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Defects in concrete surfaces are inevitably recurring during construction, which needs to be checked and accepted during construction and completion. Traditional manual inspection of surface defects requires inspectors to judge, evaluate and make decisions, which requires sufficient experience and is time-consuming and labor-intensive, and the expertise cannot be effectively preserved and transferred. In addition, the evaluation standards of different inspectors are not identical, which may lead to cause discrepancies in inspection results. Although computer vision can achieve defect recognition, there is a gap between the low-level semantics acquired by computer vision and the high-level semantics that humans understand from images. Therefore, computer vision and ontology are combined to achieve intelligent evaluation and decision-making and to bridge the above gap.

Combining ontology and computer vision, this paper establishes an evaluation and decision-making framework for concrete surface quality. By establishing concrete surface quality ontology model and defect identification quantification model, ontology reasoning technology is used to realize concrete surface quality evaluation and decision-making.

Computer vision can identify and quantify defects, obtain low-level image semantics, and ontology can structurally express expert knowledge in the field of defects. This proposed framework can automatically identify and quantify defects, and infer the causes, responsibility, severity and repair methods of defects. Through case analysis of various scenarios, the proposed evaluation and decision-making framework is feasible.

This paper establishes an evaluation and decision-making framework for concrete surface quality, so as to improve the standardization and intelligence of surface defect inspection and potentially provide reusable knowledge for inspecting concrete surface quality. The research results in this paper can be used to detect the concrete surface quality, reduce the subjectivity of evaluation and improve the inspection efficiency. In addition, the proposed framework enriches the application scenarios of ontology and computer vision, and to a certain extent bridges the gap between the image features extracted by computer vision and the information that people obtain from images.

Optimised concrete components are often of complex geometries, which are difficult and costly to cast using traditional formworks. This paper aims to propose an innovative formwork system for optimised concrete casting, which is eco-friendly, recyclable and economical.

In the proposed formwork system, ice is used as mould pattern to create desired geometry for concrete member, then sand mould is fabricated based on the ice pattern. A mix design and a mixing procedure for the proposed sand mould are developed, and compression tests are also performed to ensure sufficient strength of the sand mould. Furthermore, surface preparation of the sand mould is investigated for easy demoulding and for achieving good concrete surface quality. Additionally, recyclability of the proposed sand mould is tested.

The proposed mix design and mixing procedure can provide sufficient strength for sand mould in concrete casting. The finished components exhibit smooth surfaces and match designed geometries, and the proposed sand mould can be fully recycled with satisfactory strength.

To the best of the authors’ knowledge, this is the first study that combines ice pattern and sand mould to create recyclable formwork system for concrete casting. The new techniques developed in this research has great potential to be applied in the fabrication of large-scale concrete structures with complex geometries.

Using coconut shell aggregates (CSA) in concrete benefits agricultural waste management and reduces the demand for mineral resources. Several studies have found that concrete containing CSA can achieve strengths that are comparable to regular concrete. The purpose of the present work is to evaluate the concrete’s durability-related properties to supplement these earlier findings.

Cylindrical specimens were prepared with a constant water–cement ratio of 0.50 and CSA content ranging from 0% to 50% (at 10% increment) by volume of the total coarse aggregates. The specimens were cured for 28 days and then tested for density, surface hardness, electrical resistivity and water sorptivity. The surface hardness was measured to describe the concrete resistance to surface wearing, while the resistivity and sorptivity were evaluated to describe the material’s resistance to fluid penetration.

The results showed that the surface hardness of concrete remained on average at 325 Leeb and did not change significantly with CSA addition. The distribution of surface hardness was also similar across all CSA groups, with the interquartile range averaging 59 Leeb. These results suggest that the cement paste and gravel stiffness had a more pronounced influence on the surface hardness than CSA. On the other hand, concrete became lighter by about 9%, had lower resistivity by 80% and had significantly higher initial sorptivity by up to 110%, when 50% of its natural gravel was replaced with CSA. Future work may be done to improve the durability of CSA when used as coarse aggregate.

The present study is the first to show the lack of correlation between CSA content and surface hardness. It would mean that the surface hardness test may not completely capture the porous nature of CSA-added concrete. The paper concludes that without additional treatment prior to mixing, CSA may be limited only to applications where concrete is not in constant contact with water or deleterious substances.

There are a great number of in situ floor finishes available today, including the traditional self‐finished concrete, granolithic and sand cement screeds as well as a bewildering array of special proprietary floor finishes. These include epoxy and polyester resin mortars, and bitumen and polymer emulsion cementitious floor toppings. This article looks at the most common types of floor finish, describes their uses and looks at some of the common faults which arise both through poor materials and workmanship, and heavy usage.

This paper reviews the most common building defects and techniques for their diagnosis. Problem areas are listed by their location within a structure and the information is presented in tabular form for easy reference. The first paper in this series — ‘Effective diagnosis of material problems and defects in building and construction’ — was published in Structural Survey Volume 4 Number 1. Part 3 will be an appraisal of better known in situ testing and NDT techniques featuring specific items of equipment.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

To predict the real behavior of the full-scale model using a scale model, optimized simulation should be achieved. In reinforced concrete (RC) models, scaling can be substantially more critical than in single-material models because of multiple reasons such as insufficient bonding strength between small-diameter steel bars and concrete, and excessive aggregate size. Overall, there is a shortfall of laboratory and field-testing studies on the behavior of secant pile walls under lateral and axial loads. Accordingly, the purpose of this study is to investigate the validity and the performance of the 1/10th scaled RC secant pile wall under the influence of different types of loading.

The structural performance of the examined models was evaluated using two types of tests: bending and axial compression. A self-compacting concrete mix was suggested, which provided the best concrete mix workability and appropriate compressive strength.

Under axial and bending loads, the failure modes were typical. Where the plain and reinforced concrete piles worked in tandem to support the load throughout the loading process, even when they failed. The experimental results were relatively consistent with some empirical equations for calculating the modulus of elasticity and critical buckling load. This confirmed the validity of the proposed model.

According to the analysis and verification of experimental tests, the proposed 1/10th scaled RC secant pile model can be used for future laboratory purposes, especially in the field of geotechnical engineering.

The purpose of this paper is to establish and evaluate the concrete loss and labor productivity (LP) indicators in the concreting step of aluminum formwork system (AFS) in construction in Brazil. The loss and productivity indicators are directed to a regional database (Pernambuco, Brazil).

Case study was selected as the most appropriate approach. The methodology included data collection in the construction project with 10 residential towers of 320 apartments, in the city of Jaboatão dos Guararapes, Brazil, throughout 82 concrete pouring days using 415 concrete mixer trucks, with a total of 2,582.50 m³ of concrete.

The findings identified an average concrete loss of 2.6 percent and the LP indicator varying between 0.15 and 0.97 WH/m³. It could be verified that the loss indicators were influenced mainly by the learning effect associated to the qualification of the labor. In addition, the productivity indicators were strongly influenced by delays at the beginning of the concrete pouring and by problems coming from the sequence of concrete supply.

LP indicators are still literature restricted, especially considering only the concreting step. The direct observations of this study allow the identification of factors that inhibit productivity. The comparison of indicators for the concreting service between the ASF and the conventional system attests to the speed, low cost and efficiency of the system studied in this paper.

The limitation of bridges’ operation can cause serious social, environmental and economic losses. Therefore, the monitoring and maintenance actions of these structures must be efficient and periodic, especially for bridges located in aggressive environments, such as urban-industrial centres, where the higher volume of carbon dioxide emissions favours carbonation induced corrosion. The purpose of this paper is to analyse the utility of including non-destructive testing (NDTs) to bridges assessment in that regions as a way of obtaining more in-depth information on the conditions of the material composing the structure.

First, the main bridges’ damages were detected by visual inspection. Then, based on the observations of bridges design, environment and main damages, an NDT programme was executed including surface hardness, ultrasonic pulse velocity test, pH indicator spraying, half-cell potential measurements and concrete resistivity tests.

It was observed that, for the studied cases, the carbonation did not present harmful depths, except for the structural elements where segregation and wear of the concrete were noticed. NDTs, associated with visual inspection, indicated the regions where corrective or preventive maintenance actions were actually needed, bringing greater security to the decision maker in regions where repairs are unnecessary or could be postponed.

This paper highlights the contribution of NDTs application in structures in urban-industrial regions where the main mechanism of deterioration is carbonation-induced corrosion, demonstrating the importance of these methods in the rational decision making of investments for maintenance.