Prediction of Geopolymer Concrete Compressive Strength Using Convolutional Neural Networks

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental problems.Its attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation infrastructure.In this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering field.To achieve this goal,a new approach using convolutional neural networks(CNNs)has been adopted.This study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly ash.The selection of optimal input parameters is guided by two distinct criteria.The first criterion leverages insights garnered from previous research on the influence of individual features on compressive strength.The second criterion scrutinizes the impact of these features within the model’s predictive framework.Key to enhancing the CNN model’s performance is the meticulous determination of the optimal hyperparameters.Through a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s robustness.The model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score analyses.Furthermore,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction methods.To unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rate.The study culminates in compelling findings that underscore the CNN model’s accurate prediction of geopolymer concrete compressive strength.To maximize the dataset’s potential,the application of bivariate plots unveils nuanced trends and interactions among variables,fortifying the consistency with earlier research.Evidenced by promising prediction accuracy,the study’s outcomes hold significant promise in guiding the development of innovative geopolymer concrete formulations,thereby reinforcing its role as an eco-conscious and robust construction material.The findings prove that the CNN model accurately estimated geopolymer concrete’s compressive strength.The results show that the prediction accuracy is promising and can be used for the development of new geopolymer concrete mixes.The outcomes not only underscore the significance of leveraging technology for sustainable construction practices but also pave the way for innovation and efficiency in the field of civil engineering.

Effect of Steel Fiber on Concrete’s Compressive Strength

The general goal of this research is to investigate whether steel fiber has a significant “positive” or “negative” influence on concrete compressive strength, as well as the optimal steel fiber ratio that delivers best result. Manually, cement, fine aggregates, coarse aggregates, steel fibers, and water were mixed together properly. A slump test was carried on the mixed concrete. After determining the workability, the mixed concrete was poured into cubes dimension 150 mm × 150 mm × 150 mm and left for 24 hours. After 24 hours, the samples were removed from the mold and placed in a water tank to cure for 7 to 28 days. The cube was tested for compressive and flexural strength in a universal testing machine after the samples had cured for the required 7 - 28 days. This study focuses on how to obtain high strength concrete using with steel fiber in the Conventional mix ratio to enhance concrete strength. Concrete reinforcement using steel fibers alters the characteristics of the concrete, allowing it to withstand fracture and hence improve its mechanical qualities. This study reports on an experimental study that reveals the effect of steel fiber on concrete compressive strength and the optimal steel fiber ratio that produces the best results. Steel fiber reinforcing improved the compressive strength of concrete. The average compressive strength of normal M25 concrete with 0% steel fibers and curing ages of 7 and 28 days was determined to be 22.97 N/mm2 and 25.78 N/mm2, respectively. The steel fibers are then added in various concentrations, such as 1%, 2%, and 3%, with aspect ratios of 70. The compressive strength of concrete with 1%, 2%, and 3% steel fiber with an aspect ratio of 70 was examined at 7 days and found to be 23.96, 24.80, and 26.14 N/mm2 correspondingly.

Experimental Study on the Compressive Strength of Concrete with Different Wheat Straw Treatment Techniques

The treatment of wheat straw is very difficult,and its utilization rate is very low;accumulation causes air pollution and even fire.To make full use of wheat straw resources,we examined how using different physical and chemical methods to treat the wheat straw which can improve its strength abilities,or enhance the activity of wheat straw ash.In terms of concrete additives,it can reduce the amount of cement used.In this paper,we found that alkali treatment can significantly improve the tensile strength of wheat straw fiber,but polyvinyl alcohol treatment has no obvious effect on the strength of wheat straw fiber after alkali treatment.At the same time,we analyzed the wheat straw fiber microstructure through scanning electron microscopy,and we also studied the wheat straw ash chemical composition after 600℃ high-temperature treatment.Through the compressive strength test,we found that the strength of concrete decreases with increasing of wheat straw fiber and wheat straw powder content,and the compressive strength of concrete with wheat straw ash instead of 5%cement decreases little,and the strength of the concrete also decreases with the increasing of wheat straw ash.Through the macroscopic observation of the failure form of concrete,we found that the failure form of concrete with wheat straw ash is similar to that of common concrete,while the failure degree of concrete with wheat straw fiber and wheat straw powder is weakened.Through the scanning electron microscope test of the concrete,it was found that wheat straw fiber has an effect on the cracking of concrete and the inner compactness of concrete can also be affected by adding wheat straw ash and wheat straw powder.

Compressive Strength Estimation for the Fiber-Reinforced Polymer (FRP)-Confined Concrete Columns with Different Shapes Using Artificial Neural Networks

An evaluation of existing strength of concrete columns confined with fiber-reinforced polymer( FRP) was presented with extensive collection of experimental data. According to the evaluation results, artificial neural networks( ANNs) model to predict the ultimate strength of FRP confined column with different shapes was proposed. The models had seven inputs including the column length,the tensile strength of the FRP in the hoop direction,the total thickness of FRP,the diameter of the concrete specimen,the elastic modulus of FRP,the corner radius and the concrete compressive strength. The compressive strength of the confined concrete was the output data. The results reveal that the proposed models have good prediction and generalization capacity with acceptable errors.

Calculation on uniaxial compressive strength of high strength concrete after wrapped by FRP

A theoretical calculation method of the axial compressive strength of a high strength concrete with fibre reinforced plastics (FRP) constraint is proposed. It is shown by test verification that the FRP strength devotion factor used for this method is in accordance with actual conditions. FRP is not up to the ultimate strength when the concrete reaches the ultimate strength, whose strength devotion factor is in the range of 0.28 to 0.59, which is related to an elastic modulus. The method can be used to estimate axial compressive strength of the concrete strengthened with FRP. The theoretical strength is 10% to 30% higher than the measured one. The deviation comes mainly from a non-ideal bonding condition of FRP-concrete interfaces and discrete property of the testing data of compressive strength.

Effects of binder strength and aggregate size on the compressive strength and void ratio of porous concrete

To test the influence of binder strength, porous concretes with 4 binder strengths between 30.0-135.0 MPa and 5 void ratios between 15%-35% were tested. The results indicated that for the same aggregate, the rates of strength reduction due to the increases in void ratio were the same for binders with different strengths. To study the influence of aggregate size, 3 single size aggregates with nominal sizes of 5.0, 13.0 and 20.0 mm （Nos. 7, 6 and 5 according to JIS A 5001） were used to make porous concrete. The strengths of porous concrete are found to be dependent on aggregate size. The rate of strength reduction of porous concrete with small aggregate size is found to be higher than that with larger aggregate size. At the same void ratio, the strength of porous concrete with large aggregate is larger than that with small aggregate. The general equations for porous concrete are related to compressive strength and void ratio for different binder strengths and aggregate sizes.

Size effect on compressive strength of reactive powder concrete

In this paper the coefficient and law of the size effect of RPC were studied through experiments and theoretical analysis. The size-effect coefficients for the compressive strength of RPC are deduced through experiments.They indicate that RPC without fiber behaves quite the same as normal or high strength concrete.The size effect on compressive strength is more prominent in RPC containing fiber.Bazant's size effect formula of compressive strength applies to RPC.A formula is given to predict the compressive strength of cubic RPC specimens 100 mm on a side where the fiber dosage ranges from 0-2%.

Effect of Recycled Coarse Aggregate on Concrete Compressive Strength

The effect of recycled coarse aggregate on concrete compressive strength was investigated based on the concrete skeleton theory. For this purpose, 30 mix proportions of concrete with target cube compressive strength ranging from 20 to 60 MPa were cast with normal coarse aggregate and recycled coarse aggregate from different strength parent concretes. Results of 28-d test show that the strength of different types of recycled aggregate affects the concrete strength obviously. The coarse aggregate added to mortar matrix plays a skeleton role and improves its compressive strength. The skeleton effect of coarse aggregate increases with the increasing strength of coarse aggregate, and normal coarse aggregate plays the highest, whereas the lowest concrete strength occurs when using the weak recycled coarse aggregate. There is a linear relationship between the concrete strength and the corresponding mortar matrix strength. Coarse aggregate skeleton formula is established, and values from experimental tests match the derived expressions.

Digital Vision Based Concrete Compressive Strength Evaluating Model Using Deep Convolutional Neural Network

Compressive strength of concrete is a significant factor to assess building structure health and safety.Therefore,various methods have been developed to evaluate the compressive strength of concrete structures.However,previous methods have several challenges in costly,time-consuming,and unsafety.To address these drawbacks,this paper proposed a digital vision based concrete compressive strength evaluating model using deep convolutional neural network(DCNN).The proposed model presented an alternative approach to evaluating the concrete strength and contributed to improving efficiency and accuracy.The model was developed with 4,000 digital images and 61,996 images extracted from video recordings collected from concrete samples.The experimental results indicated a root mean square error(RMSE)value of 3.56(MPa),demonstrating a strong feasibility that the proposed model can be utilized to predict the concrete strength with digital images of their surfaces and advantages to overcome the previous limitations.This experiment contributed to provide the basis that could be extended to future research with image analysis technique and artificial neural network in the diagnosis of concrete building structures.

Quantitative Analysis of Relationship Between Pore Structure and Compressive Strength of Foamed Concrete

The effect of dry density,water-cement ratio,the addition of fly ash,and sand content on the porosity and pore distribution of foamed concrete is investigated.Digital microscopy and Image J software are employed to examine the landscape of pores with different sizes.Based on the Balshin empirical formula,a mathematical model is established to quantitatively predict the relationship between the pore structures and the compressive strength of foamed concrete.The results well demonstrate that there is a significant correlation between the modified formula and empirical parameters.

Charactersitics of Stress-strain Curve of High Strength Steel Fiber Reinforced Concrete under Uniaxial Tension

A whole of 110 specimens divided into 22 groups were tested with varying the volume fraction of steel fibers and the matrix strength of these specimens. The stress-strain behaviors of four types of steel fiber reinforced concrete （SFRC） under uniaxial tension were studied experimentally. When the matrix strength and the fiber content increase, the tensile stress and tensile strain vary differently according to the fiber type. The mechanisms of reinforcing effect for different types of fiber were analyzed and the stress-strain curves of the specimens were plotted. Some experimental factors for stress or strain of SFRC were given. A tensile toughness modulus Re0.5 was introduced to evaluate the toughness characters of SFRC under uniaxial tension. Moreover, the formula of the tensile stress-strain curve of SFRC was regressed. The theoretical curve and the experimental ones fit well, which can be used for references in construction.

Effect of Silica Fume on Compressive Strength of Oil-Polluted Concrete in Different Marine Environments

In the present research, effect of silica fume as an additive and oil polluted sands as aggregates on compressive strength of concrete were investigated experimentally. The amount ofoil in the designed mixtures was assumed to be constant and equal to 2% of the sand weight. Silica fume accounting for 10%, 15% and 20% of the weight is added to the designed mixture. After preparation and curing, concrete specimens were placed into the three different conditions： fresh, brackish and saltwater environments （submerged in fresh water, alternation of exposed in air ＆ submerged in sea water and submerged in sea water）. The result of compressive strength tests shows that the compressive strength of the specimens consisting of silica fume increases significantly in comparison with the control specimens in all three environments. The compressive strength of the concrete with 15% silica fume content was about 30% to 50% higher than that of control specimens in all tested environments under the condition of using polluted aggregates in the designed mixture.

Effect of Interfacial Strength on Bending Properties of Reinforced Concrete Beams

By taking into consideration of meso-scopic level, four-point bending numerical model of different interfaces was established to analyze the effect of interracial strength on the bending properties of reinforced concrete beams with the diagrams of crack pattern, the load- step curve and the cumulative AE- loading step curve. The experimental result shows that the peak load, the cracking load and the stiffness before cracking increase with the interfacial strength. Furthermore, the specimen with strong interface presents high brittleness during the failure process, while both bearing capability and ductility could be found in the specimen with moderate interfacial strength.

Prediction of Compressive Strength of Self-Compacting Concrete Using Intelligent Computational Modeling

In the present scenario,computational modeling has gained much importance for the prediction of the properties of concrete.This paper depicts that how computational intelligence can be applied for the prediction of compressive strength of Self Compacting Concrete(SCC).Three models,namely,Extreme Learning Machine(ELM),Adaptive Neuro Fuzzy Inference System(ANFIS)and Multi Adaptive Regression Spline(MARS)have been employed in the present study for the prediction of compressive strength of self compacting concrete.The contents of cement(c),sand(s),coarse aggregate(a),fly ash(f),water/powder(w/p)ratio and superplasticizer(sp)dosage have been taken as inputs and 28 days compressive strength(fck)as output for ELM,ANFIS and MARS models.A relatively large set of data including 80 normalized data available in the literature has been taken for the study.A comparison is made between the results obtained from all the above-mentioned models and the model which provides best fit is established.The experimental results demonstrate that proposed models are robust for determination of compressive strength of self-compacting concrete.

Predicting Concrete Compressive Strength Using Deep Convolutional Neural Network Based on Image Characteristics

In this study,we examined the efficacy of a deep convolutional neural network(DCNN)in recognizing concrete surface images and predicting the compressive strength of concrete.A digital single-lens reflex(DSLR)camera and microscope were simultaneously used to obtain concrete surface images used as the input data for the DCNN.Thereafter,training,validation,and testing of the DCNNs were performed based on the DSLR camera and microscope image data.Results of the analysis indicated that the DCNN employing DSLR image data achieved a relatively higher accuracy.The accuracy of the DSLR-derived image data was attributed to the relatively wider range of the DSLR camera,which was beneficial for extracting a larger number of features.Moreover,the DSLR camera procured more realistic images than the microscope.Thus,when the compressive strength of concrete was evaluated using the DCNN employing a DSLR camera,time and cost were reduced,whereas the usefulness increased.Furthermore,an indirect comparison of the accuracy of the DCNN with that of existing non-destructive methods for evaluating the strength of concrete proved the reliability of DCNN-derived concrete strength predictions.In addition,it was determined that the DCNN used for concrete strength evaluations in this study can be further expanded to detect and evaluate various deteriorative factors that affect the durability of structures,such as salt damage,carbonation,sulfation,corrosion,and freezing-thawing.

Experimental study on the compressive strength of grouted concrete block masonry based on nondestructive detection methods

Existing nondestructive detection methods were adopted to test the compressive strength of grouted concrete block masonry,i.e.the rebound method,pulling-out method and core drilling method were employed to test the strength of block,mortar and grouted concrete,respectively.The suitability of these methods for the testing of strength of grouted concrete block masonry was discussed,and the comprehensive strength of block masonry was appraised by combining existing nondestructive or micro-destructive detection methods.The nondestructive detection test on 25 grouted concrete block masonry specimens was carried out.Experimental results show that these methods mentioned above are applicable for the strength detection of grouted concrete block masonry.Moreover,the formulas of compressive strength,detection methods and proposals are given as well.

Shrinkage and Compressive Strength of Concrete with Superabsorbent Polymers

The effects of superabsorbent polymers on the shrinkage and mechanical properties of concrete were investigated.Results of shrinkage tests show that SAP addition reduces the shrinkage.Especially,for the concrete with 3.84 kg SAP/m3 concrete,the shrinkage is little.Compressive strength of concrete with SAP is lower than that of concrete without SAP.However,for the concrete with SAP,the ratio of compressive strength at 90 days to one at 3 days is larger than that of concrete without SAP.

Reliable evaluation method of quality control for compressive strength of concrete

Concrete in reinforced concrete structure (RC) is generally under significant compressive stress load. To guarantee required quality and ductility, various tests have to be conducted to measure the concrete’s compressive strength based on ACI (American Concrete Institute) code. Investigations of recent devastating collapses of structures around the world showed that some of the collapses directly resulted from the poor quality of the concrete. The lesson learned from these tragedies is that guaranteeing high quality of concrete is one of the most important factors ensuring the safety of the reinforced concrete structure. In order to ensure high quality of concrete, a new method for analyzing and evaluating the concrete production process is called for. In this paper, the indices of fit and stable degree are proposed as basis to evaluate the fitness and stability of concrete’s compressive strength. These two indices are combined to define and evaluate the quality index of the compressive strength of concrete. Prin-ciples of statistics are used to derive the best estimators of these indices. Based on the outcome of the study, a concrete compres-sive strength quality control chart is proposed as a tool to help the evaluation process. Finally, a new evaluation procedure to assess the quality control capability of the individual concrete manufacturer is also proposed.

Shear strengthening of pre-damaged reinforced concrete beams with carbon fiber reinforced polymer sheet strips

This paper presents the results of an experimental investigation on the response of pre-damaged reinforced concrete （RC） beam strengthened in shear using applied-epoxy unidirectional carbon fiber reinforced polymer （CFRP） sheet. The reasearch included four test rectangular simply supported RC beams in shear capacity. One is the control beam, two RC beams are damaged to a predetermined degree from ultimate shear capacity of the control beam, and the last beam is left without pre-damaged and then strengthened with using externally bonded carbon fiber reinforced polymer to upgrade their shear capacity. We focused on the damage degree to beams during strengthening, therefore, only the beams with sidebonded CFRPs strips and horizontal anchored strips were used. The results show the feasibility of using CFRPs to restore or increase the load-carrying capacity in the shear of damaged RC beams. The failure mode of all the CFRP-strengthened beams is debonding of CFRP vertical strips. Two prediction available models in AC1-440 and fib European code were compared with the experimental results.

Effect of Micro Silica on Compressive Strength of Plastic Concrete

This research describes a series of laboratory tests performed to characterize the mechanical properties of plastic concrete. The mechanical properties of plastic concrete are studied using a series of compression tests. Stress relaxation and controlled rate of loading tests are also performed to investigate the rate sensitivity and time-dependency of plastic concrete. An important requirement for the plastic concrete in such applications is adequate strength for the design loads. The replacement of cement content of plastic concrete by micro silica does not result in any significant decrease in workability of plastic concretes and hence, unlike the case for normal concretes, plasticizers or super plasticizers are not required to rectify the adverse effect of micro silica on workability. The aim of the experimental research was to investigate the effects of various levels of cement replacement by micro silica, including 0%, 3%, 6%, 9%, 12% and 15% on strength of plastic concrete. Obtained results show that the effect of micro silica on strength enhancement of plastic concretes is substantial and a replacement level of 15% resulted in 70%-180% increase in strength compared to the control mix. For normal concretes, the increase in strength due to incorporation of micro silica was generally reported as 30%-50%.