Damage assessment applied to reinforced concrete elements is one of the main activities infrastructure maintenance tasks. Among these elements, problem corrosion in particularly critical and requires careful consideration. Annually, governments invest a large amount economic resources this activity. However, most methodologies for damage rely on visual inspection, which may be subjectively interpreted, producing inconsistent results requiring considerable time resources. This study evaluates...

Concrete is a prominent construction material globally, owing to its reputed attributes such as robustness, endurance, optimal functionality, and adaptability. Formulating concrete mixtures poses formidable challenge, mainly when introducing novel materials additives evaluating diverse design resistances. Recent methodologies for projecting performance in fundamental aspects, including compressive strength, flexural tensile durability (encompassing homogeneity, porosity, internal structure),...

In recent years, advancements in deep learning (DL) have been leveraged civil engineering, but further exploration is necessary to apply DL techniques asphalt research. These advances involve employing computer vision tasks and machine approaches solve current challenges develop innovative solutions for the conservation monitoring of roads. laboratory, Hamburg-Wheel Tracking (HWT) test simulates expected vehicle traffic evaluates permanent deformation, such as rutting mixtures. Current works...

There are many different ways to estimate whether a concrete structure will be suffering corrosion degradation as experimental processes and numerical estimations relied on theoretical equations. Nevertheless, these require higher certainty satisfactory estimation accuracy. Deep Learning is causing profound changes in society. It has inspired unprecedented advances historically challenging problems. This paper proposes mathematician approach. A model capable of classifying the risk specimens...

WaveGFD is a repository inspired by the development and analysis of meshless finite difference schemes for wave equation in highly irregular domains, such as polygonal approximations geographical regions. These methods' innovative approach allows to address complexity solving partial differential equations They stand out their precision efficiency. The proposed methodology overcomes limitations conventional techniques, promising applicability broad spectrum complex physical problems....

This research explores the efficacy of YOLOR (You Only Learn One Representation) algorithm integrated with Deep Sort for real-time vehicle detection, classification, and counting in Morelia, Mexico. The study aims to enhance traffic monitoring management by leveraging advanced deep learning techniques. methodology involves deploying model at six key stations, varying confidence levels pre-trained weights, evaluate its performance across diverse conditions. results demonstrate that is...

Nowadays, society faces a catastrophic problem related to respiratory syndrome due the coronavirus SARS-CoV-2: Covid-19 disease. This virus has changed our coexistence rules and, in consequence, reshaped daily activities modern societies. Thus, there are many efforts understand behaviour order reduce its negative impact, and these produce an incredible amount of information data sources every week. Data scientists, which use techniques such as Machine learning, focusing their abilities...

The present research work shows the effect on carbonation of Portland cement-based mortars (PC) with addition green materials, specifically residues from two groups: agricultural and industrial wastes, minerals fibres. These materials have purpose helping waste disposal, recycling, improving durability concrete structures. specimens used for were elaborated CPC 30R RS, according to Mexican standard NMX-C-414, which is equivalent international ASTM C150. aggregates taken rivers Lerma...

The inclusion of additions to concrete blends helps improve performance in certain conditions. analysis two was performed, a blend with the addition natural organic polymer and control make predictive models find correlation. Tree tests were performed: Electrical resistivity ( E r ) test, Tensile strength F t Carbonation resistance. One most popular non-destructive on is , due simplicity measuring readings elements. It test that determines interconnectivity exists cementitious matrix by...

Abstract The flexural strength is a critical parameter for designing many concrete structures such as rigid pavements, beams, and bridges. standard test the compressive due to its ease of implementation. There are proposed methods estimating values with enough accuracy, although it necessary enhance accuracy this estimation, research suggests use artificial intelligence accomplish goal. Artificial Intelligence has been one most efficient approaches material parameters because performance....

Nowadays, the solid residues of concrete are considered waste, and this have been transformed into an environmental problem. This study analyzes use aggregates that comes from demolition process in order to create recycled concrete. The material reduces costs mitigates pollution. present research describes comparison blends using Opuntia Ficus Indica as addition coarse a substitution against control blend. Mechanical non-destructive tests were performed evaluate performance each mixture. A...

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. Banks of stone materials from Michoacán, Mexico were characterized, since they are used in the construction infrastructure area. With these made hydraulic concrete mixtures or asphalt mixtures, foundations, paving stones and restoration historical monuments. The rocks analyzed come banks volcanic crushed materials, which subjected to mechanical tests such as uniaxial compression resistance (UCR), addition was scanning electron microscope (SEM), by means characterization carried out,...

The study of durability is very important because buildings are expected to last; since attributed the materials used in construction, such required. Among them, stones play a fundamental role as part structures, well stone aggregates elaboration asphalt blends and concrete blends. Bearing this facts mind, quarry volcanic crushed were studied mexican state Michoacán.In work, Id2 , density, absorption data correlated obtain mathematical model that helps predict verify relationship between...

This paper proposes a deep learning model for predicting the durability benchmark on concrete specimens. The samples is commonly estimated throughout Ultrasonic Pulse Velocity measurements. test establishes relationship with taken into consideration material's homogeneity. proposed in this feed by standard laboratory tests as input parameters, making practical and efficient alternative to predict benchmark, saving time, short-cut work, avoiding sophisticated instrumentation use. Furthermore,...