Mix Design Of Self-compacting Concrete Research Articles

Utilizing Fine Marine Sediment as a Partial Substitute for Sand in Self-Compacting Concrete Specially Designed for Application in Marine Environments

The disposal of marine sediments poses a significant economic and environmental challenge on a global scale. To address this issue and promote resource optimization within a circular-economy paradigm, this research investigates the viability of incorporating untreated fine marine sediments as a partial replacement for sand in self-compacting concrete (SCC) designed especially for application in marine environments (an exposure class of XS2 and a resistance class of C30/37 according to standard NF EN 206). The concretes mis-design incorporating 30% by weight of sediment as a sand substitute was initially designed with the modified Dreux–Gorisse method. The findings indicate that it is feasible to design an SCC suitable for marine environments, incorporating 30% sediment replacement content and without significantly compromising concrete properties, durability, or the estimated lifespan of the formulated concretes. The integration of marine sediment as a sand substitute into the SCC mix design reduces the amount of binder and limestone filler without compromising the paste volume. This results in a significant saving of natural sand resources and a reduction in CO2 emissions for SCC made with marine sediment.

The role of additives in estimating service life of self-compacting concrete mix design using FIB modelling

The purpose of this study is to examine the influence of additives on estimating the useful service life of self-compacting concrete (SCC). For that, durability tests were performed on 43 SCC mix designs to estimating the service life of SCC based on the FIB model. The investigated supplementary materials included xanthan gum at concentrations of 0.2% and 0.25% by weight of cement, microsilica at concentrations of 5%, 7% and 10% by weight of cement, and nanosilica at concentrations of 2%, 3% and 4% by weight of cement. All 43 designs met the reliability index of the model, thereby obtaining the estimated service life for each design. The findings revealed that in chloride-rich environments, the control sample exhibited greater penetration depth compared to the concretes incorporating xanthan gum, microsilica and nanosilica additives. This observation suggests that the inclusion of xanthan gum extends the service life of SCC due to the formation of a denser and more cohesive structure in the hydration products of xanthan gum-modified concrete. Additionally, the investigations conducted indicate that the presence of nano and micro additives effectively reduces voids, while xanthan gum plays a significant role in minimising cracking and enhancing the thickening properties of the concrete.

Inovasi Teknologi Beton Self Compacting Concrete Terhadap Panjang Pengaliran (L-Flow) Dengan Variasi Umur Perawatan Beton

The aim of this research is to analyze the effect of adding hyperplasticizer and retarder on the compressive strength of self-compacting concrete. Fine aggregate and coarse aggregate from the Jenneberang River, Kab. Gowa. The concrete mix design uses a trial and error mix design for self-compacting concrete by making visual observations, so that the physical conditions of the mixture appear to be sufficient to produce a good mix. The stages of this research, by finding a comparison of the slump flow values ​​of the self-compacting Concrete concrete, then making test objects, after that curing the test objects using the water curing method for 28 days, then testing the compressive strength of the self-compacting Concrete concrete to produce comparison to the compressive strength of normal(conventional) concrete. The results of this research show that self-compacting concrete has a compressive strength value of 46.25 Mpa compared to normal concrete of 45.02 Mpa, an increase of 2.73% compared to normal concrete. And the slump value of normal concrete is 8 - 13 cm, while the slump flow of self-compacting concrete is 63 - 84.9 cm, with a time range between 2.53 - 3.46 seconds, able to reach a diameter of 500 mm on the segregation board.

Numerical modeling of the funnel multiphysical flow of fresh self-compacting concrete considering proportionate heterogeneity of aggregates

Filling ability is one of the prominent rheological properties of the self-compacting concrete (SCC), which has been studied in this research work deploying the functional behavior of the concrete through the studied funnel apparatus using the coupled ANSYS-SPH interface. Seven (7) model cases were studied and optimized. The aim of this numerical study is to propose a more sustainable mix of coarse and fine aggregates proportion that allows for most minimum flow time to enhance a more efficient filling of forms during concreting. The maximum size of the coarse aggregates considered is 20 mm and that of the fine aggregates is below 4 mm. The Bingham model properties for the multiphysics (SPH)-ANSYS models’ simulation are; viscosity = 20 ≤ μ ≤ 100 and the yield stress = 50 ≤τ0≤200\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\le {\ au }_{0}\\le 200$$\\end{document}, standard flow time, t (s) ranges; 6 ≤ t ≤ 25 and the funnel volume is 12 L. The minimum boundary flow time, which represents the time it takes for the SCC to completely flow through a specified distance, typically measured in seconds was modeled for in the seven (7) model cases. The second case with 40% coarse mixed with 60% fine completely flowed out in 16 s, thus fulfilling the minimum flow time. This minimum flow time was considered alongside other relevant parameters and tests, such as slump flow, passing ability, segregation resistance, and rheological properties (stresses), to comprehensively assess the filling ability of SCC in this model. By considering these factors and the optimized mix (40%C + 60%F:16s), engineers and researchers can optimize the SCC mix design to achieve the desired flowability and filling performance for their specific construction applications. The multiphase optimized mix was further simulated using the coupled interface of the ANSYS-SPH platform operating with the CFX command at air temperature of 25 °C. The results show energy reduction jump at the optimized flow time. Ideally, the mix, 40%C + 60%F:16s has been proposed as the mix with the most efficient flow to achieve the filling ability for sustainable structural concrete construction.

The Effect of Polypropylene Fibers on the Behavior of Fiber Self-Compacting Concrete

Fiber self-compacting concrete (FSCC), is a concrete that has been combined with fiber in its mix design. Extensive benefits of self-compacting concrete (SCC) in full fill the mold and achieving full compaction without vibration, with good behavior after concrete cracking, raise the idea of self-compacting concrete production. The fundamental challenge in this area is the unsatisfactory performance of concrete with fibers; In other words, using fibers in concrete will reduce concrete fluidity. Therefore, determining the appropriate percentage of fibers in SCC can be a precursor to extending the use of FSCC. In this study, polypropylene fibers with 0.5, 1, 0.1, and 2% of concrete mix design have been added to the self-compacting concrete mix design. Its impact on the performance of concrete has been evaluated using time and diameter of slump-flow, L-Box, J-ring, and V-funnel flow time tests. Based on the criteria defined by EFNARC standard, it was indicated that the FSCC containing 0.5% polypropylene fibers has an acceptable performance. Additionally, the effect of polypropylene fiber on the mechanical properties of hardened concrete has been studied using compressive strength and tensile tests and shown that changes in FSCC compressive strength and tensile with 0.5% polypropylene fiber are negligible.

Use of Ground Calcium Carbonate for Self-compacting Concrete Development based on Various Water Content and Binder Compositions

Objective: The development of a Self-Compacting Concrete (SCC) mixture requires a different composition compared to normal vibrated concrete. This experimental study was designed to propose a modification of the concrete mix design formula to produce an SCC mix that meets the specified requirements for both fresh and hardened concrete using Ground Calcium Carbonate (GCC) as local fine powder material. Methods: The research was carried out with a targeted compressive strength between 30 and 60 MPa. The materials that were used in this research were fine natural aggregate, crushed stone as a coarse aggregate with a maximum size of 19 mm, Portland pozzolan cement (PPC), GCC, freshwater, and high-range water reducer. The properties of fresh concrete were tested using the slump-flow test method, while the compressive strength test was carried out on 50 standard cylinders after 28 days of curing with water immersion. Results: Test results indicated that the compressive strength and fresh properties of SCC significantly depend on the water content, the water/cement ratio, the volume ratio between water to the total binder, and the weight ratio between the GCC and Portland cement. Conclusion: Furthermore, using the experimental data based on varied water content and binder compositions produces equations with a good fit for SCC mix design in the compressive strength range between 30 MPa to 60 MPa.

Development of a Mix Design Method for Multiplexed Powder Self-Compacting Concrete Based on the Multiscale Rheological Threshold Theory

The multiscale rheological threshold theory can guide the mix design of self-compacting concrete (SCC) from a trans-scale view. Through the paste thresholds calculated by the mini-slump flow test results, the workability of SCC can be predicted. However, this method shows insufficient prediction accuracy when handling multiplexed powder. In the existing threshold calculation formula, the characteristics of powder materials were described through empirical values, without considering the specific properties of various powders. This paper focuses on the application of the multiscale rheological threshold theory to multiplexed powder SCCs. Through the research on the characteristics of powder materials, especially D50 and Span, the effect of the powder properties on paste thresholds was carried out. The prediction accuracies were confirmed by four sets of self-compacting mixtures at paste and concrete scales and were verified with another set of tests. There are a total of 45 paste and 45 SCC test results with multiplexed powders, including cement, fly ash, and limestone powder. The predicting accuracies are expressed as the relative accuracy ε and the accuracy index ε′, calculated by the comparison of self-compacting zones at paste and SCC scales. The calculation results showed that ε and ε′ of the modified method increased. This modified method can be efficient for the mix design of SCC containing multiplexed powders.

A robust mix design method for self-compacting concrete

• A theoretical framework for analyzing SCC’s fresh behavior was established. • Multilevel excess layer model and rheology-based workability criteria were merged. • Generalized self-compacting zones reflect the robustness of SCC mix design. • A robust mix design method balancing the SCC’s content and rheology was proposed. Raw material properties greatly influence the workability of self-compacting concrete (SCC). This paper explored a robust approach to realize the mix design of SCC. A theoretical framework, which combines the excess layer composition model and rheology-based workability criteria, was proposed to analyze the fresh behaviors of the concrete. In the framework, the film-thickness-based composition model established the correlation between concrete’s content with the film’s thickness and the aggregate’s characterization. The suspending cell model could quantify the film’s separating, bearing, and lubricating effects, therefore characterizing the mixture’s flowability and stability. Besides, the derived rheology threshold defined the fresh mixture’s flow spread conditions. The framework was experimentally verified, and the experiment-based threshold calibration referring to the slump flow test significantly improved the framework’s accuracy. Two generalized self-compacting zones (SCZs) for analyzing the robustness of SCC mix design, under the coordinate of film’s thickness and rheology, were theoretically calculated. Through the analysis of the evaluation law of generalized SCZs, the area of the film-thickness-based SCZ and paste-rheology-based SCZ were able to reflect the control reliability of component content and paste rheology in SCC designing. On this basis, a robust mix design method of SCC was proposed by balancing the two ranges. The discussion on the extension of mix design framework to other types of SCC, industrial application, and reinforced structures demonstrated the framework’s broad applicability.

Development of an artificial neural network model to predict waste marble powder demand in eco‐efficient self‐compacting concrete

AbstractThe marble industry produces large amount of waste at almost every stage of marble processing. This waste is always uncontrollably discharged into open areas. Therefore, the consumption of Waste Marble Powder (WMP) in concrete is very important and will provide both an economic gain for concrete industries and an opportunity to achieve eco‐efficient concrete production. Self‐Compacting Concrete (SCC) is mostly preferred concrete type which uses the WMP as powdered material. Thus, to increase WMP usage in the production of eco‐efficient SCC, it is aimed in this study to develop a model that can predict WMP demand. To develop this model, Artificial Neural Network (ANN), an artificial intelligence method, was preferred. An ANN model was developed using a comprehensive dataset that included eco‐efficient SCC mixture compositions, workability measurements, and compressive strengths. The ANN model with seven inputs and one output as WMP was successfully trained and managed to produce the correct outputs to both validation and test datasets. Mix design of SCC with aimed properties can be a long process compared to conventional concrete. The proposed ANN model could reduce time loss in the production process. ANN's success is expected to facilitate the production of eco‐efficient SCC with WMP.

A review on the application of artificial intelligence in the mix design optimization and development of self-compacting concrete

Obtaining the strength-oriented mix design, balanced proportions of the additional constituents of Self Compacting Concrete (SCC) has remained a time-consuming, approximated, and repetitive work. In addition, the conventional evaluation methods have raised the challenges of accuracy and interpretation of the results, thereby limiting SCC applications. Nevertheless, in the past few years, researchers are working to overcome these challenges by incorporating the optimization methods and prediction models for the mix designing using artificial intelligence (AI) concepts and modern optimization methods, namely artificial neural network (ANN). This paper reviews the recent advances in integrating the AI methods to obtain mix design of the SCC ingredients and the strength prediction of the optimized mixtures. The review revealed that an appropriate AI-based optimization method could provide the optimum proportions of the varying constituents of SCC effectively and accurately. Moreover the AI-based methods supported the construction and utilization of the models to predict the strength and durability properties. On the other hand, the review highlighted the need to extend the AI concepts to automate the conventional testing methods of SCC mixes. The review also provides essential information about the innovative futuristic work required to refine the SCC mix design and performance further using AI methods.

The Role of Additives in Estimating Service Life of Self-Compacting Concrete Mix Design Using Fib Modeling

The Role of Additives in Estimating Service Life of Self-Compacting Concrete Mix Design Using Fib Modeling

Preventing plastic shrinkage cracking by monitoring the capillary pressure build-up in self-compacting concrete

Plastic shrinkage cracking is a problem for the service life, aesthetics and durability of concrete members. It occurs when tensile stresses are induced in fresh concrete, through plastic shrinkage that is restrained. Plastic shrinkage is caused by negative capillary pressure build-up, but the capillary pressure of fresh concrete can be controlled to prevent plastic shrinkage. In this paper, the control of capillary pressure to prevent plastic shrinkage cracking using high-capacity capillary pressure sensors is explored. The capillary pressure behaviour of a self-compacting concrete mix design in various evaporation rates was determined. Capillary pressure boundaries for concrete wetting to relieve tensile stresses were identified. The effectiveness of wetting fresh concrete at a predefined capillary pressure boundary was investigated.

Optimization of fresh and hardened properties of structural light weight self-compacting concrete mix design using response surface methodology

A response surface methodology (RSM) was employed to model and predict the fresh and hardened properties of powder type light weight self-compacting concrete (LWSCC) produced with coarse grained light expanded clay aggregates (LECA) as partial replacement of normal weight aggregates (NWA). Two mix design parameters were selected to derive mathematical-statistical models for predicting thirteen LWSCC properties. Volumetric ratio of LECA to total aggregates (LV/AV) of 40% to 60% and high range water reducing super-plasticizer (Sp) of 0.78 to 0.89% (by weight of cement) were utilized for designing and testing of fifteen LWSCC mixtures in which the contents of other mix constituents including cement, lime stone powder (LSP) and water were kept constant. Marsh-cone flow time of each respective paste was measured for determining the appropriate range of Sp dosage. The influence of mix design parameters on the responses were analyzed and discussed. Utilizing the derived models within the studied domains, the optimum parameters of LWSCC mixture satisfying the EFNARC criteria for vertical applications in structures with complex shapes and very congested reinforcements were obtained and verified with high statistical desirability.

Fracture properties of ternary blended fiber reinforced self-compacting concrete-A plastic viscosity approach

With the demand in the usage of Self-Compacting Concrete (SCC) there is a need to look into an alternate procedure of mix design to address the present practical issues. The existing standards of SCC mix design either underestimates or overestimates the materials used for the production of concrete which reduces the workability, durability and increases the cost. In the present study a mix design procedure which is based on the plastic viscosity of paste and target compressive strength of the SCC mix is being developed using a micromechanical procedure. Cement Replacement Materials like Slag and Fly ash are used for the present study in binary and ternary mix compositions. To address the issue of scarcity of river sand in India, Crushed Rock Fine is used a fine aggregate for the proposed mix design. To enhance the mechanical characteristics of SCC mixes, influence of varying fiber fraction is also studied for the Ternary SCC mixes. The volume fraction of fibers and aspect ratio of fibers are entered as an input into the programming tool to obtain combinations of SCC mixtures. Hooked end steel fibers with volume ranging from 0.1% to 0.5% are chosen for the experimental investigation. Results indicated that the compressive, split tensile and flexural strengths increased with the increase in fiber volume fraction but the fresh properties slump flow, T500 and J-ring spread, V-funnel and L-box decreased. Further, the study is extended in evaluating the fracture energy of Ternary SCC mixes with and without fibers. Fracture energy increased with the increase in fiber volume and post-peak responses are captured more accurately with the presence of fibers. The evaluated fracture energy will be useful for the analysis of cracked concrete structural components.

Analyzing the Filling Ability Property of Self-Compacting Concrete Using Fly Ash and Superplasticizer

Self-compacting concrete (SCC) is an innovative concrete which can flow and consolidate under its own weight without any vibration. It can also resist segregation. This kind of concrete is durable and environment friendly. Deformability and stability are also the major characteristics of self-compacting concrete. To achieve such properties, it is essential to develop a method for mix design of SCC. The cost of concrete can be minimized by substituting cement with material like fly ash. Properties of materials have effect on the flow behavior of SCC. Hence it is vital to determine the right quantities of material such that the concrete can flow without segregation. This paper presents an experimental course of actions for the investigation of filling ability property of self-compacting concrete. Nine trial mixes have been conducted in order to upgrade the flow value as well as flow time and the interaction between fine aggregate, coarse aggregate, cement, fly ash as well as superplasticizer has been closely observed. The high flowability is attained by exchanging cement with fly ash at different percentages along with varying superplasticizer content. Flowability is a means for a concrete’s filling ability which is determined in terms of spread of slump flow by using a slump flow test. The viscosity, measured indirectly by T500 test by visually observing the time required at which concrete spreads. Guidelines given by EFNARC are followed here.

Glass powder replacement in self-compacting concrete and its effect on rheological and mechanical properties

The effect of replacement of Portland cement using glass powder on fresh and mechanical properties of self-compacting concrete (SCC) was investigated in this study. A standard SCC mix design was used with substitution with either fly ash or glass powder of different fineness and replacement levels. Compressive strength, splitting tensile strength, and elastic modulus were measured at 7, 28, 90, 180, 365, and 545 days. Rheological testing found that SCC containing glass powder had consistently higher yield shear stress than the control despite testing being conducted at optimum slump flow levels. Replacement of Portland cement with glass powder was found to reduce strength performance in the shorter-term but longer-term strengths were comparable. Tensile strength and elastic modulus of SCC containing glass powder were consistent with design guidelines and can be reliably predicted from compressive strength as is typically used in structural design.

Improved Powder Equivalence Model for the Mix Design of Self‐Compacting Concrete with Fly Ash and Limestone Powder

The use of fly ash (FA) limestone and powder (LP) in combination with cement in concrete has several practical, ecological, and economic advantages by reducing carbon dioxide emissions, reducing the excessive consumption of natural resources, and contributing to a cleaner production of self‐compacting concrete (SCC). A mix design method for SCC based on paste rheological threshold theory can guide the SCC mix design by paste tests. This method can be visualized by the self‐compacting paste zone (SCP zone), a plane area where all the mix points meet the paste threshold theory, and SCC zone, a plane area consisting of all the mix points satisfying the criteria of qualified SCC. In the case of cement SCC, the SCP zone coheres with the SCC zone. However, in the case of the addition of FA or LP with different granulometry and shape characteristics from cement, experimental results indicate that the SCP zone is separated from the SCC zone. This work quantitatively studied the influence of FA and LP on the movement of the SCP zone by introducing the improved powder equivalence model. The improved model was obtained by powder equivalence coefficients calculated through the mortar test results with or without FA or LP, instead of SCC tests in the former method. The equivalence coefficients by volume of FA and LP are 0.55 and 0.79, respectively, which means that 1.82 unit volume of FA or 1.27 unit volume of LP is equivalent to one unit volume of cement. The improved powder equivalence model was verified by the successful preparation of SCC incorporating FA or LP simply and effectively. The equivalent SCP zone cohered better with the SCC zone than the former SCP zone, which could guide the quick mix design of SCC without SCC premix tests.

A Review on Mix Design of Self-Compacting Concrete

A Review on Mix Design of Self-Compacting Concrete

Simulation of self-compacting concrete properties containing silica quicksand using ANN models

Self-compacting concrete (SCC) mix designs exhibit complexities in their mechanical properties due to composite nature of the material and the multitude and variety of factors that affect such properties. In this paper, a set of SCC mix designs are made using silica quicksand (as filler) instead of rock powder with other required materials. The tests of fresh concrete such as the slump flow, J-ring, V-funnel, L-box tests and the hardened concrete tests are investigated and considered. The tests results are shown that, a high quality has been achieved for SCC mixture contains the quicksand and silica fume contents with low lubricant admixture dosage. The research is embodied the use of a branch of Artificial Neural Networks (ANN) as a quick and reliable alternative to such experimental testing. Results show that the ANN technique can perform as a satisfactory alternative to experimental testing to provide speedy prediction of optimum silica quicksand content must be added prior to SCC mix design. As such, proposed method for the SCC mix design are limited in scope and are approximate at best as they must rely on the results of experimental tests, which are both costly and time-consuming to perform.

Modeling the Fresh and Hardened Stage Properties of Self-Compacting Concrete using Random Kitchen Sink Algorithm

High performance concrete especially self compacting concrete (SCC) has got wide popularity in construction industry because of its ability to flow through congested reinforcement without segregation and bleeding. Even though European Federation of National Associations Representing for Concrete (EFNARC) guidelines are available for the mix design of SCC, large number of trials are required for obtaining an SCC mix with the desired engineering properties. The material and time requirement is more to conduct such large number of trials. The main objective of the study presented in this paper is to demonstrate use of regularized least square algorithm (RLS) along with random kitchen sink algorithm (RKS) to effectively predict the fresh and hardened stage properties of SCC. The database for testing and training the algorithm was prepared by conducting tests on 40 SCC mixes. Parametric variation in the SCC mixes were the quantities of fine and coarse aggregates, superplasticizer dosage, its family and water content. Out of 40 test results, 32 results were used for training and 8 set results were used for testing the algorithm. Modelling of both fresh state properties viz., flowing ability (Slump Flow), passing ability (J Ring), segregation resistance (V funnel at 5 min) as well as hardened stage property (compressive strength) of the SCC mix was carried out using RLS and RKS algorithm. Accuracy of the model was checked by comparing the predicted and measured values. The model could accurately predict the properties of the SCC within the experimental domain.