scholarly journals A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC)

2020 ◽  
Vol 10 (20) ◽  
pp. 7330 ◽  
Author(s):  
Furqan Farooq ◽  
Muhammad Nasir Amin ◽  
Kaffayatullah Khan ◽  
Muhammad Rehan Sadiq ◽  
Muhammad Faisal Faisal Javed ◽  
...  
Keyword(s):  
Machine Learning ◽  
Compressive Strength ◽  
Random Forest ◽  
Decision Tree ◽  
High Strength Concrete ◽  
High Strength ◽  
Supervised Machine Learning ◽  
Fine Aggregate ◽  
Strength Concrete ◽  
Statistical Measures

Supervised machine learning and its algorithm is an emerging trend for the prediction of mechanical properties of concrete. This study uses an ensemble random forest (RF) and gene expression programming (GEP) algorithm for the compressive strength prediction of high strength concrete. The parameters include cement content, coarse aggregate to fine aggregate ratio, water, and superplasticizer. Moreover, statistical analyses like MAE, RSE, and RRMSE are used to evaluate the performance of models. The RF ensemble model outbursts in performance as it uses a weak base learner decision tree and gives an adamant determination of coefficient R2 = 0.96 with fewer errors. The GEP algorithm depicts a good response in between actual values and prediction values with an empirical relation. An external statistical check is also applied on RF and GEP models to validate the variables with data points. Artificial neural networks (ANNs) and decision tree (DT) are also used on a given data sample and comparison is made with the aforementioned models. Permutation features using python are done on the variables to give an influential parameter. The machine learning algorithm reveals a strong correlation between targets and predicts with less statistical measures showing the accuracy of the entire model.

scholarly journals Strength Determination of High Strength Concrete Blended with Copper Slag and Fly Ash

2021 ◽  
Vol 9 (VII) ◽  
pp. 1198-1203
Author(s):  
Jamshed Alam
Keyword(s):  
Compressive Strength ◽  
Fly Ash ◽  
High Strength Concrete ◽  
Free Water ◽  
High Strength ◽  
Copper Slag ◽  
Partial Replacement ◽  
Fine Aggregate ◽  
Strength Concrete ◽  
Free Water Content

An experimental analysis was conducted to study the effects of using copper slag as a fine aggregate (FA) and the effect of fly ash as partial replacement of cement on the properties high strength concrete. In this analysis total ten concrete mixtures were prepared, out of which five mixes containing different proportions of copper slag ranging from 0% (for the control mix) to 75% were prepared and remaining five mixes containing fly ash as partial replacement of cement ranging from 6% to 30% (all mixes contains 50% copper slag as sand replacements). Concrete matrix were tested for compressive strength, tensile strength and flexural strength tests. Addition of copper slag as sand replacement up to 50% yielded comparable strength with that of the control matrix. However, further additions of copper slag, caused reduction in strength due to an increment of the free water content in the mix. Concrete mix with 75% copper slag replacement gave the lowest compressive strength value of approximately 80 MPa at 28 days curing period, which is almost 4% more than the strength of the control mix. For this concrete containing 50% copper slag, fly ash is introduced in the concrete to achieve the better compressive, split and flexural strengths. It was also observed that, introduction of the fly ash gave better results than concrete containing 50% copper slag. When concrete prepared with 18 % of fly ash, the strength has increased approximately 4%, and strength decreased with further replacements of the cement with fly ash. Hence, it is suggested that 50% of copper slag can be used as replacement of sand and 18% fly ash can be used as replacement of cement in order to obtain high strength concrete.

scholarly journals Applications of Gene Expression Programming for Estimating Compressive Strength of High-Strength Concrete

2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Fahid Aslam ◽  
Furqan Farooq ◽  
Muhammad Nasir Amin ◽  
Kaffayatullah Khan ◽  
Abdul Waheed ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Strength Concrete ◽  
Gene Expression Programming ◽  
Empirical Relation ◽  
High Strength ◽  
Target Strength ◽  
Fine Aggregate ◽  
Learning Approaches ◽  
Variable Intensity ◽  
Strength Concrete

The experimental design of high-strength concrete (HSC) requires deep analysis to get the target strength. In this study, machine learning approaches and artificial intelligence python-based approaches have been utilized to predict the mechanical behaviour of HSC. The data to be used in the modelling consist of several input parameters such as cement, water, fine aggregate, and coarse aggregate in combination with a superplasticizer. Empirical relation with mathematical expression has been proposed using engineering programming. The efficiency of the models is assessed by statistical analysis with the error by using MAE, RRMSE, RSE, and comparisons were made between regression models. Moreover, variable intensity and correlation have shown that deep learning can be used to know the exact amount of materials in civil engineering rather than doing experimental work. The expression tree, as well as normalization of the graph, depicts significant accuracy between target and output values. The results reveal that machine learning proposed adamant accuracy and has elucidated performance in the prediction aspect.

scholarly journals Prediction of Compressive Strength of Fly-Ash-Based Concrete Using Ensemble and Non-Ensemble Supervised Machine-Learning Approaches

2021 ◽  
Vol 12 (1) ◽  
pp. 361
Author(s):  
Yang Song ◽  
Jun Zhao ◽  
Krzysztof Adam Ostrowski ◽  
Muhammad Faisal Javed ◽  
Ayaz Ahmad ◽  
...  
Keyword(s):  
Machine Learning ◽  
Compressive Strength ◽  
Fly Ash ◽  
Random Forest ◽  
Cross Validation ◽  
High Performance Concrete ◽  
Supervised Machine Learning ◽  
Gradient Boosting ◽  
Fine Aggregate ◽  
Neuron Network

The utilization of waste material, such as fly ash, in the concrete industry will provide a valuable alternative solution for creating an eco-friendly environment. However, experimental work is time-consuming; employing soft machine learning techniques can accelerate the process of forecasting the strength properties of concrete. Ensemble machine learning modeling using Python Jupyter Notebook was employed in the forecasting of compressive strength (CS) of high-performance concrete. Multilayer perceptron neuron network (MLPNN) and decision tree (DT) were used as individual learning which then ensembled with bagging and boosting to provide strong correlations. Random forest (RF) and gradient boosting regression (GBR) were also used for prediction. A total of 471 data points with input parameters (e.g., cement, fine aggregate, coarse aggregate, superplasticizer, water, days, and fly ash), and an output parameter of compressive strength (CS), were retrieved to train and test the individual learners. Cross-validation with K-fold and statistical error (i.e., MAE, MSE, RMSE, and RMSLE) analysis was applied to check the accuracy of all models. All models showed the best correlation with an ensemble model rather than an individual one. DT with AdaBoost and random forest gave a strong correlation of R2 = 0.89 with fewer errors. Cross-validation results revealed a good response with an error of less than 10 MPa. Thus, ensemble modeling not only trains the data by employing several weak learners but also produces a robust correlation that can then be used to model and predict the mechanical performance of concrete.

Experimental Study on Mechanical Properties of High-Strength Concrete Using Blast Furnace Slag Fine Aggregate

2011 ◽  
Vol 217-218 ◽  
pp. 113-118 ◽  
Author(s):  
Dong Sheng Shi ◽  
Yoshihiro Masuda ◽  
Young Ran Lee
Keyword(s):  
Mechanical Properties ◽  
Compressive Strength ◽  
Blast Furnace ◽  
High Strength Concrete ◽  
Blast Furnace Slag ◽  
High Strength ◽  
Fine Aggregate ◽  
River Sand ◽  
Strength Concrete ◽  
Furnace Slag

In this experiment, blast furnace slag fine aggregate that was produced by 3 different steel factory was been used in high-strength concrete, and mechanical properties of high-strength concrete were studied. The concrete using the blast furnace slag fine aggregate is admitted the increase of compressive strength as well as the case of the river sand when the water cement ratio is reduced, and the compressive strength can attain 100N/mm2. The strength of concrete using blast furnace slag fine aggregate is lower than the strength of concrete using natural river sand as fine aggregate, and the strength of concrete using mixture fine aggregate is middle of strength used river sand and strength used blast furnace slag fine aggregate. The crushing value of blast furnace slag fine aggregate is bigger than the natural river sand, and it could influence the strength of high-strength concrete using blast furnace slag fine aggregate.

Effects of Nano-CaCO3 on the Compressive Strength and Microstructure of High Strength Concrete in Different Curing Temperature

2011 ◽  
Vol 121-126 ◽  
pp. 126-131 ◽  
Author(s):  
Qing Lei Xu ◽  
Tao Meng ◽  
Miao Zhou Huang
Keyword(s):  
Compressive Strength ◽  
Low Temperature ◽  
High Strength Concrete ◽  
High Strength ◽  
Curing Temperature ◽  
Test Results ◽  
Strength Concrete ◽  
Calcium Nitrite ◽  
Orientation Index ◽  
Early Strength

In this paper, effects of nano-CaCO3 on compressive strength and Microstructure of high strength concrete in standard curing temperature(21±1°C) and low curing temperature(6.5±1°C) was studied. In order to improve the early strength of the concrete in low temperature, the early strength agent calcium nitrite was added into. Test results indicated that 0.5% dosage of nano-CaCO3 could inhibit the effect of calcium nitrite as early strength agent, but 1% and 2% dosage of nano-CaCO3 could improve the strength of the concrete by 13% and 18% in standard curing temperature and by 17% and 14% in low curing temperature at the age of 3days. According to the XRD spectrum, with the dosage up to 1% to 2%, nano-CaCO3 can change the orientation index significantly, leading to the improvement of strength of concrete both in standard curing temperature and low curing temperature.

Effect of Chopped Basalt Fiber on the Fresh and Hardened Properties of Fly Ash High Strength Concrete

2014 ◽  
Vol 567 ◽  
pp. 381-386 ◽  
Author(s):  
Nasir Shafiq ◽  
Muhd Fadhil Nuruddin ◽  
Ali Elheber Ahmed Elshekh ◽  
Ahmed Fathi Mohamed Salih
Keyword(s):  
Compressive Strength ◽  
Fly Ash ◽  
High Strength Concrete ◽  
Basalt Fiber ◽  
High Strength ◽  
Progressive Increase ◽  
Test Results ◽  
Strength Concrete ◽  
Hardened Properties ◽  
Chopped Basalt Fiber

In order to improve the mechanical properties of high strength concrete, HSC, several studies have been conducted using fly ash, FA. Researchers have made it possible to achieve 100-150MPa high strength concrete. Despite the popularity of this FAHSC, there is a major shortcoming in that it becomes more brittle, resulting in less than 0.1% tensile strain. The main objective of this work was to evaluate the fresh and hardened properties of FAHSC utilizing chopped basalt fiber stands, CBFS, as an internal strengthening addition material. This was achieved through a series of experimental works using a 20% replacement of cement by FA together with various contents of CBFS. Test results of concrete mixes in the fresh state showed no segregation, homogeneousness during the mixing period and workability ranging from 60 to 110 mm. Early and long terms of compressive strength did not show any improvement by using CBFS; in fact, it decreased. This was partially substituted by the effect of FA. Whereas, the split and flexural strengths of FASHC were significantly improved with increasing the content of CBFS as well as the percentage of the split and flexural tensile strength to the compressive strength. Also, test results showed a progressive increase in the areas under the stress-strain curves of the FAHSC strains after the CBFS addition. Therefore, the brittleness and toughness of the FAHSC were enhanced and the pattern of failure moved from brittle failure to ductile collapse using CBFS. It can be considered that the CBFS is a suitable strengthening material to produce ductile FAHSC.

Influence of Nano Particles in the Flexural Behavior of High-Strength Reinforced Concrete Beams

2021 ◽  
Vol 1160 ◽  
pp. 25-43
Author(s):  
Naglaa Glal-Eldin Fahmy ◽  
Rasha El-Mashery ◽  
Rabiee Ali Sadeek ◽  
L.M. Abd El-Hafaz
Keyword(s):  
Tensile Strength ◽  
Compressive Strength ◽  
High Strength Concrete ◽  
High Strength ◽  
Reinforced Concrete Beams ◽  
Nano Particles ◽  
Flexural Behavior ◽  
Single Type ◽  
Strength Concrete ◽  
Flexural Ductility

High strength concrete (HSC) characterized by high compressive strength but lower ductility compared to normal strength concrete. This low ductility limits the benefit of using HSC in building safe structures. Nanomaterials have gained increased attention because of their improvement of mechanical properties of concrete. In this paper we present an experimental study of the flexural behavior of reinforced beams composed of high-strength concrete and nanomaterials. Eight simply supported rectangular beams were fabricated with identical geometries and reinforcements, and then tested under two third-point loads. The study investigated the concrete compressive strength (50 and 75 N/mm2) as a function of the type of nanomaterial (nanosilica, nanotitanium and nanosilica/nanotitanium hybrid) and the nanomaterial concentration (0%, 0.5% and 1.0%). The experimental results showed that nano particles can be very effective in improving compressive and tensile strength of HSC, nanotitanium is more effective than nanosilica in compressive strength. Also, binary usage of hybrid mixture (nanosilica + nanotitanium) had a remarkable improvement appearing in compressive and tensile strength than using the same percentage of single type of nanomaterials used separately. The reduction in flexural ductility due to the use of higher strength concrete can be compensated by adding nanomaterials. The percentage of concentration, concrete grade and the type of nanomaterials, could predominantly affect the flexural behavior of HSRC beams.

scholarly journals SHEAR STRENGTH OF RC BEAMS WITHOUT STIRRUP USING HIGH-STRENGTH CONCRETE OF COMPRESSIVE STRENGTH RANGING TO 130MPa

2003 ◽  
pp. 75-91
Author(s):  
Motoyuki SUZUKI ◽  
Mitsuyoshi AKIYAMA ◽  
Wei Lun WANG ◽  
Masayoshi SATO ◽  
Naomi MAEDA ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Shear Strength ◽  
High Strength Concrete ◽  
High Strength ◽  
Rc Beams ◽  
Strength Concrete

Estimation of Compressive Strength of Recycled Aggregate High Strength Concrete Using Ultrasonic Pulse Velocity

2014 ◽  
Vol 605 ◽  
pp. 147-150
Author(s):  
Seong Uk Hong ◽  
Seung Hun Kim ◽  
Yong Taeg Lee
Keyword(s):  
Compressive Strength ◽  
High Strength Concrete ◽  
Coarse Aggregate ◽  
High Strength ◽  
Ultrasonic Pulse Velocity ◽  
Ultrasonic Pulse ◽  
Pulse Velocity ◽  
Recycled Aggregate ◽  
Strength Concrete ◽  
Recycled Coarse Aggregate

This study used the ultrasonic pulse velocity method, one of the non-destructive test methods that does not damage the building for maintenance of to-be-constructed concrete structures using recycled aggregates in order to estimate the compressive strength of high strength concrete structure using recycled coarse aggregate and provide elementary resources for technological establishment of ultrasonic pulse velocity method. 200 test pieces of high strength concrete 40, 50MPa using recycled coarse aggregate were manufactured by replacement rates (0, 30, 50, 100%) and age (1, 7, 28, 180days), and air curing was executed to measure compressive strength and wave velocity. As the result of compressive strength measurement, the one with age of 180day and design strength of 40MPa was 43.69MPa, recycled coarse aggregate replacement rate of 30% 50% 100% were 42.82, 41.22, 37.35MPa, and 50MPa was 52.50MPa, recycled coarse aggregate replacement rate of 30% 50% 100% were 49.02, 46.66, 45.30MPa, and while it could be seen that the test piece substituted with recycled aggregate was found to have lower strength than the test piece with natural aggregate only, but it still reached the design strength to a degree. The correlation of compressive strength and ultrasonic pulse velocity was found and regression analysis was conducted. The estimation formula for compressive strength of high strength concrete using recycled coarse aggregate was found to be Fc=0.069Vp4.05, R2=0.66

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