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Relation Between Tensile Strength and Compressive Strength of Concrete01:30

Relation Between Tensile Strength and Compressive Strength of Concrete

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Concrete is a fundamental building material, and understanding its strengths is crucial for construction projects. The relationship between its tensile and compressive strengths is intricate, showing that while these strengths are related, they do not increase at the same rate. Tensile strength's growth is slower and is affected by various factors such as the methods used for testing, the size and shape of the specimen, the texture of the aggregate used, and the moisture content of the...
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Behavior of Concrete Under Compressive Load01:23

Behavior of Concrete Under Compressive Load

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Concrete exhibits specific behaviors under different compressive loads. Understanding this is crucial for understanding its structural integrity. When concrete undergoes uniaxial compression, it tends to develop cracks that run parallel to the direction of the force. These parallel cracks stem from localized tensile stresses that occur perpendicular to the compression direction. Additionally, angled cracks may appear due to the formation of shear planes.
As the concrete specimen fractures under...
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Non-destructive Tests for Concrete Strength01:12

Non-destructive Tests for Concrete Strength

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The rebound hammer test, also known as the Schmidt hammer test, is a non-destructive technique for evaluating the hardness of concrete and, indirectly, the strength of concrete. It operates on the principle that the rebound of a spring-driven mass from a concrete surface correlates to the surface's hardness. The device comprises a mass within a tubular housing, a spring mechanism, and a plunger that strikes the concrete. Upon release, the energy imparted to the mass by the spring causes it...
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Dynamic Modulus of Elasticity of Concrete01:16

Dynamic Modulus of Elasticity of Concrete

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The dynamic modulus of elasticity assesses how a concrete structure deforms under impact or dynamic loads. It is typically higher than the static modulus of elasticity, measured under slow, steady loading conditions.
The sonic test is a common method to determine the dynamic modulus. In this test, a concrete beam, sized either 6 x 6 x 30 inches or 4 x 4 x 20 inches, is clamped at its center. Vibrations are initiated at one end of the beam by an electromagnetic exciter unit powered by a...
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Tensile Strength Considerations of Concrete01:16

Tensile Strength Considerations of Concrete

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Considering the tensile strength of concrete involves recognizing that the theoretical strength of cement paste can be up to a thousand times higher than what is observed in practical applications. This significant discrepancy is largely attributed to the presence of microscopic cracks within the concrete. These cracks tend to amplify stress at their tips when a load is applied, a phenomenon explained by Griffith's theory of brittle fracture.
The dimensions and shape of a concrete specimen...
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Strength of Cement01:20

Strength of Cement

669
Strength tests for cement are not performed directly on neat cement paste due to difficulty in obtaining consistent, reliable specimens. Instead, cement is typically tested in the form of cement-sand mortar.
For compressive strength tests, ASTM C 109-05 standards prescribe a cement-sand mix ratio of 1:2.75 and a water/cement ratio of 0.485 for making 2-inch cubes. These cubes are mixed, cast, and cured in saturated lime water at 23°C until testing. Flexural strength testing, outlined in...
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Updated: Feb 28, 2026

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

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Predicción de la resistencia a la compresión del hormigón mediante aprendizaje profundo optimizado y modelos de

Safaa Zaman1, Marwa M Eid2, Ebrahim A Mattar3

  • 1Information Sciences Department, College of Life Sciences, Kuwait University, Kuwait City, Kuwait.

Scientific reports
|February 26, 2026
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio presenta un novedoso marco de IA que combina el algoritmo de optimización iHowOA y redes convolucionales de grafos espacio-temporales (STGCN) para la predicción precisa de la resistencia a la compresión del hormigón, mejorando el diseño de materiales de construcción sostenibles.

Palabras clave:
Resistencia a la compresión del hormigónLLMMetaheurísticasSTGCNMateriales de construcción sostenibles

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Área de la Ciencia:

  • Ciencia de Materiales; Ingeniería Civil; Inteligencia Artificial

Sus antecedentes:

  • La predicción de la resistencia a la compresión del hormigón es crucial para la construcción sostenible.; Las complejas interacciones entre los componentes de la mezcla, los aditivos y las condiciones de curado plantean desafíos.; Los métodos existentes a menudo luchan con la naturaleza no lineal de estas interacciones.

Objetivo del estudio:

  • Desarrollar un marco híbrido avanzado de IA para mejorar la predicción de la resistencia a la compresión del hormigón.; Mejorar la precisión y robustez de los modelos predictivos para materiales de construcción.; Aprovechar técnicas novedosas de optimización y aprendizaje profundo para aplicaciones en ciencia de materiales.

Principales métodos:

  • Integración del algoritmo de optimización iHowOA con redes convolucionales de grafos espacio-temporales (STGCN).; Utilización de un modelo de lenguaje grande (LLM) para el preprocesamiento de datos, incluida la validación semántica y la armonización de características.; Optimización de la arquitectura STGCN utilizando las capacidades de toma de decisiones adaptativas y adquisición de conocimiento de iHowOA.; Modelado basado en grafos para capturar dependencias espaciales y evolución temporal de la resistencia.

Principales resultados:

  • El marco propuesto iHowOA-STGCN demostró un rendimiento predictivo superior en comparación con otros diez optimizadores metaheurísticos.; Se lograron errores de predicción más bajos y coeficientes de correlación más altos en un conjunto de datos público.; Se identificaron relaciones clave entre las propiedades del cemento, la ganancia de resistencia dependiente de la edad y las interacciones fisicoquímicas.

Conclusiones:

  • El marco iHowOA-STGCN ofrece una prometedora herramienta de apoyo a la toma de decisiones basada en datos para la predicción de la resistencia del hormigón.; El preprocesamiento impulsado por LLM mejora la calidad de los datos y la robustez de la entrada del modelo.; Se recomienda una validación adicional en conjuntos de datos diversos para confirmar la generalización y la aplicabilidad práctica en escenarios del mundo real.