The use of GA-ANNs in the modelling of compressive strength of cement mortar

In this paper, results of a project aimed at modelling the compressive strength of cement mortar under standard curing conditions are reported. Plant data were collected for 6 months for the chemical and physical properties of the cement that were used in model construction and testing. The training and testing data were separated from the complete original data set by the use of genetic algorithms (GAs). A GA-artificial neural network (ANN) model based on the training data of the cement strength was created. Testing of the model was also done within low average error levels (2.24%). The model was subjected to sensitivity analysis to predict the response of the system to different values of the factors affecting the strength. The plots obtained after sensitivity analysis indicated that increasing the amount of C₃S, SO₃ and surface area led to increased strength within the limits of the model. C₂S decreased the strength whereas C₃A decreased or increased the strength depending on the SO₃ level. Because of the limited data range used for training, the prediction results were good only within the same range. The utility of the model is in the potential ability to control processing parameters to yield the desired strength levels and in providing information regarding the most favourable experimental conditions to obtain maximum compressive strength.     

Predicting compressive strength of different geopolymers by artificial neural networks

In the present study, six different models based on artificial neural networks have been developed to predict the compressive strength of different types of geopolymers. The differences between the models were in the number of neurons in hidden layers and in the method of finalizing the models. Seven independent input parameters that cover the curing time, Ca(OH)₂ content, the amount of superplasticizer, NaOH concentration, mold type, geopolymer type and H₂O/Na₂O molar ratio were considered. For each set of these input variables, the compressive strength of geopolymers was obtained. A total number of 399 input-target pairs were collected from the literature, randomly divided into 279, 60 and 60 data and were trained, validated and tested, respectively. The best performance model was obtained through a network with two hidden layers and absolute fraction of variance of 0.9916, the absolute percentage error of 2.2102 and the root mean square error of 1.4867 in training phase. Additionally, the entire trained, validated and tested network showed a strong potential for predicting the compressive strength of geopolymers with a reasonable performance in the considered range.     

A new model for the estimation of compressive strength of Portland cement concrete

In this article, on the basis of the existing experimental data, an empirical equation for calculating the compressive strength of Portland cement concrete is developed. The determination of the compressive strengths by the equation described here relies on accurate determination of the water to cement ratio which gives maximum compressive strength and the analysis of its variation with the curing time. The results obtained for the plain (without admixture) and latex modified concretes at the age of 28 days show that this ratio ranges from 0.18 to 0.23. These values are reasonably close to the non-evaporable water content reported for the Portland cement. On the other hand, this range as determined by the above procedure limits the usefulness of the proposed equation for predicting the compressive strength of silica fume blended Portland cement concretes. However, a general method of solving problems of this type allows the determination of upper and lower bounds of this range. This method requires the measurement of at least two compressive strengths corresponding to two different water to cement ratios.     

Prediction of cement strength using soft computing techniques

In this paper, it is aimed to propose prediction approaches for the 28-day compressive strength of Portland composite cement (PCC) by using soft computing techniques. Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise regression analysis is also used to have an idea about the predictive power of the soft computing techniques in comparison to classical statistical approach. The application of the genetic programming (GP) technique GEP to the cement strength prediction is shown for the first time in this paper. The results obtained from the computational tests have shown that GEP is a promising technique for the prediction of cement strength.     

Effects of densified silica fume on microstructure and compressive strength of blended cement pastes

Some experimental investigations on the microstructure and compressive strength development of silica fume blended cement pastes are presented in this paper. The silica fume replacement varies from 0% to 20% by weight and the water/binder ratio (w/b) is 0.4. The pore structure by mercury intrusion porosimetry (MIP), the micromorphology by scanning electron microscopy (SEM) and the compressive strength at 3, 7, 14, 28, 56 and 90 days have been studied. The test results indicate that the improvements on both microstructure and mechanical properties of hardened cement pastes by silica fume replacement are not effective due to the agglomeration of silica fume particles. The unreacted silica fume remained in cement pastes, the threshold diameter was not reduced and the increase in compressive strength was insignificant up to 28 days. It is suggested that the proper measures should be taken to disperse silica fume agglomeration to make it more effective on improving the properties of materials.     

Prediction model of compressive strength development of fly-ash concrete

Based on experimental results concerning the compressive strength development of concrete containing fly ash, the authors derived an estimation equation for compressive strength development. The equation can express coefficient , which indicates the activity of fly ash as a binder, in the form of a function of age, fly-ash content, and Blaine specific surface area of fly ash.

This equation is capable of explaining the increases in the early strength due to fly ash in place of part of fine aggregate, the decreases in the early strength due to fly ash in place of part of cement, the increases in the long-term strength due to pozzolanic reaction, the relationship between the fly-ash replacement ratio and the ratio of strength increase/decrease, and the effect of fly ash's Blaine specific surface area on the strength.     

Study on the improvement of compressive strength and fracture toughness of calcium phosphate cement

Calcium phosphate cement (CPC) has superior properties, such as excellent bioactivity, biocompatibility, osteoconductivity and degradability, since its hydration product is hydroxyapatite (HA). As a novel cement material, CPC also shows injectable and self-setting properties. However, the compressive strength (CS) and fracture toughness of most CPCs are far lower than that of human weight-bearing bones, which largely limit their applications in the repairment of weight-bearing bones. To improve the CS and fracture toughness of CPC, several methods, including in-situ reinforcement by Ca4(PO4)2O (TTCP) ceramic particles, suitable nanofibers are introduced in this study. The maximal CS of CPC prepared with TTCP (average particle size of 22.3 ± 0.4 μm) reached to 98.4 MPa, which is close to the strength of human long bones. The enhanced CS of CPC was attributed to the in-situ reinforcing effect of residual TTCP particles. Tendon collagen slices and HA nanofibers were used to improve the fracture toughness of CPC. The flexural strength (FS) and the work of facture (WOF) of CPC were slightly increased by adding HA nanofibers but was significantly increased by the addition of tendon collagen slices. With 1.000 wt% tendon collagen slices, the FS and WOF of CPC were increased by 61.3% and 22.6 times, respectively.     

The effect of waste oil-cracking catalyst on the compressive strength of cement pastes and mortars

Epcat, one of the spent fluid catalytic cracking (FCC) catalysts from oil-cracking refineries, shows pozzolanic activity. In this study, pastes and mortars with Epcat were prepared and cured, and their compressive strengths after 3, 7 and 28 curing days were measured. The water/binder (W/B) ratios were 0.2, 0.25 and 0.3, and the replacement levels of cement by Epcat were 0, 5, 10 and 15 wt.%. Proper amount of superplasticizer was added into each mix to ensure similar workability.The results indicate that the presence of Epcat would increase the compressive strength of mortars substantially, but increase the compressive strength of the related pastes only slightly. Epcat mortars with W/B=0.25 show more strength-enhancing effect than those with W/B=0.3, and this effect increases with the catalyst content. Therefore, the mix (W/B=0.25) incorporated 15% Epcat exhibits the greatest compressive strength (92.3 MPa). For mortars with W/B=0.2, the strength-enhancing effect occurs only for those containing 5% catalyst; this effect becomes unclear when mixes containing 10% Epcat or more because high dosage of superplasticizer was added in obtaining proper workability and that affects the strength development. The improvement in the mechanical properties of mortars is attributed to the increase in the hydrated cement paste itself and, more importantly, improved bonds between the cement paste and aggregate.     

The correlation between compressive strength and ultrasonic parameters of calcium aluminate cement materials

Calcium aluminate cement (CAC) mortars were investigated by nondestructive ultrasonic measurement in the through-transmission mode and compressive strength measurements. The detected profile of ultrasonic signal was fitted as a sine wave modulated with the Gauss function. The linear relationship between compressive strength and the product of the amplitude and angular frequency of the signal was established. A qualitative explanation of the proposed correlation based on the existing theories was given.     

Prediction of unconfined compressive strength of cement paste with pure metal compound additions

Neural network analysis was used to construct models of unconfined compressive strength (UCS) as a function of mix composition using existing data from literature studies of pure compound additions to Portland cement paste. The models were able to represent the known nonlinear dependency of UCS on age and water content, and generalised from the literature data to find relationships between UCS and contaminant concentrations, resulting in the following ranking of the UCS values predicted for addition of the contaminants, on an equimolar basis: at 7 days, Cl≈Cr(III)>NO₃⁻≈Cd>control>Zn≥Ni>Pb>Cu?Ba; at 28 days, Cl>Cr(III)>NO₃⁻≈control≥Zn≥Cd>Ni>Pb>Cu?Ba. Application of the best neural network to other data suggested that Cs is a retarder and Cr(VI) has no effect. No trends could be discerned for Hg, K, Mn, Na and SO₄²⁻. The root-mean-square error for the best neural network seems to be an estimate of the interlaboratory error for UCS.     

Bending and compressive behaviours of a new cement composite

The Laboratoire Central des Ponts et Chaussées (LCPC) has recently developed and patented a new cement composite, the CEMTEC_multiscale, which is stress hardening in tension and has a very high uniaxial tensile strength, more than 20 MPa. This paper is about the determination of the compressive and bending behaviors of the CEMTEC_multiscale used in the frame of ribbed slabs.The principal results obtained are the following:

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the characteristic modulus of rupture is equal to 42 MPa for the “slab” function;

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the characteristic modulus of rupture is equal to 48 MPa for the “rib” function;

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the ultimate tensile strain is around 5 10⁻³;

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the characteristic strength and ultimate strain in compression are equal to 205 MPa and 4 10⁻³, respectively; and

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the Young modulus is equal to 55 GPa and the Poisson coefficient is equal to .21.

     

Experimental relationship between splitting tensile strength and compressive strength of GFRC and PFRC

This paper describes an experimental investigation into the relationship between the splitting tensile strength and compressive strength of glass fiber reinforced concrete (GFRC) and polypropylene fiber reinforced concrete (PFRC). The splitting tensile strength and compressive strength of GFRC and PFRC at 7, 28 and 90 days are used. Test results indicate that the addition of glass and polypropylene fibers to concrete increased the splitting tensile strength of concrete by approximately 20-50%, and the splitting tensile strength of GFRC and PFRC ranged from 9% to 13% of its compressive strength. Based on this investigation, a simple 0.5 power relationship between the splitting tensile strength and the compressive strength was derived for estimating the tensile strength of GFRC and PFRC.     

Green and early age compressive strength of extruded cement mortar monitored with compression tests and ultrasonic techniques

Knowledge about the early age compressive strength development of cementitious materials is an important factor for the progress and safety of many construction projects. This paper uses cylindrical mortar specimens produced with a ram extruder to investigate the transition of the mortar from plastic and deformable to hardened state. In addition, wave transmission and reflection measurements with P- and S-waves were conducted to obtain further information about the microstructural changes during the setting and hardening process. The experiments have shown that uniaxial compression tests conducted on extruded mortar cylinders are a useful tool to evaluate the green strength as well as the initiation and further development of the compressive strength of the tested material. The propagation of P-waves was found to be indicative of the internal structure of the tested mortars as influenced, for example, by the addition of fine clay particles. S-waves used in transmission and reflection mode proved to be sensitive to the inter-particle bonding caused by the cement hydration and expressed by an increase in compressive strength.     

Investigation of the effects of fatty acids on the compressive strength of the concrete and the grindability of the cement

In cement industry, a great energy consumption has been observed during grinding of clinker. To reduce this consumption, some waste products have been used as grinding aids.In this investigation, the effects of sunflower oil (SO), oleic acid (OA), stearic acid (SA), myristic acid (MA) and lauric acid (LA) on the fineness and strength of the cement have been examined. These aids were added into clinker in certain ratios based on the cement clinker weight and the grinding has been done for a definite time at the same condition.All of the fatty acids used increased the fineness as compared with the cement without the grinding additives. SO and OA decreased the strength significantly, LA decreased it to a lesser extent and SA increased it definitely according to the common cement. But MA did not alter the strength of the cement as much as SA. In addition, the covering of the balls influences the grinding of cement clinker unfavourably.     

The effects of different cement dosages, slumps and pumice aggregate ratios on the compressive strength and densities of concrete

Compressive strengths of concretes made up of mixtures of pumice aggregate (PA) and normal aggregate were measured. To determine the effect of PA ratio, different cement dosage and slumps on the compressive strength of concrete, (1) 25%, 50%, 75% and 100% pumice ratios were used instead of normal aggregate by volume, (2) 200, 250, 350, 400 and 500 kg/m³ cement dosages were used and (3) 3±1, 5±1 and 7±1 cm slumps were also used in this study.The analysis of the test results leads to the conclusion that PA decreased the density of concretes up to 41.5% and reductions occurred due to the increase of the PA ratio in the mixes. With the increase of cement dosage in the mixes, both density and compressive strength of concretes increased up to 3.2% and 265%, respectively, when compared to the control sample that contain 200 kg/m³ cement dosage. The effect of the slump on the density and compressive strength was varied. Elasticity moduli were decreased with an increase of PA ratio and increased with an increase of cement dosage. Water absorption improved with an increase of cement content.     

Roughness of fracture surfaces and compressive strength of hydrated cement pastes

A new type of roughness number Rn_o is formulated as a possible analytical tool for surface studies using confocal microscopy. The formulation accommodates fractal dimension and both of the boundary length scales limiting the fractal region of the fracture surface under investigation. Besides the number Rn_o other roughness characteristics are discussed and their effectiveness in the field of cementitious materials is tested. 3D-surface profile SP and surface roughness SR parameters designed for surface 3D-analysis were calculated for fracture surfaces of hydrated Portland cement pastes with different values of water-to-cement ratio. The surface profile SP parameters monotonically increased with water-to-cement ratio and monotonically decreased with compressive strength. A short discussion of possible reasons for such a behavior is presented.     

Optimum usage of a natural pozzolan for the maximum compressive strength of concrete

Pozzolans provide an economic production possibility in the concrete industry and improve the properties of concrete, such as durability. Effects of a pozzolan on the properties of concrete vary with the pozzolan type and volume.In this study, effect of a natural pozzolan on the properties of concrete was investigated. Fifteen concrete mixtures were produced in three series with control mixes having 300, 350 and 400 kg cement content. These control mixes were modified to have a combination of 250, 300 and 350 kg cement content and 40, 50, 75 and 100 kg pozzolan addition for 1 m³ concrete. The efficiency of the pozzolan was obtained by using Bolomey and Feret strength equations on 28-day-old concretes. Maximum pozzolan amount with the optimum efficiency was determined. This study shows that the efficiencies obtained from each strength equations are similar and these values decrease with the increase of pozzolan/cement ratio.     

Preparation and characterization of high compressive strength foams from sheet glass

High compressive strength glass foams were produced using sheet glass cullet with the aid of 1 wt.% SiC powder, as gassing agent, and the incorporation of small amounts of an alkali earth aluminosilicate glass powder (AD), which is intrinsically prone to be crystallised to anorthite and diopside. The amount of SiC used as well as the mean particle sizes of the powders of both glasses and SiC were lower than those used in earlier studies. The experimental results showed that homogenous microstructures of large pores could be obtained by adding 1 wt.% SiC. The compressive strength of the glass foams was considerably increased when the incorporated AD-glass was higher than 1 wt.%. It is concluded that the presence of the AD glass is beneficial for the produced glass foams because of the formation of a well packed honeycomb structure which features an optimal distribution of pentagonal- and hexagonal-like shaped pores surrounded by dense struts. The crystallization of wollastonite and diopside inside the struts should also have a positive impact on the mechanical behaviour of the produced porous glass foams.