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Comportamiento a flexión pura de muros de mampostería en arcilla, reforzados con barras de FRP

Quintana Ruiz, Luis Alfonso (Escuela Colombiana de Ingeniería Julio GaravitoMaestría en Ingeniería Civil con Énfasis en Estructuras, 2017)

Due to the interest in the Colombian environment to be at the vanguard with the latest available technologies and materials, a research project was proposed in order to evaluate the flexion capacity of clay masonry, ...
Machine Learning Prediction of Flexural Behavior of UHPFRC

Abellán García, Joaquín; Fernández Gómez, Jaime A.; Torres Castellanos, Nancy; Núñez López, Andrés M. (Springer NatureSwitzerland, 2020)

To evaluate the possibility of predicting the flexural behaviour of UHPFRC, four analytical models were developed, based on artificial neural networks (ANN), to predict the first cracking tension or Limit of Proportionality ...

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Comportamiento a flexión pura de muros de mampostería en arcilla, reforzados con barras de FRP
...
Quintana Ruiz, Luis Alfonso | 2017

Due to the interest in the Colombian environment to be at the vanguard with the latest available technologies and materials, a research project was proposed in order to evaluate the flexion capacity of clay masonry, reinforced with FRP bars at perpendicu-lar loads to plane, and take the first step to generate a preliminary design protocol for the future based on the ACI 440 and TMS402 / ACI 530, Being that there is no design guide yet to contemplate the behavior of masonry under this approach. The experimental program included the construction and test of 16 masonry walls in clay, seven walls were reinforced with Glass fiber Reinforced Polymer (GFRP) bars, and the other seven were reinforced with CFRP Carbon fiber Reinforced polymer, and the remaining two were reinforced with conventional steel rods. The variables that were taken into account in the investigation were the dimensions of the wall in plan and the rebar. The walls were tested in a test frame which had a length between supports of 2030 mm and loaded the walls with two concentrade loads in the thirds along the wall, looking for a pure bending behavior in the central third. A very similar behavior of the analytical model was observed, compared to the experimental results for service loads. As for the ultimate loads, differences were found between theory and tests.

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Machine Learning Prediction of Flexural Behavior of UHPFRC
...
Abellán García, Joaquín | 2020

To evaluate the possibility of predicting the flexural behaviour of UHPFRC, four analytical models were developed, based on artificial neural networks (ANN), to predict the first cracking tension or Limit of Proportionality (LOP), its corresponding deflection (δLOP), ultimate strength or Modulus of Rupture (MOR), and its corresponding deflection (δMOR) of UHPFRC under bending test. The models that were composed of an input level, one output level, and four hidden levels were developed through the R platform. The input level applied the most significative Principal Components (PC) of a large dimension of input dataset. To avoid overfitting K-fold validation and l2 regularization was used. After the models were created, an improvement based on assembling of models by incorporating the predicted values in the dataset of features. The results indicated that the developed assembling models have a good accuracy for the prediction of the behaviour of UHPFRC under three or four points bending test, even when containing supplementary cementitious materials and hybrid mixture of fibers.

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Listar por tema "Flexibilidad"

Comportamiento a flexión pura de muros de mampostería en arcilla, reforzados con barras de FRP

Machine Learning Prediction of Flexural Behavior of UHPFRC

Envíos recientes

Comportamiento a flexión pura de muros de mampostería en arcilla, reforzados con barras de FRP

Machine Learning Prediction of Flexural Behavior of UHPFRC

Listar por tema "Flexibilidad"

Comportamiento a flexión pura de muros de mampostería en arcilla, reforzados con barras de FRP ﻿

Machine Learning Prediction of Flexural Behavior of UHPFRC ﻿

Envíos recientes

Comportamiento a flexión pura de muros de mampostería en arcilla, reforzados con barras de FRP

Machine Learning Prediction of Flexural Behavior of UHPFRC

Comportamiento a flexión pura de muros de mampostería en arcilla, reforzados con barras de FRP

Machine Learning Prediction of Flexural Behavior of UHPFRC