Adrian Long

Clam' Tests for Measuring in-Situ Permeation Properties of Concrete

Abstract This paper descirbes a simple test measuring the sorptivity (a measure of the absorption property if concrete) and the air and water permeability of concrete on site. Using this test, the decay of pressure is monitired for the air permeability test.whereas water penetrating into the concrete at a constant pressure of 0.01 bar and 1.5 bar are recorded for the sorptivity and the water permeability tests respectively. These tests are essentially non-destructive in nature and a skilled operator is not needed. It is possible to carry out a number of tests quickly and efficiently on site without prior planning. It has been found that statistically satisfactory results can be obtained from a mean of three tests. As the flow lines are largely concentrated within 40 mm from the surface, reasonably reliable results can be obtained by drying the surface even if the surface under test is initially wet.

Fibre optic chemical sensor systems for internal concrete condition monitoring

Methods for estimating the lifetime of reinforced concrete structures are being investigated with a fiber optic chemical sensor system, using a sol-gel as the matrix for the active material, for embedment in concrete for evaluation and testing. Results are presented on recent work.

Fiber optic chemical sensor systems for monitoring pH changes in concrete

Carbonation-induced corrosion of steel is one of the principal causes of deterioration of reinforced concrete structures. When concrete carbonates, its pH decreases from a value in excess of 12.6 to less than 9 and, hence, a measure of the pH is an indicator of the degree of carbonation. This paper describes the development, testing and evaluation of two types of fibre optic sensors for the pH monitoring. One of these used a sol-gel based probe tip, into which an indicator dye has been introduced and the second used a disc containing an indicator operating over a narrower range of pH with shorter lifetime. Both were connected to a portable spectrometer system, which is used to monitor the spectral changes in optical absorption of the probe tip. A white light source to interrogate the active elements is used as the systems operate in the visible part of the spectrum. The two types of sensors have been found to be sensitive to the changes in pH due to carbonation, but the response time depended on the thickness of the coating material in the case of the sol-gel sensor. The durability of the sensors is still under investigation. The disc type sensor has a life span of approximately 1 month and, hence, it is not suitable for embedding in concrete for long-term monitoring of pH changes. However, it can be used for assessing the pH in vivo. The harder sol-gel is more durable and, hence, has a slower, but acceptable response time.

A machine vision approach to the grading of crushed aggregate

The grading of crushed aggregate is carried out usually by sieving. We describe a new image-based approach to the automatic grading of such materials. The operational problem addressed is where the camera is located directly over a conveyor belt. Our approach characterizes the information content of each image, taking into account relative variation in the pixel data, and resolution scale. In feature space, we find very good class separation using a multidimensional linear classifier. The innovation in this work includes (i) introducing an effective image-based approach into this application area, and (ii) our supervised classification using wavelet entropy-based features.

Grading of construction aggregate through machine vision: results and prospects

Traditionally, crushed aggregate to be used in construction is graded using sieves. We describe an innovative machine vision approach to such grading. Our operational scenario is one where a camera takes images from directly overhead of a layer of aggregate on a conveyor belt. In this article, we describe effective solutions for (i) image segmentation, allowing larger pieces of aggregate to be measured and (ii) supervised classification from wavelet entropy features, for class assignment of both finer and coarse aggregate.

A Flexible Concrete Arch System for Durable Bridges

Masonry arch bridges are one of the oldest forms of bridge construction and have been around for thousands of years. Brick and stone were the original materials used and these bridges have proved to have a high level of durability, as most of them have remained serviceable after hundreds of years. In contrast, many bridges built of modern materials have required extensive repair and strengthening after being in service for a relatively short part of their design life and subsequently unable to meet current European loading standards [1][2]. This paper describes the development of a flexible concrete arch system that has virtually no embedded steel and can be constructed without centring thereby providing a highly durable and cost effective structure.

Pullout test correlations and in-place strength assessment : The European concrete frame building project

A full-scale, seven-story, reinforced concrete building frame was constructed in-place at the Building Research Establishments Cardington Laboratory, which encompassed a range of different concrete mixtures and advanced construction techniques. This provided an opportunity to assess in-place nondestructive test methods, namely the pullout test, and more specifically the Danish version, which has been known as the Lok test, on a systematic basis during the construction of the building. It was used in conjunction with both standard and temperature-matched cube specimens to assess its practicality and accuracy under site conditions. Strength correlations were determined using linear and power function regression analysis. Strength predictions from these were found to be in very good agreement with the compressive strengths of temperature-matched cube specimens. When a general correlation is used, however, estimates for compressive strength are likely to have 95% confidence limits of around ′20% of the mean value of four results.

Preliminary Development and Evaluation of Fiber-Optic Chemical Sensors

Conventional methods of measuring carbonation and chloride ingress exist, but they are either inaccurate, expensive, or involve destructive testing. In seeking new solutions to this problem, the potential to use novel fiber-optic chemical sensors developed specifically for this application and designed to monitor chemical changes in cementitious materials, in situ and nondestructively, was explored in this study. Three types of fiber-optic sensors were thus constructed, tested, and evaluated, viz a temperature sensor, a pH sensor, and chloride sensors. The temperature sensor was based on the fluorescence decay of temperature-dependent materials, whereas the pH and chloride sensors were based on sol-gel technology, with pH and chloride sensitive indicators impregnated in the sol-gels. All the sensors were tested in situ, and subsequently, the temperature and the pH sensors were embedded in mortar and tested. It was found that both the temperature sensor and the pH sensor could function correctly for over 18 months after placement, but there was an issue with alignment of the sensor each time it was reconnected to the hardware. However, the laboratory tests showed that the chloride sensor was not reversible, and therefore further refinement was considered to be necessary before it could be used in situ in environments where the chloride content was known, from other measurements, to decrease. Research is ongoing to refine the sensor performance and expands the in situ testing program. The sensors themselves are inexpensive to fabricate, but the sensing hardware used in this work is costly because of its high versatility.

Benchmarking segmentation results using a Markov model and a Bayes information criterion

Features are derived from wavelet transforms of images containing a mixture of textures. In each case, the texture mixture is segmented, based on a 10-dimensional feature vector associated with every pixel. We show that the quality of the resulting segmentations can be characterized using the Potts or Ising spatial homogeneity parameter. This measure is defined from the segmentation labels. In order to have a better measure which takes into account both the segmentation labels and the input data, we determine the likelihood of the observed data given the model, which in turn is directly related to the Bayes information criterion, BIC. Finally we discuss how BIC is used as an approximation in model assessment using a Bayes factor.

Machine vision methods for the grading of crushed aggregate

We address the problems of (1) segmenting coarse from fine granularity materials, and (2) discriminating between materials of different granularities. For the former we use wavelet features, and an enhanced version of the widely used EM algorithm. A weighted Gaussian mixture model is used, with a second order spatial neighborhood. For granularity discrimination we investigate the use of multiresolution entropy. We illustrate the good results obtained with a number of practical cases.