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).