Managing Information Risks in asset management - Experiences from an in-depth case study in the utility industry

Information is one of the most important resources in our globalized economy. The value of information often exceeds the value of physical assets. Information quality has, in many ways, an impact on asset management organisations and asset managers struggle to understand and to quantify it, which is a prerequisite for effective information quality improvement. Over the past few years, we have developed an innovative management concept that addresses these new asset management challenges: a process for Total Information Risk Management (TIRM), which has been already tested in a number of asset management industries. The TIRM process enables to manage information quality more effectively in asset management organisations as it focuses specifically on the risks that are imposed by information quality. In this paper, we show how we have applied the TIRM process in an in-depth study at a medium-sized European utility provider, the Manx Electricity Authority (MEA), at the Isle of Man.

Effect of buried depth and diameter on uplift of underground structures in liquefied soils

In an earthquake, underground structures located in liquefiable soil deposits are susceptible to floatation following an earthquake event due to their lower unit weight relative to the surrounding saturated soil. The uplift displacement of an underground structure in liquefiable soil deposit can be affected by the buried depth and size of the structure. Dynamic centrifuge tests have been carried out to investigate the influence of these factors by measuring the uplift displacement of shallow model circular structures. Ratios for the buried depth and diameter effects of the structure are introduced to compare the uplift displacement in different soil and earthquake conditions. With the depth effect and diameter effect ratios, the uplift displacement of a buoyant structure in liquefiable soil can also be estimated based on performance of similar structures in comparable soil condition and subjected to a similar earthquake event. © 2012 Elsevier Ltd.

Innovative Stereo Vision-Based Approach to Generate Dense Depth Map of Transportation Infrastructure

Three-dimensional (3-D) spatial data of a transportation infrastructure contain useful information for civil engineering applications, including as-built documentation, on-site safety enhancements, and progress monitoring. Several techniques have been developed for acquiring 3-D point coordinates of infrastructure, such as laser scanning. Although the method yields accurate results, the high device costs and human effort required render the process infeasible for generic applications in the construction industry. A quick and reliable approach, which is based on the principles of stereo vision, is proposed for generating a depth map of an infrastructure. Initially, two images are captured by two similar stereo cameras at the scene of the infrastructure. A Harris feature detector is used to extract feature points from the first view, and an innovative adaptive window-matching technique is used to compute feature point correspondences in the second view. A robust algorithm computes the nonfeature point correspondences. Thus, the correspondences of all the points in the scene are obtained. After all correspondences have been obtained, the geometric principles of stereo vision are used to generate a dense depth map of the scene. The proposed algorithm has been tested on several data sets, and results illustrate its potential for stereo correspondence and depth map generation.

Testing of Depth-Encoded Hough Voting for Infrastructure Object Detection

The lack of viable methods to map and label existing infrastructure is one of the engineering grand challenges for the 21st century. For instance, over two thirds of the effort needed to geometrically model even simple infrastructure is spent on manually converting a cloud of points to a 3D model. The result is that few facilities today have a complete record of as-built information and that as-built models are not produced for the vast majority of new construction and retrofit projects. This leads to rework and design changes that can cost up to 10% of the installed costs. Automatically detecting building components could address this challenge. However, existing methods for detecting building components are not view and scale-invariant, or have only been validated in restricted scenarios that require a priori knowledge without considering occlusions. This leads to their constrained applicability in complex civil infrastructure scenes. In this paper, we test a pose-invariant method of labeling existing infrastructure. This method simultaneously detects objects and estimates their poses. It takes advantage of a recent novel formulation for object detection and customizes it to generic civil infrastructure scenes. Our preliminary experiments demonstrate that this method achieves convincing recognition results.

Innovative Stereo Vision-Based Approach to Generate Dense Depth Map of Transportation Infrastructure

Three-dimensional (3-D) spatial data of a transportation infrastructure contain useful information for civil engineering applications, including as-built documentation, on-site safety enhancements, and progress monitoring. Several techniques have been developed for acquiring 3-D point coordinates of infrastructure, such as laser scanning. Although the method yields accurate results, the high device costs and human effort required render the process infeasible for generic applications in the construction industry. A quick and reliable approach, which is based on the principles of stereo vision, is proposed for generating a depth map of an infrastructure. Initially, two images are captured by two similar stereo cameras at the scene of the infrastructure. A Harris feature detector is used to extract feature points from the first view, and an innovative adaptive window-matching technique is used to compute feature point correspondences in the second view. A robust algorithm computes the nonfeature point correspondences. Thus, the correspondences of all the points in the scene are obtained. After all correspondences have been obtained, the geometric principles of stereo vision are used to generate a dense depth map of the scene. The proposed algorithm has been tested on several data sets, and results illustrate its potential for stereo correspondence and depth map generation.

Augmenting depth camera output using photometric stereo

We present a system for augmenting depth camera output using multispectral photometric stereo. The technique is demonstrated using a Kinect sensor and is able to produce geometry independently for each frame. Improved reconstruction is demonstrated using the Kinect's inbuilt RGB camera and further improvements are achieved by introducing an additional high resolution camera. As well as qualitative improvements in reconstruction a quantitative reduction in temporal noise is shown. As part of the system an approach is presented for relaxing the assumption of multispectral photometric stereo that scenes are of constant chromaticity to the assumption that scenes contain multiple piecewise constant chromaticities.

Design of quantum cascade microcavity lasers based on Q factor versus etching depth

The choice of the etching depth for semiconductor microcavities is a compromise between a high Q factor and a difficult technique in a practical fabricating process. In this paper, the influences of the etching depth on mode Q factors for mid-infrared quantum cascade microcylinder and microsquare lasers around 4.8 and 7.8 mu m are simulated by three-dimensional (3D) finite-difference time-domain (FDTD) techniques. For the microcylinder and the microsquare resonators, the mode Q factors of the whispering-gallery modes (WGMs) increase exponentially and linearly with the increase in the etching depth, respectively Furthermore, the mode Q factors of some higher order transverse WGMs may be larger than that of the fundamental transverse WGM in 3D microsquares. Based on the field distribution of the vertical multilayer slab waveguide and the mode Q factors versus the etching depth, the necessary etching depth is chosen at the position where the field amplitude is 1% of the peak value of the slab waveguide. In addition, the influences of sidewall roughness on the mode Q factors are simulated for microsquare resonators by 2D FDTD simulation. (C) 2009 Optical Society of America

Depth dependent elastic strain in ZnO epilayer: combined Rutherford backscattering/channeling and X-ray diffraction

A ZnO layer was grown by metalorganic chemical vapor deposition (MOCVD) on a sapphire (0 0 0 1) substrate. The perpendicular and parallel elastic strain of the ZnO epilayer, e(perpendicular to) = 0.19%, e(parallel to) = -0.29%, respectively, were derived by using the combination of Rutherford backscattering (RBS)/channeling and X-ray diffraction (XRD). The ratio vertical bar e(parallel to)/ e(perpendicular to)vertical bar = 1.5 indicates that ZnO layer is much stiffer in the a-axis direction than in the c-axis direction. By using RBS/C, the depth dependent elastic strain was deduced. The strain is higher at the depth close to the interface and decreases towards the surface. The negative tetragonal distortion was explained by considering the lattice mismatch and thermal mismatch in ZnO thin film. (c) 2004 Elsevier B.V. All rights reserved.