Paul O’Hanlon, R&D Project Manager, Holcim Innovation Center, France
Arnaud Delaplace, Senior R&D Expert, Holcim Innovation Center, France​

In addition to the mix design optimization, optimization of the production process can lead to a significant reduction of the carbon footprint of the precast industry. In this article, the authors demonstrate how digital solutions can be used to achieve this goal. This is achieved by modeling the binder hydration. Thanks to numerical analysis, the temperature evolution, the hydration rate can be computed for different scenarios, including heat treatment. Which allows the identification and selection of the most efficient solution with respect to environmental constraints.

The world is set to build a new New York City every month for now until 2050. Building faster and in a more sustainable manner are the biggest challenges of the construction industry today. A concerted effort is already being made in the reduction of the carbon footprint of construction materials. The authors believe that digital tools are a crucial factor in building a sustainable future!

The goal for this digital evolution is the real time adjustment in the production process. At present it’s challenging to make this happen in the readymix concrete industry with the limitations of existing plants. On the other hand, the precision, accuracy and more controlled environment means the precast industry can pave the way, by taking into account the variability of the curing environment (temperature, humidity) as well as the variability of the raw materials to optimize and make the curing protocol more sustainable.

Benefits of the Precast Industry

The precast concrete industry certainly has an important role in the decarbonization of the construction industry. Compared to typical site construction there are specific advantages which precast can offer:

• Better quality control over the whole production
• Negligible variation of the concrete design over time
• Controlled curing
• Accelerated construction phase on site
• No impact of the weather conditions

These advantages lead to a significant reduction in the carbon footprint during the construction phase. This reduction can be dramatically increased by using very-low CO2 concrete. Different recipes have already been proposed, but the smaller robustness of the mix design (i.e. a strict respect of the component dosages and especially the water content) makes it difficult to use them in most traditional readymix concrete plants. On the other hand, the precast industry offers precision and a high degree of quality control allowing the use of these new sustainable mixes. Which enables an easier approach to reduce the footprint of the current production by optimizing the whole process.

Hydration Control

One lever to achieve this level of sustainable optimization is to control the hydration kinetics of the binder, considering that the strength development is directly correlated to the hydration degree [1]. It is therefore important to be able to optimize the development of the hydration to fulfill the production process requirements. It can be achieved by selecting the right binders (strength, fineness, usage of secondary cementitious materials) and by applying the relevant curing [2].

This optimization process can be advantageously facilitated by using digital tools. At least two of them are already used: tagging systems, for example using RFID tags, allowing to track elements [3, 4]. Additionally, maturity, based on temperature probes, enables the user to obtain real time strength development, thanks to a calibration curve linking the temperature and strength.

Digital Thermal Modeling

In addition to these, Holcim has recently developed another one, based on a predictive model, useful for the optimization process: it’s a part of Holcim’s I-CONCrete solutions, a selection of digital tools for the construction industry (Fig. 1). The predictive models are based on physical considerations and allow users to compute the hydration degree for different environmental conditions.

The hydration degree is computed by solving the well known heat equation, in which the source term is the heat generated during the hydration of the binder. An Arrhenius law is chosen to take into account the dependence of the reaction rate with the temperature. Solving the heat equation is easy, by using numerous available softwares. For the I-CONCrete Thermal application, Holcim has selected a Finite Element solver, allowing the user to effortlessly model different geometries and different boundary conditions (Fig. 2). An important part of the process is the identification of the model parameters, representative of each binder and each water-binder ratio used in the concrete. Due to the variety of materials that can be used in a concrete, an experimental characterization at lab scale is still required to identify these parameters (Fig. 3). Some of them are easy to obtain, such as the density, but others need a specific insulated calibrated test [5, 6], like the hydration parameters.

Holcim’s I-CONCrete thermal tool covers all these different steps:

1. Experimental characterization at lab scale, based on a quasi-adiabatic test, to identify the thermal fingerprint of the binder
2. Development of the numerical model representative of the target concrete element.
3. Prediction of hydration degree for different environmental conditions, allowing to optimize the pouring and curing processes.

Precast Thermal Modeling Examples

Holcim’s I-CONCrete digital toolbox has already been used on various projects, for different applications. The accuracy of the model has been shown by comparing the predicted temperature to the one measured on a real structure (Fig. 4). Here the authors have selected a few of them as illustrative examples:

Optimization of the heat treatment

In the precast industry, heat curing is widely used to accelerate the hydration rate, and then the strength development. The plant manager has to optimize the process between the energy consumption of the heaters and the gain brought by the strength increase. Usually, the heating is characterized by a fixed power over a predefined time. In order to limit the environmental impact of the heating phase (and to decrease the spend associated with the always increasing energy cost), a stepwise heating evolution can be considered. In practice, it’s rarely the case due to the difficulty of selecting the best evolution in a production environment. The predictive model has a strong interest in that case: one can consider dozens of predefined heating scenarios, analyze the effect on the strength development and select the best one (Fig. 5). A saving of at least 10% can be achieved compared to a constant heat power delivery. Note that using an advanced optimization algorithm, the best theoretical heat evolution can be identified with respect to the production requirements.

Selection of the most suitable binder

In order to reduce the embodied carbon content of precast elements, the usage of secondary cementitious materials is more and more applied [7]. But the selection of these materials based on the available sourcing, their potential substitution rates lead to numerous solutions. The selection of the best one can become difficult if not impossible without a model. In this case, predictive models can also be extremely helpful. The principle is quite simple: it consists in making a characterization of the thermal fingerprint of each potential binder: a range of substitution rates, binary- or ternary- blended binders can be considered. Then, the predictive model can be used to compute the hydration rate of the different binders in the production environment, and the most suitable binder is then selected.

Differential heat treatment on large precast elements

This less common example demonstrates the wide offering of predictive models. For large precast elements, more than one heater can be used to accelerate the curing phase. For the sake of simplicity, the heat evolution is usually the same for all heaters. On the other hand if the precast element is made with thick and slender sections, the gradient of thermal strain can be obtained during the cooling phase: the thick parts have stored more heat than the thin ones, and the temperature decrease is slower than in these thin parts. Because the thermal strains are proportional to the temperature, a major difference can be obtained between thin and thick parts, leading to thermal cracks. To avoid these gradients, one can use different heat curing scenarios. These scenarios will depend on the geometry (thickness) of the different parts of the structure, and of the requirement of the production. Predictive numerical models to allow the user to compute the temperature at any point and any time in the precast elements, during the heating phase and during the cooling one (Fig. 6 and 7). Then, different scenarios of heating for the different element parts can be tested, and the one minimizing the temperature gradient all along the production can be identified. This approach has been successfully applied to precast elements, allowing to completely avoid further thermal cracks.

Conclusion

Through these three examples, the interest of digital tools for the precast industry is quite obvious. Benefiting from recent technical developments (wireless sensors, web services, cloud storage of data, etc), it becomes more and more easy to use these services. Thanks to the data collected by the sensors all along the supply chain, the heating evolution may be adjusted in real time in order to get the appropriate properties of the concrete and to obtain a more efficient production of precast elements. For sure, the constraints applied to the construction industry to reduce its carbon footprint, as in many other industries, will increase the usage of digital services. The authors believe that digital tools are a crucial factor in building a sustainable future!

References

[1] ASTM C1074-17, Standard Practice for Estimating Concrete
Strength by the Maturity Method - ASTM International, USA (2017).
[2] Bamforth, P. B., Control of cracking caused by restrained deformation
in concrete, CIRIA C760, London (2018).
[3] S. Maier, The fourth industrial (r)evolution, Concrete Plant International,
Vol. 1 (2016).
[4] T. Hess, Unequivocal Production Board Identification With RFID,
Concrete Plant International, Vol. 4 (2021).
[5] ASTM C186-17. Standard Test Method for Heat of Hydration
of Hydraulic Cement - ASTM International, USA (2017).
[6] EN 196-9. Methods of testing cement - Part 9: Heat of hydration –
Semi-adiabatic method (2010).
[7] A. Delaplace, D. Garcia, M. Bayle, Q. Favre-Victoire, Heat of hydration
of binary-, ternary-, quaternary-blended cements, Syner-
Crete’18 International Conference on Interdisciplinary Approaches
for Cement-based Materials and Structural Concrete (2018).