An Image-Based Framework for Measuring the Prestress Level in CFRP Laminates: Experimental Validation

Image-based methods have been applied to support structural monitoring, product and material testing, and quality control. Lately, deep learning for compute vision is the trend, requiring large and labelled datasets for training and validation, which is often difficult to obtain. The use of synthetic datasets is often applying for data augmentation in different fields. An architecture based on computer vision was proposed to measure strain during prestressing in CFRP laminates. The contact-free architecture was fed by synthetic image datasets and benchmarked for machine learning and deep learning algorithms. The use of these data for monitoring real applications will contribute towards spreading the new monitoring approach, increasing the quality control of the material and application procedure, as well as structural safety. In this paper, the best architecture was validated during experimental tests, to evaluate the performance in real applications from pre-trained synthetic data. The results demonstrate that the architecture implemented enables estimating intermediate strain values, i.e., within the range of training dataset values, but it does not allow for estimating strain values outside those range. The architecture allowed for estimating the strain in real images with an error ∼0.5%, higher than that obtained with synthetic images. Finally, it was not possible to estimate the strain in real cases from the training performed with the synthetic dataset.

Special Issue: Structural Concrete Material-New Trends for Eco-Efficiency and Performance

During the last few years, structural concrete has experienced significant advances, stimulated by the demand for stricter requirements in terms of sustainability, durability and strength [...].

Benchmarking for Strain Evaluation in CFRP Laminates Using Computer Vision: Machine Learning versus Deep Learning

The strengthening of concrete structures with laminates of Carbon-Fiber-Reinforced Polymers (CFRP) is a widely adopted technique. retained The application is more effective if pre-stressed CFRP laminates are adopted. The measurement of the strain level during the pre-stress application usually involves laborious and time-consuming applications of instrumentation. Thus, the development of expedited approaches to accurately measure the pre-stressed application in the laminates represents an important contribution to the field. This paper proposes and benchmarks contact-free architecture for measuring the strain level of CFRP laminate based on computer vision. The main objective is to provide a solution that might be economically feasible, automated, easy to use, and accurate. The architecture is fed by digitally deformed synthetic images, generated based on a low-resolution camera. The adopted methods range from traditional machine learning to deep learning. Furthermore, dropout and cross-validation methods for quantifying traditional machine learning algorithms and neural networks are used to efficiently provide uncertainty estimates. ResNet34 deep learning architecture provided the most accurate results, reaching a root mean square error (RMSE) of 0.057‱ for strain prediction. Finally, it is important to highlight that the architecture presented is contact-free, automatic, cost-effective, and measures directly on the laminate surfaces, which allows them to be widely used in the application of pre-stressed laminates.

Design and Durability Assessment of Restoring Mortar for Concrete Heritage

Interventions in concrete heritage deal with challenges related to conservation, and must be performed from an integrated restoration perspective. In addition to the material technical performance, the aesthetic compatibility between the repair and the structure, in terms of colour and texture, needs to be ensured. Therefore, the characterisation of the restoration mortar concerning colour match and aging, and the mechanical and durability performances, is essential. In this article, the long-term behaviour of restoration mortar, previously designed and produced by the addition of pigments to white and grey cement-based reference mortar, is evaluated. The durability properties, colour change due to aging, and service life are estimated and analysed. An experimental program is performed to characterise the following properties: (i) water capillary absorption; (ii) accelerated carbonation; (iii) migration of chloride ions; (iv) electrical resistivity; and (v) shrinkage. The colour evolution, when exposed to carbonation, is measured through image processing. The obtained results allow the establishment of a correlation between durability and design parameters. Finally, service life considering deterioration due to steel corrosion is estimated, considering the carbonation resistance and the chloride diffusion values. It is concluded that the W/C ratio influences not only most of the characterised parameters, but also the type and content of the pigment. Furthermore, no colour variation due to carbonation is detected.

Influence of Pozzolan, Slag and Recycled Aggregates on the Mechanical and Durability Properties of Low Cement Concrete

The sustainability of the construction sector demands the reduction of CO₂ emissions. The optimization of the amount of cement in concrete can be achieved either by partially replacing it by additions or by reducing the binder content. The present work aims at optimizing the properties of concrete used in the production of reinforced concrete poles for electrical distribution lines, combining the maximization of compactness with the partial replacement of cement by fly ash, natural pozzolans, and electric furnace slags. Natural aggregates were also partially replaced by recycled ones in mixtures with fly ash. Two types of concrete were studied: a fresh molded one with a dry consistency and a formwork molded one with a plastic consistency. The following properties were characterized: mechanical properties (flexural, tensile splitting, and compressive strengths, as well as Young's modulus) and durability properties (capillary water absorption, water penetration depth under pressure, resistance to carbonation, chloride migration, and concrete surface resistivity). The service life of structures was estimated, taking the deterioration of reinforcement induced by concrete carbonation or chloride attack into account. Results revealed that mixtures with fly ash exhibit higher mechanical performance and mixtures with fly ash or pozzolans reveal much higher durability results than the full Portland cement-based mixtures.

Durability and Time-Dependent Properties of Low-Cement Concrete

The sustainability concerns of concrete construction are focused both on the materials’ eco-efficiency and on the structures’ durability. The present work focuses on the characterization of low cement concrete (LCC), regarding time-dependent and durability properties. LCC studies which explore the influence of the formulation parameters, such as the W/C (water/cement ratio), W/Ceq, (which represents the mass ratio between water and equivalent cement), W/B (water/binder) ratio, and the reference curves, on the aforementioned properties are limited. Thus, several LCC mixtures were formulated considering two dosages of binder powder, 350 and 250 kg/m³, the former with very plastic consistency and the latter with dry consistency, which were combined with a large spectrum of cement replacement rates (up to 70%), through adding fly ash and limestone filler, and with different compactness levels. The main objectives were to study the influence of the formulation parameters on the properties: shrinkage and creep, accelerated carbonation and water absorption, by capillarity, and by immersion. The lifetime of structures produced with the studied LCC was estimated, considering the durability performance, regarding the carbonation effect on the possible corrosion of the steel reinforcement. LCC mixtures with reduced cement dosage and high compactness, despite the high W/C ratios, have low shrinkage and those with higher strength have reduced creep, however depending on W/C_eq ratio. Those mixtures can be formulated and produced presenting good performance regarding carbonation resistance and, consequently, a long lifetime, which is mandatory for a sustainable construction. LCC with 175 kg/m³ of cement dosage is an example with higher lifetime than current concrete with 250 kg/m³ of cement; depending on the XC exposure classes (corrosion induced by carbonation), the amount of cement can be reduced between 37.5% and 42%, since the LCC with 175 kg/m³ of cement allows reducing the concrete cover below the minimum recommended, ensuring simultaneously the required lifetime for current and special structures.