice, and thereby influence the collective decision-making strategy of the group. Using colonies of the Australian meat ant, Iridomyrmex purpureus, we demonstrate that when individual workers are trained to a rewarding arm in a Y maze, the trained ants use private information (memory) in route choice when social information (trail pheromone) is experimentally removed and have no preference when private information and social information are in direct conflict with each other. Additional experience did not provide a strong training effect, such that ants returning after their first training trip tended to choose the path they had been trained on (private information) and subsequent trips did not have a significant additional effect on this initial preference

The 18 kDa translocator protein, microglia and neuroinflammation

The 18 kDa translocator protein (TSPO), previously known as the peripheral benzodiazepine receptor, is expressed in the injured brain. It has become known as an imaging marker of “neuroinflammation” indicating active disease, and is best interpreted as a nondiagnostic biomarker and disease staging tool that refers to histopathology rather than disease etiology. The therapeutic potential of TSPO as a drug target is mostly based on the understanding that it is an outer mitochondrial membrane protein required for the translocation of cholesterol, which thus regulates the rate of steroid synthesis. This pivotal role together with the evolutionary conservation of TSPO has underpinned the belief that any loss or mutation of TSPO should be associated with significant physiological deficits or be outright incompatible with life. However, against prediction, full Tspo knockout mice are viable and across their lifespan do not show the phenotype expected if cholesterol transport and steroid synthesis were significantly impaired. Thus, the “translocation” function of TSPO remains to be better substantiated. Here, we discuss the literature before and after the introduction of the new nomenclature for TSPO and review some of the newer findings. In light of the controversy surrounding the function of TSPO, we emphasize the continued importance of identifying compounds with confirmed selectivity and suggest that TSPO expression is analyzed within specific disease contexts rather than merely equated with the reified concept of “neuroinflammation.” © 2014 The Authors© 2014 The Authors. Brain Pathology published by John Wiley & Sons Ltd on behalf of International Society of Neuropathology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited

Analysis of fiber-optic strain-monitoring data from a prestressed concrete bridge

This paper presents data from fiber-optic strain monitoring of the Nine Wells Bridge, which is a three-span, pretensioned, prestressed concrete beam-and-slab bridge located in Cambridgeshire in the United Kingdom. The original deployment at the site and the challenges associated with collecting distributed strain data using the Brillouin optical time domain reflectometry (BOTDR) technique are described. In particular, construction and deployment issues of fiber robustness and temperature effects are highlighted. The challenges of interpreting the collected data as well as the potential value of information that may be obtained are discussed. Challenges involved with relating measurements to the expected levels of prestress, including the effects due to debonding, creep, and shrinkage, are discussed and analyzed. This paper provides an opportunity to study whether two commonly used models for creep and shrinkage, adequately model data collected in field conditions.This work was supported by the following EPSRC grants: EP/D076870/1, Smart Infrastructure: Wireless Sensor Network System for Condition Assessment and Monitoring of Infrastructure; EP/I019308/1, Innovation Knowledge Centre for Smart Infrastructure and Construction; and EP/K000314/1, Innovation and Knowledge Centre for Smart Infrastructure and Construction - Collaborative Programme Tranche 1

Biophysical Factors Affecting the Distribution of Demersal Fish around the Head of a Submarine Canyon Off the Bonney Coast, South Australia

We sampled the demersal fish community of the Bonney Canyon, South Australia at depths (100–1,500 m) and locations that are poorly known. Seventy-eight species of demersal fish were obtained from 12 depth-stratified trawls along, and to either side, of the central canyon axis. Distributional patterns in species richness and biomass were highly correlated. Three fish assemblage groupings, characterised by small suites of species with narrow depth distributions, were identified on the shelf, upper slope and mid slope. The assemblage groupings were largely explained by depth (ρw = 0.78). Compared to the depth gradient, canyon-related effects are weak or occur at spatial or temporal scales not sampled in this study. A conceptual physical model displayed features consistent with the depth zonational patterns in fish, and also indicated that canyon upwelling can occur. The depth zonation of the fish assemblage was associated with the depth distribution of water masses in the area. Notably, the mid-slope community (1,000 m) coincided with a layer of Antarctic Intermediate Water, the upper slope community (500 m) resided within the core of the Flinders Current, and the shelf community was located in a well-mixed layer of surface water (<450 m depth)

The Incidence of Molluscum contagiosum among American Indians and Alaska Natives

The epidemiology of Molluscum contagiosum (MC) in the United States is largely unknown, despite the fact that the virus is directly communicable and large outbreaks occur. This study provides population-based estimates to describe the epidemiology of MC in the United States among American Indian and Alaska Native (AI/AN) persons. This population was selected because of the comprehensiveness and quality of available data describing utilization of out-patient services.Outpatient visits listing MC as a diagnosis in the Indian Health Service National Patient Information Reporting System during 2001-2005 were analyzed to assess patient characteristics, visit frequency and concurrent skin conditions. Outpatient visit rates and incidence rates were calculated based on known population denominators (retrospective cohort). Overall outpatient visit rates were also calculated for the general US population using national data. The average annual rate of MC-associated outpatient visits was 20.15/10,000 AI/AN persons for 2001-2005 (13,711 total visits), which was similar to the rate for the general US population (22.0/10,000 [95% CI: 16.9-27.1]). The incidence of MC-associated visits was 15.34/10,000. AI/AN children 1-4 years old had the highest incidence (77.12), more than twice that for children 5-14 years old (30.79); the incidence for infants (<1 year) was higher than that for adults. AI/AN persons living in the West region had the highest incidence, followed by those in the East and Alaska regions (26.96, 22.88 and 21.38, respectively). There were age-specific associations between MC and concurrent skin conditions (e.g., atopic dermatitis, eczema).This study highlights the need for periodic population-based measurements to assess trends in incidence and healthcare utilization for MC in the United States. High rates of MC were found among AI/AN persons, especially among children <15 years old. The AI/AN population would benefit from greater availability of effective strategies for prevention and treatment of MCV infection