Real-time Spatial Detection and Tracking of Resources in a Construction Environment

Construction accidents with heavy equipment and bad decision making can be based on poor knowledge of the site environment and in both cases may lead to work interruptions and costly delays. Supporting the construction environment with real-time generated three-dimensional (3D) models can help preventing accidents as well as support management by modeling infrastructure assets in 3D. Such models can be integrated in the path planning of construction equipment operations for obstacle avoidance or in a 4D model that simulates construction processes. Detecting and guiding resources, such as personnel, machines and materials in and to the right place on time requires methods and technologies supplying information in real-time. This paper presents research in real-time 3D laser scanning and modeling using high range frame update rate scanning technology. Existing and emerging sensors and techniques in three-dimensional modeling are explained. The presented research successfully developed computational models and algorithms for the real-time detection, tracking, and three-dimensional modeling of static and dynamic construction resources, such as workforce, machines, equipment, and materials based on a 3D video range camera. In particular, the proposed algorithm for rapidly modeling three-dimensional scenes is explained. Laboratory and outdoor field experiments that were conducted to validate the algorithm’s performance and results are discussed

Real-Time, Three-Dimensional Object Detection and Modeling in Construction

This paper describes a research effort directed to produce methods to model three-dimensional scenes of construction field objects in real-time that adds valuable data to construction information management systems, as well as equipment navigation systems. For efficiency reasons, typical construction objects are modeled by bounding surfaces using a high-frame rate range sensor, called Flash LADAR. The sensor provides a dense cloud of range points which are segmented and grouped into objects. Algorithms are being developed to accurately detect these objects and model characteristics such as volume, speed, and direction. Initial experiments show the feasibility of this method. The advantages and limitations, and potential solutions to limitations are summarized in this paper

Integrating data from 3D CAD and 3D cameras for Real-Time Modeling

In a reversal of historic trends, the capital facilities industry is expressing an increasing desire for automation of equipment and construction processes. Simultaneously, the industry has become conscious that higher levels of interoperability are a key towards higher productivity and safer projects. In complex, dynamic, and rapidly changing three-dimensional (3D) environments such as facilities sites, cutting-edge 3D sensing technologies and processing algorithms are one area of development that can dramatically impact those projects factors. New 3D technologies are now being developed, with among them 3D camera. The main focus here is an investigation of the feasibility of rapidly combining and comparing – integrating – 3D sensed data (from a 3D camera) and 3D CAD data. Such a capability could improve construction quality assessment, facility aging assessment, as well as rapid environment reconstruction and construction automation. Some preliminary results are presented here. They deal with the challenge of fusing sensed and CAD data that are completely different in nature

Variation of the density of states in amorphous GdSi at the metal-insulator transition

We performed detailed conductivity and tunneling mesurements on the amorphous, magnetically doped material $\alpha$-Gd$_x$Si$_{1-x}$ (GdSi), which can be driven through the metal-insulator transition by the application of an external magnetic field. Conductivity increases linearly with field near the transition and slightly slower on the metallic side. The tunneling conductance, proportional to the density of states $N(E)$, undergoes a gradual change with increasing field, from insulating, showing a soft gap at low bias, with a slightly weaker than parabolic energy dependence, i.e. $N(E) \sim E^c$, $c \lesssim 2$, towards metallic behavior, with $E^d$, $0.5 \lt d \lt 1$ energy dependence. The density of states at the Fermi level appears to be zero at low fields, as in an insulator, while the sample shows already small, but metal-like conductivity. We suggest a possible explanation to the observed effect.Comment: 6 pages, 6 figure

Analytic Density of States in the Abrikosov-Gorkov Theory

Since the early 1960s, Abrikosov-Gorkov theory has been used to describe superconductors with paramagnetic impurities. Interestingly, the density of states resulting from the theoretical framework has to date only been known approximately, as a numeric solution of a complex polynomial. Here we introduce an exact analytic solution for the density of states of a superconductor with paramagnetic impurities. The solution is valid in the whole regime of Abrikosov-Gorkov theory; both where there is an energy gap and gapless. While of fundamental interest, we argue that this solution also has computational benefits in the evaluation of integrals for tunneling conductances and allows for an analytic description of materials with densities of states that are modeled from the basic Abrikosov-Gorkov density of states.Comment: 5 pages, 1 figur

An Exact Solution for the Lattice Gas Model in One Dimension

A simple method to obtain a canonical partition function for one dimensional lattice gas model is presented. The simplification is based upon rewriting a sum over all possible configurations to a sum over numbers of clusters in the system.Comment: 6 pages, LaTe

Quantum states and specific heat of low-density He gas adsorbed within the carbon nanotube interstitial channels: Band structure effects and potential dependence

We calculate the energy-band structure of a He atom trapped within the interstitial channel between close-packed nanotubes within a bundle and its influence on the specific heat of the adsorbed gas. A robust prediction of our calculations is that the contribution of the low-density adsorbed gas to the specific heat of the nanotube material shows pronounced nonmonotonic variations with temperature. These variations are shown to be closely related to the band gaps in the adsorbate density of states