100 resultados para Height Tolerance of Concrete Blocks


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Several research studies have been recently initiated to investigate the use of construction site images for automated infrastructure inspection, progress monitoring, etc. In these studies, it is always necessary to extract material regions (concrete or steel) from the images. Existing methods made use of material's special color/texture ranges for material information retrieval, but they do not sufficiently discuss how to find these appropriate color/texture ranges. As a result, users have to define appropriate ones by themselves, which is difficult for those who do not have enough image processing background. This paper presents a novel method of identifying concrete material regions using machine learning techniques. Under the method, each construction site image is first divided into regions through image segmentation. Then, the visual features of each region are calculated and classified with a pre-trained classifier. The output value determines whether the region is composed of concrete or not. The method was implemented using C++ and tested over hundreds of construction site images. The results were compared with the manual classification ones to indicate the method's validity.

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Manually inspecting concrete surface defects (e.g., cracks and air pockets) is not always reliable. Also, it is labor-intensive. In order to overcome these limitations, automated inspection using image processing techniques was proposed. However, the current work can only detect defects in an image without the ability of evaluating them. This paper presents a novel approach for automatically assessing the impact of two common surface defects (i.e., air pockets and discoloration). These two defects are first located using the developed detection methods. Their attributes, such as the number of air pockets and the area of discoloration regions, are then retrieved to calculate defects’ visual impact ratios (VIRs). The appropriate threshold values for these VIRs are selected through a manual rating survey. This way, for a given concrete surface image, its quality in terms of air pockets and discoloration can be automatically measured by judging whether their VIRs are below the threshold values or not. The method presented in this paper was implemented in C++ and a database of concrete surface images was tested to validate its performance. Read More: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0000126?journalCode=jcemd4

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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

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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.

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Aging concrete infrastructure in developed economies and more recently constructed concrete infrastructure in the developing world are frequently found to be deficient in structural strength relative to current needs. This can be attributed to a variety of factors including deterioration, construction defects, accidental damage, changes in understanding and failure to design for future loading requirements. Strengthening existing concrete structures can be a cost and carbon effective alternative to replacement. A competitive option for the strengthening of concrete slab-on-beam structures that are deficient in shear capacity is the U-wrapping of the down-stand beam portion of the shear span with externally bonded FRP fabric. While guidance exists for the strengthening of reinforced concrete by U-wrapping, the interaction between internal steel reinforcement, concrete and external FRP in the presence of a dominant diagonal shear crack is not well understood. An approach adopted in previous work has been to explore this interaction through conventional push-off testing. In conventional push-off testing, unlike in a beam, the shear plane is parallel to the direction of loading and perpendicular to the principal fibre orientation. This paper presents a novel push-off test variation in which the shear plane is inclined at 45° to the direction of loading and the principal fibre orientation. A variety of reinforcement ratios, FRP thicknesses and FRP end conditions are modelled. The implications of inclined cracking on debonding of FRP are investigated. The suitability and relevance of inclined push-off tests for further work in this area is also assessed. © 2013, NetComposite Limited.

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A class of ultra-high-performance fibre-reinforced cementitious composites (UHPFRCC) has been developed at Cardiff university and registered under the trade name CARDIFRC. The method of its production and its mechanical and fracture properties were reported previously in a series of papers in Magazine of Concrete Research. Here the results of recent fatigue and shrinkage tests on this material are reported. As with the mechanical and fracture properties, it is shown that an even and uniform distribution of fibres throughout the bulk of the material is crucial to its superior fatigue performance and to the reduction in the shrinkage strains. © 2010 Thomas Telford Ltd.

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This study investigates the effect of thermal cycling on the performance of concrete beams retrofitted with CARDIFRC, a new class of high performance fiber-reinforced cement-based material that is compatible with concrete. Twenty four beams were subjected to 24 h thermal cycles between 25 and 90°C. One third of the beams were reinforced either in flexure only or in flexure and shear with conventional steel reinforcement and used as control specimens. The remaining sixteen beams were retrofitted with CARDIFRC strips to provide external flexural and/or shear strengthening. All beams were exposed to a varied number of 24 h thermal cycles ranging from 0 to 90 and were tested in four-point bending at room temperature. The tests indicated that the retrofitted members were stronger and stiffer than control beams, and more importantly, that their failure initiated in flexure without any signs of interfacial delamination cracking. The results of these tests are presented and compared to analytical predictions. The predictions show good correlation with the experimental results. © 2010 ASCE.

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Concrete is the most widely used construction material. At the same time, however, the concrete industry is a major CO2 emitter thus contributing towards global warming. While enhanced efficiency in the production of concrete is not likely to dramatically reduce the CO2 emissions, cement replacement by a supplementary material or mineral additive, such as silica fume, which is not associated with CO2 emission, can substantially reduce the aforementioned problem. The present work discusses the benefits of incorporating mineral additives in concrete and shows that these additives can improve both the mechanical and physical properties of the end-product, and hence its durability, albeit with a reduction in cement content. © 2009 WIT Press.