The use of centrifuge tests in the study of arching

The horizontal arching mechanism transfers horizontal earth pressures acting on flexible retaining wall panels to stiffer neighbouring elements via soil shear stresses. In this research, the horizontal arching mechanism and lateral displacements of fixed cantilever walls in a model basement are investigated using centrifuge tests. A series of six tests was carried out at 45 gravities where the panel widths and thicknesses around the model basement were varied, so that the effects of panel geometry and stiffness on horizontal arching could be studied. It is shown that panel crest displacements and base bending moments of the most flexible, narrow panels can be an order of magnitude smaller than conventional active earth pressure calculations would allow. It is suggested that the reduction of earth pressure acting on a panel is directly correlated to the mobilized soil shear strength and hence, soil shear strain. Earth pressure coefficients K are plotted against panel displacements normalized by the panel width, u/B, to simulate the reduction of K with increasing soil strain.An idealized K-u/B curve is introduced, characterised by a reference distortion (u/B) ref beyond which fully plastic soil arching can be inferred, and which is related to the corresponding reference shear strain γ ref at which soil strength is fully mobilized in element tests. © 2006 Taylor & Francis Group, London.

Case study on a deep excavation in soft ground by centrifuge model tests

This paper provides a case study on the deepest excavation carried out so far in the construction of the metro network in Shanghai, which typically features soft ground. The excavation is 38 m deep with retaining walls 65 m deep braced by 9 levels of concrete props. To obtain a quick and rough prediction, two centrifuge model tests were conducted, in which one is for the 'standard' section with green field surrounding and the other with an adjacent piled building. The tests were carried out in a run-stop-excavation-run style, in which excavation was conducted manually. By analyzing the lateral wall displacement, ground deformation, bending moment and earth pressure, the test results are shown to be reasonably convincing and the design and construction were validated. Such industry orientated centrifuge modeling was shown to be useful in understanding the performance of geotechnical processes, especially when engineers lack relevant field experience. © 2010 Taylor & Francis Group, London.

Dynamic centrifuge tests on shallow tunnel models in dry sand

In the framework of the Italian research project ReLUIS-DPC, a set of centrifuge tests were carried out at the Schofield Centre in Cambridge (UK) to investigate the seismic behaviour of tunnels. Four samples of dry sand were prepared at different densities, in which a small scale model of circular tunnel was inserted, instrumented with gauges measuring hoop and bending strains. Arrays of accelerometers in the soil and on the box allowed the amplification of ground motion to be evaluated; LVDTs measured the soil surface settlement. This paper describes the main results of this research, showing among others the evolution of the internal forces during the model earthquakes at significant locations along the tunnel lining. © 2010 Taylor & Francis Group, London.

Particle Image Velocimetry analysis in dynamic centrifuge tests

The Particle Image Velocimetry (PIV) technique is an image processing tool to obtain instantaneous velocity measurements during an experiment. The basic principle of PIV analysis is to divide the image into small patches and calculate the locations of the individual patches in consecutive images with the help of cross correlation functions. This paper focuses on the application of the PIV analysis in dynamic centrifuge tests on small scale tunnels in loose, dry sand. Digital images were captured during the application of the earthquake loading on tunnel models using a fast digital camera capable of taking digital images at 1000 frames per second at 1 Megapixel resolution. This paper discusses the effectiveness of the existing methods used to conduct PIV analyses on dynamic centrifuge tests. Results indicate that PIV analysis in dynamic testing requires special measures in order to obtain reasonable deformation data. Nevertheless, it was possible to obtain interesting mechanisms regarding the behaviour of the tunnels from PIV analyses. © 2010 Taylor & Francis Group, London.

Tests for conceptual design of 6.6 kV class superconducting fault current limiter with YBCO thin film elements

A superconducting fault current limiter (SFCL) for 6.6 kV and 400 A installed in a cubicle for a distribution network substation was conceptually designed. The SFCL consists of parallel- and series-connected superconducting YBCO elements and a limiting resistor. Before designing the SFCL, some tests were carried out. The width and length of each element used in the tests are 30 mm and 210 mm, respectively. The element consists of YBCO thin film of about 200 nm in thickness on cerium dioxide (CeO2) as a cap-layer on a sapphire substrate by metal-organic deposition with a protective metal coat. In the tests, characteristics of each element, such as over-current, withstand-voltage, and so on, were obtained. From these characteristics, series and parallel connections of the elements, called units, were considered. The characteristics of the units were obtained by tests. From the test results, a single phase prototype SFCL was manufactured and tested. Thus, an SFCL rated at 6.6 kV and 400 A can be designed. © 2009 IEEE.

Comparative study of vision tracking methods for tracking of construction site resources

Vision tracking has significant potential for tracking resources on large scale, congested construction sites, where a small number of cameras strategically placed around the site could replace hundreds of tracking tags. The correlation of vision tracking 2D positions from multiple views can provide the 3D position. However, there are many 2D vision trackers available in the literature, and little information is available on which one is most effective for construction applications. In this paper, a comparative study of various vision tracker categories is carried out, to identify which one is most effective in tracking construction resources. Testing parameters for evaluating categories of trackers are identified, and benefits and limitations of each category are presented. The most promising trackers are tested using a database of construction operations videos. The results indicate the effectiveness of each tracker in relation to each parameter of the test, and the most suitable tracker needed to research effective 3D vision trackers of construction resources.

Automated Computation of the Fundamental Matrix for Vision-Based Construction Site Applications

Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.

Automated vision tracking of project related entities

Tracking of project related entities such as construction equipment, materials, and personnel is used to calculate productivity, detect travel path conflicts, enhance the safety on the site, and monitor the project. Radio frequency tracking technologies (Wi-Fi, RFID, UWB) and GPS are commonly used for this purpose. However, on large-scale sites, deploying, maintaining and removing such systems can be costly and time-consuming. In addition, privacy issues with personnel tracking often limits the usability of these technologies on construction sites. This paper presents a vision based tracking framework that holds promise to address these limitations. The framework uses videos from a set of two or more static cameras placed on construction sites. In each camera view, the framework identifies and tracks construction entities providing 2D image coordinates across frames. Combining the 2D coordinates based on the installed camera system (the distance between the cameras and the view angles of them), 3D coordinates are calculated at each frame. The results of each step are presented to illustrate the feasibility of the framework.

Testing in harsh conditions: Tracking resources on construction sites with machine vision

When tracking resources in large-scale, congested, outdoor construction sites, the cost and time for purchasing, installing and maintaining the position sensors needed to track thousands of materials, and hundreds of equipment and personnel can be significant. To alleviate this problem a novel vision based tracking method that allows each sensor (camera) to monitor the position of multiple entities simultaneously has been proposed. This paper presents the full-scale validation experiments for this method. The validation included testing the method under harsh conditions at a variety of mega-project construction sites. The procedure for collecting data from the sites, the testing procedure, metrics, and results are reported. Full-scale validation demonstrates that the novel vision tracking provides a good solution to track different entities on a large, congested construction site.

Machine vision based concrete surface quality assessment

Manually inspecting concrete surface defects (e.g., cracks and air pockets) is not always reliable. Also, it is labor-intensive. In order to overcome these limitations, automated inspection using image processing techniques was proposed. However, the current work can only detect defects in an image without the ability of evaluating them. This paper presents a novel approach for automatically assessing the impact of two common surface defects (i.e., air pockets and discoloration). These two defects are first located using the developed detection methods. Their attributes, such as the number of air pockets and the area of discoloration regions, are then retrieved to calculate defects’ visual impact ratios (VIRs). The appropriate threshold values for these VIRs are selected through a manual rating survey. This way, for a given concrete surface image, its quality in terms of air pockets and discoloration can be automatically measured by judging whether their VIRs are below the threshold values or not. The method presented in this paper was implemented in C++ and a database of concrete surface images was tested to validate its performance. Read More: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0000126?journalCode=jcemd4

Automated 3D Vision Tracking for Project Control Support

On-site tracking in open construction sites is often difficult because of the large amounts of items that are present and need to be tracked. Additionally, the amounts of occlusions/obstructions present create a highly complex tracking environment. Existing tracking methods are based mainly on Radio Frequency technologies, including Global Positioning Systems (GPS), Radio Frequency Identification (RFID), Bluetooth and Wireless Fidelity (Wi-Fi, Ultra-Wideband, etc). These methods require considerable amounts of pre-processing time since they need to manually deploy tags and keep record of the items they are placed on. In construction sites with numerous entities, tags installation, maintenance and decommissioning become an issue since it increases the cost and time needed to implement these tracking methods. This paper presents a novel method for open site tracking with construction cameras based on machine vision. According to this method, video feed is collected from on site video cameras, and the user selects the entity he wishes to track. The entity is tracked in each video using 2D vision tracking. Epipolar geometry is then used to calculate the depth of the marked area to provide the 3D location of the entity. This method addresses the limitations of radio frequency methods by being unobtrusive and using inexpensive, and easy to deploy equipment. The method has been implemented in a C++ prototype and preliminary results indicate its effectiveness