Future-proofed energy design for dwellings: Case studies from England and application to the Code for Sustainable Homes

This paper investigates 'future-proofing' as an unexplored yet all-important aspect in the design of low-energy dwellings. It refers particularly to adopting lifecycle thinking and accommodating risks and uncertainties in the selection of fabric energy efficiency measures and low or zero-carbon technologies. Based on a conceptual framework for future-proofed design, the paper first presents results from the analysis of two 'best practice' housing developments in England; i.e., North West Cambridge in Cambridge and West Carclaze and Baal in St. Austell, Cornwall. Second, it examines the 'Energy and CO2 Emissions' part of the Code for Sustainable Homes to reveal which design criteria and assessment methods can be practically integrated into this established building certification scheme so that it can become more dynamic and future-oriented.Practical application: Future-proofed construction is promoted implicitly within the increasingly stringent building regulations; however, there is no comprehensive method to readily incorporate futures thinking into the energy design of buildings. This study has a three-fold objective of relevance to the building industry:Illuminating the two key categories of long-term impacts in buildings, which are often erroneously treated interchangeably:- The environmental impact of buildings due to their long lifecycles.- The environment's impacts on buildings due to risks and uncertainties affecting the energy consumption by at least 2050. This refers to social, technological, economic, environmental and regulatory (predictable or unknown) trends and drivers of change, such as climate uncertainty, home-working, technology readiness etc.Encouraging future-proofing from an early planning stage to reduce the likelihood of a prematurely obsolete building design.Enhancing established building energy assessment methods (certification, modelling or audit tools) by integrating a set of future-oriented criteria into their methodologies. © 2012 The Chartered Institution of Building Services Engineers.

Detecting air pockets for architectural concrete quality assessment using visual sensing

Air pockets, one kind of concrete surface defects, are often created on formed concrete surfaces during concrete construction. Their existence undermines the desired appearance and visual uniformity of architectural concrete. Therefore, measuring the impact of air pockets on the concrete surface in the form of air pockets is vital in assessing the quality of architectural concrete. Traditionally, such measurements are mainly based on in-situ manual inspections, the results of which are subjective and heavily dependent on the inspectors’ own criteria and experience. Often, inspectors may make different assessments even when inspecting the same concrete surface. In addition, the need for experienced inspectors costs owners or general contractors more in inspection fees. To alleviate these problems, this paper presents a methodology that can measure air pockets quantitatively and automatically. In order to achieve this goal, a high contrast, scaled image of a concrete surface is acquired from a fixed distance range and then a spot filter is used to accurately detect air pockets with the help of an image pyramid. The properties of air pockets (the number, the size, and the occupation area of air pockets) are subsequently calculated. These properties are used to quantify the impact of air pockets on the architectural concrete surface. The methodology is implemented in a C++ based prototype and tested on a database of concrete surface images. Comparisons with manual tests validated its measuring accuracy. As a result, the methodology presented in this paper can increase the reliability of concrete surface quality assessment

Defects Detection and Assessment in Concrete Surfaces

Aside from cracks, the impact of other surface defects, such as air pockets and discoloration, can be detrimental to the quality of concrete in terms of strength, appearance and durability. For this reason, local and national codes provide standards for quantifying the quality impact of these concrete surface defects and owners plan for regular visual inspections to monitor surface conditions. However, manual visual inspection of concrete surfaces is a qualitative (and subjective) process with often unreliable results due to its reliance on inspectors’ own criteria and experience. Also, it is labor intensive and time-consuming. This paper presents a novel, automated concrete surface defects detection and assessment approach that addresses these issues by automatically quantifying the extent of surface deterioration. According to this approach, images of the surface shot from a certain angle/distance can be used to automatically detect the number and size of surface air pockets, and the degree of surface discoloration. The proposed method uses histogram equalization and filtering to extract such defects and identify their properties (e.g. size, shape, location). These properties are used to quantify the degree of impact on the concrete surface quality and provide a numerical tool to help inspectors accurately evaluate concrete surfaces. The method has been implemented in C++ and results that validate its performance are presented.