*3.1. Experimental Program*

A reinforced concrete block was cut from the reactor facility with a length, width, and depth of 7 feet 4 inches, 3 feet, and 3 feet 4 inches, respectively. An accelerated corrosion test was conducted to corrode three different areas over the course of this study. Three concrete cores were drilled (3 inches in diameter and 9 inches in length) at three locations to create different concrete cover thickness for three vertical steel reinforcing bars adjacent to the cores (Figure 15). During the coring process, a transverse reinforcing bar was unavoidably cut at a depth of approximately 6 inches from the surface of the concrete test block specimen.

The test was initiated by placing 3% NaCl solution in the drilled holes to a depth of 3 inches on 2 December 2014. The solution was maintained in the drilled holes for two months to ensure that chloride concentration reached a needed level for corrosion initiation [29,30]. Wet/dry cycles were then initiated (three days wet and four days dry) on 19 February 2015 to accelerate the corrosion process. A galvanic cell was created during the wet days by inserting a copper plate in the cored locations. Figure 15d shows the 'as measured' concrete cover after the cores were drilled.

The first location has a concrete cover of 0.25 inches and was monitored using three broadband sensors (WDI) and one resonant sensor (R15I) while the second location has a cover of 1.0 inch and was monitored using four resonant sensors (R6I). The third location has a cover of 0.125 inches and was monitored using eight resonant sensors (R6I). On 22 May 2015 one of the sensors at the 1.0 inch cover location was removed from the test block and, on 27 May 2015, it was placed on a small concrete specimen (control specimen) with dimensions of 3.0 inches × 3.0 inches × 11.25 inches. The control specimen is not reinforced and, therefore, is known not to have corrosion activity. Data collected from the control specimen was used to verify the efficiency of the data filters developed during the course of the project. Acoustic emission activity was recorded continuously throughout the test period.

Half-cell potential (HCP) and linear polarization resistance (LPR) measurements were recorded once a week with the objective of providing insight related to the corrosion process of targeted reinforcement locations. HCP method is described in ASTM C876 [31] and is traditionally employed to determine the likelihood of corrosion activity, which is described in Table 3. Linear polarization resistance (LPR) is a method used to measure polarization resistance (*Rp*), which can be used to calculate corrosion current (*Icorr*) and corrosion current density (*icorr*). These parameters can be used to estimate the corrosion rate (*CR*). Figure 16 shows a schematic of the test setup and acoustic emission sensor layout to monitor the corrosion process of the reinforcing bars. A schematic of the aged concrete block control specimen is also shown in this figure.


**Table 3.** ASTM corrosion for Cu-CuSO4 reference electrode [31].

**Figure 15.** Aged concrete block specimen: (**a**) Left side view, (**b**) front view, (**c**) right side view, (**d**) top view, and (**e**) control location.

**Figure 16.** Schematic of aged reactor concrete test block: (**a**) Left side view, (**b**) front view, (**c**) right side view, (**d**) top view, and (**e**) control location.

#### *3.2. Results and Discussion*

#### 3.2.1. Electrochemical Measurements

Initial electrochemical measurements known as the half-cell potential were taken prior to the initiation of the conditioning period. These measurements indicated a passive state of steel reinforcement. The NaCl solution was then placed in the cored areas on 2 December 2015 and electrochemical readings were recorded weekly thereafter. As shown in Figure 17, three weeks after conditioning, half-cell potential values were observed to be more negative than −350 mV (referred to as the corrosion threshold) at all three locations. At the conclusion of the wet/dry cycles, half-cell potential readings indicated high corrosion risk in one of the three locations (0.25 inch cover location) and severe corrosion damage (more negative than −500 mV) in the other two locations (0.125 inch and 1.0 inch cover locations). The 1.0 inch cover location is known to have leakage associated with it since the NaCl solution drained continuously from this location from the commencement of the testing. While chloride diffusion is often assumed to be the primary initiator of corrosion damage, the presence of cracking in the concrete matrix may have a more profound effect on corrosion in some instances. The 0.125 inch cover and the 0.25 inch cover locations did not experience similar issues with leakage. The bottom of the hole at the 1.0 inch cover location was sealed with epoxy in the first week of April in 2015.

Figure 18 shows linear polarization resistance results at the three locations with a logarithmic fit of the data points. The x-axis in Figure 18 represents the number of days after the solution was placed in the cored areas (initiated on 2 December 2014). The results indicate that all locations had relatively high corrosion rates since the polarization resistance was less than 100 ohms [4]. As seen in the figure, data was not collected between 24 December 2014 and 19 February 2015 (between 22 and 79 days) due to a malfunction with the potentiostat/galvanostat cable over that time period. This was addressed and the testing was resumed after 29 February, 2015. Since these readings are taken weekly over a time span of 300 days and due to the instantaneous nature of the readings, trends in the data set are more important than readings taken on a particular day. Therefore, trend lines with both upper and lower estimates are shown in the figures. A statistical method was used to eliminate outliers with low values to obtain the upper estimate and eliminate outliers with high values to obtain the lower estimate.

#### 3.2.2. Detection of Damage Using Acoustic Emission

Figure 19 shows the acoustic emission activity, in terms of amplitude versus time, recorded at locations monitored with resonant sensors (the 1.0 inch concrete cover location, the 0.125 inch concrete cover location, and the control location which was initiated on 27 May 2015). Figure 20 shows the acoustic emission activity recorded using broadband sensors at the 0.25 inch concrete cover location. The data shown in Figures 19 and 20 was filtered using the data filters discussed in Table 2. An unusual amount of data that had characteristics related to electromagnetic interference was continually collected at the control location potentially due to damage in the sensor or cable during the removal and re-installation process. RMS and Duration data rejection limits were developed and were able to delete the majority of the false data without affecting data collected from other locations.

As seen in Figures 19 and 20, acoustic emission activity at the 1.0 inch concrete cover location and the 0.125 inch concrete cover location was higher than the acoustic emission activity at the 0.25 inch concrete cover location. This is attributed to the inherently higher sensitivity of the resonant sensors. It is noted that the rate of activity recorded at 1.0 inch concrete cover locations decreased during wet days after sealing the bottom of the hole.

To reduce the possibility of contaminating the acoustic emission data set with unrelated data generated from ongoing work in the University of South Carolina Structures and Materials Laboratory, the acoustic emission data acquisition system was intentionally paused on several occasions. Significant pauses in data acquisition are shown in the figures. A video camera monitoring the system was utilized

to cross-verify and to aid in the development of data filters that are specific to ongoing work in the laboratory environment.

**Figure 17.** Half-cell potential measurements at: (**a**) 0.25-inch concrete cover location, (**b**) 1.0-inch concrete cover location, and (**c**) 0.125-inch concrete cover locations.

**Figure 18.** Linear polarization resistance (LPR) measurements at: (**a**) 0.25-inch concrete cover location, (**b**) 1.0-inch concrete cover location, and (**c**) 0.125-inch concrete cover location.

**Figure 19.** AE data recorded from resonant sensors on the reactor concrete block specimen: (**a**) 1.0-inch concrete cover location, (**b**) 0.125-inch concrete cover location, and (**c**) control location.

**Figure 20.** AE data recorded from broadband sensors on the reactor concrete block specimen at the 0.25-inch concrete cover location.

Figure 21 shows cumulative signal strength versus time at locations monitored using resonant sensors. It can be seen from this figure that cumulative signal strength increases rapidly at the beginning of the test, which corresponds to a period of rapid damage growth associated with corrosion initiation, enters a dormant period, and then increases slightly near the end of the testing period for the 1.0 inch and 0.125 inch locations. This trend in the data mirrors a trend noticed in the linear polarization resistance plots. The magnitude of the cumulative signal strength is greater for the 1.0-inch location when compared to the 0.125-inch location, which indicates increased acoustic emission activity and, therefore, increased damage growth at the 1.0-inch location. This is consistent with the electrochemical readings at this location and may be attributable to the presence of cracking in this location. The control location has minimal cumulative signal strength magnitude as would be expected. The relatively low cumulative signal strength magnitude at the control location demonstrates that unwanted acoustic emission data caused by ongoing laboratory activities in the vicinity of the test block specimen were minimized in the data sets.

The broadband sensor data shows a similar trend of rapidly increasing damage early in the testing period, which is followed by a relatively dormant period at the 0.25 inch location. This is shown in Figure 22. The magnitude of cumulative signal strength from the broadband sensors is lower in comparison to the resonant sensors, which is expected due to the lower sensitivity of the broadband sensors.

**Figure 21.** Cumulative signal strength from resonant sensors on the aged concrete block specimen.

**Figure 22.** Cumulative signal strength versus time from broadband sensors on the aged concrete block specimen.

Figures 23 and 24 show the Intensity Analysis results calculated at each location. The estimation of initial damage for the aged concrete block specimen based on visual inspection and electrochemical results was located near the border between the 'no damage' region and the 'depassivation' region of the chart. For the control location, a lower initial damage state was used since no corrosion damage is expected in this specimen. AE activity from the resonant sensors at the 1.0-inch concrete cover location progressed from the initial state to the severe damage zone over the duration of the monitoring period. AE activity from the resonant sensors at the 0.125-inchconcrete cover location progressed from the initial state to the border of the cracking and severe damage zones. For the broadband sensors at the 0.25-inch concrete cover location, acoustic emission activity progressed from the initial state to the border of the cracking and severe damage zones.

**Figure 23.** Intensity Analysis for resonant sensors on the reactor concrete block specimen.

**Figure 24.** Intensity Analysis for broadband sensors on the reactor concrete block specimen.

The above results are indicative of cracking in the concrete matrix due to corrosion activity at all three locations. As with the electrochemical measurements, the acoustic emission activity indicated that the most severe damage occurred at the 1.0-inch concrete cover location. As mentioned above, this location is affected by cracking as noticed through leakage of the NaCl solution at this location. While many degradation models for reinforced concrete are based on diffusion and, therefore, do not directly address the presence of cracking in the matrix. The effect of cracking in the matrix may, nonetheless, be significant. Similarly, many models assume a homogeneous concrete matrix. The lack of homogeneity in the concrete matrix for actual structures such as the concrete test block may also play a significant role in the results.

#### **4. Summary and Conclusions**

This investigation explores the implementation of acoustic emission monitoring as a remote structural assessment method. Acoustic emission systems were used to monitor corrosion damage and cracking in a decommissioned nuclear reactor facility as well as to monitor corrosion damage in a concrete block cut from the nuclear facility in laboratory conditions. The monitoring period in this study extended to approximately one year.

The study showed that long-term remote monitoring of ongoing damage in large scale existing structures is feasible using acoustic emission systems. For the wired system, AC power and cellular network connection are required for successful operation of the system. No major issues were encountered in terms of electromagnetic interference with the sensors, external noise and remote monitoring, and data transfer. The wireless system used has the potential to be used with solar power paired with cellular connections for the remote monitoring, which makes this approach well suited for long-term monitoring efforts. However, adequate protection to the electrical components is required especially in humid environments, which is illustrated by the failure of the data acquisition laptop due to moisture damage.

For the Reactor Building 105-C Crane Maintenance Area, the acoustic emission activity recorded at the 'vertical column to roof interface location' and 'horizontal beam location' varied throughout the monitoring period and tended to be associated with seasonal temperature fluctuations. The acoustic emission activity recorded at the 'control location' was significantly less when compared to the activity from the other two locations. Intensity Analysis was used to quantify the damage progression over the course of the monitoring period for both the broadband and resonant sensor types. The results of this method were in agreement with visually observed distress in the monitored locations. The assessed condition of the actively corroding areas progressed from the assumed condition of 'no corrosion/approaching depassivation' to 'severe damage' over the monitoring period while no change

was observed in the state of the control location. It is noted that the assessed condition based on Intensity Analysis progressed to 'cracking/severe damage' within the first two months of monitoring. This shows the feasibility of this technique to successfully qualify active corrosion damage in structures in relatively small monitoring periods.

For the Reactor Building 105-C +48 level, the acoustic emission activity at the +48 location also varied with seasonal temperature fluctuations. This area contained a vertical crack in the exterior wall and it is possible that crack growth or friction between surfaces of this crack was the cause of much of the acoustic emission activity. Source location was carried out at this location and events were located in the vicinity of the vertical crack, which shows the feasibility of acoustic emission to detect and locate ongoing damage from cracking given that appropriate data filters are used.

For the Aged Concrete Test Block, both electrochemical results and acoustic emission cumulative signal strength versus time indicated that the corrosion activity occurred primarily during the first three to four months of conditioning and then continued at a reduced rate. Intensity Analysis based on the acquired data indicated that damage progressed from the assumed initial condition of 'no corrosion/approaching depassivation', determined based on electrochemical results upon arrival at the laboratory to 'cracking/severe damage' over the monitoring period for all three locations and for both sensor types. This Intensity Analysis result is similar to the one reported for the 'vertical column-to-roof interface location'.

One of the main areas that hinder wide implementation of structural health monitoring systems is the large amounts of data that is collected and the subsequent effort needed to interpret and analyze this data in order to produce meaningful assessment of the condition of the structures. An important contribution of this study is that it proved the ability of well-developed data reduction and damage assessment algorithms to provide accurate evaluation of the condition of the structures. The results of the study showed that the developed filtering techniques along with the Intensity Analysis chart used for corrosion damage classification were able to successfully qualify the damage in the monitored areas. A method to account for pre-existing damage in the AE Intensity Analysis chart was also developed. These methods can be easily programmed and used to provide meaningful information to facility managers without the need for further assessment of large data sets. This can subsequently help in maintenance planning and prioritization especially in large scale and complex infrastructure systems.

Future research is needed to correlate acoustic emission data to electrochemical measurements especially in early corrosion stages, which will further enhance the outcome of monitoring. This will provide more insight regarding the progression of corrosion damage and can ultimately enable estimation of remaining service life.

**Author Contributions:** Conceptualization, M.A., M.E., K.D., M.S. and P.Z.; Methodology, P.Z., M.E. and M.A.; Validation, M.A. and M.E.; Formal Analysis, M.A.; Writing-Original Draft Preparation, M.A.; Writing-Review & Editing, M.E., P.Z., K.D. and M.S.; Supervision, P.Z.; Project Administration, P.Z. and M.S.; Funding Acquisition, P.Z., M.S., K.D. and M.E.

**Acknowledgments:** The authors would like to thank the support of Savannah River National Laboratory. Portions of this work are supported by the U.S. Department of Energy and Savannah River National Laboratory through SCUREF Funding. Portions of this work are supported by the U.S. Department of Commerce, National Institute of Standards and Technology (NIST), Technology Innovation Program (TIP), Cooperative Agreement 70NANB9H9007.

**Conflicts of Interest:** The authors declare no conflict of interest.
