An experimental model of relay deployment planning tool for a wireless sensor network system to monitor civil engineering structures

It is essential to monitor deteriorated civil engineering structures cautiously to detect symptoms of their serious disruptions. A wireless sensor network can be an effective system for monitoring civil engineering structures. It is fast to deploy sensors especially in difficult-to-access areas, and it is extendable without any cable extensions. Since our target is to monitor deteriorations of civil engineering structures such as cracks at tunnel linings, most of the locations of sensors are known, and sensors are not required to move dynamically. Therefore, we focus on developing a deployment plan of a static network in order to reduce the value of a cost function such as initial installation cost and summation of communication distances of the network. The key issue of the deployment is the location of relays that forward sensing data from sensors to a data collection device called a gateway. In this paper, we propose a relay deployment-planning tool that can be used to design a wireless sensor network for monitoring civil engineering structures. For the planning tool, we formalize the model and implement a local search based algorithm to find a quasi-optimal solution. Our solution guarantees two routings from a sensor to a gateway, which can provide higher reliability of the network. We also show the application of our experimental tool to the actual environment in the London Underground.

Restoration of images and 3D data to higher resolution by deconvolution with sparsity regularization

Image convolution is conventionally approximated by the LTI discrete model. It is well recognized that the higher the sampling rate, the better is the approximation. However sometimes images or 3D data are only available at a lower sampling rate due to physical constraints of the imaging system. In this paper, we model the under-sampled observation as the result of combining convolution and subsampling. Because the wavelet coefficients of piecewise smooth images tend to be sparse and well modelled by tree-like structures, we propose the L0 reweighted-L2 minimization (L0RL2 ) algorithm to solve this problem. This promotes model-based sparsity by minimizing the reweighted L2 norm, which approximates the L0 norm, and by enforcing a tree model over the weights. We test the algorithm on 3 examples: a simple ring, the cameraman image and a 3D microscope dataset; and show that good results can be obtained. © 2010 IEEE.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Automated Detection of Concrete Columns from Visual Data

After earthquakes, licensed inspectors use the established codes to assess the impact of damage on structural elements. It always takes them days to weeks. However, emergency responders (e.g. firefighters) must act within hours of a disaster event to enter damaged structures to save lives, and therefore cannot wait till an official assessment completes. This is a risk that firefighters have to take. Although Search and Rescue Organizations offer training seminars to familiarize firefighters with structural damage assessment, its effectiveness is hard to guarantee when firefighters perform life rescue and damage assessment operations together. Also, the training is not available to every firefighter. The authors therefore proposed a novel framework that can provide firefighters with a quick but crude assessment of damaged buildings through evaluating the visible damage on their critical structural elements (i.e. concrete columns in the study). This paper presents the first step of the framework. It aims to automate the detection of concrete columns from visual data. To achieve this, the typical shape of columns (long vertical lines) is recognized using edge detection and the Hough transform. The bounding rectangle for each pair of long vertical lines is then formed. When the resulting rectangle resembles a column and the material contained in the region of two long vertical lines is recognized as concrete, the region is marked as a concrete column surface. Real video/image data are used to test the method. The preliminary results indicate that concrete columns can be detected when they are not distant and have at least one surface visible.

Data Analysis on Complicated Construction Data Sources: Vision, Research, and Recent Developments

Compared with construction data sources that are usually stored and analyzed in spreadsheets and single data tables, data sources with more complicated structures, such as text documents, site images, web pages, and project schedules have been less intensively studied due to additional challenges in data preparation, representation, and analysis. In this paper, our definition and vision for advanced data analysis addressing such challenges are presented, together with related research results from previous work, as well as our recent developments of data analysis on text-based, image-based, web-based, and network-based construction sources. It is shown in this paper that particular data preparation, representation, and analysis operations should be identified, and integrated with careful problem investigations and scientific validation measures in order to provide general frameworks in support of information search and knowledge discovery from such information-abundant data sources.

An analytical model for guided wave inspection optimization for prismatic structures of any cross section.

This paper presents an analytical modeling technique for the simulation of long-range ultrasonic guided waves in structures. The model may be used to predict the displacement field in a prismatic structure arising from any excitation arrangement and may therefore be used as a tool to design new inspection systems. It is computationally efficient and relatively simple to implement, yet gives accuracy similar to finite element analysis and semi-analytical finite element analysis methods. The model has many potential applications; one example is the optimization of part-circumferential arrays where access to the full circumference of the pipe is restricted. The model has been successfully validated by comparison with finite element solutions. Experimental validation has also been carried out using an array of piezoelectric transducer elements to measure the displacement field arising from a single transducer element in an 88.9-mm-diameter pipe. Good agreement has been obtained between the two models and the experimental data.

Geometry and interaction of structures in homogeneous isotropic turbulence

A strategy to extract turbulence structures from direct numerical simulation (DNS) data is described along with a systematic analysis of geometry and spatial distribution of the educed structures. A DNS dataset of decaying homogeneous isotropic turbulence at Reynolds number Reλ = 141 is considered. A bandpass filtering procedure is shown to be effective in extracting enstrophy and dissipation structures with their smallest scales matching the filter width, L. The geometry of these educed structures is characterized and classified through the use of two non-dimensional quantities, planarity' and filamentarity', obtained using the Minkowski functionals. The planarity increases gradually by a small amount as L is decreased, and its narrow variation suggests a nearly circular cross-section for the educed structures. The filamentarity increases significantly as L decreases demonstrating that the educed structures become progressively more tubular. An analysis of the preferential alignment between the filtered strain and vorticity fields reveals that vortical structures of a given scale L are most likely to align with the largest extensional strain at a scale 3-5 times larger than L. This is consistent with the classical energy cascade picture, in which vortices of a given scale are stretched by and absorb energy from structures of a somewhat larger scale. The spatial distribution of the educed structures shows that the enstrophy structures at the 5η scale (where η is the Kolmogorov scale) are more concentrated near the ones that are 3-5 times larger, which gives further support to the classical picture. Finally, it is shown by analysing the volume fraction of the educed enstrophy structures that there is a tendency for them to cluster around a larger structure or clusters of larger structures. Copyright © 2012 Cambridge University Press.

Accurate screened exchange band structures for the transition metal monoxides MnO, FeO, CoO and NiO.

We report calculations of the band structures and density of states of the four transition metal monoxides MnO, FeO, CoO and NiO using the hybrid density functional sX-LDA ('screened exchange local density approximation'). Late transition metal oxides are prototypical examples of strongly correlated materials, which pose challenges for electronic structure methods. We compare our results with available experimental data and show that our calculations generally yield accurate predictions for the fundamental band gaps and valence bands, in favourable agreement with previously reported theoretical studies. For MnO, the band gaps are still underestimated, suggesting additional many-body effects that are not captured by our screened hybrid functional approach.

A flexural crack model for damage detection in reinforced concrete structures

The use of changes in vibration data for damage detection of reinforced concrete structures faces many challenges that obstruct its transition from a research topic to field applications. Among these is the lack of appropriate damage models that can be deployed in the damage detection methods. In this paper, a model of a simply supported reinforced concrete beam with multiple cracks is developed to examine its use for damage detection and structural health monitoring. The cracks are simulated by a model that accounts for crack formation, propagation and closure. The beam model is studied under different dynamic excitations, including sine sweep and single excitation frequency, for various damage levels. The changes in resonant frequency with increasing loads are examined along with the nonlinear vibration characteristics. The model demonstrates that the resonant frequency reduces by about 10% at the application of 30% of the ultimate load and then drops gradually by about 25% at 70% of the ultimate load. The model also illustrates some nonlinearity in the dynamic response of damaged beams. The appearance of super-harmonics shows that the nonlinearity is higher when the damage level is about 35% and then decreases with increasing damage. The restoring force-displacement relationship predicted the reduction in the overall stiffness of the damaged beam. The model quantitatively predicts the experimental vibration behaviour of damaged RC beams and also shows the damage dependency of nonlinear vibration behaviour. © 2011 Published under licence by IOP Publishing Ltd.

Achievements and challenges in machine vision-based inspection of large concrete structures

Large concrete structures need to be inspected in order to assess their current physical and functional state, to predict future conditions, to support investment planning and decision making, and to allocate limited maintenance and rehabilitation resources. Current procedures in condition and safety assessment of large concrete structures are performed manually leading to subjective and unreliable results, costly and time-consuming data collection, and safety issues. To address these limitations, automated machine vision-based inspection procedures have increasingly been proposed by the research community. This paper presents current achievements and open challenges in vision-based inspection of large concrete structures. First, the general concept of Building Information Modeling is introduced. Then, vision-based 3D reconstruction and as-built spatial modeling of concrete civil infrastructure are presented. Following that, the focus is set on structural member recognition as well as on concrete damage detection and assessment exemplified for concrete columns. Although some challenges are still under investigation, it can be concluded that vision-based inspection methods have significantly improved over the last 10 years, and now, as-built spatial modeling as well as damage detection and assessment of large concrete structures have the potential to be fully automated.

Magnetic characterisation of large grain, bulk Y-Ba-Cu-O superconductor-soft ferromagnetic alloy hybrid structures

Large grain, bulk Y-Ba-Cu-O (YBCO) high temperature superconductors (HTS) have significant potential for use in a variety of practical applications that incorporate powerful quasi-permanent magnets. In the present work, we investigate how the trapped field of such magnets can be improved by combining bulk YBCO with a soft FeNi, ferromagnetic alloy. This involves machining the alloy into components of various shapes, such as cylinders and rings, which are attached subsequently to the top surface of a solid, bulk HTS cylinder. The effect of these modifications on the magnetic hysteresis curve and trapped field of the bulk superconductor at 77 K are then studied using pick-up coil and Hall probe measurements. The experimental data are compared to finite element modelling of the magnetic flux distribution using Campbell's algorithm. Initially we establish the validity of the technique involving pick-up coils wrapped around the bulk superconductor to obtain its magnetic hysteresis curve in a non-destructive way and highlight the difference between the measured signal and the true magnetization of the sample. We then consider the properties of hybrid ferromagnet/superconductor (F/S) structures. Hall probe measurements, together with the results of the model, establish that flux lines curve outwards through the ferromagnet, which acts, effectively, like a magnetic short circuit. Magnetic hysteresis curves show that the effects of the superconductor and the ferromagnet simply add when the ferromagnet is saturated fully by the applied field. The trapped field of the hybrid structure is always larger than that of the superconductor alone below this saturation level, and especially when the applied field is removed. The results of the study show further that the beneficial effects on the trapped field are enhanced when the ferromagnet covers the entire surface of the superconductor for different ferromagnetic components of various shapes and fixed volume. © 2014 Elsevier B.V. All rights reserved.