Traditionally, for conventional Portland concrete a limit of 3 days for curing, 7 days for rapid hardening, and 28 days for the development of the characteristic strength of the concrete is considered. Considering a tradeoff between the accuracy of a thermo-chemical-mechanical model that could analyze the concrete curing and the use of a wireless sensor network with motes supplied from batteries, the sampling period of temperature for the sensors was set as follows: four measurements every hour for the first three days. From day four, one measurement every hour until the seventh day. Between day 7 and day 28, one temperature measurement is performed every three hours. To save power consumption, several sensor readings are stored and sent together in the same message. This approach provides lower power consumption in the radio module, but the longer frames increase the error rate. Thus, a maximum of 128 bytes per frame was set. The estimation of power consumption, including a safety margin, determines a minimum battery capacity of 707 mAh. The average power consumption of each mote has been estimated using a Simulink model and considering each component separately. After the model, real world estimations have been taken into account, like battery discharge caused by temperature, loss of efficiency on components and non-linear effects such as communication issues. Therefore, the selected battery has a capacity of 1100 mAh.
4.1. Calibration and Testing
Once the DS18B20 sensor was chosen all efforts were devoted to checking the suitability of the protection based on lacquer and resin. The accuracy and linearity of the sensor were monitored, as well as the effect that the protection had on the accuracy. Nevertheless, the suitability of the package in
Figure 3 for the SHT21P sensor was also determined testing the ability of the acetal material and the poly propylene membrane to protect the sensor and also its effect on the measurement accuracy. This fact will allow evaluating the acetal material to be used to protect the wireless board in
Figure 2. First, the effect of the lacquer and resin on the sensor response was tested within a water container, since it allows simultaneously checking the sealing of the sensors and the accuracy, as shown in
Figure 7.
Figure 8a,b show the thermocouples, named TerEle and TerEst respectively, used as reference for the calibration. The sensor was found to work accurately when compared to the temperature readings of the thermocouples with PT100 probes, as shown in
Figure 9. Note that the sensor features a similar evolution to that of the references (0.99) with an offset of only 0.72 ± 0.5 °C. The results showed a proper operation without communication problems.
On the other hand, the transmission of each node was analyzed under different situations, especially considering the power of the output signal, which is a critical parameter taking into account the attenuation due to the concrete and the steel.
Figure 10 shows the mote and a FSIQ 3 spectrum analyzer (Rhode & Schwarz, Munich, Germany). The tests were carried out both open air and inside concrete.
A preliminary test was performed to verify the validity of the specifications on several specimens of concrete as shown in
Figure 11.
Figure 11a also shows the data acquisition board used to gather physical signals from several sensors. The aim of this test is to determine if the sensors can perform inside a concrete specimen in order to replicate, as closely as possible, the construction site conditions. The specimens are created using a steel mould and filled with concrete. This test allows determining the effect of the combination of formwork and concrete on the transmission of data. In addition, the test also examines the transmission distance of the sensors. The radio transmission was tested by an emission test at fixed intervals of a data frame. As expected, the effect of concrete, rebar and formwork reduced the transmission distance of the system. When the moulds were taken out of the specimens, the transmission distance doubled. The design has been optimized to achieve a percentage of packets successfully received above 95%. The data was transmitted since the first pouring of concrete for 28 days. These results are obtained for a transmission distance of approximately two meters. Results confirmed the feasibility of the proposed approach. There were no changes in the transmission of data in the early stages of concrete pouring when it is wetter.
A simple LabVIEW program was designed to interact with the sensors, logging the time, temperature readings and also from which sensor the data was received.
4.2. Construction Site
The designed motes and the wireless sensor network were introduced in a construction site. The place is located in a viaduct of the high-speed Antequera-Granada railway in the region of Andalucia, in the South of Spain.
The preliminary study of the location of the motes determined the use of the 869.4 MHz to 869.65 MHz band given by ETSI EN 300 220 and short-range device (SRD)of unspecified use, with a transmission power of 500 mW (+27 dBm). This need arises from the distances to be treated being around three meters, which are larger than the ones tested in the laboratory, and therefore the dynamic range should be increased. Thus, to reach the mentioned power level, it is necessary to include in the design an output power amplifier and a linear noise amplifier to improve the reception of signals.
Figure 12 depicts the construction, the dimensions in centimeters and the location of each sensor. It consists of a footing to support a shaft. The dimensions of the footing are 8 × 11 × 3 m. The placement of the sensors is performed in the middle plane 1.5 m above the base. This location was carefully chosen from experimental results.
For a distance of 1.5 m the motes can transmit from within the concrete to the outside, with a signal loss between 48 dBm and 64 dBm. Given an initial signal of −36 dBm and an error margin, it’s the maximum distance where a sniffer can receive packets in order to debug the deployment, considering a sensibility of −102 dBm. Eight points of measurement are taken, as indicated in
Figure 12b. The devices must be installed prior to pouring the concrete, and placed in preset positions using clamps or flanges to ensure that the measuring point corresponds to the one required. Each sensor is installed and tested individually by placing the antenna in different positions. Due to the nature of the test and the inability to repeat the process, several repeaters where included in the structure, to assure transmission of the values and to provide redundancy.
Figure 13a shows an operator testing a mote on the structure, and
Figure 13b shows a mote tied to a steel bar. For the wireless sensing node, a 4 mm thick acetal box has been used. The final dimensions of the prototype wireless node package are 85 mm width and length, and a height of 60 mm.
Figure 14 shows the ambient temperature profile since the first hours that the concrete is poured up to day 28, respectively. Note that the variations in temperature can reach almost 10 °C.
Figure 15 shows the temperature profile of the sensors located into the concrete. Note how the temperature of the concrete increased during the first hours due to the reaction between cement and water (hydration process). Once the temperature reaches a peak, then it starts to drop following the fluctuations of the ambient temperature. It can also be seen that the sensors 3 and 4 provide a slightly lower temperature, probably because they are located at the edges of the structure and the heat was dissipated away.
The higher temperatures inside the concrete structure did not affect the operation of the wireless sensor network, and measurements were gathered with the expected sensor accuracy, which is protected from impacts produced during the pouring process.
The applicability of the developed monitoring system in civil engineering is evident. For example, by considering a thermo-mechanical model of the hydration kinetics of the cement (see for example [
15]), the degree of hydration of the cement can be controlled by monitoring the evolution of the temperature with time. These experimental measurements provide useful information to validate the theoretical predictions and to check whether the hydration process inside the concrete bulk is developing correctly. Combining these measurements with those of the mechanical properties of concrete at early age and a convenient thermo-mechanical model of the structure (by using a finite elements model, for example) provides a powerful tool to determine the most convenient stripping time and, subsequently, the associated costs can be reduced.
Table 1 shows the results of the main mechanical parameters, such as the compressive strength (
fc), the Young’s modulus (
E) and splitting tensile strength (
fst) of the employed concrete at early age and at 28 days. These results were obtained in laboratory by means of standard tests on cubic and cylindrical concrete specimens [
19].
In order to confirm the reliability of the results, a thermo-chemical-mechanical finite element model (FEM) of the concrete footing has been implemented in ABAQUS. Details about the hydration kinetics modeling of the concrete employed in this analysis are given in [
15]. The composition of the concrete in this work was 1/0.43/2.31/3.07/2.57/0.009 (cement/water/sand/gravel/superplasticizer) with a class II Portland cement content of 325 kg/m
3. The concrete parameters necessary to perform the thermal analysis were a density of 2240 kg/m
3, a coefficient of thermal expansion of 10
−5 K
−1, a thermal conductivity of 2.5 W/mK, a specific heat of 922 J/kgK, a film coefficient between concrete-air of 9 W/m
2∙K and a room temperature of 18 °C. The behavior of the material was considered linear and elastic with a Young modulus ranging with age according to the values indicated in
Table 1.
Figure 16a shows the geometry and discretization employed in the FEM model for the concrete and the steel rebars, as well as a view of the internal profile of temperatures obtained for concrete at 7 days. In
Figure 16b the evolution of the temperature with age for the nodal points of the FEM model corresponding with the location of sensors 3 and 5 (
Figure 12b) are shown.
As observed from the results shown in
Figure 16b, the evolution of the temperature with age predicted by the numerical model is in good agreement with that measured by the sensors placed in the structure. Obviously, the values of the numerical prediction are not exactly the same than those obtained experimentally because of several factors, which are difficult to consider in the model. For example, variation of the room temperature between day and night was not considered, the film coefficient was estimated from literature [
19] and not experimentally obtained, and the temperature of the soil was also estimated, etc. However, the maximum values of the temperature given by the sensors, the age at which these values were obtained and the evolution of the concrete temperature after the peak value (cooling) are quite similar, which reflects the reliability of the experimental measurements.