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Prediction of cementbased mortars compressive strength

Prediction of cementbased mortars compressive strength

Prediction of cement-based mortars compressive strength ...

Apr 23, 2021  10%  The present study collected 424 laboratory data from the available literature (referenced below) to develop intelligent models for the prediction of cement-based mortars compressive strength (CS). After reviewing the data, the importance of each parameter was examined and the relationship between them was identified.

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Prediction of cement-based mortars compressive strength ...

Jul 23, 2021  10%  Hence, the present study investigates the applicability of other common machine learning techniques, i.e., support vector machine, random forest (RF), decision tree, AdaBoost and k-nearest neighbors in mapping the behavior of the compressive strength (CS) of cement-based mortars.

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An approach for predicting the compressive strength of ...

In this paper, a support vector machine (SVM) model which can be used to predict the compressive strength of mortars exposed to sulfate attack was established. An accelerated corrosion test was applied to collect compressive strength data. For predicting the compressive strength of mortars

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ANN prediction of cement mortar compressive strength ...

May 01, 2017  An artificial neural network (ANN) study is presented to predict the compressive strength (Fc) of mortar mixtures containing different cement strength classes of CME 32.5, 42.5, and 52.5 MPa.For this purpose, 54 mixtures considering six water/cement ratios (W/C) (0.25, 0.3, 0.35, 0.4, 0.45, and 0.5) and three sand/cement ratios (S/C) (2.5, 2.75, and 3) along with the abovementioned

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An approach for predicting the compressive strength of ...

Jan 18, 2018  There have been few studies on the prediction of the compressive strength of cement-based materials exposed to sulfate attack using SVM. Most of these studies established the prediction models of concrete compressive strength mainly based on the material factors (e.g., water-binder ratio, water content and aggregate content) and curing age [ 9 ...

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Various simulation techniques to predict the compressive ...

Mar 02, 2021  10%  From the histogram of compressive strength for cement mortar up to 180 days of curing (Fig. 2c), 32% of the data out of the overall 450 compressive strength varied from 20 to 40 MPa as shown in Fig. 3. More than 4% of the compressive strength of the cement mortar modified with SF data was 25 MPa out of maximum compressive strength reported of ...

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Prediction of compressive strength of lightweight mortar ...

slowly process on cement-based materials. Some properties ... compressive strength of mortars exposed to 1% sulfate ... Prediction of compressive strength of lightweight mortar exposed to sulfate ...

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Prediction of compressive strength development for blended ...

For ultrafine fly ash mortar, the 28-day compressive strength of mortar shows an evident trend of first increase and then decrease with the increase of replacement ratio. Under the condition of ensuring the same compressive strength, upgraded finer fly ash can replace more cement, thus realizing energy saving and CO 2 emission reduction.

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Prediction of Compressive Strength of Calcined Clay Based ...

Prediction of strength in cement based materials is vital in construction industry as it forms the basis upon which important ... Compressive strengths for the mortars. 2.2.2 Machine Learning The 2, 7 and 28 days laboratory data was processed before it was fitted to the model. This involved selecting

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On the metaheuristic models for the prediction of cement ...

compressive strength of the cement-based mortars; this is an important finding, because these parameters are usually not taken into account in the research studies concerned in the prediction of compressive strength through

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Prediction of compressive strength development for blended ...

Feb 15, 2021  The calculated gel/(gel + pore) and its corresponding compressive strength obtained in experiments are plotted in Fig. 1.As we can see in Fig. 1(a) to (c), whether cement is replaced by coarse quartz or fly ash (FAA and FAC), the compressive strength of mortar has a good linear relationship with gel/(gel + pore), and all the correlations have reached 97% in this experiments.

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Prediction of Cement Compressive Strength Based on ...

Prediction of cement compressive strength was studied with accelerated curing methods, e.g. warm water and boiling water curing. The results indicate that fineness and the type of cements is few influencing on the 28-day compressive strength, and the difference is not distinct between the two methods. The boiling water fast-curing method is recommended since it doesn’t need additional ...

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Prediction of early compressive strength of mortars at ...

This paper presents an experimental and modeling study on the influence of curing temperature (T) and relative humidity (RH) on the development of early-age compressive strength of cement mortars.By introducing an RH factor γ RH into the age conversion factor of concrete, a modified maturity function was proposed considering both effects of T and RH on the mechanical properties of mortars.

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Prediction of concrete compressive strength based on early ...

This pioneering research opened the way for microwave nondestructive compressive strength prediction of cement-based materials. On one hand, electrical conductivity or resistivity was often used for monitoring the evolution of porosity in cement pastes and concretes using 28-day experimental measurement [12,13].

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[PDF] Prediction of Compressive Strength of Calcined Clay ...

Prediction of strength in cement based materials is vital in construction industry as it forms the basis upon which important tasks can be performed such as the time for mortar form removal, project scheduling and quality control among others. The paper reports both experimental and simulated findings on compressive strength of laboratory prepared blended cement mortars.

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Mathematical prediction of the compressive strength of ...

May 04, 2021  For example, Bundur et al. reported that bacterial mortar's compressive strength improved (specifically, at 7, 28 and 56 days) compared to the control mix. The improvement in compressive strength was attributed to the precipitation of calcium carbonate, which filled the pores and thus enhanced the concrete microstructure.

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An approach for predicting the compressive strength of ...

Jan 18, 2018  There have been few studies on the prediction of the compressive strength of cement-based materials exposed to sulfate attack using SVM. Most of these studies established the prediction models of concrete compressive strength mainly based on the material factors (e.g., water-binder ratio, water content and aggregate content) and curing age [ 9 ...

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Compressive strength prediction of nano-silica ...

Feb 05, 2017  The compressive strength testing of cement paste, mortar and concrete also confirmed that the optimum compressive strength is achieved for the mix with 8% nano-silica content. A numerical approach based on a hierarchical multiscale method was then proposed to predict the compressive strength of nano-silica integrated concrete.

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Water-Cement-Density Ratio Law for the 28-Day Compressive ...

Jul 13, 2020  Relative apparent density of the cement-based material is an important one of all the factors determining the compressive strength of the cement-based material. The water-cement-density ratio law will be beneficial for the precise and generalized prediction of the 28-day standard curing compressive strength of cement-based materials.

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Search results for: strength prediction models.

To improve the compressive strength of samples, Nano- Silica replaced with 10% of cement weight in concrete mixtures. By doing the tests, the results showed that, adding Nano-silica to the samples with less percentage of fine recycled concrete aggregates, lead to more increase on the compressive strength.

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Frontiers Effect of Iron Tailings and Slag Powders on ...

Jul 26, 2021  The compressive strength, flexural strength, and splitting tensile strength of concrete are tested, and the long-term strength prediction model is established and verified. This study can fill the research blank of iron tailings powder concrete long-term mechanical properties, which provides a theoretical basis for the application of fine ...

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Sustainability Free Full-Text Stacking Ensemble Tree ...

In this research, a new machine-learning approach was proposed to evaluate the effects of eight input parameters (surface area, relative compactness, wall area, overall height, roof area, orientation, glazing area distribution, and glazing area) on two output parameters, namely, heating load (HL) and cooling load (CL), of the residential buildings. The association strength of each input ...

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ANN prediction of cement mortar compressive strength ...

May 01, 2017  An artificial neural network (ANN) study is presented to predict the compressive strength (Fc) of mortar mixtures containing different cement strength classes of CME 32.5, 42.5, and 52.5 MPa.For this purpose, 54 mixtures considering six water/cement ratios (W/C) (0.25, 0.3, 0.35, 0.4, 0.45, and 0.5) and three sand/cement ratios (S/C) (2.5, 2.75, and 3) along with the abovementioned

get price

Prediction of Compressive Strength of Calcined Clay Based ...

Prediction of strength in cement based materials is vital in construction industry as it forms the basis upon which important ... Compressive strengths for the mortars. 2.2.2 Machine Learning The 2, 7 and 28 days laboratory data was processed before it was fitted to the model. This involved selecting

get price

Prediction of early compressive strength of mortars at ...

Aug 18, 2020  This paper presents an experimental and modeling study on the influence of curing temperature (T) and relative humidity (RH) on the development of early‐age compressive strength of cement mortars.By introducing an RH factor γ RH into the age conversion factor of concrete, a modified maturity function was proposed considering both effects of T and RH on the mechanical properties of mortars.

get price

An approach for predicting the compressive strength of ...

genetic algorithms to predict compressive strength of concrete. Gupta [21] investigated the potential use of SVM for predicting CCS by combining radial basis function with SVM. There have been few studies on the prediction of the compressive strength of cement-based materials exposed to sulfate attack using SVM.

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Proposed a model for compressive strength of cement

concrete materials. Since cement-based mortar is considered as an important concrete adhesive, it is very useful to present an applicable and accurate model for predicting the properties of such mortar. In this study, the influence of the effective parameters on the compressive strength of cement-based mortar is

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Fuzzy Logic Model for the Prediction of Compressive ...

May 05, 2015  Microstructural formation was related to the strength values of cement mortars, in the scope of this study. The established relationship was modeled by using fuzzy logic prediction model. Pore area, unhydrated part and hydrated part of cement mortars were addressed for microstructural investigations. These parameters were taken into account as area ratios for each.

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Compressive strength prediction of nano-silica ...

Feb 05, 2017  The compressive strength testing of cement paste, mortar and concrete also confirmed that the optimum compressive strength is achieved for the mix with 8% nano-silica content. A numerical approach based on a hierarchical multiscale method was then proposed to predict the compressive strength of nano-silica integrated concrete.

get price

Mathematical prediction of the compressive strength of ...

May 04, 2021  For example, Bundur et al. reported that bacterial mortar's compressive strength improved (specifically, at 7, 28 and 56 days) compared to the control mix. The improvement in compressive strength was attributed to the precipitation of calcium carbonate, which filled the pores and thus enhanced the concrete microstructure.

get price

Prediction of compressive strength development for blended ...

Prediction of compressive strength development for blended cement mortar considering fly ash fineness and replacement ratio Authors Sun, Y. ; Wang, K.Q. ; Lee, H.S.

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Machine learning techniques to predict the compressive ...

A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength. Springer London, 2020. [11] Duan Z.H., Kou S.C., Poon C.S. Prediction of compressive strength of recycled aggregate concrete using artificial neural networks.

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Water-Cement-Density Ratio Law for the 28-Day Compressive ...

Jul 13, 2020  Relative apparent density of the cement-based material is an important one of all the factors determining the compressive strength of the cement-based material. The water-cement-density ratio law will be beneficial for the precise and generalized prediction of the 28-day standard curing compressive strength of cement-based materials.

get price

Comparison Between Two Nonlinear Models to Predict the ...

Jul 03, 2021  On the metaheuristic models for the prediction of cement-metakaolin mortars compressive strength. 1, 1(1): 063. Benyounes K, Benmounah A (2014) Effect of bentonite on the rheological behavior of cement grout in presence of superplasticizer.

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Prediction of Concrete Compressive Strength by ...

Mar 03, 2015  Compressive strength of concrete has been predicted using evolutionary artificial neural networks (EANNs) as a combination of artificial neural network (ANN) and evolutionary search procedures, such as genetic algorithms (GA). In this paper for purpose of constructing models samples of cylindrical concrete parts with different characteristics have been used with 173 experimental data

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Compressive Strength Evaluation of Ordinary Portland ...

Strength was improved 20.4% for cement mortar added with Graphene Oxide after reacting with SAM containing APTMS. When the texture of both mortars became denser, early compressive strength at 7 days each was 20.4-31.1% higher than that of OPC mortar. Finally, the strength was increased by 10.2% at 28 days.

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