In this paper, an artificial neural network is being used to predict the concrete mix ratio to achieve the desired strength. The parameters such as, 28-day strength, maximum gravel size, presence ...
Read MoreConcrete mix design is a process based on sound technical principles for proportioning of ingredients in right quantities. This paper demonstrates the applicability of Artificial Neural Networks (ANN) Model for approximate proportioning of concrete mixes. For ANN a trained back propagation neural network is integrated in the model to learn experimental data pertaining to predict 7, 14 and 28 ...
Read More2020-9-17 Using the ACI 211.1 method, here is an abbreviated run-through on how to design a mix: Choose the maximum aggregate size—remember that the larger the better for reducing shrinkage and curling. Estimate the water and air content using ACI 211.1
Read MoreThis study proposes a new methodology with harmony search (HS) algorithm and neural networks (NNs) for concrete mix proportioning. The basic procedure for the methodology consists of four steps: (1) constructing a database of mix designs; (2) establishing appropriate models for strength and workability; (3) optimizing mix proportion using the modified HS algorithm; and (4) refining the mixture ...
Read More2006-7-1 A concrete mix proportion design algorithm based on a way from aggregates to paste, a least paste content, Modified Tourfar's Model and artificial neural networks (ANNs) was proposed. The proposed concrete mix proportion design algorithm is expected to reduce the number of trial and error, save cost, laborers and time.
Read More2014-12-24 An artificial neural network (ANN) has a wide application field for mathematical problems. Specifically, an ANN is successfully applied to problems that are difficult to solve or do not have any information on their operating techniques. In this article, an ANN was applied to predict the concrete mix composition for steel fiber-reinforced concrete (SFRC). Thus, an ANN model was developed and ...
Read More2008-11-26 The primary objective of this research was to combine three technologies, namely design of experiments (DOE), artificial neural network (ANN), and mathematical programming (MP), into an integrated methodology for mixing concrete containing SP, fly ash, and slag, consistent with desirable structural grade concrete properties. The function of DOE and ANN is to reduce the number of test
Read MoreI-Cheng Yeh, "A mix Proportioning Methodology for Fly Ash and Slag Concrete Using Artificial Neural Networks," Chung Hua Journal of Science and Engineering, Vol. 1, No. 1, pp. 77-84 (2003). 6. Yeh, I-Cheng, "Analysis of strength of concrete using design of experiments and neural networks," Journal of Materials in Civil Engineering, ASCE, Vol.18 ...
Read MoreA quality concrete mix design is crucial for successful construction. At Concrete Supply Co., we sleep better at night knowing our end-to-end ready mix concrete solution meets the highest quality performance in concrete, and our integrity in doing so is
Read More2021-11-10 The Association for Concrete-friends at RISE gathers industrial and public authority members in a forum for discussion about most actual subjects within material and construction areas. The purpose of the association is to create a direct contact between member company employees and RISE experts in the concrete, stone and aggregate area.
Read MoreIn this paper, an artificial neural network is being used to predict the concrete mix ratio to achieve the desired strength. The parameters such as, 28-day strength, maximum gravel size, presence ...
Read MoreConcrete mix design is a process based on sound technical principles for proportioning of ingredients in right quantities. This paper demonstrates the applicability of Artificial Neural Networks (ANN) Model for approximate proportioning of concrete mixes. For ANN a trained back propagation neural network is integrated in the model to learn experimental data pertaining to predict 7, 14 and 28 ...
Read MoreConcrete Mix Design Using Neural Network. Authors: Rama Shanker, Anil Kumar Sachan. Abstract: Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade ...
Read More2014-12-24 An artificial neural network (ANN) has a wide application field for mathematical problems. Specifically, an ANN is successfully applied to problems that are difficult to solve or do not have any information on their operating techniques. In this article, an ANN was applied to predict the concrete mix composition for steel fiber-reinforced concrete (SFRC). Thus, an ANN model was developed and ...
Read MoreSCMs are used as replacement for cement, and since they have a very small particle size, they reduce the permeability of concrete, which is good. Fly ash is the most common SCM and it improves finishability, although it tends to slow the set time, especially in
Read MorePozzolanic concrete has superior properties, such as high strength and workability. The precise proportioning and modeling of the concrete mixture are important when considering its applications. There have been many efforts to develop computer-aided approaches for pozzolanic concrete mix design, such as artificial neural network- (ANN-) based approaches, but these approaches have
Read More2018-6-30 Thus accurate intensity prediction could be realized through a certain training and iteration. A 7-20-3 BP neural network model is employed in to predict the recycled concrete slump. In , the neural network model and ultrasonic pulse velocity test are proposed to predict the concrete compressive strength. Although BP neural network shows good ...
Read More2013-5-1 Highlights For the first time, models developed for prediction of the strength properties of EPS concrete. Robust ANN and ANFIS models proposed for predicting the compressive strength of EPS concrete. The overall performance of trained ANN is more accurate than ANFIS model. Such robust models could be easily utilized for EPS concrete mix proportioning as a problem with high complexities ...
Read MoreA quality concrete mix design is crucial for successful construction. At Concrete Supply Co., we sleep better at night knowing our end-to-end ready mix concrete solution meets the highest quality performance in concrete, and our integrity in doing so is
Read MoreThe selection of appropriate type and grade of concrete for a particular application is the critical step in any construction project. Workability and compressive strength are the two significant parameters that need special attention. This study aims to predict the slump along with 7-days 28-days compressive strength based on the data collected from various RMC plants.
Read MoreIn this paper, an artificial neural network is being used to predict the concrete mix ratio to achieve the desired strength. The parameters such as, 28-day strength, maximum gravel size, presence ...
Read MoreConcrete mix design is a process based on sound technical principles for proportioning of ingredients in right quantities. This paper demonstrates the applicability of Artificial Neural Networks (ANN) Model for approximate proportioning of concrete mixes. For ANN a trained back propagation neural network is integrated in the model to learn experimental data pertaining to predict 7, 14 and 28 ...
Read MoreConcrete Mix Design Using Neural Network. Authors: Rama Shanker, Anil Kumar Sachan. Abstract: Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade ...
Read MoreConcrete Mix Design Using Artificial Neural Network 31 Journal on Today’s Ideas – Tomorrow’s Technologies (JOTITT), Volume 1, Number 1, June 2013 interconnections. Neural networks might be single-or multi layered.
Read MoreSCMs are used as replacement for cement, and since they have a very small particle size, they reduce the permeability of concrete, which is good. Fly ash is the most common SCM and it improves finishability, although it tends to slow the set time, especially in
Read MoreHow to do it: Dump the required amount of bagged mix into the bucket, form a depression in the middle of the mix, and then slowly add about three-quarters of the amount of water called for per the package directions. (If you don’t need to use the entire bag, remember to adjust the amount of water accordingly.)
Read More2016-5-24 compressive strength, to create artificial neural networks (ANNs). These ANNs learnt from the input data and output a compressive strength for each input line of data. This output value was obtained via set algorithms based on ... Concrete Mix Design from database..... 26 3.1.7 Ground-granulated Blast-furnace Slag Concrete Mix Design ...
Read More2013-5-1 Highlights For the first time, models developed for prediction of the strength properties of EPS concrete. Robust ANN and ANFIS models proposed for predicting the compressive strength of EPS concrete. The overall performance of trained ANN is more accurate than ANFIS model. Such robust models could be easily utilized for EPS concrete mix proportioning as a problem with high complexities ...
Read MoreA quality concrete mix design is crucial for successful construction. At Concrete Supply Co., we sleep better at night knowing our end-to-end ready mix concrete solution meets the highest quality performance in concrete, and our integrity in doing so is
Read MoreEVALUATION OF CONCRETE COMPRESSIVE STRENGTH USING ARTIFICIAL « 425 Ó= =0 + ÃIF =1 =F: F (1) ZKHUHÓLVWKHPRGHOCVRXWSXW : F `s are the independant input variables to the model, and =0,=1,=2,å ,=I are partial regression coefficients. 2.2 Artificial neural network model Artificial neural network (ANN) is a collection of neural and weighted nodes which each of
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