A Prediction Model for the Calculation of Effective Stiffness Ratios of Reinforced Concrete Columns

Das, Sourav; Mansouri, Iman; Choudhury, Satyabrata; Gandomi, Amir H.; Hu, Jong Wan

doi:10.3390/ma14071792

Cited by 9 publications

(3 citation statements)

References 30 publications

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“…Stiffness is the ratio between the maximum load and the displacement in concrete [42]. Concrete stiffness can be calculated by comparing concrete's maximum force and maximum deflection [43].…”

Section: Concrete Stiffness Test Resultsmentioning

confidence: 99%

Effect of Bacillus Subtilis Bacteria on The Mechanical Properties of Corroded Self-Healing Concrete

Nindhita,

Zaki,

Zeyad

2024

Frattura Ed Integrità Strutturale

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Reinforced concrete has a weakness for corrosion which can cause the concrete to crack and the concrete structure to fail. To overcome this problem, a self-healing concrete method is needed that can close cracks and inhibit the rate of natural corrosion. Bacillus subtilis as a self-healing agent in concrete has been proven to be able to increase the compressive strength and flexural strength of concrete. The method used in this research is to add bacterial hydrogel encapsulation to concrete with a variation of 0%; 0.1%; 0.6%; and 1.5% by weight of sand. The test object is a reinforced concrete beams and cylindrical concrete with compressive design strength of 30 MPa. The concrete specimens will go through a series of tests, such as corrosion acceleration tests using DC power supply, self-healing tests by visual observation, flexural strength, ductility, stiffness, and compressive strength tests using Universal Testing Machine (UTM). From the test results, it was found that the addition of 0.1% bacterial encapsulation variation was the optimum value for increasing the mechanical properties of self-healing concrete and reduce the corrosion rate on self-healing concrete.

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Section: Concrete Stiffness Test Resultsmentioning

confidence: 99%

Effect of Bacillus Subtilis Bacteria on The Mechanical Properties of Corroded Self-Healing Concrete

Nindhita,

Zaki,

Zeyad

2024

Frattura Ed Integrità Strutturale

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“…De acuerdo con, (34,38,69,70,71) las series de Fourier permiten determinar el espectro de frecuencia de mediciones de frecuencias y sus amplitudes, producto de señales. También comenta que dicho proceso que cuantifica las diversas intensidades de cada frecuencia es conocido como análisis espectral, las mismas que se representan de acuerdo con las siguientes ecuaciones:…”

Section: Transformadas De Fourierunclassified

Estimation of effective rigidity in reinforced concrete structures through modal identification tests and sclerometry

Mamani Uscamayta,

Rodríguez Vásquez,

Jarecca Cusacani

et al. 2023

Salud, Ciencia y Tecnología - Serie de Conferencias

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Actualmente es conocido que los elementos estructurales de una edificación pueden agrietarse por fallas estructurales bajo cargas de servicio, por sismos frecuentes de baja intensidad o durante los primeros instantes de un sismo severo, lo cual podría resultar en secciones agrietadas cuando se tenga la acción del sismo de máxima intensidad, para tales consideraciones, la norma peruana de análisis sísmico no contempla secciones agrietadas para el análisis sísmico. El presente estudio tuvo como finalidad estimar los factores de rigidez efectiva de 4 edificaciones de concreto armado. La investigación tiene un enfoque cuantitativo de diseño no experimental, la muestra está constituida por 4 edificaciones de concreto armado de la ciudad de Juliaca, a las que se realizaron ensayos de esclerometría e identificación modal con sensores X16 – 1D para obtener las resistencias a la compresión y periodos naturales de vibración de campo respectivamente. Se obtuvieron los modelos numéricos con sus resistencias de concreto reales considerando la tabiquería existente a los cuales se aplicaron factores de reducción de rigidez mediante códigos internacionales e iteraciones para aproximar sus periodos naturales a los periodos naturales obtenidos por identificación modal. Los resultados demuestran que existe una diferencia de periodos naturales de vibración entre el modelo numérico con resistencias reales considerando los efectos de la tabiquería y los obtenidos con ensayos de identificación modal en un rango del 5 % al 30 %, lo cual demuestra que el periodo fundamental de vibración de campo es mayor al proyectado.

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“…Nowadays, artificial intelligence methods are widely used in estimating concrete properties [1][2][3][4][5][6][7][8][9][10]. The demand for cement has significantly increased over the past few decades as a result of building new infrastructure and supporting global population growth.…”

Section: Introductionmentioning

confidence: 99%

Environmentally Friendly Concrete Compressive Strength Prediction Using Hybrid Machine Learning

Mansouri

Manfredi²,

2022

Sustainability

Self Cite

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In order to reduce the adverse effects of concrete on the environment, options for eco-friendly and green concretes are required. For example, geopolymers can be an economically and environmentally sustainable alternative to portland cement. This is accomplished through the utilization of alumina-silicate waste materials as a cementitious binder. These geopolymers are synthesized by activating alumina-silicate minerals with alkali. This paper employs a three-step machine learning (ML) approach in order to estimate the compressive strength of geopolymer concrete. The ML methods include CatBoost regressors, extra trees regressors, and gradient boosting regressors. In addition to the 84 experiments in the literature, 63 geopolymer concretes were constructed and tested. Using Python language programming, machine learning models were built from 147 green concrete samples and four variables. Three of these models were combined using a blending technique. Model performance was evaluated using several metric indices. Both the individual and the hybrid models can predict the compressive strength of geopolymer concrete with high accuracy. However, the hybrid model is claimed to be able to improve the prediction accuracy by 13%.

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A Prediction Model for the Calculation of Effective Stiffness Ratios of Reinforced Concrete Columns

Cited by 9 publications

References 30 publications

Effect of Bacillus Subtilis Bacteria on The Mechanical Properties of Corroded Self-Healing Concrete

Effect of Bacillus Subtilis Bacteria on The Mechanical Properties of Corroded Self-Healing Concrete

Estimation of effective rigidity in reinforced concrete structures through modal identification tests and sclerometry

Environmentally Friendly Concrete Compressive Strength Prediction Using Hybrid Machine Learning

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