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Corrosion monitoring techniques for concrete in corrosive environments

  • Manjunath Pagadala

    Manjunath Pagadala is an undergraduate student from the Department of Civil Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, India. He is a 2020 GS Ramaswamy fellowship awardee, presented by the Structural Engineering Research Center, India and rank 1 multi-domain expert in the All-India Altair Optimization Contest 2021. His research interests are in structural optimization, high performance computing, computational mechanics, and structural health monitoring.

         , Sanjay Mundra

    Dr. Sanjay Mundra is working as a general manager in Structural Assessment & Rehabilitation (S.A.R.) Division, Centre for Construction Development and Research, National Council for Cement and Building Materials, Ballabgarh, Haryana, India. He has 24 years of experience in quality requirements of cement, concrete mix design, ready-mix concrete, quality assurance in construction, condition assessment of existing structures, and seismic resistant design of structures. His research interests include utilizing cement and sustainable waste building materials, especially mineral waste, in concrete composites and assessing the durability of concrete structures. He has published more than 15 research papers in various international and national conferences and journals.

     EMAIL logo     und Shivang Bansal

    Shivang Bansal holds a Bachelor of Technology in Civil Engineering from GLA University, Mathura, India. He is working as a lab manager in the Mechanical and Physical Investigation Lab, Centre for Construction Development and Research, National Council for Cement and Building Materials, Ballabgarh, India. He has four years of experience in the field of quality requirements and testing of building materials. His research interests are in developing alkali-activated concrete (geopolymer), construction & demolition aggregates, sustainable waste building materials in concrete composites, and durability assessment of concrete structures.
Veröffentlicht/Copyright: 5. Juli 2022
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Abstract

Replacing or servicing corroded reinforced concrete structures requires careful consideration of the rate of corrosion of the embedded rebar. Corrosion rates are usually measured using monitoring techniques, but these techniques may not always give reliable results due to the effect of factors called rate influencers. Though the consideration of rate influencers does not entirely alleviate the problem, monitoring them during measurements will significantly reduce the probable error. Hence, this paper compares the experimental results of prior studies with an effort to draw out the best corrosive environment for the efficient working of a few widely used monitoring techniques and presents a list of some major rate influencers that need concern for the accurate evaluation of corrosion. A literature review is performed to achieve the above objectives. The Monitoring techniques considered in this study are linear polarization resistance (LPR), electrochemical impedance spectroscopy (EIS), galvanostatic pulse technique (GPT), and half-cell potential (HCP).

Keywords: electrochemical impedance spectroscopy; galvanostatic pulse technique; half-cell potential; linear polarization resistance; rate influencers

1 Introduction

The efficacy of corrosion monitoring techniques in concrete structures has been a constant concern for several decades. Determining the extent of corrosion or corrosion rate is critical for predicting a structure’s service life. Factors depicting the corrosion-prone material, corrosion environment, and monitoring test procedure play an essential role in affecting corrosion and corrosion measurements (Law et al. 2004; Rengaraju et al. 2019; Sohail et al. 2020). The influence of these factors makes corrosion monitoring an arduous task. Precise implementation of corrosion monitoring techniques offers engineers an opportunity to employ the available preventive measures to enhance the structure’s durability and increase its service life. Incapable of doing so would jeopardize the structure’s service life and economy, resulting in a global annual maintenance cost of nearly 2.5 trillion US dollars as of 2016 (Koch et al. 2016). Accurate measurement of the corrosion rate would help engineers assess the structure’s service life and evaluate the corrosion state to reduce further damage. Thus, the objective is to compare prior experimental results to influence the varying corrosion state of corrosion monitoring techniques and recommend major parameters that need to be considered while measuring corrosion rate.

Existing literature shows extensive use of linear polarization resistance (LPR), galvanostatic pulse technique (GPT), electrochemical impedance spectroscopy (EIS), and half-cell potential (HCP) for corrosion monitoring. Several studies investigating the efficacy of corrosion monitoring techniques in diverse corrosive conditions utilizing various rebar and concrete components have been undertaken (Sohail et al. 2020; Soleymani and Ismail 2004). Various studies have also been conducted to evaluate the working efficiency of electrochemical techniques in determining the corrosion rate in carbonated and chloride-containing environments. Experimental studies were performed by Sathiyanarayanan et al. (2006) and Vedalakshmi and Thangavel (2011) using LPR, EIS, HCP, and GPT to compare the corrosion rate by themselves as well as with the weight loss method to test their reliability in real case scenarios. Researchers have also tried replacing the conventional concrete with high-performance, high-porosity, or high-resistance cementitious systems to evaluate the monitoring technique’s versatility (Hren et al. 2019; Rengaraju et al. 2019; Soleymani and Ismail 2004). Many environmental factors and instrumental parameters were also studied by researchers to evaluate their effect on corrosion rate measurements (Durrani et al. 2020; Nazir et al. 2018; Rengaraju et al. 2019).

Intending to bring these myriad works together and help future researchers make sound decisions, this review aims to (i) compare previous results to recommend suitable corrosive conditions for efficient use of each monitoring technique and (ii) show the effect of rate influencers on corrosion or corrosion measurements. A systematic literature review is carried out by conducting a comparative analysis of the results of prior studies to accomplish these goals.

2 Overview of corrosion mechanism

Understanding the corrosion mechanism requires a comprehensive knowledge of the passivation process. Passivation can be defined as the formation of a protective oxide layer resulting from a surface reaction (water + oxide) that occurs in the high pH of the surrounding cement environment (Broomfield 2003). The removal of this layer, called de-passivation, expedites the onset of corrosion, which is primarily caused due to carbonation or chloride attack. Ingress of carbonation due to atmospheric carbon dioxide destroys the passive layer by precipitating calcium carbonate, an acidic compound that lowers the pH in the vicinity of the rebar, making the rebar prone to corrosion. Whereas chloride attack caused by exposure to marine environments or de-icing salts, rather than lowering pH, directly attacks the passive layer and catalyzes its breakdown (Broomfield 2003).

The exposed rebar surface (anodic region), developed as a consequence of de-passivation, undergoes oxidation in the presence of potent oxidizing agents and converts solid iron to iron ions with the release of electrons. These released electrons flow (icorr-corrosion current) through the rebar to enable a cathodic reaction, thereby allowing iron ions to react with cathodic by-products, resulting in a deposition of a brick-red compound on the rebar surface called iron oxide, commonly referred to as rust. This entire process is defined as corrosion, and Figure 1 gives an overview of it. The icorr values measured using the monitoring techniques can be used to calculate the total weight of steel lost by using the equation below (Law et al. 2004).

(1)Mass loss of steel=(∫icorrC)∗M

where ∫icorr = total current passed, C = charge per mole of iron, M = atomic mass of iron. The chemical reactions at the cathodic and anodic sites governing corrosion are called half-cell reactions. The possible anodic half-cell reactions depending on the electrolyte, anions present at the interface, and the existence of electrochemical potential are presented below (Ahmad 2003).

(2a)3Fe+4H2O→Fe3O4+8H++8e−
(2b)2Fe+3H2O→Fe2O3+6H++6e−
(2c)Fe+2H2O→HFeO2−+3H++2e−
(2d)Fe→Fe2++2e−
Figure 1: Corrosion mechanism (Ahmad 2003).
Figure 1:

Corrosion mechanism (Ahmad 2003).

The possible cathodic half-cell reactions depending on the O2 availability and pH at the vicinity (12–12.5) of the rebar are presented below (Ahmad 2003).

(3a)2H2O+O2+4e−→4OH−

Or

(3b)2H++2e−→H2

The type of corrosion occurring depends on the cause of de-passivation. Chloride attack can cause pitting corrosion, and uniform carbonation induces uniform corrosion (Law et al. 2004). Besides, corrosion exists in two forms: micro and macrocell. Microcell corrosion occurs when anodic and cathodic regions are located adjacent to each other. In contrast, macrocell corrosion occurs when both regions form at distant locations allowing electrons to flow from one location to another.

The service life of a reinforced cement concrete (RCC) structure is divided into two phases. First, the corrosion initiation time, and second the propagation time between initiation and cracking of the concrete depending on the threshold concentration (Angst et al. 2009), as shown in Figure 2. The increasing concentration of the corrosion inducers at the vicinity of the rebar, as seepage progresses, causes a change in pH and [cl−] concentration, which can further be related to the condition of the reinforcement (see Table 1). Researchers have used this notion to develop mathematical models that depict the corrosion inducers seepage, for example, Fick’s 2nd law (Lu et al. 2012) and the Nernst-plank equation (Rahman et al. 2012), to predict the service life of a structure. A few additional equations can also be derived from these, based on the type of diffusion coefficient used, for instance, a time-dependent coefficient (Luping and Gulikers 2007).

Figure 2: Service life phases of an RCC structure (Ahmad 2003).
Figure 2:

Service life phases of an RCC structure (Ahmad 2003).

Table 1:

pH versus corrosion (Ahmad 2003; Berkeley and Pathmanaban 1990).

pH State of reinforcement corrosion
Below 9.5 Commencement of steel corrosion
At 8.0 Passive film on the steel surface disappears
Below 7 Catastrophic corrosion occurs

3 Corrosion monitoring techniques

This section explains the working principle of a few monitoring techniques and reviews/compares the recently conducted experimental studies to determine the suitable corrosive setting for efficient working of each instrument.

3.1 Linear polarization resistance (LPR)

LPR is an electrochemical corrosion technique with the ability to measure the instantaneous mean corrosion rates. LPR measurements are taken by applying a small potential sweep about the Ecorr (corrosion potential) potentiostatically or potentiodynamically while measuring the current response. An alternative way is to apply a galvanostatic or galvanodynamic current and measure the potential response (Esmaeilpoursaee 2007). These measurements are utilized to calculate the polarization resistance (Rp) from Eq. (4), essentially the slope of the potential-current curve.

(4)Rp=ΔEΔI

where ΔE is the applied over potential and ΔI is the resulting current response in a potentiostatic system. The applied voltage is generally between 10 and 30 mV to ensure that the potential sweep lies inside the linear Stern-Geary region (Law et al. 2004). In the case of a galvanostatic system, the current perturbation is applied so that the resulting voltage falls in the linear stern-geary region. If the perturbation is insufficient, the metal is allowed to re-equilibrate, and the test is repeated with a different current to achieve the desired potential shift (So and Millard 2007). The icorr is then calculated using Eqs. (5) and (6).

(5)icorr=BRct=BRp−RΩ
(6)B=βaβc2.3(βa+βc)

B is the Stern-Geary constant, Rct is the charge transfer resistance, RΩ is the electrolyte resistance, and βa and βc are anodic and cathodic Tafel constants, respectively (Gowers et al. 1994). The corrosion rate is calculated by using the Faraday’s law:

(7)Corrosion rate (μmyear)=0.129∗icorr∗EWρ∗A

where EW is the equivalent weight of the corroding material, icorr is the corrosion current intensity in μA/cm2, A is the exposed surface area of the steel in cm2, and ρ is the density of the steel in g/cm3 (Soleymani and Ismail 2004). A schematic three-electrode setup of an LPR instrument is shown in Figure 3.

Figure 3: A three-electrode test setup for LPR and EIS (Rengaraju et al. 2019).
Figure 3:

A three-electrode test setup for LPR and EIS (Rengaraju et al. 2019).

B is often approximately considered 25 mV for actively corroding steel and 50 mV for passive steel in concrete. But, this assumption can cause differences in the obtained corrosion rates in LPR. On the other hand, Rct is also commonly approximated to Rp due to RΩ being negligible; however, in corrosion of steel in concrete, the electrolyte resistance may not always be negligible (Gowers et al. 1994). Assuming Rct = Rp produces inaccurate values due to the negligence of a large RΩ which can be around 1000 Ω, contributed by the concrete cover. Hence, it is safer to take Rct = Rp − RΩ to avoid a possible error. A few comparative studies on LPR in concrete are shown in Table 2 with their assumptions and methodologies.

Table 2:

LPR studies.

References Assumptions Methodology Findings
Law et al. (2004)

  1. B was assumed as 25 mV for corroding steel and 50 mV for passive conditions.

  2. Active condition: Rct < 10,000 Ω/cm.

  3. Passive condition: Rct > 10,000 Ω/cm.

  4. Assumed the whole surface to be polarized.

  1. 27 lab specimens were equally divided for carbonation (CAE), chlorine (CHE), and nitrogen-rich environment.

  2. Low grade 20 N/mm2 portland cement concrete mix was used for making the specimens.

  3. Considered ohmic resistance in calculating icorr.

 CHE LPR overestimated metal loss by 128% compared with the actual metal loss from the weight loss method. This was attributed to the non-uniform distribution of the perturbed current along the rebar. A probable cause for the large deviation was said to be because of high potential variation between the pits and passive steel, along with the effect of external factors like pH, chloride concentration, and condition of steel.
CAE LPR produced good results with 57% overestimation compared with the actual metal loss from the weight loss method.
Poursaee (2010) Constant B value was used for the conventional LPR’s active and passive state corrosion.

  1. Nine portland concrete specimens were equally divided to test the effect of transverse, longitudinal, and no cracks on steel corrosion.

  2. The actual value of B was found for the particular test scenario at different instants by using a potentiostatic transient technique.

  3. The conventional LPR (constant B) was compared with the potentiostatic transient technique to understand the effect of constant B.

  4. The effect of ohmic resistance was compensated in all calculations.

 CHE

  1. Corrosion rates from LPR had more fluctuations and discrepancies compared to the actual corrosion rate from the gravimetric method and potentiostatic transient technique under active corrosion.

  2. Potentiostatic transient technique was used as a simple and relatively fast technique to calculate the corrosion current density of steel rebars without knowing the value of B.
Rengaraju et al. (2019) Assumed RΩ to be negligible. LPR and EIS were used on three systems, ordinary portland cement (OPC), OPC with pulverized fly ash (PFA), and limestone calcined clay cement (LC3), for evaluating their suitability in assessing Rp in highly resistive systems. CHE The LPR technique without positive feedback/current interruption couldn’t detect the corrosion initiation compared to visual examination for the used instrument configuration.
Sathiyanarayanan et al. (2006)

  1. B = 0.026 V and B = 0.052 V were used for active and passive states, respectively.

  2. No data could be acquired with IR eliminated LPR with the instrument used.

  1. A GPT device was used to measure polarized potential after eliminating IR drop.

  2. LPR and GPT were used to evaluate M15, M20, M30, and M35 specimens containing 0, 1, 3, and 5% chloride ion concentration.

 CHE

  1. LPR produced a corrosion rate lower than the actual corrosion rate from the mass loss method due to inclusion of resistance of concrete in the LPR measurements.

  2. Corrosion rates from GPT are in good agreement with the weight loss method.
Pradhan and Bhattacharjee (2009) B is assumed as 26 mV assuming active corrosion of embedded steel.

  1. Three types of steel, three w/c ratios, and four admixed chloride contents were used to prepare the reinforced concrete specimens.

  2. LPR with IR compensation was used by the corrosion equipment that estimates the IR drop by the concrete cover and compensates while determining corrosion current density.

  3. LPR with guard ring, an auxiliary electrode used to confine the current dispersion, was also tested.

 CHE LPR with guard ring gave corrosion rates close to the gravimetric results.
Zornoza et al. (2009)

  1. B = 26 mV was assumed in the active state.

  2. Other assumptions may include those used by the instrument used.

  1. Six different samples were used, of which one is used as a reference without any fly ash or plasticizer.

  2. Potentiostat-Galvanostat 362EG&G was used for measuring icorr.

 CAE LPR produced comparable results with the gravimetric method validating the assumed B values.
Stefanoni et al. (2018) – Review CAE Out of the 53 papers referred to in the literature review on the determination of corrosion rate of steel in carbonated concrete/mortar, 37 used LPR for evaluating corrosion.

From Table 2, it may be said that LPR is suitable for CHE, but its substantial reliance on rate influencers makes the results conservative. Based on its wide applicability in previous studies, LPR may also be used in CAE. Poursaee (2010) showed that the use of constant B might affect the obtained corrosion rates. But a few studies, even with constant B, have obtained close results to that of the mass loss method. This shows that those studies had their experiment done under similar conditions as the constant B experiment. While many other factors might have influenced the results (refer to Section 4), care should be taken in using the most suitable B for the given system. Similarly, RΩ needs to be considered in calculations for accurate results.

3.2 Electrochemical impedance spectroscopy (EIS)

EIS, also referred to as the AC (alternating current) impedance technique, considers the conventional corroding interface as a simplified Randles circuit with the double layer capacitance, solution resistance, and charge transfer resistance. It provides information on a variety of factors, like the presence of surface films, concrete properties, etc. (Montemor et al. 2003). Usage of EIS includes subjecting a rebar in a concrete environment to an alternate voltage amplitude of about 10–20 mV and measuring its impedance response (Song and Saraswathy 2007). Impedance Z consists of a real component (Z′) and an imaginary component (Z″). Z is evaluated by Eq. (8).

(8)Z=EωIω=Eosin(ωt)Iosin(ωt+∅)=Zo exp(j∅)=Z′+jZ″

where Eω is frequency-dependent voltage and Iω is frequency-dependent current. The E and I are at a phase shift ∅, and the variation of Z with ∅ is shown in Table 3. The two commonly used plots to analyze the EIS data are Bode and Nyquist plots. The Bode plot plots between Z and ∅ against frequency. The results obtained are used to understand the variation of double-layer capacitance (Cdl) and evaluate polar and solution resistances. The Rp calculated is substituted in Eq. (5) to get the corrosion current, thereby corrosion rates. Similarly, the Nyquist plot is a vector plot plotted between Z′ and Z″, which results in a semi-circular plot through which the concrete cover/electrolyte resistance (RΩ), Rct, and Cdl can be obtained (Sohail et al. 2020). RΩ is the real axis intercept at high frequency, and Rct is the difference of the real axis intercept at low and high frequencies, i.e., the diameter of the semicircle. The Cdl is given by Eq. (9).

(9)Cdl=12πRctf

where f is the frequency at the highest point of the semicircle (Song and Saraswathy 2007). The advantages of EIS are its (i) ability to accurately detect corrosion in highly resistive cementitious systems (CHE), (ii) produce stabilized corrosion potentials, (iii) suitability for determining the concrete resistance (can be obtained by extrapolating the high-frequency arc in the Nyquist plot), and (iv) reliability to assess corrosion in epoxy coated rebars demonstrating that it could be used to determine the epoxy health of the reinforcement (Rengaraju et al. 2019; Sohail et al. 2020; Vedalakshmi and Thangavel 2011). A few comparative studies on EIS in concrete are shown in Table 4 with their assumptions and methodologies.

Table 3:

Phase shift versus impedance.

Phase shift (∅) 0° −90° +90°
Z R − j / ω C (Faradays) − j ω L (Henrys)
Table 4:

EIS studies.

References Assumptions Methodology Findings
Vedalakshmi et al. (2010)

  1. Constant B = 26 mV is assumed for both active and passive states.

  2. Ohmic resistance is neglected in calculating icorr.

  1. 150 OPC specimens with a 0.5 w/c ratio were cast along with RCC slabs.

  2. EIS measurements were taken periodically using a high input impedance multimeter.

  3. R p was determined by extrapolating the low-frequency arc, and icorr was determined by B/Rp.

 CHE The EIS corrosion rates are precise and accurate in the passive state and underestimated in the active state compared to weight loss measurement.
Fahim et al. (2018) The area under the counter electrode was assumed to be polarized.

  1. Five monitoring techniques along with EIS were used on RCC specimens.

  2. 16 OPC specimens were cast for testing, with them being equally divided into four different sets, admixed with different chloride concentrations.

  3. A simplified spectrum analysis was used, which involves subtracting the high-frequency impedance representing ohmic resistance (RΩ) of concrete from the low-frequency impedance (RΩ + R) to eliminate the effect of the equivalent circuit model choice on the polarization resistance estimation.

 CHE EIS, combined with simplistic spectrum analysis, is found to give an accurate rate in both active and passive states.
Herrera et al. (2019) No assumptions were explicitly mentioned related to the working of EIS Instruments used.

  1. Concrete blocks were cast using commercial grade portland cement.

  2. A three-electrode setup with an IM6-ZAHNER workstation was used for obtaining EIS spectra.

 CAE EIS was shown to be a practical non-destructive tool for evaluating carbonation progress in RCC. The electrical resistivity monitored by EIS was correlated with the carbonation depth from the phenolphthalein indicator test and compared with concrete pore resistance, calculated by means of a mathematical simulation.
Chávez-Ulloa et al. (2013)

  1. 12 concrete beams were molded: 6 plain and 6 having reinforcement.

  2. An accelerated carbonation chamber was built to generate exposure data.

  3. A potentiostat ACM Instruments field machine serial 914 was connected to the electrochemical cell.

 CAE EIS was also able to detect passive situations, activity, passive-active transition, and ohmic control in the concrete-steel interface.
Chi et al. (2002)

  1. Two concrete mixtures made from OPC and SCC (self-compacting concrete) were designed and tested.

  2. A three-electrode AC impedance (Impedance Gain-phase Analyzer and a Nichia model Potentialstat) and open circuit potential were performed on the specimens.

 CAE EIS showed that carbonation of concrete enhances the rate of corrosion, similar to the HCP results, which showed a >90% probability of corrosion just after carbonating. This was attributed to a possible pH reduction of the pore water, causing chloride ions to diffuse easily.

From Table 4, it can be said that EIS may be used in CHE with simplified spectrum analysis for both active and passive states, but its reliance in active situations is questionable and requires further analysis. In the case of CAE, EIS may be chosen while considering the assumptions undertaken by the instruments.

3.3 Galvanostatic pulse technique (GPT)

GPT works based on galvanostatically impressing a short anodic impulse and measuring the resulting change in potential of the reinforcement (Figure 4). When a constant anodic current Iapp is applied, a jump in the polarization potential is observed, whose locus is represented by Eq. (10) (Elsener et al. 1997).

(10)Vt=Iapp[Rp[1−exp(−tRpCdl)]+RΩ]
Figure 4: Potential response due to Iapp (Poursaee and Hansson 2008).
Figure 4:

Potential response due to Iapp (Poursaee and Hansson 2008).

The applied current is usually in the range of 10–200 μA, and the typical pulse duration is up to 10 s. Two different methods, linearization (Klinghoffer 1995) and curve-fitting procedure (Elsner 1995), were proposed to obtain the resistance values from the Vt expression with their respective equations are provided below. The annotation and solving methodology can be looked at in the respective journal papers.

(11)Linearization: ln(Vmax−Vt)=ln(IappRp)−t/(RpCdl)
(12a)Curve fitting:Vt=K0−K1exp(−tK2)
(12b)K0=(IappRp+IappRΩ)
(12c)K1=IappRp
(12d)K2=RpCdl

A GPT setup is shown in Figure 5. It allows combined potential and resistance mapping and rapidly gives information on the state of rebars embedded in concrete (Elsner 1995). It is usually preferred over LPR, as it eliminates concrete resistance (Sathiyanarayanan et al. 2006). A few comparative studies on GPT in concrete are shown in Table 5 with their assumptions and methodologies.

Table 5:

GPT studies.

References Assumptions Methodology Findings
Vedalakshmi et al. (2010)

  1. B = 26 mV was used in calculating corrosion rate from resistance.

  2. Other assumptions may include those used by the GalvaPulse GP 5000.

  1. 150 OPC specimens with a 0.5 w/c ratio were cast along with RCC slabs.

  2. GPT was performed using GalvaPulse GP 5000.

 CHE

  1. GPT is more precise than EIS and predicts corrosion rate closer to coupon calculated rate in active state.

  2. GPT with a pulse duration of 10 s and anodic impulse of 100 μA (CR = 1.8 μm/year) showed the ability to discriminate the active and passive area of the rebar in a chloride environment, but it overestimates the rate by 10 times in the passive state.
Vedalakshmi and Thangavel (2011)

  1. 150 OPC specimens with thermo-mechanically treated bars (TMT) were used.

  2. LPR, EIS, Harmonic Analysis technique, and Tafel exploration technique were carried out using advanced corrosion measurements (ACM, UK) model version 5-field machine, whereas GPT was done by GalvaPulse GP 5000.

 CHE GPT is more precise than LPR and EIS in an active state.
Fahim et al. (2018) No assumptions were explicitly mentioned related to the working of GPT Instruments used.

  1. Five monitoring techniques along with EIS were used on RCC specimens.

  2. 16 OPC specimens were cast for testing, with each four being admixed with different chloride concentrations.

  3. A commercially available GPT device (GalvaPulse) was used.

 CHE

  1. The ratio of the predicted corrosion rates obtained from the GPT with the weight loss method was in the range of 0.5–2 for most actively corroding specimens.

  2. GPT failed in detecting passivity. This was believed to result from several assumptions used by the device. The GPT device uses a similar current confinement procedure for both states, which is an assumption that has been shown to be inaccurate due to the high resistance to polarization exhibited by passive steel. Another source of error is not considering the additional current due to the guard ring. The last reason was a low measuring period of 10 s, which is insufficient for the system to attain quasi-steady-state conditions.
So and Millard (2007) B = 25 mV for active and B = 50 mV for passive states were used to obtain rates from Rct. LPR and GPT tests were conducted on concrete slabs with a compressive strength of 40 N/mm2 and w/c = 60% CHE GPT gives a more reliable corrosion rate than LPR.
Frølund et al. (2002)

  1. B is an empirical constant of 25 mV for actively corroding steel and 50 mV for passive steel.

  2. Other assumptions may include those used by the GPT instrument.

  1. Onsite tests were performed on the Skovdiget bridge north of Copenhagen, Denmark, along with lab tests on seven concrete blocks.

  2. A GPT instrument produced by the FORCE institute was used (Danish Patent 171925B1 1997).

 CHE A good correlation was determined between GPT results and the mass loss method when the test was performed in a laboratory. And for on-site tests, the GPT corrosion rates compared to the average corrosion rates from actual cross-section loss at places where the actual corroding area is the same as the confined area were comparable.
Verma et al. (2013) – Review In some cases, GPT may also produce un-stabilized readings.
Pereira et al. (2015) No assumptions were explicitly mentioned related to the working of GPT Instruments used.

  1. Three situations were considered: corrosion by chlorides, carbonation, and passive state, for testing.

  2. Potentiodynamic polarization, GPT, and EIS were used for monitoring corrosion.

  3. Voltalab PGZ 301 was used for performing GPT.

 CAE GPT produced an average Rp comparable to the potentiodynamic and potentiostatic polarization resistance method.
Hren et al. (2021)

  1. OPC and three other commercially available blended cement, cylindrical specimens and mortar prisms, were cast.

  2. Corrosion was monitored by galvanostatic pulse and electrical resistance sensors.

  3. GalvaPulse was used for GPT.

 CHE GPT considerably overestimated corrosion rates for carbonated specimens compared to the rates obtained from corrosion damage evaluation.

From the studies in Table 5, it can be said that GPT may be used in the active and transient state in CHE and may produce satisfactory results in CAE. While most of the papers used a constant B for deriving rates, further testing may be required, similar to Poursaee (2010), to understand the effect of a variable B.

3.4 Half-cell potential (HCP)

HCP, also known as open circuit potential or rest potential, is a technique used to predict the probability of corrosion based on the voltage/potential difference between the reference electrode and the rebar. The potential difference depends on the reference electrode and corrosion condition (Elsener et al. 2003). The potential readings in the voltmeter indicate the probability of corrosion at a particular location. The more negative the readings, the higher the probability that the rebar is undergoing active corrosion (due to dissolution of the anode). Its exact classification can be seen in Table 6 and its setup in Figure 6.

Table 6:

Relation between corrosion probability and potential readings according to ASTM C876-15.

Potential readings Ecorr Probability
E corr < −350 mV 90% probability that corrosion is taking place
−350 mV < Ecorr < −200 mV The activity of corrosion is unknown
−200 mV < Ecorr 90% probability of no corrosion
Figure 6: Half-cell potential setup (Yodsudjai and Pattarakittam 2017).
Figure 6:

Half-cell potential setup (Yodsudjai and Pattarakittam 2017).

HCP is considered to be easy to use and helps to locate corrosion-prone areas. It can even be used for corrosion detection on surface-treated concrete using high impedance equipment (Cairns and Melville 2003). It can only give information about corrosion probability and not corrosion rate. Although laboratory testing can provide an empirical relationship between corrosion rate and potential readings, the correlation is not universal, as wide variations of corrosion rate are possible in a narrow range of potentials (Sagüés 1993). Research by Leelalerkiet et al. (2004) shows that the half-cell potential technique produces more negative values than actual corroding areas and maybe unreliable without compensation when the specimen is under cyclic (CHE) wet and (ambient) dry conditions. For reliable results, HCP is compensated with the inverse boundary element method, a numerical technique applied to analyze the potential problems (Leelalerkiet et al. 2004). Similarly, Sadowski (2013) suggests complementing HCP with the concrete resistivity method to obtain maximum information on corrosion probability. Chansuriyasak et al. (2010) showed that the HCP measurements shifted to more negative values after corrosion initiation in CHE but more positive values in CAE. This was attributed to the increasing resistance of the carbonated concrete due to a reduction in the permeability and porosity of the specimen. Frølund et al. (2003) performed four onsite testing’s and showed that HCP might lead to mistakes in cases where concrete is water-saturated, carbonated, or exposed to very low temperatures.

4 Effect of rate influencers on corrosion/corrosion measurements

Corrosion rate depends on various factors; however, the important rate influencers are as follows:

4.1 General rate influencers

4.1.1 Oxide composition

The percentage of oxide constituents such as goethite, lepidocrocite, akaganeite, and magnetite affects the rate of corrosion (Choudhary et al. 2016). Lepidocrocite, seen in the early stages of mild steel corrosion in slightly acidic conditions, eventually converts into a more stable compound (goethite), slowing the corrosion process by limiting additional exposure of the embedded rebar to the corrosive environment. As a result, the alpha/gamma (goethite/(lepidocrocite + akaganeite + magnetite)) quantitative ratio rises as exposure time increases. The higher the alpha/gamma ratio, the higher the polar resistance (Rp) and, as a result, decreases the corrosion rate (Choudhary et al. 2016).

4.1.2 Surface contaminants

Rapid micro-climate changes in the vicinity of rebars, such as alternate wetting and drying, cause rebar to corrode. The change in temperature makes it possible to deposit the salts and contaminants present in the atmospheric moisture/water on the rebar surface (assuming that water reaches the steel surface within the wetting period), thereby decreasing the critical relative humidity of steel and rendering the rebar more vulnerable to corrosion (Nazir et al. 2018). Lower critical humidity is responsible for the early initiation of corrosion at low relative humidity values due to the high wettability rate of steel (Yadav et al. 2004). The wettability of steel is, therefore, an essential parameter in evaluating the corrosion rate.

4.1.3 Reinforcement composition

The rebar elemental composition also influences the corrosion behavior. High-chromium (HC) steel produces a polarization resistance value that is 1.5 times that of mild steel (MS) and at least four times that of high strength (HS) steel, suggesting a higher corrosion resistance based on the corrosion rate (Sohail et al. 2020), following the order HC > MS > HS. Higher HC resistance is attributed to the formation of a less porous stable oxide passive layer due to the presence of higher chromium in the alloy, and lower HS resistance is associated with the high manganese content, an active metal that forms oxides and promotes pitting corrosion. Therefore, the rebar composition plays an important role in determining corrosion rate.

4.1.4 Concrete composition

The use of different compositions for concrete cover affects reinforcement corrosion. Sathiyanarayanan et al. (2006) used four concrete specimens with increasing average compressive strength from 15 to 35 MPa and found corrosion rate to be dependent on strength for a given chloride concentration. As the concrete strength increased, the corrosion rate decreased. This trend was evaluated by obtaining corrosion rates from LPR, GPT, and weight loss techniques.

4.1.5 De-icing salts

De-icing salts are used to melt snow/ice deposited on the roads to avoid the reduction in friction between tyres and concrete pavements during winters. De-icing salts mainly contain sodium chloride, magnesium chloride, and calcium chlorides (Padilla et al. 2013). These compounds decrease the melting point of water/moisture without allowing them to precipitate on the pavement. While de-icing salts are advantageous in winters, it has a negative impact on the concrete pavement. The three chlorides, being hydrophobic, absorb water and become active corrosive agents at a particular temperature and relative humidity (Houska 2015).

4.1.6 Corrosion inhibitors

Corrosion inhibitors are an alternative way to delay corrosion (Ormellese et al. 2006). Inhibitors are admixtures, added during the making of fresh concrete and migrators, used for repairing hardened concrete. Though inhibitors exist as organic or inorganic, their usage needs critical concern. Low admixture dosage or presence of concrete cracks may produce an opposite effect to delaying corrosion with a possible increase in corrosion rate (Ormellese et al. 2006). As these may directly affect the measured value of corrosion, corrosion rate depends on the inhibitors used.

4.1.7 Corrosion parameters

A parametric study by Ge and Isgor (2007) demonstrated that the corrosion parameters directly affect the potential gradient between anodic and cathodic surfaces, affecting the measured corrosion rate. It was found that the corrosion rate is susceptible to change in cathodic Tafel slope and anodic half-cell potential. The Stern-Geary B typically considered are values derived for corrosion of steel in saturated Ca(OH)2, which is a simplified environment for steel in concrete (Poursaee 2010). The B value varies between 8 mV and infinity for different environmental conditions for steel in concrete (Song 2000). Many studies (Alonso et al. 1998; Locke and Siman 1980) show that B is not constant, and it changes based on the anodic and cathodic reactions, and using a constant value for all experiments would induce errors. Hence, B is another factor that influences the obtained corrosion rate.

4.2 Instrument specific rate influencers

Table 7 lists out the Instrument specific rate influencers and summarizes their effect on the monitoring techniques.

Table 7:

Effect of rate-influencers on monitoring techniques.

Influence factors Monitoring techniques
LPR EIS GPT HCP
Time A suitable monitoring period is required to avoid measuring inaccurate Rp values caused due to the inclusion of non-related resistances like the ohmic and ion diffusion resistance that do not directly affect the corrosion (Law et al. 2000). A 30 s delay time was seen to better correlate with weight loss measurements than 120 s for both active and passive rebars (Gowers and Millard 1999). Taking EIS spectrum measurements in a system before reaching steady-state leads to inaccurate results (Instruments 2007). A minimum measuring time can avoid over-polarizing the rebar (Sathiyanarayanan et al. 2006). A measuring period of 60 s may be appropriate as per Gowers and Millard (1999); however, complete stabilization may not occur for 60 s in passive situations. Sufficient time should be given after wetting the surface to allow potential stabilization of about a minimum of 15–20 min (Esmaeilpoursaee 2007).
Surface Errors occur due to a lack of good electrolytic contact with the concrete surface. This can be overruled by (1) wetting the surface if the surface is too dry, (2) removing the salts present on the surface/sponge, and (3) wetting the reference electrode membrane if it lacks moisture to re-establish the electrolytic connection (Andrade and Alonso 2004).

  1. Wetting the surface before taking the Rp measurements produced higher and closer to actual values than measuring it without wetting (Sehgal et al. 1992).

  2. Sehgal et al. (1992) also performed tests varying the surface morphology (roughness) and found that the measured Rp values are reasonable on a flat concrete surface. Better signal transmission to the concrete is aided by improving the contact.

 Implementing GPT on a free and planar concrete surface, similar to HCP, would allow for more electrical connectivity, resulting in a uniform distribution of electrical signals.

  1. Readings must be taken on the free concrete surface. The presence of isolating layers like asphalt, organic coating, paints, etc., may make measurements erroneous (Elsener et al. 2003).

  2. Changing the moisture content, i.e., wetting the concrete surface, shifts the potential readings to a more negative value (Elsener et al. 2003).
Probe/electrode According to a study by Durrani et al. (2020), a corroded LPR probe overestimates the corrosion rate by 20% than the cleaned probe. Offsetting the probe even a little from the symmetrical position, i.e., exactly above the rebar, would produce lower Rp values due to an increase in the rebars polarized area (area on the rebar that has deviated from its equilibrium due to the application of potential) (Sehgal et al. 1992). GPT’s reliability in large reinforced structures lowers with the use of an estimated value of C (capacitance) per unit area when the size of CE used is smaller than the rebar (Gonzalez et al. 2001). The electrode potential changes as a function of the reference electrode position on rebars with a concrete cover of 10 mm. The result indicates the non-homogeneous rusting on the metal surface (Grimaldia et al. 1986).
Cover depth Research by Da et al. (2018) shows that Rp increases with an increase in concrete cover thickness, demonstrating that the corrosion resistance is related to the thickness of the coral aggregate seawater concrete. It is found from the research of Argyle (2014) that the cover depth has a significant effect on impedance measurements. An experimental study by Dou et al. (2014) proved an increase in Icorr with a decrease in cover thickness. Locating corroding spots becomes difficult with a deep concrete cover (Elsener et al. 2003).
Temperature Durrani et al. (2020) found that the corrosion rate increases by 3.5% on average for every 1 °C rise in temperature. These experimental results were obtained using water as the electrolyte. Deus et al. (2014) showed the corrosion rate to have a complex dependency on temperature Appropriate temperature correction factors are advised for measurements to avoid incorrect estimation (Raczkiewicz and Wójcicki 2020). Research work of Zou et al. (2016) shows that increasing the temperature would decrease the potential readings under the same level of corrosion.
Miscellaneous factors

  1. Usage of the guard ring would primarily address the inability to differentiate the polarized area of the bar (Law et al. 2000).

  2. Increasing the scan rate from 0.05 to 0.1667 m V s−1 decreases the measured Rp due to the increase in the current across the double layer (Cdl) (Rengaraju et al. 2019).

  1. The guard ring configuration was only successful in measuring corrosion current densities when the corrosion was uniform, and the exterior combined electrode was large in comparison to the concrete cover, in a study by Kranc and Sagües (1993).

  2. Positioning RE very close to the mortar surface of the specimen caused severe distortion in the high-frequency region of the Nyquist plot in a study by Rengaraju et al. (2019) due to short-circuiting.

  1. Research work of Elsener et al. (1997) showed that the ohmic resistance and the polarisation resistance are unaffected by the use of a guard ring in actively corroding rebars. But, it produced accurate results when used on passive rebars in low-resistive concrete.

  2. At corroding sites, the Rp values measured are proportional to the region of the rebar polarized under the CE (Elsener et al. 1997).

  1. Chloride content, oxygen, concrete cover, and corrosion inhibitors influence the potential measurements. (Yodsudjai and Pattarakittam 2017; Gu and Beaudoin 1998).

  2. Environmental factors such as the date of testing, weather (temperature and humidity) at the time of testing, and a few days before testing should all be considered (Assouli et al. 2008).

5 Preventive measures

Minimizing depassivation is a better way to prolong corrosion initiation, which can be achieved by reducing/slowing the potential seepage of chloride or carbon dioxide into the concrete pores. Seepage reduction can be enabled by using sufficient concrete cover, a low w/c ratio, and good quality cement. Well-cured concrete and good compaction may also reduce pore connectivity (Broomfield 2003). An alternative way to reduce seepage is by using corrosion inhibitors that fill up concrete pores, blocking the porosity by forming complex compounds. Ormellese et al. (2006) observed that commercial organic inhibitors delay the occurrence of chloride-induced corrosion. The addition of superplasticizer and water-reducing admixtures also showcases a similar effect by decreasing the passing of NaCl solution/moisture to the steel surface. Tammam et al. (2020) showed the effect of superplasticizer by performing EIS and potentiodynamic polarization on three different samples.

A study by Gowripalan and Mohamed (1998) showed that the use of high-performance concrete (HPC) with galvanized steel bars would delay the onset of corrosion, thereby demonstrating a delay in depassivation. PPC (portland pozzolana cement) and PSC (portland slag cement) can also be used instead of OPC (ordinary portland cement) as it is seen to have a higher tolerance to chloride-induced corrosion (Pradhan and Bhattacharjee 2009). Another strategy is by using normal-weight concrete as an alternative to total-lightweight concrete, as prior research indicates that it provides greater corrosion resistance (Baronio et al. 1996). This was attributed to the high porosity of lightweight concrete that absorbs high amounts of salts during moisture exposure which leads to building up of concentration in the pores that later tend to migrate towards reinforcement owing to capillary absorption.

6 Conclusions

The suitable corrosive environment for the efficient use of corrosion monitoring techniques is evaluated based on the results of the literature review. In a chloride-containing environment, the non-destructive tool, EIS, is the best method for evaluating passive state corrosion, while GPT for the active state and transient state would produce relatively good results. Similarly, LPR can be used in active state condition, but its substantial reliance on rate influencers make the results conservative. In a carbonation environment, the non-destructive techniques and LPR, would produce comparable results. On the other hand, HCP gives reliable results with compensation in a chloride environment, while the measurements may be misleading in carbonation. Though these recommendations are followed, utmost care is needed to rate influencers as these produce errors in results in experimental studies. A minor disturbance would cause the corrosion rate to be underestimated or overestimated, jeopardizing the structure’s service life. A few major physical influencers like time, surface properties, and probe condition can be directly monitored due to them being in control of the instrument user, but other non-physical influencers are difficult to monitor. However, these can be used to understand the deviation of the measured results and may also be used to derive coefficients that can compensate for their effect in later experiments. The future scope of study involves conducting laboratory and empirical studies using LPR, EIS, GPT, and HCP to verify the experimental data from the reviewed references while also testing the effect of rate influencers on the calculated corrosion rate.

Nomenclature

AC

alternating current

CAE

carbonation environment

C dl

double-layer capacitance

CE

counter electrode

CHE

chloride-containing environment

CR

corrosion rate

E corr

Corrosion potential

EIS

electrochemical impedance spectroscopy

GPT

galvanostatic pulse technique

HAT

harmonic analysis technique

HC

high chromium steel

HCP

half-cell potential

HPC

high performance concrete

HS

high strength steel

LPR

linear polarization resistance technique

MS

mild steel

OPC

ordinary Portland concrete

PPC

Portland pozzolana cement

PSC

Portland slag cement

R ct

charge transfer resistance

RE

reference electrode

R p

polarization resistance

R Ω

electrolyte resistance

Corresponding author: Sanjay Mundra, Centre for Construction Development and Research, National Council for Cement and Building Materials (NCCBM), Ballabgarh, Haryana500078, India, E-mail:

About the authors

Manjunath Pagadala

Manjunath Pagadala is an undergraduate student from the Department of Civil Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, India. He is a 2020 GS Ramaswamy fellowship awardee, presented by the Structural Engineering Research Center, India and rank 1 multi-domain expert in the All-India Altair Optimization Contest 2021. His research interests are in structural optimization, high performance computing, computational mechanics, and structural health monitoring.

Sanjay Mundra

Dr. Sanjay Mundra is working as a general manager in Structural Assessment & Rehabilitation (S.A.R.) Division, Centre for Construction Development and Research, National Council for Cement and Building Materials, Ballabgarh, Haryana, India. He has 24 years of experience in quality requirements of cement, concrete mix design, ready-mix concrete, quality assurance in construction, condition assessment of existing structures, and seismic resistant design of structures. His research interests include utilizing cement and sustainable waste building materials, especially mineral waste, in concrete composites and assessing the durability of concrete structures. He has published more than 15 research papers in various international and national conferences and journals.

Shivang Bansal

Shivang Bansal holds a Bachelor of Technology in Civil Engineering from GLA University, Mathura, India. He is working as a lab manager in the Mechanical and Physical Investigation Lab, Centre for Construction Development and Research, National Council for Cement and Building Materials, Ballabgarh, India. He has four years of experience in the field of quality requirements and testing of building materials. His research interests are in developing alkali-activated concrete (geopolymer), construction & demolition aggregates, sustainable waste building materials in concrete composites, and durability assessment of concrete structures.

Acknowledgments

This work was supported by National Council for Cement and Building Materials (NCCBM), Ballabgarh, India.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

  3. Conflicts of interest: The authors declare that they have no conflicts of interest regarding this article.

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Received: 2022-05-05
Accepted: 2022-05-06
Published Online: 2022-07-05
Published in Print: 2022-10-26

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. In this issue
  3. Reviews
  4. An overview of anti-corrosion properties of ionic liquids for corrosion of carbon steel in acidic media
  5. Corrosion monitoring techniques for concrete in corrosive environments
  6. Graphene-based coatings for magnesium alloys: exploring the correlation between coating architecture, deposition methods, corrosion resistance and materials selection
  7. Original Articles
  8. Decision support system to evaluate a vandalized and deteriorated oil pipeline transportation system using artificial intelligence techniques. Part 1: modeling
  9. The third-generation biodiesel blends corrosion susceptibility of oxide particle-reinforced Si-rich aluminum alloy matrix composites
  10. Electrodeposition and corrosion characterization of epoxy/polyaniline coated AZ61 magnesium alloy
  11. Novel anticorrosive coating of silicone acrylic resin modified by graphene oxide and polyaniline
https://doi.org/10.1515/corrrev-2022-0036
Schlagwörter für diesen Artikel
electrochemical impedance spectroscopy; galvanostatic pulse technique; half-cell potential; linear polarization resistance; rate influencers

Artikel in diesem Heft

  1. Frontmatter
  2. In this issue
  3. Reviews
  4. An overview of anti-corrosion properties of ionic liquids for corrosion of carbon steel in acidic media
  5. Corrosion monitoring techniques for concrete in corrosive environments
  6. Graphene-based coatings for magnesium alloys: exploring the correlation between coating architecture, deposition methods, corrosion resistance and materials selection
  7. Original Articles
  8. Decision support system to evaluate a vandalized and deteriorated oil pipeline transportation system using artificial intelligence techniques. Part 1: modeling
  9. The third-generation biodiesel blends corrosion susceptibility of oxide particle-reinforced Si-rich aluminum alloy matrix composites
  10. Electrodeposition and corrosion characterization of epoxy/polyaniline coated AZ61 magnesium alloy
  11. Novel anticorrosive coating of silicone acrylic resin modified by graphene oxide and polyaniline
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