Statistical modelling of cement slurries for self compacting SIFCON containing silica fume

This paper reports a study carried out to develop a self-compacting fibre reinforced concrete containing a high fibre content with slurry infiltrated fibre concrete (SIFCON). The SIFCON was developed with 10% of steel fibres which are infiltrated by self-compacting cement slurry without any vibration. Traditionally, the infiltration of the slurry into the layer of fibres is carried out under intensive vibration. A two-level fractional factorial design was used to optimise the properties of cement-based slurries with four independent variables, such as dosage of silica fume, dosage of superplasticiser, sand content, and water/cement ratio (W/C). Rheometer, mini-slump test, Lombardi plate cohesion meter, J-fibre penetration test, and induced bleeding were used to assess the behaviour of fresh cement slurries. The compressive strengths at 7 and 28 days were also measured. The statistical models are valid for slurries made with W/C of 0.40 to 0.50, 50 to 100% of sand by mass of cement, 5 to 10% of silica fume by mass of cement, and SP dosage of 0.6 to 1.2% by mass of cement. This model makes it possible to evaluate the effect of individual variables on measured parameters of fresh cement slurries. The proposed models offered useful information to understand trade-offs between mix variables and compare the responses obtained from various test methods in order to optimise self-compacting SIFCON.

Applications of statistical models in proportioning medium strength self-compacting concrete

Self-compacting concrete (SCC) is generally designed with a relatively higher content of finer, which includes cement, and dosage of superplasticizer than the conventional concrete. The design of the current SCC leads to high compressive strength, which is already used in special applications, where the high cost of materials can be tolerated. Using SCC, which eliminates the need for vibration, leads to increased speed of casting and thus reduces labour requirement, energy consumption, construction time, and cost of equipment. In order to obtain and gain maximum benefit from SCC it has to be used for wider applications. The cost of materials will be decreased by reducing the cement content and using a minimum amount of admixtures. This paper reviews statistical models obtained from a factorial design which was carried out to determine the influence of four key parameters on filling ability, passing ability, segregation and compressive strength. These parameters are important for the successful development of medium strength self-compacting concrete (MS-SCC). The parameters considered in the study were the contents of cement and pulverised fuel ash (PFA), water-to-powder ratio (W/P), and dosage of superplasticizer (SP). The responses of the derived statistical models are slump flow, fluidity loss, rheological parameters, Orimet time, V-funnel time, L-box, JRing combined to Orimet, JRing combined to cone, fresh segregation, and compressive strength at 7, 28 and 90 days. The models are valid for mixes made with 0.38 to 0.72 W/P ratio, 60 to 216 kg/m3 of cement content, 183 to 317 kg/m3 of PFA and 0 to 1% of SP, by mass of powder. The utility of such models to optimize concrete mixes to achieve good balance between filling ability, passing ability, segregation, compressive strength, and cost is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mix parameters on slump flow, loss of fluidity, flow resistance, segregation, JRing combined to Orimet, and compressive strength at 7 and 28 days. Cost analysis is carried out to show trade-offs between cost of materials and specified consistency levels and compressive strength at 7 and 28 days that can be used to identify economic mixes. The paper establishes the usefulness of the mathematical models as a tool to facilitate the test protocol required to optimise medium strength SCC.

Filling Ability and Passing Ability of Self-Consolidating Concrete

This paper reviews statistical models obtained from a composite factorial design study, which was carried out to determine the influence of three key parameters of mixture composition on filling ability and passing ability of self-consolidating concrete (SCC). This study was a part of the European project “Testing SCC”- GRD2-2000-30024. The parameters considered in this study were the dosages of water and high-range water-reducing admixture (HRWRA), and the volume of coarse aggregates. The responses of the derived statistical models were slump flow, T50 , T60, V-funnel flow time, Orimet flow time, and blocking ratio (L-box). The retention of these tests was also measured at 30 and 60 minutes after adding the first water. The models are valid for mixtures made with 188 to 208 L/m3 (317 to 350 lb/yd3) of water, 3.8 to 5.8 kg/m3 (570 to 970 mL/100 kg of binder) of HRWRA, and 220 to 360 L/m3 (5.97 to 9.76 ft3/yd3) of coarse aggregates. The utility of such models to optimize concrete mixtures and to achieve a good balance between filling ability and passing ability is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mixture parameters on slump flow, T50 , T60 , V-funnel flow time, Orimet flow time, and blocking ratio. The paper also illustrates the various trade-offs between the mixture parameters on the derived responses that affected the filling and the passing ability.

Factorial Design of Cement Slurries Containing Limestone Powder for Self-Consolidating Slurry-Infiltrated Fiber Concrete

Slurries with high penetrability for production of Self-consolidating Slurry Infiltrated Fiber Concrete (SIFCON) were investigated in this study. Factorial experimental design was adopted in this investigation to assess the combined effects of five independent variables on mini-slump test, plate cohesion meter, induced bleeding test, J-fiber penetration test and compressive strength at 7 and 28 days. The independent variables investigated were the proportions of limestone powder (LSP) and sand, the dosages of superplasticiser (SP) and viscosity agent (VA), and water-to-binder ratio (w/b). A two-level fractional factorial statistical method was used to model the influence of key parameters on properties affecting the behaviour of fresh cement slurry and compressive strength. The models are valid for mixes with 10 to 50% LSP as replacement of cement, 0.02 to 0.06% VA by mass of cement, 0.6 to 1.2% SP and 50 to 150% sand (% mass of binder) and 0.42 to 0.48 w/b. The influences of LSP, SP, VA, sand and W/B were characterised and analysed using polynomial regression which identifies the primary factors and their interactions on the measured properties. Mathematical polynomials were developed for mini-slump, plate cohesion meter, J-fiber penetration test, induced bleeding and compressive strength as functions of LSP, SP, VA, sand and w/b. The estimated results of mini-slump, induced bleeding test and compressive strength from the derived models are compared with results obtained from previously proposed models that were developed for cement paste. The proposed response models of the self-consolidating SIFCON offer useful information regarding the mix optimization to secure a highly penetration of slurry with low compressive strength

Influence of mix proprtions on rheolgy of cement grouts containing limestone powder

In this paper the parameters of cement grout affecting rheological behaviour and compressive strength are investigated. Factorial experimental design was adopted in this investigation to assess the combined effects of the following factors on fluidity, rheological properties, induced bleeding and compressive strength: water/binder ratio (W/B), dosage of superplasticiser (SP), dosage of viscosity agent (VA), and proportion of limestone powder as replacement of cement (LSP). Mini-slump test, Marsh cone, Lombardi plate cohesion meter, induced bleeding test, coaxial rotating cylinder viscometer were used to evaluate the rheology of the cement grout and the compressive strengths at 7 and 28 days were measured. A two-level fractional factorial statistical model was used to model the influence of key parameters on properties affecting the fluidity, the rheology and compressive strength. The models are valid for mixes with 0.35-0.42 W/B, 0.3-1.2% SP, 0.02-0.7% VA (percentage of binder) and 12-45% LSP as replacement of cement. The influences of W/B, SP, VA and LSP were characterised and analysed using polynomial regression which can identify the primary factors and their interactions on the measured properties. Mathematical polynomials were developed for mini-slump, plate cohesion meter, inducing bleeding, yield value, plastic viscosity and compressive strength as function of W/B, SP, VA and proportion of LSP. The statistical approach used highlighted the limestone powder effect and the dosage of SP and VA on the various rheological characteristics of cement grout

Prediction of Fresh and Hardened Properties of Self-Consolidating Concrete Using Neurofuzzy Approach

Self-consolidating concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work conditions and also reduce the impact on the environment by elimination of the need for compaction. This investigation aimed at exploring the potential use of the neurofuzzy (NF) approach to model the fresh and hardened properties of SCC containing pulverised fuel ash (PFA) as based on experimental data investigated in this paper. Twenty six mixes were made with water-to-binder ratio ranging from 0.38 to 0.72, cement content ranging from 183 to 317 kg/m3 , dosage of PFA ranging from 29 to 261 kg/m3 , and percentage of superplasticizer, by mass of powder, ranging from 0 to 1%. Nine properties of SCC mixes modeled by NF were the slump flow, JRing combined to the Orimet, JRing combined to cone, V-funnel, L-box blocking ratio, segregation ratio, and the compressive strength at 7, 28, and 90 days. These properties characterized the filling ability, the passing ability, the segregation resistance of fresh SCC, and the compressive strength. NF model is constructed by training and testing data using the experimental results obtained in this study. The results of NF models were compared with experimental results and were found to be quite accurate. The proposed NF models offers useful modeling approach of the fresh and hardened properties of SCC containing PFA.

Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash

Self-compacting concrete (SCC) flows into place and around obstructions under its own weight to fill the formwork completely and self-compact without any segregation and blocking. Elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. This investigation aimed to show possible applicability of genetic programming (GP) to model and formulate the fresh and hardened properties of self-compacting concrete (SCC) containing pulverised fuel ash (PFA) based on experimental data. Twenty-six mixes were made with 0.38 to 0.72 water-to-binder ratio (W/B), 183–317 kg/m³ of cement content, 29–261 kg/m³ of PFA, and 0 to 1% of superplasticizer, by mass of powder. Parameters of SCC mixes modelled by genetic programming were the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength at 7, 28 and 90 days. GP is constructed of training and testing data using the experimental results obtained in this study. The results of genetic programming models are compared with experimental results and are found to be quite accurate. GP has showed a strong potential as a feasible tool for modelling the fresh properties and the compressive strength of SCC containing PFA and produced analytical prediction of these properties as a function as the mix ingredients. Results showed that the GP model thus developed is not only capable of accurately predicting the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength used in the training process, but it can also effectively predict the above properties for new mixes designed within the practical range with the variation of mix ingredients.

Modelling the performance of self-compacting SIFCON of cement slurries containing limestone powder using genetic programming technique

The paper explores the potential of applicability of Genetic programming approach (GP), adopted in this investigation, to model the combined effects of five independent variables to predict the mini-slump, the plate cohesion meter, the induced bleeding test, the J-fiber penetration value, and the compressive strength at 7 and 28 days of self-compacting slurry infiltrated fiber concrete (SIFCON). The variables investigated were the proportions of limestone powder (LSP) and sand, the dosage rates of superplasticiser (SP) and viscosity modifying agent (VMA), and water-to-binder ratio (W/B). Twenty eight mixtures were made with 10-50% LSP as replacement of cement, 0.02-0.06% VMA by mass of cement, 0.6-1.2% SP and 50-150% sand (% mass of binder) and 0.42-0.48 W/B. The proposed genetic models of the self-compacting SIFCON offer useful modelling approach regarding the mix optimisation in predicting the fluidity, the cohesion, the bleeding, the penetration, and the compressive strength.

Effect of Mix Proportions on Rheological and Hardened Properties of Composite Cement Pastes

There is an increasing need to identify the effect of mix composition on the rheological properties of composite cement pastes using simple tests to determine the fluidity, the cohesion and other mechanical properties of grouting applications such as compressive strength. This paper reviews statistical models developed using a fractional factorial design which was carried out to model the influence of key parameters on properties affecting the performance of composite cement paste. Such responses of fluidity included mini-slump, flow time using Marsh cone and cohesion measured by Lombardi plate meter and unit weight, and compressive strength at 3 d, 7 d and 28 d. The models are valid for mixes with 0.35 to 0.42 water-to-binder ratio (W/B), 10% to 40% of pulverised fuel ash (PFA) as replacement of cement by mass, 0.02 to 0.06% of viscosity enhancer admixture (VEA), by mass of binder, and 0.3 to 1.2% of superplasticizer (SP), by mass of binder. The derived models that enable the identification of underlying primary factors and their interactions that influence the modelled responses of composite cement paste are presented. Such parameters can be useful to reduce the test protocol needed for proportioning of composite cement paste. This paper attempts also to demonstrate the usefulness of the models to better understand trade-offs between parameters and compare the responses obtained from the various test methods which are highlighted. The multi parametric optimization is used in order to establish isoresponses for a desirability function of cement composite paste. Results indicate that the replacement of cement by PFA is compromising the early compressive strength and up 26%, the desirability function decreased.

Artificial Intelligence Model for Flowable Concrete Mixtures Used in Underwater Construction and Repair

This study explores using artificial neural networks to predict the rheological and mechanical properties of underwater concrete (UWC) mixtures and to evaluate the sensitivity of such properties to variations in mixture ingredients. Artificial neural networks (ANN) mimic the structure and operation of biological neurons and have the unique ability of self-learning, mapping, and functional approximation. Details of the development of the proposed neural network model, its architecture, training, and validation are presented in this study. A database incorporating 175 UWC mixtures from nine different studies was developed to train and test the ANN model. The data are arranged in a patterned format. Each pattern contains an input vector that includes quantity values of the mixture variables influencing the behavior of UWC mixtures (that is, cement, silica fume, fly ash, slag, water, coarse and fine aggregates, and chemical admixtures) and a corresponding output vector that includes the rheological or mechanical property to be modeled. Results show that the ANN model thus developed is not only capable of accurately predicting the slump, slump-flow, washout resistance, and compressive strength of underwater concrete mixtures used in the training process, but it can also effectively predict the aforementioned properties for new mixtures designed within the practical range of the input parameters used in the training process with an absolute error of 4.6, 10.6, 10.6, and 4.4%, respectively.

Filling Ability and Plastic Settlement of Self-Compacting Concrete

The use of self-compacting concrete (SCC) facilitates the placing of concrete by eliminating the need for compaction by vibration. Given the highly flowable nature of such concrete, care is required to ensure excellent filling ability and adequate stability. This is especially important in deep structural members and wall elements where concrete can block the flow, segregate and exhibit bleeding and settlement which can result in local defects that can reduce mechanical properties, durability and quality of surface finish. This paper shows results of an investigation of fresh properties of self-compacting concrete, such as filling ability measured by slump flow and flow time (measured by Orimet) and plastic fresh settlement measured in a column. The SCC mixes incorporated various combinations of fine inorganic powders and admixtures. The slump flow of all SCCs was greater than 580 mm and the time in which the slumping concrete reached 500 rnm was less than 3 s. The flow time was less than 5 s. The results on SCCs were compared to a control mix. The compressive strength and splitting tensile strength of SCCs were also measured. The effects of water/powder ratio, slump and nature of the sand on the fresh settlement were also evaluated. The volume of coarse aggregate and the dosage of superphsticizer were kept constant. It can be concluded that the settlement of fresh self-compacting concrete increased with the increase in water/powder ratio and slump. The nature of sand influenced the maximum settlement.

Experimental Design to Optimize High-Volume Ash Grout in the Presence of Welan Gum and Superplasticizer

Applications such as soil, rock and oil-well grouting all require enormous amounts of cement and are good examples of areas where a high volume of fly ash could partially replace cement to produce low-cost, environmentally safe and durable concrete. There is an increasing need to identify the rheological properties of cement grout using a simple test to determine the fluidity, and other properties of underwater grouts such as washout resistance and compressive strength. This paper presents statistical models developed using a fractorial design which was carried out to model the influence of key parameters on properties affecting the performance of underwater grout. Such responses of fluidity included mini-slump and flow time measured by Marsh cone, washout resistance, unit weight and compressive strength. The models are valid for mixes with 0.40 to 0.60 water-to-cementitious materials ratio, 0.02 to 0.08% of anti-washout admixture, by mass of binder, and 0.6 to 1.8% of superplasticizer, by mass of cementitious materials. The grout was made with 50% of pulverized-fuel ash replacement, by mass ofcementitious materials. Also presented are the derived models that enable the identification of underlying primary factors and their interactions that influence the modelled responses of underwater cement grout. Such parameters can be useful to reduce the test protocol needed for proportioning of underwater cement grout. This paper highlighted the influence of W/CM and dosage of antiwashout admixture and superplasticizer on fluidity, washout resistance and compressive strength and attempted also to demonstrate the usefulness of the models to improve understanding of trade-offs between parameters.

Effect of Mixture Composition on Washout Resistance of Highly Flowable Underwater Concrete

The underwater casting of relatively thin lifts of concrete in water requires the proportioning of highly flowable concrete that can resist water dilution and segregation and spread readily into place. An investigation was carried out to determine the effects of antiwashout admixture concentration, water-cementitious materials ratio, and binder composition on the washout resistance of highly flowable concrete. Two main types of antiwashout admixtures were used: 1) a powdered welan gum at concentrations of 0.07 and 0.15% (by mass of binder); and 2) a liquid-based cellulosic admixture with dosages up to 1.65 L/100 kg of binder. The water-cementitious materials ratios were set at 0.41 and 0.47, corresponding to high-quality underwater concrete. Four binder compositions were used: a standard Canadian Type 10 cement, the same cement with 10% silica fume replacement, the cement with 50% granulated blast-furnace slag replacement, and a ternary cement containing 6% silica fume and 20% Class F fly ash. The concentrations of anti-washout admixture have direct impact on washout resistance. For a given washout loss, greater slump flow consistency can be achieved with the increases in anti-washout admixture concentration and decreases in water-binder ratio. The washout mass loss can be reduced, for a given consistency

Effect of Mixture Composition on Relative Strength of Highly Flowable Underwater Concrete

Concrete used for underwater repair is often proportioned to spread readily into place and self-consolidate, and to develop high resistance to segregation and water dilution. An investigation was carried out to determine the effect of the dosage of antiwashout admixture, water-cementitious materials ratio (w/cm), and binder composition on the relative residual strength of highly flowable underwater concrete. Two types of antiwashout admixtures were used: a powdered welan gum at 0.07 and 0.15% by mass of binder, and a liquid-based cellulosic admixture employed at a high dosage of 1 to 1.65 L/100 kg of cementitious materials. The w/cms were set at 0.41 and 0.47 to secure adequate performance of underwater concrete for construction and repair. Four binder compositions were used: a Canadian Type 10 cement; a cement with 10% silica fume replacement; a cement with 50% replacement of granulated blast-furnace slag; and a ternary binder containing 6% silica fume and 20% Class F fly ash. Test results indicate that for a given washout mass loss and slump flow consistency, greater relative residual strength can be secured when the dosage of antiwashout admixture is increased, the w/cm is reduced, and a binary binder with 10% silica fume substitution or the ternary binder are employed. Such mixtures can develop relative residual compressive strengths of 85 and 80%, compared to mixtures cast in air, when the value of washout loss is limited to 4 and 6% for mixtures with slump flow values of 450 and 550 mm, respectively.

Effect of Free-Fall Height in Water on Performance of Flowable Concrete

Concrete placed under water should be proportioned to flow readily into place with minimum materials separation. Unlike concrete cast for deep tremie seals, the use of concrete in repairs often necessitates some free fall of the mixture through water. Such placement conditions lead to greater risk of water erosion and segregation, and should be addressed in proportioning highly flowable underwater concrete. This paper evaluates the effect of free-fall height (FFH) of concrete through water on resulting in-place properties. Concrete was cast in blocks measuring 0.54 x 0.44 x 1 m with the initial FFH in water ranging between 0.25 and 0.60 m. In-place compressive and splitting tensile strengths, unit weight, and depth of washed-out and sedimentation materials were determined. In total, 24 highly flowable mixtures with slump flows greater than 500 mm were investigated. The evaluated mixtures were prepared with various hydraulic binders, including conventional Type 10 cement, a binary mixture with 10% of silica fume (SF), and a ternary binder incorporating 20% of fly ash (FA) and 6% of SF. The mixtures were proportioned with water-binder ratios (w/b) ranging between 0.41 and 0.47. Test results show that the increase of FFH of fresh concrete in water can greatly decrease the residual strength and significantly increase the thickness of washed out and sedimentation materials. The incorporation of 10% of SF, or 20% of FA and 6% of SF, and the reduction of the w/b from 0.47 to 0.41 can, however, lead to a significant increase in washout resistance and residual strength. A relationship between residual strength and the coupled factor of free-fall drop of concrete in water and washout resistance is established.