machine learning techniques in concrete mix design
Welcome to Cina Charm

machine learning techniques in concrete mix design.

Machine Learning Techniques in Concrete Mix Design

In our paper, we would like to utilise state-of-the-art achievements in machine learning techniques for concrete mix design. In our research, we prepared an extensive database of concrete recipes with the according destructive laboratory tests, which we used to feed the selected optimal architecture of an

Get Price

Machine Learning Techniques in Concrete Mix Design - MDPI

Concrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method.

Get Price

(PDF) Machine Learning Techniques in Concrete Mix Design

Apr 17, 2019  creating a concrete mix is much broader, including the following steps: The first step is to determine. the data needed to design the mix, such as the purpose of the concrete use, the compressive ...

Get Price

Machine Learning Techniques in Concrete Mix Design

The presented equation does not reflect the behaviour of the concrete perfectly and has boundary conditions. However, it is a step on the way to the introduction of machine learning techniques for concrete mix design. In its present form, it can be a tool for a rough estimation of the concrete class.

Get Price

[PDF] Machine Learning Techniques in Concrete Mix Design ...

Machine Learning Techniques in Concrete Mix Design. Concrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the ...

Get Price

Machine Learning Techniques in Concrete Mix Design

2. The Contemporary Concrete Mix Design and Machine Learning Techniques 2.1. Concrete Mix Design in European Corporate Practice The primary goal of concrete mix design is to estimate the proper ...

Get Price

Machine Learning Techniques in Concrete Mix Design - NASA/ADS

Apr 01, 2019  adshelp[at]cfa.harvard The ADS is operated by the Smithsonian Astrophysical Observatory under NASA Cooperative Agreement NNX16AC86A

Get Price

[PDF] Machine Learning Techniques in Concrete Mix Design ...

Machine Learning Techniques in Concrete Mix Design. Concrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the ...

Get Price

Machine Learning Techniques in Concrete Mix Design - NASA

adshelp[at]cfa.harvard The ADS is operated by the Smithsonian Astrophysical Observatory under NASA Cooperative Agreement NNX16AC86A

Get Price

Model-Based Adaptive Machine Learning Approach in Concrete ...

In presented study, a machine learning model was built with a deep neural network architecture, trained on an extensive database of concrete recipes, and translated into a mathematical formula. Testing on four concrete mix recipes was performed, which were calculated according to contemporary design methods (Bolomey and Fuller method), and a ...

Get Price

Machine Learning Methods for Predicting the Field ...

Machine Learning Methods for Predicting the Field Compressive Strength of Concrete M.A. DeRousseau 1, E. Laftchiev 2, J.R. Kasprzyk 1, B. Rajagopalan 1, W.V. Srubar III 1,† 1 Department of Civil, Environmental, and Architectural Engineering, University of Colorado Boulder, ECOT 441 UCB 428, Boulder, Colorado 80309-0428 USA, 2Mitsubishi Electric Research Labs, 201 Broadway FL8, Cambridge, MA ...

Get Price

Machine Learning Techniques in Concrete Mix Design ...

In our paper, we would like to utilise state-of-the-art achievements in machine learning techniques for concrete mix design. In our research, we prepared an extensive database of concrete recipes with the according destructive laboratory tests, which we used to feed

Get Price

Comparison of Machine Learning Techniques for the ...

A comparative analysis for the prediction of compressive strength of concrete at the ages of 28, 56, and 91 days has been carried out using machine learning techniques via “R” software environment. R is digging out a strong foothold in the statistical realm and is becoming an indispensable tool for researchers. The dataset has been generated under controlled laboratory conditions.

Get Price

Comprehensive Machine Learning-Based Model for

Feb 25, 2021  to predict concrete CS based on the design recipe. The concrete production process is affected by several factors, which have strong nonlinear relationships with the product CS and are strongly interrelated. With the rapid development of machine learning, there is a trend to employ data-driven techniques for concrete CS prediction. Compared with

Get Price

Application and Analysis of Machine Learning Algorithms ...

The objective of this paper is to find an alternative to conventional method of concrete mix design. For finding the alternative, 4 machine learning algorithms viz. multi-variable linear regression, Support Vector Regression, Decision Tree Regression and Artificial Neural Network for designing concrete mix of desired properties. The multi-variable linear regression model is just a simplistic ...

Get Price

A Comparative Study of Machine Learning Methods for ...

The machine learning techniques will be more appropriate to be applied for modelling the complex behaviour of many engineering problems with ... Babanajad et al. [26] proposed a model to correlate the concrete true-triaxial strength to mix design parameters and

Get Price

Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures ...

Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures Using Machine Learning. So far, alkali-activated concrete has primarily focused on the effect of source material properties and ratio of mixture proportions on the compressive strength development. A little research has focused on developing a standard mixture design procedure for alkali ...

Get Price

Prediction of Compressive Strength of Concrete: Critical ...

The use of machine learning (ML) techniques to model quantitative composition–property relationships in concrete has received substantial attention in the past few years. This paper presents a novel hybrid ML model (RF-FFA) for prediction of compressive strength of concrete by combining the random forests (RF) model with the firefly algorithm ...

Get Price

(PDF) Comparison of methods of prediction of compressive ...

The use of machine learning (ML) techniques to model quantitative composition–property relationships in concrete has received substantial attention in the past few years.

Get Price

Cement and Concrete Research

Dec 10, 2017  1.2. Computational design optimization of concrete mixtures Computational design optimization of concrete mixtures is a mathematical—as opposed to experimental—approach to mixture proportioning. Fig. 1c illustrates that computational optimization of concrete mixtures is a process whereby an optimal design solution can be found.

Get Price

DESIGN OF ALKALI ACTIVATED SLAG‒FLY ASH CONCRETE

concrete for a range of compressive strength grades. This study developed a standard mix design procedure for alkali activated slag‒fly ash (low calcium, class F) blended concrete using two machine learning techniques, Artificial Neural Networks (ANN) and Multivariate Adaptive Regression Spline (MARS).

Get Price

2 EXPANSION AND OTHER PROPERTIES USING MACHINE

33 learning techniques [1–5], there have been fewer studies on prediction of concrete coefficient of 34 thermal expansion (CTE), and none exploring machine learning methods for this property. 35 Concrete CTE is an important input in pavement design, as detailed in the American

Get Price

Comprehensive Machine Learning-Based Model for

Feb 25, 2021  to predict concrete CS based on the design recipe. The concrete production process is affected by several factors, which have strong nonlinear relationships with the product CS and are strongly interrelated. With the rapid development of machine learning, there is a trend to employ data-driven techniques for concrete CS prediction. Compared with

Get Price

Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures ...

Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures Using Machine Learning. So far, alkali-activated concrete has primarily focused on the effect of source material properties and ratio of mixture proportions on the compressive strength development. A little research has focused on developing a standard mixture design procedure for alkali ...

Get Price

Metaheuristic-Based Machine Learning System for Prediction ...

This research develops an advanced machine learning method to forecast the concrete compressive strength using the concrete mix proportion and early-age strength test results. Thirty-eight historical cases in total were used to create the intelligence prediction method.

Get Price

Prediction of cement-based mortars compressive strength ...

Apr 23, 2021  Many models based on the influential factors affecting machine learning techniques have been developed, and their prediction capacities have been assessed using performance indexes. The present research highlights the potential of AdaBoost and RF models as useful tools which can assist in mortar design and/or optimization.

Get Price

Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures ...

The targeted compressive strengths ranging from 25–45 MPa (3.63–6.53 ksi) at 28 days were achieved with laboratory testing, using the proposed machine learning mix design procedure. Thus, this tool has the capability to provide a novel approach for the design of slag-fly

Get Price

PREDICTION OF CONCRETE COMPRESSIVE STRENGTH

from a ready mix (RMX) plant in spite of variations in the results. The strengthening of concrete is a complex process involving many factors. A number of prediction techniques have been proposed by including empirical or computational modeling, statistical techniques and artificial intelligence approaches. Apart of

Get Price

UCI Machine Learning Repository: Concrete Compressive ...

I-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 ...

Get Price

Machine Learning Software for Facade Inspection Video ...

T2D2 was initially trained essentially for concrete structures, but now the capabilities have been expanded. The tool can now easily identify and classify damage on masonry, brick, stucco, and other commonly used materials. Due to the inclusion of machine-learning elements, the algorithm improves every time it

Get Price

Patryk Ziółkowski - Profil naukowy - MOST Wiedzy

Machine Learning Techniques in Concrete Mix Design ... Concrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which ...

Get Price

Machine Learning and its Applications in Construction ...

In construction, machine learning can help project engineers, supervisors, and everyone else involved in a project. ML can help monitor the work progress, assess the risks involved, notify the managers and supervisors of critical issues, improve the design and planning activities, and make informed predictions for a more streamlined workflow. 1.

Get Price

On the Convergence Rate of Incremental Aggregated Gradient ...

(2019) Machine Learning Techniques in Concrete Mix Design. Materials 12 :8, 1256. (2019) Distributed Constrained Convex Optimization with Accumulated Subgradient Information over

Get Price

A Sensitivity and Robustness Analysis of GPR and ANN for ...

Rafiei et al. [50] presented an innovative approach for the concrete mix design problem through fusion of an optimization algorithm, the patented neural dynamics optimization model of Adeli and Park [51,52], and an ML classification algorithm used as a virtual lab to predict

Get Price

Experimental investigation and comparative machine ...

Jan 13, 2021  Moreover, to prepare the concrete mix design, the density and water absorption tests were carried out according to ASTM C 128-15 (ASTM 2015b) and ASTM C 127-15 (), respectively.Mechanical properties of the aggregates are reported in Table 2.As can be seen,

Get Price
Copyright © 2021.Cina Charm All rights reserved.Cina Charm