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Concrete mixing monitoring by image analysis applied to recycled aggregate concrete
J. Moreno-Juez1, 2, R. Artoni1, B. Cazacliu1, E. Khoury1. 1
IFSTTAR, Aggregates and Material Processing Laboratory, Route de Bouaye – CS4, 44344 Bouguenais Cedex, Nantes, France
2
TECNALIA, Parque Tecnológico de Bizkaia, 28160 Derio, Spain
Abstract
The improvement of inline mixer measurements is imposed in a growing concrete industry employing increasingly complex manufacturing processes and materials. Improper mixing, water content estimation and fresh properties control are one of the most important concerns of concrete manufacturers. These problems have increased in recent decades due to the expansion of new materials like Recycled Aggregates Concretes (RAC) employing very heterogeneous materials making the mixing and properties control very complex. An inline image analysis technique applied to the monitoring of concrete mixing has been then developed to try to address this problem. This technique is based on the evolution of the texture of pictures taken at the surface of the mixing bed. The method is used to study the evolution of the paste during processing in laboratory and industrial scale mixers. The evolution of the texture allows obtaining important information on the evolution of the different formulations during mixing.
Thanks to this simple monitoring of the mixing evolution, the study of the different parameters affecting the mixing time is easily conducted. In this work, the effect of the water-to-powder ratio, the constituent’s temperature and the kind of aggregate employed (natural or recycled) on the mixing time and on the final fresh properties has been quantified. The differences in water dosage between a RAC and a standard concrete can also be estimated to design more precise formulations.
Keywords: Concrete mixing monitoring, Recycling technologies, Recycled Aggregate Concrete (RAC), Image analysis, Online water content estimation.
Introduction
The future of concrete targets the growth of recycled aggregate concretes (RAC). These materials usually require better control of the properties during the manufacturing phase, which we are not able to provide satisfactorily today. This production is often hampered by the lack of technical confidence in the practical use. especially with regard to the high porosity of the Recycled Concrete Aggregates RCA particles which alters the aggregate water absorption and density [1]. During the mixing process, this bad control of water absorption has a direct and adverse impact in the water to powder ratio control. The theoretical water content in concrete and the initial expected formulation can suffer important variations during the practical mixing process. These variation are caused by multiple factors like the material heterogeneity, its initial moisture content the moisture characterisation technique, or by the mixing process [1,2].
In this context a good reliable technique to monitor and characterize these mixtures in real time with is imposed. An inline image analysis technique has been then developed [3]. This technique is based on the evolution of the texture of pictures taken at the surface of the mixing bed. The evolution of the texture allows obtaining important information on the
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evolution of a concrete during mixing; and allows identifying with a good repeatability the main characteristic points of the mixture evolution, the cohesion time and fluidity time (tc and tf) explained by authors [4] (see Figure 1).
A direct innovative application is the estimation of the water content in RAC from a homologous reference Natural Aggregate Concrete. We will see that a RAC does not lead to the same consistency than his homologous NAC containing the same effective water. The differences in water dosage can therefore be estimated to design more precise formulations.
Figure 1. Inline image analysis technique applied to the monitoring of concrete mixing (from [3]).
Experimental method
1. Materials and equipment
The technique has been developed, improved and validated in a 5 liters intensive laboratory pan mixer (Eirich Gmbh) with a standard mortar and concrete employing natural aggregates NA. For this first part of experiments the materials employed where cement CEMI 52.5, polycarboxylates superplasticizer SP (ChrysoFluid® Optima 352 EMx), calcium carbonate filler (Betocarb), natural 0/4 silico-calcareous sand and a natural 4/10 siliceous crushed aggregate. The same materials where employed in a second part to study the effect of RCA. RCA 6/10 with different initial moisture states (dry and saturated) are employed in addition to the materials previously mentioned. The different mixture formulation and temperatures are presented in Table1.
Table 1. Formulation of the mixtures studied. Mixture Type W/P Ratio Temp. (°C) Initial moisture of coarse aggregates Coarse aggregate 4/10 Kg/m3 Sand Kg/m3 Cement Kg/m3 Filler Kg/m3 SP Kg/m3 Effective Water (W) Kg/m3 Mortar 0.26 to 0.29 5; 25; 45 - - 1269 to 1245 533 to 523 254 to 249 16.5 to 16.2 205.7 to 220.4 NA Concrete 0.26 to 0.29 5; 25; 45 Dry 422 to 415 1054 to 1037 443 to 436 211 to 208 13.7 to 13.5 169.4 to 182.3 Mortar* 0.31 to 0.38 25 - - 1338 455 227 14 201 to 251 NA 0.31 25 Dry 862 882 300 150 9 139 to
61 Concrete* to 0.38 171 RCA Concrete* 0.31 to 0.38 25 Dry and saturated 758 to 995 882 300 150 9 130 to 204 * Formulations from Eliane Khoury PhD thesis.
2. Experimental method
Batches were carried out on the given mixtures (Table 1). The solids materials were loaded before starting the mixer. Pictures were recorded without interruption for the entire mixing process. After mixing the dry constituents for 60 seconds to ensure homogenization of dry materials, the water and HRWR were added with a constant flow rate during 20 seconds and the complete mixture was mixed for 300 seconds after the end of liquid addition.
3. Image analysis technique
The image signal was obtained using a digital GoPro camera and controlled lightning conditions. The camera was placed on the top of the vessel to take pictures of the sample surface (Figure 1).
The image analysis technique used in this paper is described by the authors [3], being an adaptation of that developed by Nalesso et al. [5] for wet granulation in pharmaceutical industry. The tool employed for our application is the histogram image analysis. The gray level histogram of a picture characterizes the relative frequency of each gray-scale level in an image. From the histogram, we can understand the gray-level distribution and detect the image contrast. The texture index of the image, which we use throughout this work, is simply the standard deviation of the grey level histogram. For example, a smooth and homogeneous bed surface means a low image contrast and therefore a low texture level. Conversely, a more rough and uneven bed surface is characterized by a high image contrast due to the presence of shadows and therefore a high texture level.
Results and Discussions
The image analysis technique is employed in a first time to estimate the impact of water to powder (cement + filler) ratio W/P in a mortar and concrete (with natural materials) mixing evolution.
Once this technique improved and well developed, it was employed in more complex applications like the estimation of the mixing temperature in mixing times or the quantification of the water content in recycled aggregate concretes made with different initial moisture RCA.
1. Effect of the water to powder ratio and temperature
Both mortar and concrete mixtures followed the same general trend (Figure2), i.e. higher the water content shorter the transition times. In other words, the mixing time decreased with the water. This fact does not bring anything new, what is interesting is that we can base on these curves to quantify the water content of an unknown water to powder formulation during an early stage of the mixing process and correct this parameter if possible.
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Figure 2. Cohesion and Fluidity times as a function of the water to powder ratio.
We can also observe that water demanded by the concrete mixture exceed the water demanded by mortar for a same mixing time. This excess roughly corresponded to 0.23% of dry coarse aggregates mass (see the aggregates proportions in Table 1). We estimate this value as the water involved in the wall effect exerted by a coarse grain on a fine grain packing. Ben-Aïm (1970) postulated the existence of a strong disruptive effect on the packing of particles around the coarse grain in which a perturbed volume is entrapped and then not available as effective water. We can then estimate the real effective water necessary in our formulation depending on the aggregates size, form or properties. We can on the other hand estimate the excess or lack of water in a given formulation.
This technique can be also employed to estimate the impact of mixing temperature on the mixing times and the concrete fresh properties. When the temperature increases, the mixing times decreases (Figure 3).
Figure 3. Cohesion and Fluidity times as a function of mixing temperature.
This application is interesting to adapt mixing times and mixing process to the weather conditions during production.
2. Effect of recycled concrete aggregate
Finally, this technique can be applied to estimate the water content and the fresh properties of concretes made with RCA. The employment of the same effective water for concretes with initial dry RCA, initial saturated RCA and natural aggregates (NA) does not lead to the same mixing evolution (Figure 4). The fluidity times are different for a same W/P which means that the concrete fresh properties are different [3]. With this technique, we can easily estimate in real time by observing the mixing evolution, the difference in concrete water content (W) caused by different kind of aggregates and different initial moistures states. A better
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formulation and a better online control during manufacturing of our RAC can therefore be made.
Figure 4. Fluidity time evolution with water to powder ratio for equivalent concretes produced with
different aggregates.
Conclusions
The image analysis technique proves to be a simple and reliable tool for monitoring and control the mixing concrete process. The technique allows us to detect different transition points, characteristics of each mixture which indicate the progress of the mixing process. With these characteristics points we can quantify the effect of different parameters on the mixing evolution and on the mixture fresh properties. On the other hand, if we have a well calibrated mixture we can estimate in real time the water content, the kind of aggregates, the mixing temperature or the aggregates absorption. Well developed, this tool proves to be very powerful and effective in controlling concretes properties. A real time characterisation of water absorption or water release during mixing new RAC is then expected with the consequent advantages that this entails.
References
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[2] M. Quattrone, B. Cazacliu, S.C. Angulo, E. Hamard, A. Cothenet, Measuring the water absorption of recycled aggregates, what is the best practice for concrete production?, Constr. Build. Mater. 123 (2016) 690–703.
[3] J. Moreno Juez, R. Artoni, B. Cazacliu, Monitoring of concrete mixing evolution using image analysis Article, Powder Technol. 305 (2017) 477–487.
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[4] B. Cazacliu, N. Roquet, Concrete mixing kinetics by means of power measurement, Cem. Concr. Res. 39 (2009) 182–194. doi:10.1016/j.cemconres.2008.12.005. [5] S. Nalesso, C. Codemo, E. Franceschinis, N. Realdon, R. Artoni, A.C. Santomaso,
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