Material-Based Construction Site Image Retrieval

The technological advancements in digital imaging, the widespread popularity of digital cameras, and the increasing demand by owners and contractors for detailed and complete site photograph logs have triggered an ever-increasing growth in the rate of construction image data collection, with thousands of images being stored for each project. However, the sheer volume of images and the difficulties in accurately and manually indexing them have generated a pressing need for methods that can index and retrieve images with minimal or no user intervention. This paper reports recent developments from research efforts in the indexing and retrieval of construction site images in architecture, engineering, construction, and facilities management image database systems. The limitations and benefits of the existing methodologies will be presented, as well as an explanation of the reasons for the development of a novel image retrieval approach that not only can recognize construction materials within the image content in order to index images, but also can be compatible with existing retrieval methods, enabling enhanced results.

Content-Based Search Engines for Construction Image Databases

Images represent a valuable source of information for the construction industry. Due to technological advancements in digital imaging, the increasing use of digital cameras is leading to an ever-increasing volume of images being stored in construction image databases and thus makes it hard for engineers to retrieve useful information from them. Content-Based Search Engines are tools that utilize the rich image content and apply pattern recognition methods in order to retrieve similar images. In this paper, we illustrate several project management tasks and show how Content-Based Search Engines can facilitate automatic retrieval, and indexing of construction images in image databases.

The flow of steel into the construction sector

Half of the world's annual production of steel is used in constructing buildings and infrastructure. Producing this steel causes significant amounts of carbon dioxide to be released into the atmosphere. Climate change experts recommend this amount be halved by 2050; however steel demand is predicted to have doubled by this date. As process efficiency improvements will not reach the required 75% reduction in emissions per unit steel output, new methods must be examined to deliver service using less steel production. To apply such methods successfully to construction, it must first be known where steel is used currently within the industry. This information is not available so a methodology is proposed to estimate it from known data. Results are presented for steel flows by product for ten construction sectors for both the UK and the world in 2006. An estimate for steel use within a 'typical' building is also published for the first time. Industrial buildings and utility infrastructure are identified as the largest end-uses of steel, while superstructure is confirmed as the main use of steel in a building. The results highlight discrepancies in previous steel estimates and life-cycle assessments, and will inform future research on lowering demand for steel, hence reducing carbon emissions. © 2012 Elsevier B.V. All rights reserved.

Multi-Modal Image Retrieval from Construction Databases and Model-Based Systems

In the modern and dynamic construction environment it is important to access information in a fast and efficient manner in order to improve the decision making processes for construction managers. This capability is, in most cases, straightforward with today’s technologies for data types with an inherent structure that resides primarily on established database structures like estimating and scheduling software. However, previous research has demonstrated that a significant percentage of construction data is stored in semi-structured or unstructured data formats (text, images, etc.) and that manually locating and identifying such data is a very hard and time-consuming task. This paper focuses on construction site image data and presents a novel image retrieval model that interfaces with established construction data management structures. This model is designed to retrieve images from related objects in project models or construction databases using location, date, and material information (extracted from the image content with pattern recognition techniques).

Mechanics of capillary forming of aligned carbon nanotube assemblies.

Elastocapillary self-assembly is emerging as a versatile technique to manufacture three-dimensional (3D) microstructures and complex surface textures from arrangements of micro- and nanoscale filaments. Understanding the mechanics of capillary self-assembly is essential to engineering of properties such as shape-directed actuation, anisotropic wetting and adhesion, and mechanical energy transfer and dissipation. We study elastocapillary self-assembly (herein called "capillary forming") of carbon nanotube (CNT) microstructures, combining in situ optical imaging, micromechanical testing, and finite element modeling. By imaging, we identify sequential stages of liquid infiltration, evaporation, and solid shrinkage, whose kinetics relate to the size and shape of the CNT microstructure. We couple these observations with measurements of the orthotropic elastic moduli of CNT forests to understand how the dynamic of shrinkage of the vapor-liquid interface is coupled to the compression of the forest. We compare the kinetics of shrinkage to the rate of evporation from liquid droplets having the same size and geometry. Moreover, we show that the amount of shrinkage during evaporation is governed by the ability of the CNTs to slip against one another, which can be manipulated by the deposition of thin conformal coatings on the CNTs by atomic layer deposition (ALD). This insight is confirmed by finite element modeling of pairs of CNTs as corrugated beams in contact and highlights the coupled role of elasticity and friction in shrinkage and stability of nanoporous solids. Overall, this study shows that nanoscale porosity can be tailored via the filament density and adhesion at contact points, which is important to the development of lightweight multifunctional materials.

Structurally programmed capillary folding of carbon nanotube assemblies.

We demonstrate the fabrication of horizontally aligned carbon nanotube (HA-CNT) networks by spatially programmable folding, which is induced by self-directed liquid infiltration of vertical CNTs. Folding is caused by a capillary buckling instability and is predicted by the elastocapillary buckling height, which scales with the wall thickness as t(3/2). The folding direction is controlled by incorporating folding initiators at the ends of the CNT walls, and the initiators cause a tilt during densification which precedes buckling. By patterning these initiators and specifying the wall geometry, we control the dimensions of HA-CNT patches over 2 orders of magnitude and realize multilayered and multidirectional assemblies. Multidirectional HA-CNT patterns are building blocks for custom design of nanotextured surfaces and flexible circuits.

Non-destructive characterization of structural hierarchy within aligned carbon nanotube assemblies

Understanding and controlling the hierarchical self-assembly of carbon nanotubes (CNTs) is vital for designing materials such as transparent conductors, chemical sensors, high-performance composites, and microelectronic interconnects. In particular, many applications require high-density CNT assemblies that cannot currently be made directly by low-density CNT growth, and therefore require post-processing by methods such as elastocapillary densification. We characterize the hierarchical structure of pristine and densified vertically aligned multi-wall CNT forests, by combining small-angle and ultra-small-angle x-ray scattering (USAXS) techniques. This enables the nondestructive measurement of both the individual CNT diameter and CNT bundle diameter within CNT forests, which are otherwise quantified only by delicate and often destructive microscopy techniques. Our measurements show that multi-wall CNT forests grown by chemical vapor deposition consist of isolated and bundled CNTs, with an average bundle diameter of 16 nm. After capillary densification of the CNT forest, USAXS reveals bundles with a diameter 4 m, in addition to the small bundles observed in the as-grown forests. Combining these characterization methods with new CNT processing methods could enable the engineering of macro-scale CNT assemblies that exhibit significantly improved bulk properties. © 2011 American Institute of Physics.

Bending of nanoscale filament assemblies by elastocapillary densification

We report a mechanism by which nanoscale filaments self-assemble into asymmetric aggregates by elastocapillary action. Specifically, capillary rise of liquid into an asymmetric pattern of vertically aligned filaments causes the filaments to deflect laterally during elastocapillary densification. We quantitatively show that the lateral deflection can be controlled precisely by the pattern shape and the coupling strength among the filaments. We exploit this mechanism to fabricate asymmetric micropillars and multidirectional bridges of densely packed carbon nanotubes. Analogous behavior occurs as biological filaments interact with liquids, and these findings enable scalable fabrication of anisotropic filament assemblies for manipulating surface interactions between solids and liquids. © 2010 The American Physical Society.

Structural analysis of plate-type fuel assemblies and development of a non-destructive method to assess their integrity

This work is concerned with the structural behaviour and the integrity of parallel plate-type nuclear fuel assemblies. A plate-type assembly consists of several thin plates mounted in a box-like structure and is subjected to a coolant flow that can result in a considerable drag force. A finite element model of an assembly is presented to study the sensitivity of the natural frequencies to the stiffness of the plates' junctions. It is shown that the shift in the natural frequencies of the torsional modes can be used to check the global integrity of the fuel assembly while the local natural frequencies of the inner plates can be used to estimate the maximum drag force they can resist. Finally a non-destructive method is developed to assess the resistance of the inner plates to bear an applied load. Extensive computational and experimental results are presented to prove the applicability of the method presented. © 2013 Elsevier B.V. All rights reserved.