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.

An efficient approach of modelling the flexural cracking behaviour of un-notched plain concrete prisms subject to monotonic and cyclic loading

In the field of vibration-based damage detection of concrete structures efficient damage models are needed to better understand changes in the vibration properties of cracked structures. These models should quantitatively replicate the damage mechanisms in concrete and easily be used as damage detection tools. In this paper, the flexural cracking behaviour of plain concrete prisms subject to monotonic and cyclic loading regimes under displacement control is tested experimentally and modelled numerically. Four-point bending tests on simply supported un-notched prisms are conducted, where the cracking process is monitored using a digital image correlation system. A numerical model, with a single crack at midspan, is presented where the cracked zone is modelled using the fictitious crack approach and parts outside that zone are treated in a linear-elastic manner. The model considers crack initiation, growth and closure by adopting cyclic constitutive laws. A multi-variate Newton-Raphson iterative solver is used to solve the non-linear equations to ensure equilibrium and compatibility at the interface of the cracked zone. The numerical results agree well with the experiments for both loading scenarios. The model shows good predictions of the degradation of stiffness with increasing load. It also approximates the crack-mouth-opening-displacement when compared with the experimental data of the digital image correlation system. The model is found to be computationally efficient as it runs full analysis for cyclic loading in less than 2. min, and it can therefore be used within the damage detection process. © 2013 Elsevier Ltd.

The sensitivity of vibration characteristics of reinforced concrete beams under incremental static and cyclic loading

The use of changes in vibration properties for global damage detection and monitoring of existing concrete structures has received great research attention in the last three decades. To track changes in vibration properties experimentally, structures have been artificially damaged by a variety of scenarios. However, this procedure does not represent realistically the whole design-life degradation of concrete structures. This paper presents experimental work on a set of damaged reinforced concrete beams due to different loading regimes to assess the sensitivity of vibration characteristics. Of the total set, three beams were subject to incremental static loading up to failure to simulate overloading, and two beams subject to 15 million loading cycles with varying amplitudes to produce an accelerated whole-life degradation scenario. To assess the vibration behaviour in both cases, swept sine and harmonic excitations were conducted at every damage level. The results show that resonant frequencies are not sensitive enough to damage due to cyclic loading, whereas cosh spectral and root mean square distances are more sensitive, yet more scattered. In addition, changes in non-linearity follow a softening trend for beams under incremental static loading, whilst they are significantly inconsistent for beams under cyclic loading. Amongst all examined characteristics, changes in modal stiffness are found to be most sensitive to damage and least scattered, but modal stiffness is tedious to compute due mainly to the difficulty of constructing restoring force surfaces from field measurements. © (2013) Trans Tech Publications.

Mechanical and durability properties of concretes containing recycled lime powder and recycled aggregates

According to a recent report by the European Commission, within the European Union, the construction and demolition wastes come to at least 450 million tons per year. Roughly 75% of the waste is disposed to landfill, despite its major recycling potential. The bulk constituents of demolition debris are concrete (50-55%) and masonry (30-40%) with only small percentages of other materials such as metals, glass and timber. In Cyprus, at present, recycling of waste materials is practically inexistent and almost the entire demolition waste products are disposed in landfill sites, with all possible economic, technical and environmental impacts. This research paper presents the evaluation and the effective reuse of waste construction materials, such as recycled lime powder (RLP) and recycled concrete aggregates (RCA), disposed to landfill sites in Cyprus, due to the lack of a lucid recycling policy and knowledge. Results show that both RLP and RCA have the potential to produce good quality and robust concrete mixtures both in terms of mechanical and durability performance. © 2013 Elsevier B.V. All rights reserved.

Durability of similar self-compacting concrete batches produced in two different EU laboratories

The present study intends to evaluate the sensitivity of self-compacting concrete (SCC) mixtures, cast in two different laboratories of the European Union, with a focus on rheological parameters, mechanical characteristics and durability properties. Six SCC mixtures with different water-to-binder ratios and silica fume levels of cement replacement and two normally vibrated concrete (NVC) mixtures have been compared. It has been found that the reproducibility of similar mixtures is possible, when using different constituent materials that conform to the European Standards. Comparable rheological, mechanical and durability properties can be achieved. Open porosity and sorptivity appear to be more sensitive than chloride penetrability. © 2012 Elsevier Ltd. All rights reserved.

Reproducibility of self-compacting concrete batches between two different EU laboratories

Self Compacting Concrete (SCC) offers a wide variety of advantages during casting. Considering the worldwide uniformity of guidelines concerning the composition and casting instructions for the production of fresh SCC, there is a need to explore the reproducibility of similar self-compacting concrete batches between different countries. In the present study, the fresh properties of similar SCC batches produced in two different laboratories of the European Union are being compared and evaluated.

Mix design, mechanical properties and impact resistance of UHPFRCCs

The research work focused on the determination of guidelines for the production of an UHPFRCC, and the experimental investigation of the quality and the behaviour of this material in a highly demanding application, such as the impact resistance of structures. Specifically, the aim of this study is to present the results of an extended work on the development of an UHPFRCC and the experimental determination of the mechanical properties of the produced material. Furthermore, the paper will present preliminary experimental results on the impact resistance of Reinforced Concrete and UHPFRCC slab specimens. © 2012 Taylor & Francis Group.

Mechanical and fracture properties of cement-based bi-materials after thermal cycling

This study investigates the effect of thermal cycles on the fracture properties of the cement-based bi-materials. Sixty eight cubes were exposed to a varied number of 24-hour thermal cycles ranging from 0 to 90 and subsequently were tested in a wedge splitting configuration. The mechanical and fracture properties of normal strength and high strength concretes are substantially improved after 30 thermal cycles, but less so after 90 thermal cycles both in isolation and when bonded to an ultra high-performance fibre-reinforced cement-based composite. © 2009 Elsevier Ltd. All rights reserved.

MgO expansive cement and concrete in China: Past, present and future

Uniquely, China employs MgO already contained in cement clinker or as an expansive additive to compensate for the thermal shrinkage of mass concrete, particularly dam concrete, with almost 40 years' experience in both research activities and industrial applications. Compensating shrinkage with expansion produced by MgO has been proved to effectively prevent thermal cracking of mass concrete, and reduce the cost of temperature control measures and speed up the construction process. Moreover, the expansion properties of MgO could be designed flexibly, through adjusting its microstructure by changing the calcination conditions (calcining temperature and residence time). The collective knowledge and experience of MgO expansive cement and concrete is worthy of sharing with relevant engineers and researchers globally but dissemination has been hindered as most of the relevant literature is published in Chinese. This paper reviews the history, state-of-the-art progress and future research needs in the field of MgO expansive cement and concrete. © 2013 Elsevier Ltd.

Reinforcement corrosion initiation and activation times in concrete structures exposed to severe marine environments

The corrosion of steel reinforcement bars in reinforced concrete structures exposed to severe marine environments usually is attributed to the aggressive nature of chloride ions. In some cases in practice corrosion has been observed to commence already within a few years of exposure even with considerable concrete cover to the reinforcement and apparently high quality concretes. However, there are a number of other cases in practice for which corrosion initiation took much longer, even in cases with quite modest concrete cover and modest concrete quality. Many of these structures show satisfactory long-term structural performance, despite having high levels of localized chloride concentrations at the reinforcement. This disparity was noted already more than 50 years ago, but appears still not fully explained. This paper presents a systematic overview of cases reported in the engineering and corrosion literature and considers possible reasons for these differences. Consistent with observations by others, the data show that concretes made from blast furnace cements have better corrosion durability properties. The data also strongly suggest that concretes made with limestone or non-reactive dolomite aggregates or sufficiently high levels of other forms of calcium carbonates have favourable reinforcement corrosion properties. Both corrosion initiation and the onset of significant damage are delayed. Some possible reasons for this are explored briefly.

Factorial Design of Cement Slurries Containing Limestone Powder for Self-Consolidating Slurry-Infiltrated Fiber Concrete

Slurries with high penetrability for production of Self-consolidating Slurry Infiltrated Fiber Concrete (SIFCON) were investigated in this study. Factorial experimental design was adopted in this investigation to assess the combined effects of five independent variables on mini-slump test, plate cohesion meter, induced bleeding test, J-fiber penetration test and compressive strength at 7 and 28 days. The independent variables investigated were the proportions of limestone powder (LSP) and sand, the dosages of superplasticiser (SP) and viscosity agent (VA), and water-to-binder ratio (w/b). A two-level fractional factorial statistical method was used to model the influence of key parameters on properties affecting the behaviour of fresh cement slurry and compressive strength. The models are valid for mixes with 10 to 50% LSP as replacement of cement, 0.02 to 0.06% VA by mass of cement, 0.6 to 1.2% SP and 50 to 150% sand (% mass of binder) and 0.42 to 0.48 w/b. The influences of LSP, SP, VA, sand and W/B were characterised and analysed using polynomial regression which identifies the primary factors and their interactions on the measured properties. Mathematical polynomials were developed for mini-slump, plate cohesion meter, J-fiber penetration test, induced bleeding and compressive strength as functions of LSP, SP, VA, sand and w/b. The estimated results of mini-slump, induced bleeding test and compressive strength from the derived models are compared with results obtained from previously proposed models that were developed for cement paste. The proposed response models of the self-consolidating SIFCON offer useful information regarding the mix optimization to secure a highly penetration of slurry with low compressive strength

Casting of Self-Compacting Concrete

Increased productivity and improved working environment have had high priority in the development of concrete construction over the last decade. Development of a material not needing vibration for compaction—i.e. selfcompacting concrete (SCC)—has successfully met the challenge and is now increasingly being used in routine practice. The key to the improvement of fresh concrete performance has been nanoscale tailoring of molecules for surface active admixtures, as well as improved understanding of particle packing and of the role of mineral surfaces in cementitious matrixes. Fundamental studies of rheological behaviour of cementitious particle suspensions were soon expanded to extensive innovation programmes incorporating applied research, site experiments, instrumented full scale applications supporting technology, standards and guides, information efforts as well as training programmes. The major impact of the introduction of SCC is connected to the production process. The choice and handling of constituents are modified as well as mix design, batching, mixing and transporting. The productivity is drastically improved through elimination of vibration compaction and process reorganisation. The working environment is significantly enhanced through avoidance of vibration induced damages, reduced noise and improved safety. Additionally, the technology is improving performance in terms of hardened material properties like surface quality, strength and durability.

Artificial Intelligence Model for Flowable Concrete Mixtures Used in Underwater Construction and Repair

This study explores using artificial neural networks to predict the rheological and mechanical properties of underwater concrete (UWC) mixtures and to evaluate the sensitivity of such properties to variations in mixture ingredients. Artificial neural networks (ANN) mimic the structure and operation of biological neurons and have the unique ability of self-learning, mapping, and functional approximation. Details of the development of the proposed neural network model, its architecture, training, and validation are presented in this study. A database incorporating 175 UWC mixtures from nine different studies was developed to train and test the ANN model. The data are arranged in a patterned format. Each pattern contains an input vector that includes quantity values of the mixture variables influencing the behavior of UWC mixtures (that is, cement, silica fume, fly ash, slag, water, coarse and fine aggregates, and chemical admixtures) and a corresponding output vector that includes the rheological or mechanical property to be modeled. Results show that the ANN model thus developed is not only capable of accurately predicting the slump, slump-flow, washout resistance, and compressive strength of underwater concrete mixtures used in the training process, but it can also effectively predict the aforementioned properties for new mixtures designed within the practical range of the input parameters used in the training process with an absolute error of 4.6, 10.6, 10.6, and 4.4%, respectively.