• International Journal of Technology (IJTech)
  • Vol 12, No 3 (2021)

Normal Concrete Mix Design based on the Isoresponse of Slump as a Function of Specific Surface Area of Aggregate and Cement Paste-Aggregate Ratio

Normal Concrete Mix Design based on the Isoresponse of Slump as a Function of Specific Surface Area of Aggregate and Cement Paste-Aggregate Ratio

Title: Normal Concrete Mix Design based on the Isoresponse of Slump as a Function of Specific Surface Area of Aggregate and Cement Paste-Aggregate Ratio
Nabil Dhiya Ulhaq, Relly Andayani

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Ulhaq, N.D., Andayani, R. 2021. Normal Concrete Mix Design based on the Isoresponse of Slump as a Function of Specific Surface Area of Aggregate and Cement Paste-Aggregate Ratio. International Journal of Technology. Volume 12(3), pp. 495-505

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Nabil Dhiya Ulhaq Department of Civil Engineering, Faculty of Civil Engineering and Planning, Gunadarma University, Depok 16424, Indonesia
Relly Andayani Department of Civil Engineering, Faculty of Civil Engineering and Planning, Gunadarma University, Depok 16424, Indonesia
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Abstract
Normal Concrete Mix Design based on the Isoresponse of Slump as a Function of Specific Surface Area of Aggregate and Cement Paste-Aggregate Ratio

Many methods of normal concrete mix design produce the same proportion of cement and water content of concrete for different specific surface area of aggregate. Therefore, they often produce inappropriate workability of fresh concrete in the first batch. In the end, several trial batch adjustments are required by increasing or decreasing cement paste for reaching the required slump. This research aims to find out the correlation between specific surface area of aggregate and cement paste-aggregate ratio (C/A) to slump in a constant water-cement ratio (W/C) in normal concrete. This correlation will be used as an alternative method of normal concrete mix design. First, the new fine aggregate was established by modifying natural fine aggregate gradation. Then, two reference mixtures with these natural and modified fine aggregates were designed based on SNI 03-2834-2000. From each of these mixtures, the water content was added and reduced at multiple of 10 kg/m3 in a constant water-cement ratio until the measured slumps of samples had approached or reached 6 and 18 cm. Thus, different specific surface area of aggregate, cement paste-aggregate ratio, and slump could be known. Then, an isoresponse is developed to present the correlation between these variables. Finally, other mixtures are designed based on this isoresponse to validate it. The isoresponse is considered satisfactory if the measured slump of the validation mixtures does not deviate more than 2 cm of the required slump. The result shows that the measured slumps of validation mixtures had maximum deviations of 1 cm only. It means that the isoresponse of slump as a function of specific surface area of aggregate and cement paste-aggregate ratio can be used to predict the slump of a mixture and also as an alternative method of normal concrete mix design.

Cement paste-aggregate ratio; Isoresponse; Normal concrete mix design; Slump; Specific surface area of aggregate

Introduction

        Concrete is a favoured building material due to its ease of production and use (Han et al., 2016). Along with the increasing use of concrete as a building material, concrete improvement was also carried out by researchers in the past few years. One way to improve concrete mixtures is to do experimental research about the possibility of using other concrete constituents as additives or substitutions. For example, Yadav et al. (2018) that have conducted research on high range replacement of normal aggregates with recycled aggregates. Likewise, Eddhie (2017) developed mathematical equations that account for the relationship between the content of nanosilica and the mechanical properties of concrete so it can be applied to any concrete mixture.  The improvement of concrete mixtures can also be done by finding the influence of various variables and their correlation that affect the properties of fresh and hardened concrete.

Amini et al. (2019) have investigated the relationship between paste ingredients for achieving an optimum paste-to-void volume ratio to meet given performance requirements. Curing as a variable that affects the properties of concrete has also been taken to the next level, Nie et al. (2016) explored the internal curing as a way of overcoming the disadvantages associated with heat curing and for improving the performance of heat-cured concrete. Another way to improve concrete mixtures is by developing optimum proportioning of concrete. In this case, the new method of concrete mixtures design can also be developed. Yeh (2007) applied analytical methods by using Computer-Aided Design system to search for the optimum mixture of concrete composition. Moreover, Yong et al. (2018) have developed a new method of high-performance concrete mixture design based on the 4-parameters compressible packing model of Packing Density Theory. Ahmad and Alghamdi (2014) also conducted a statistical analysis of experimental data and developed mathematical polynomials regression to obtain an approach in the optimum proportioning of concrete mixtures. Actually, there is a possibility that there are other ways to improve the concrete mixtures besides those already mentioned. The point is how this concrete mixtures improvement produces concrete that is more satisfying. One factor that shows concrete satisfaction is workability and it can be influenced by many variables such as the specific surface area of aggregate.

ACI (2008) 238.1R-08 explains that the specific surface area of aggregate is a derivative of the factors that affect the workability of concrete. Hughes (1973) explained that the specific surface area of aggregate can represent the gradation of an aggregate as a single numerical value or commonly known as grading modulus. It can be calculated by simplifying the specific surface area of aggregate as the surface area per unit volume of spheres which pass the same sieve sizes as the actual aggregate. Moreover, other methods for quantifying the specific surface area of aggregate have developed in recent studies, such as using imaging techniques, developed mathematical models, Brunauer-Emmett-Teller model, etc. (Rabbani et al., 2014; Panda et al., 2016; Zhang and Luo, 2018). Tattersall (1991) explains that specific surface area of aggregate is the ratio of the total surface area to the total mass or volume, and is measured in m2/kg or m2/m3. In concrete, this means that the area of surface to be coated and lubricated by finer particles and by cement paste is greater and thus, other things being equal, it would be expected that the finer the fine aggregate, the less workable the concrete.

However, there are many mix design standard methods that do not accommodate specific surface area of aggregate as a variable that influence concrete. SNI 03-2834-2000 and IS 10262:2009 as standard methods in concrete mix design in Indonesia and India classify fine aggregate gradations into four grading zones. Moreover, the results of mix design will produce the same proportion of water and cement content for specific grading zone and required slump. However actually, all fine aggregates classified into the same grading zone can have specific surface areas of aggregate that are very different from each other. In British method which was presented by Teychenné et al. (1997), the proportion of fine aggregate is determined based on the percentage of fine aggregate that passes 600 µm sieve. In fact, even though there are two fine aggregates with the same percentage of 600 µm of sieve passing, they likely have very different specific surface areas of aggregate. In ACI (2002) 211.1-91, the fineness modulus of fine aggregate determines the proportion of coarse and fine aggregates in a mixture. However, the fineness modulus actually cannot describe the specific surface area of aggregate. In this case, it is possible for two fine aggregates to have the same fineness modulus but actually, they have different specific surface areas of aggregate. Likewise, for SNI 7656:2012 which is an adoption of ACI (2002) 211.1-91 and is the most recent standard method in concrete mix design in Indonesia. In the end, concrete mixtures that were designed using those standard methods require several trial batch adjustments by increasing or decreasing cement paste for reaching the required slump.

        In the present study, the effort has been made by changing the value of cement paste-aggregate ratio (C/A) of concrete mixtures. These changes will affect the value of the specific surface area of aggregate and slump of concrete mixtures. Thus, the correlation between specific surface area of aggregate, cement paste-aggregate ratio, and slump can be presented in the form of an isoresponse, or what can be known as a contour plot. Sonebi (2004) has also used isoresponse to present the relationship of several variables in concrete, such as W/C, cement content, slump flow, fluidity loss, compressive strength, et cetera. This is because isoresponse is very easy to present relationships between three or more variables in one form. Finally, from the isoresponse developed in this study, it is expected that the measured slump of a concrete mixture can be predicted. Furthermore, this isoresponse is also expected to be used as a new method of normal concrete mix design.

Conclusion

    Based on the experimental results in this study, the following conclusions have been drawn: (1) Indeed there is a correlation between specific surface area of aggregate and cement paste-aggregate ratio to slump which can be presented in an isoresponse. The greater the specific surface area of aggregate, the slump value will be smaller. Otherwise, the greater the cement paste-aggregate ratio, the slump value will be even greater; (2) From that correlation, a new alternative method of mix design has been developed. The advantage of this new alternative method is that a mixture of concrete with specific slump values can be designed. In contrast to the British Standard and Indonesian Standard methods which classify required slump in four ranges, which will complicate when designing concrete mixtures with slump values that are more specific; (3) In addition, a new method for predicting slump values of a concrete mixture also has been developed using that correlation. This method is a new thing because only by looking at the proportion of concrete materials and aggregate gradations, the slump value of the concrete mixture can be predicted without mixing the concrete and testing the slump before; (4) Improvements are still needed on these methods, it is recommended to examine variations in W/C or other variables that can affect slump or other variables that can affect slump.

References

ACI Committee 211, 2002. Standard Practice for Selecting Proportions for Normal, Heavyweight, and Mass Concrete (ACI 211.1-91 Reapproved 2002). American Concrete Institute, Farmington Hills, Michigan, USA

ACI Committee 238, 2008. Report on Measurements of Workability and Rheology of Fresh Concrete (ACI 238.1R-08). American Concrete Institute, Farmington Hills, Michigan, USA

Ahmad, S., Alghamdi, S.A., 2014. A Statistical Approach to Optimizing Concrete Mixture Design. The Scientific World Journal, Volume 2014, pp. 17

Amini, K., Vosoughi, P., Ceylan, H., Taylor, P., 2019. Effect of Mixture Proportions on Concrete Performance. Construction and Building Materials, Volume 212, pp. 77–84

Cement and Concrete Sectional Committee, 2009. Concrete Mix Proportioning Guidelines
(IS 10262:2009). Bureau of Indian Standards, New Delhi, India

Cement and Concrete Sectional Committee, 2016. Coarse And Fine Aggregate for Concrete Specification (IS 383:2016). Bureau of Indian Standards, New Delhi, India

Eddhie, J., 2017. Strength Development of High-Performance Concrete using Nanosilica. International Journal of Technology. Volume 8(4), pp. 728-736

Han, A., Gan, B.S., Pratama, M.M.A., 2016. Effects of Graded Concrete on Compressive Strengths. International Journal of Technology, Volume 7(5), pp. 732-740

Hughes, B.P., 1973. The Vebe Test and the Effect of Aggregate and Cement Properties on Concrete Workability. In: Fresh Concrete: Important Properties and Their Measurement: Proceedings of a RILEM Seminar, Leeds, England, 22–24 March 1973, Volume 2, pp. 4.3-1–4.3-12

Nie, S., Hu, S., Wang, F., Yuan, P., Zhu, Y., Ye, J., Liu, Y., 2016. Internal curing A suitable method for improving the performance of heat-cured concrete. Construction and Building Materials, Volume 122, pp. 294–301

Panda, R.P., Das, S.S., Sahoo, P.K., 2016. An Empirical Method for Estimating Surface Area of Aggregates in Hot Mix Asphalt. Journal of Traffic and Transportation Engineering, Volume 3(2), pp. 127–136

Panitia Teknis Bahan Konstruksi Bangunan dan Rekayasa Sipil, 2012. Tata Cara Pemilihan Campuran untuk Beton Normal, Beton Berat dan Beton Massa (Standard Practice for Selecting Proportion for Normal, Heavyweight, and Mass Concrete) (SNI 7656:2012). Badan Standardisasi Nasional, Jakarta, Indonesia

Pusat Penelitian dan Pengembangan Teknologi Permukiman, 2000. Tata Cara Pembuatan Rencana Campuran Beton Normal (Standard Practice for Making Normal Concrete Mix Design) (SNI 03-2834-2000). Badan Standardisasi Nasional, Jakarta, Indonesia

Rabbani, A., Jamshidi, S., Salehi, S., 2014. Determination of Specific Surface of Rock Grains by 2D Imaging. Journal of Geological Research, Volume 2014, pp. 1–7

Sonebi, M., 2004. Applications of Statistical Models in Proportioning Medium-Strength Self-Compacting Concrete. ACI Materials Journal, Volume 101(5), pp. 339–346

Tattersall, G.H., 1991. Workability and Quality Control of Concrete. E&FN Spon, London, England

Teychenné, D.C., Nicholls, J.C., Franklin, R.E., Hobbs, D.W., 1997. Design of Normal Concrete Mixes Second Edition. Building Research Establishment, Watford, England

Yadav, N., Deo, S.V., Ramtekkar, G.D., 2018. Workable and Robust Concrete using High Volume Construction and Demolition Waste in Sub Tropical Climate. International Journal of Technology, Volume 9(3), pp. 537–548

Yeh, I.C., 2007. Computer-Aided Design for Optimum Concrete Mixtures. Cement & Concrete Composites, Volume 29, pp. 193–202

Yong, S., Zonglin, W., Qingfei, G., Chenguang, L., 2018. A New Mixture Design Methodology Based on the Packing Density Theory for High Performance Concrete in Bridge Engineering. Construction and Building Materials, Volume 182, pp. 80–93

Zhang, D., Luo, R., 2019. Modifying the BET Model for Accurately Determining Specific Surface Area and Surface Energy Components of Aggregates. Construction and Building Materials, Volume 175, pp. 653–663