Employing vision-based sensing for long-term monitoring

This is the author accepted manuscript.Despite the crucial role of structural health monitoring (SHM), traditional approaches rely on contact-based sensors which are both costly and lack automation. Vision-based sensing techniques such as Digital Image Correlation (DIC) have recently emerged as a viable substitute, due to their non-contact nature and low cost. To date, however, the long-term performance of DIC has not been evaluated. This study assesses DIC for long-term displacement monitoring. Firstly, the robustness of the monitoring of ambiently excited structures over long periods is examined. This is achieved through the measurement of drift of control points. Then, correlation is examined between the drift measurements and the ambient temperature, to examine the influence of temperature on the robustness of the DIC measurements. After, the effectiveness of employing DIC for monitoring ambiently excited structures is examined. Towards this aim, the displacements of the midspan of the experimental bridge structure are monitored for one month and compared with those of a traditional contact-based sensor, i.e., a Linear Variance Displacement Transducer (LVDT). Finally, to further demonstrate the effectiveness of employing DIC measurements for ambiently excited structures, a correlation is sought between the midspan displacements and the ambient temperature. Concerning the robustness of the long-term DIC measurements, the drift was found to be relatively small (i.e., equal to 0.06 mm) whilst the temperature was found to potentially influence this. With regard to the overall effectiveness of long-term monitoring with DIC, the study found that non-contact sensing has comparable accuracy to the LVDT, with a correlation coefficient equal to 0.996, root mean square error of 0.012 mm, and mean absolute error of 0.010 mm. Moreover, the correlation of DIC measurements with temperature showed its effectiveness in capturing complex structural behaviours (e.g., extremely slow and small movements) typically associated with ambiently excited structures. Whilst this study is only on a small-scale structure, it paves the way for the employment of vision-based on large-scale structures enabling the general use of DIC for SHM.Innovate U

On non-QRT Mappings of the Plane

We construct 9-parameter and 13-parameter dynamical systems of the plane which map bi-quadratic curves to other bi-quadratic curves and return to the original curve after two iterations. These generalize the QRT maps which map each such curve to itself. The new families of maps include those that were found as reductions of integrable lattices

On the performance of online and offline green path establishment techniques

© 2015, Ruiz-Rivera et al. To date, significant effort has gone into designing green traffic engineering (TE) techniques that consolidate traffic onto the minimal number of links/switches/routers during off-peak periods. However, little works exist that aim to green Multi-Protocol Label Switching (MPLS) capable networks. Critically, no work has studied the performance of green label switched paths (LSPs) establishment methods in terms of energy savings and acceptance rates. Henceforth, we add to the current state-of-the-art by studying green online and offline (LSP) establishment methods. Online methods rely only on past and current LSP requests while offline ones act as a theoretical benchmark whereby they also have available to them future LSP requests. We introduce a novel metric that takes into account both energy savings and acceptance rates. We also identify a new simpler heuristic that minimizes energy use by routing source–destination demands over paths that contain established links and require the fewest number of new links. Our evaluation of two offline and four online LSP establishment methods over the Abilene and AT&T topologies with random LSP setup requests show that energy savings beyond 20 % are achievable with LSP acceptance rates above 90 %

Three-dimensional discrete element modelling of rubble masonry structures from geospatial data

This is the final version.This paper presents a framework for the three-dimensional structural analysis of full-scale, geometrically irregular discontinuum structures such as rubble masonry, directly from geospatial data. A convex decomposition algorithm is adopted, whereby a watertight mesh is subdivided into so-called voronoi blocks which approximate the anisotropic nature of the rubble masonry for structural analysis. The proposed “Voronoi4DEM” framework was implemented to assess the structural stability of the southwest leaning tower of Caerphilly Castle in Wales, UK. Simulations were performed with the three-dimensional computational software 3DEC, based on the Discrete Element Method (DEM) of analysis whilst each voronoi block of the rubble masonry was represented as a rigid, distinct block while mortar joints were modelled as zero thickness interfaces which can open and close depending on the magnitude and direction of the stresses applied to them. The innovation of this framework lies in the specific geometric strategy which approximates the random nature of discontinuous materials at a blockbased level (such as rubble) with sufficient accuracy, whilst vastly reducing computational times. Consequently, the approach can simulate the highly complex behaviour of rubble masonry structures with a high degree of efficiency, geometric accuracy, and automation. It is anticipated that the methodology proposed here to enable unprecedented high-level numerical modelling (block-based numerical modelling) of full-scale rubble masonry structures with, until now, unemployed techniques such as the DEM.Innovate U

Quantifying the effect of geometric uncertainty on the structural behaviour of arches developed from direct measurement and Structure-from-Motion (SfM) photogrammetry

The aim of this paper is to quantify the effect of geometric uncertainty on the structural behaviour of arches developed using traditional geospatial and remote sensing techniques. Geometric models of twenty-five dry-jointed, rigid block arch specimens were developed using the proposed “Image2DEM” framework, encompassing the Structure-from-Motion (SfM) photogrammetry pipeline. Assessment of the framework was carried out with respective geometric models developed from tape measurements, in terms of geometry and structural behaviour. The geometric variables investigated were the: a) joint inclination angle; b) joint mid-point location; c) joint length; d) block volume; and e) block centroid location. Concerning structural behaviour, experimental testing of the arch specimens was numerically simulated with the Discrete Element Method (DEM), and the stiffness, load multiplier and normal forces between joints were obtained. Results showed that even small variations (approx. 8%) between geometric models developed from SfM photogrammetry and tape measurements can influence the collapse load and stiffness of the arch by more than 10% and 46% respectively. Also, of the geometric variables investigated, the joint inclination angle was found to influence the collapse load the most. These findings highlight the importance of developing accurate geometric models, and subsequent employment of accurate geometric data acquisition techniques, to reliably capture the structural behaviour of arches. Although an investigation on arch specimens constructed in the laboratory is demonstrated here, the developed outcomes have important implications for the broader topic of data-driven masonry diagnostics using SfM photogrammetry and high-level numerical modelling using micro-modelling strategies such as the DEM

S01 674: FROM POINT CLOUDS TO GEOMETRY FOR DETAILED MICROMODELLING OF MASONRY STRUCTURES

Over the last few decades significant efforts have been placed on the development of detailed numerical models to predict the mechanical behavior of historical masonry structures. However, an issue faced in the numerical modelling of historic and damaged masonry structures is the development of accurate models to represent their real-world geometries. This paper presents the first stage of a research programme which aims to develop an automatic approach to generate the detailed geometry of masonry from point clouds. Such geometry can then be input into micro models for the structural analysis of masonry structures. In the proposed approach, point clouds generated using the Structure-from-Motion (SfM) pipeline were converted into watertight meshes and then voxelized. Models were represented as a sum of cuboid-blocks jointed by zero thickness interfaces. The developed methodology was applied to derive geometries of two small scale masonry specimens constructed under laboratory conditions and a full-scale masonry arch bridge