COMPARISON OF CHLORIDE DIFFUSION COEFFICIENT TESTS FOR CONCRETE Chloride diffusion tests for concrete

Transcription

1 COMPARISON OF CHLORIDE DIFFUSION COEFFICIENT TESTS FOR CONCRETE Chloride diffusion tests for concrete M. A. MILTENBERGER, J. J. LUCIANO, and B. D. MILLER Master Builders, Inc., Technical Service Laboratories, Cleveland, Ohio, USA Durability of Building Materials and Components 8. (1999) Edited by M.A. Lacasse and D.J. Vanier. Institute for Research in Construction, Ottawa ON, K1A 0R6, Canada, pp National Research Council Canada 1999 Abstract: Corrosion service life predictions based on Fick s second law of diffusion require an estimate of the chloride diffusion coefficient for concrete. Since the industry lacks a standard diffusion coefficient test procedure, several procedures are currently being used. Not surprisingly, the value of the diffusion coefficient depends on the test method employed. This paper presents the results of a three-year study aimed at producing a valid laboratory procedure to estimate the chloride diffusion coefficient for concrete. The investigation involved obtaining chloride diffusion coefficients using different laboratory procedures: natural chloride flux, chloride migration, and chloride ponding. The paper discusses each test method, calculation procedure, and practical limitations. It is shown that the natural chloride flux test is the most fundamentally sound procedure to obtain the chloride diffusion coefficient, but is too slow for practical application. The data indicate that diffusion coefficients obtained by the chloride flux and accelerated migration test methods are significantly different from chloride ponding tests. In addition, the influence of silica fume and an organic corrosion-inhibiting admixture on chloride diffusion coefficients are discussed. Keywords: chloride flux, chloride migration, chloride ponding, chloride diffusion, chloride diffusion coefficient, service life, concrete, corrosion, Fick s second law of diffusion, organic corrosion-inhibiting admixture.

2 1 Introduction Most corrosion service life models are based on Fick s second law of diffusion. In order to use these models, estimates of the chloride loading and chloride diffusion coefficient must be made. (Amey et al. 1998; Bamforth 1994; Berke and Hicks 1993; Weyers et al. 1993) Historically, these parameter estimates came from determining the chloride content at multiple depths in existing concrete structures or chloride ponding experiments. The chloride content was then mathematically fitted to Fick s second law as a function of sample depth in order to obtain the surface concentration and diffusion coefficient. The primary drawbacks of determining the parameter estimates from fitting chloride profiles are: 1) making the incorrect assumption that diffusion is the only mechanism for chloride ingress in concrete, and 2) obtaining a chloride analysis from structures is expensive. In reality, this process requires too much time and effort to be useful for modern designers; especially those interested in evaluating new materials. In the last decade, accelerated methods to estimate the diffusion coefficient have developed (Andrade 1993; Streicher and Alexander 1995; Zhang and Gjorv 1994), but the values obtained from the different methods do not necessarily agree. Most chloride diffusion coefficient test methods fall into three basic categories: 1. Chloride flux procedures determine the diffusion coefficient by measuring the flow of chloride through a known area of concrete over time (flux). The driving force in this test is simply a concentration gradient across the sample. The test schematic is shown in Fig.1. The diffusion coefficient is calculated from the rate of change in the chloride concentration in the sodium hydroxide reservoir. 2. Chloride migration procedures reduce the test duration by driving the chloride through concrete with an electrical potential. The diffusion coefficient calculation varies between the two migration methods typically used; one method is based on the conductivity of chloride-saturated concrete, and the other is similar to the chloride flux test with corrections for the electrical current. 3. Chloride ponding tests also have two versions; one is known as static ponding, and the other is known as bulk diffusion. Increasing the solution concentration, the ambient temperature, or both accelerates these procedures. In one procedure, a concrete specimen is ponded with a chloride solution, while in the other method the specimen is immersed in the chloride solution. After a certain time period, the chloride content data are mathematically fit to Fick s second law of diffusion as a function of depth to obtain the apparent surface concentration and diffusion coefficient.

3 2 Research significance The data presented in this paper show the relationship between three chloride diffusion coefficient tests for concrete. In addition, the data show the effect of silica fume and an organic corrosion-inhibiting admixture 1 (OCI) on the chloride diffusion coefficient estimate. 3 Experimental The data were collected over three years as part of six different evaluations. As such, data presentation has been abbreviated. Each evaluation was performed under controlled laboratory conditions following standard procedures for mixing, casting, and curing by ACI-certified technicians. All concrete mixtures used materials in conformance with ASTM specifications, and were moist-cured for 28 days prior to testing. Two sets of specimens were exposed at Treat Island, ME, a severe weathering exposure site run by the US Army Corps of Engineers. The exposure site is a wood platform set at mean sea level, so the concrete is exposed to tidal oscillations. This facility exposes concrete to two wet/dry, or freeze/thaw cycles per day. 3.1 Mixture proportions Since the data presented in Table 1 come from multiple evaluations, the concrete mixture proportions differ. In order to identify the pertinent experimental variables without listing individual mixture proportions, an observation number and mixture code were assigned to each mixture. The mixture code format is: (c+m) w/(c+m) SF - OCI Where: (c+m) = cementitious materials content, kg/m 3 w/(c+m) = 100 * water-to-cementitious materials ratio SF = silica fume percentage by mass of total cementitious materials, OCI = dose of organic corrosion-inhibiting admixture, L/m 3 For example, the code indicates that the concrete contained a total cementitious content of 356 kg/m 3 ; the water-to-cementitious materials ratio was 0.45, 6 % of the cementitious materials mass was silica fume; and 5 L/m 3 of an organic corrosion-inhibiting admixture 1 were added. 1 Rheocrete 222+; an aqueous solution of amines and fatty acid esters, is manufactured by Master Builders, Inc., Cleveland, Ohio

4 3.2 Test methods Fig. 1 presents a schematic of the test setups used to determine the chloride diffusion coefficients Chloride flux The chloride flux procedure uses a pre-saturated 25-mm thick by 100-mm diameter concrete sample cut from a core or cast cylinder. The concrete specimen is placed in the cell so the top (finished) surface faces the sodium chloride (NaCl) reservoir, and the cut surface faces the sodium hydroxide (NaOH) reservoir. The minimum specimen thickness is twice the maximum size aggregate, to avoid the potential for a continuous flow path along the aggregate. This cell is designed to accommodate specimens taken from either cylinders or cores using a recessed rim to create a watertight seal, and exposing a 75-mm diameter surface. The reservoir capacity of the cells employed was approximately 720 ml. 25 mm _ 50 mm M NaCl 0.1M NaOH 2.5 M NaCl 0.1M NaOH a) Chloride flux apparatus b) Chloride migration apparatus 15% NaCl 5M 40C c) Chloride ponding specimen d) Bulk diffusion specimen Fig. 1: Schematic representation of diffusion coefficient test methods

5 The NaOH reservoir is monitored for chloride breakthrough using chloride titrator strips on a monthly basis. Once chloride breakthrough occurs, 10-mL aliquots are removed from both reservoirs and titrated for chloride concentration. Aliquots are then removed and titrated monthly until at least six consecutive diffusion coefficient calculations agree to within ± 1 mm 2 /yr. The exposed surface is centered in the reservoir, so the aliquots do not lower the solution level enough to expose the concrete surface. The effective diffusion coefficient, D e, is calculated from the chloride concentration measurements using Fick s second law of diffusion (Eq.1). The calculation is simplified using Eq Since solution concentrations, the specimen thickness, and time of exposure are known, the effective diffusion coefficient is determined by setting the Ratio in Eq. 2 to ( )( [ x ]) 1 Cx, t = Co + Cse Co erf Cx, t Co Cse Co Ratio = x 1 erf 2 Det 2 Dt (1) (2) Where: C x,t = C se = C o = x = erf = D e = t = The chloride concentration in the NaOH reservoir at time t, ppm The chloride concentration in the NaCl reservoir, ppm Background chloride concentration, ppm Sample thickness, mm The error function The effective chloride diffusion coefficient, mm 2 /yr Time of exposure in cell, yr The chloride flux test is fundamentally the most sound procedure to determine the diffusion coefficient, since the only driving force is a concentration gradient. Also, since the specimen is primarily a membrane, chloride binding does not skew the calculation. However, it is a real-time test that can take a couple of years to complete for high quality concrete. Practically, the usefulness of this procedure is limited to long-term research. 1 In this study, C o is set to 0.0 because the NaOH solution was made with de-ionized water. If the initial NaOH solution contained Cl -, use the net concentrations for C se and C x,t. 2 In practice, the trial and error process is simplified by using the Goal Seek or Solver functions of an Excel spreadsheet.

6 3.2.2 Migration methods Both chloride migration procedures use the same basic cell design as the chloride flux test except that the concrete slice is thicker, and the reservoirs contain mesh electrodes. The application of a modest electrical potential (10 to 15 VDC) accelerates the migration test from a multi-year test to a few weeks, even with a larger specimen thickness. The authors chose to modify the migration cell commonly employed in the literature by using an anode electrode (+) made from platinized niobium mesh instead of stainless steel to minimize cell maintenance resulting from anode corrosion after chloride break-through. Migration procedure 1 is a modified version of Streicher and Alexander s (1995) chloride conduction procedure. The modification is simply that the concrete is saturated with chloride by applying the electrical potential, instead of vacuum saturation. After polarization the reservoir solutions are emptied, and both sides are refilled with fresh 2.5 M NaCl solution for the conductivity measurement. Fig. 2 shows that the modification saturates the sample with chloride prior to the measurement, validating the calculation assumption that the pore solution conductivity is known. The diffusion coefficient is calculated from conductivity measurements using Eq. 3 below. The fundamental assumption behind this calculation is that the pore solution conductivity is known. For most concrete the pore solution conductivity is not known, so preconditioning is required to saturate the sample with a known chloride solution. For this technique, a 2.5 M concentration of NaCl solution was selected to saturate the pore solution. Although the 2.5 M solution exceeds the 0.5 M limit of the Debye-Huckel theory for chloride transport, the larger concentration was chosen to minimize the error induced by other ions solvating into the pore solution from the concrete. Therefore, the pore conductivity and diffusivity numbers can be assumed to be that of a 2.5 M Cl - solution, and any charge carried by ions solvating from the concrete (i.e., K +, Na +, Ca +2, SO 4-2, OH - ) can be considered negligible. Please refer to the original work by Streicher and Alexander (1995) for a more detailed discussion of the method, assumptions, and calculation procedures. D c = *( 10) 13 D o σ σ c o Where: *(10) 13 is the conversion factor for m 2 /s to mm 2 /yr D c = Diffusion of chloride ions through concrete pores (mm 2 /yr) D o = Diffusion of chloride ions through 2.5M NaCl solution (0.165 m 2 /s) σ c = Conductivity of concrete (calculated from voltage drop and current measurements on cell), S/m σ o = Conductivity of solution (16 S/m for 2.5 M NaCl) (3)

7 Migration procedure 2 is the accelerated chloride flux procedure presented by Zhang and Gjorv (1994 and 1995). Calculation of the diffusion coefficient in this method is based on the drift velocities of chloride ions within concrete. Zhang assumed that the drift velocity of chloride ions is affected by relaxation and electrophoretic effects of the ionic cloud, and by a concentration related retardation in ion migration velocity. By taking these assumptions into consideration, they proposed that the effective diffusion coefficient could be calculated as described in Eq. 4. Chloride Content (ppm Distance from Cast Surface (mm) D = 12 D = 15 D = 17 D = 19 D = 82 D = 87 Fig. 2 Chloride content of specimens after Migration procedure 1 In this procedure, the concentration of chloride must remain less than 0.5 M for the Debye-Huckel theory to be satisfied, thereby making Eq. 4 valid. In practice, the constants β (Volt/K o ) and α (cm 2 L o K/mol Volt) are calculated for each specimen, and the change in chloride concentration over time in the anodic chamber is monitored to obtain dc/dt. The effective diffusion coefficient is then calculated using Eq. 4. The original work by Zhang and Gjorv (1994) provides a detailed discussion of the derivation of the equations, assumptions, and calculation procedures. A practical limitation of this procedure is that it is laborious, requiring daily monitoring and chloride sampling, so it was discontinued after use in two evaluations. D e 9 = *(10) βα dc dt (4)

8 Where: *(10) 9 is the conversion factor from cm 2 /s to mm 2 /yr o 300kV β = zeovact T LV α = Ψ c A o o D e = Effective chloride diffusion coefficient, mm 2 /yr A o = Cross section area, cm 2 c o = Source chloride concentration, mmol/cm 3 e o = Charge of a proton, 4.8 (10) -10 esu. k = Boltzmann constant, 1.38 (10) -16 erg./k ion L = Distance between electrodes, cm T = Absolute temperature, K V = Volume of collecting cell, cm 3 V o = Drift velocity of at infinite dilution, (see reference) V act = Actual net drift velocity for ions in solution, (see reference) z = Ionic valance Ψ = Applied electric potential, Volts dc = Rate of change in chloride concentration over time dt Chloride ponding The chloride ponding specimens were 150-mm diameter by 150-mm high concrete cylinders. The bottom half of a 150- x 300-mm cylinder mold was used to cast the specimen and the top half of the mold was used to form the ponding dike. Specimens were cast, stripped, moist-cured for 28 days, dried for one week, and had the sides covered with two coats of epoxy paint before the dike was caulked in place. After the silicone caulk dried, the dike was filled with 2.5 M NaCl solution and then covered by a plastic bag. The 150- x 150-mm chloride ponding specimens were stored on racks and routinely monitored for evaporation and leaks. Individual ponding specimens were cast for each exposure period of interest. At the end of each exposure period the dike and any silicone remnants were removed, the cylinder was rinsed, and then sliced in 6-mm increments. Each slice had the epoxy-coated edge removed, and was carefully dried, pulverized, and analyzed for the acid soluble chloride content according to ASTM C 1152 and AASHTO 260. The apparent diffusion coefficient, D a, and effective surface concentration were calculated from the chloride content profile using Eq. 1 and a nonlinear regression routine. The background chloride content, C o, was determined for each evaluation from initial chloride content measurements taken from specially cast cubes or compressive strength specimens.

9 3.2.4 Bulk diffusion Bulk diffusion differs from the ponding test (3.2.3) in that the specimen is coated with epoxy on all but the finished surface, is saturated with water prior to chloride exposure, and is totally immersed in a chloride solution. The acid soluble chloride profile is then obtained from powder samples taken at 1-mm increments after the exposure period. The diffusion coefficient is calculated by fitting the chloride profile to Eq. 1. The test conditions force chloride ingress to occur only by diffusion, whereas conditions in the ponding test allow combined diffusion, sorption, and wicking. 4 Results Table 1 summarizes diffusion coefficient estimates from six individual experiments. Evaluations A through E were included in analysis of variance. Evaluation F was provided only for illustrative purposes and was not included in the statistical analysis. Fig. 3 illustrates the effect of chemical and mineral admixtures on the diffusion coefficient using three different test methods. Each bar represents the pooled mean value of within-evaluation comparisons from Table 1, using evaluations A through D. It is important to note that the comparisons shown in Fig. 3 are not isolated experimental results, but are the pooled results from four individual experiments. The trends indicated in the graphs are repeatable, as each individual experiment produced similar results, even though mixture proportions differed. To illustrate, the diffusion coefficients pooled for the Reference shown in the left graph are Mix numbers 1, 3, 4, 5, 9,10, 11, 15, and 16. The comparable OCI Mix numbers are 2, 6, 7, 8, 12, 13, 14, 17, and 18, respectively. Similarly, the values pooled together for the Reference shown in the right graph are from Mix numbers 3, 6, 9, 12, 15, and 17. The 4% SF values are the mean values from Mix numbers 4, 7, 10 and 13. The 8% SF values come from Mix numbers 5, 8, 11, 14, 16, and /yr) Reference OCI Chloride Flux Migration 1 Ponding yr) Reference 4% SF 8% SF Chloride Flux Migration 1 Ponding Fig. 3: Comparison of admixture effect across test methods

10 5 Discussion The goal of any engineering property test is to produce unbiased parameter estimates useable in subsequent calculations. Therefore, an appropriate test method must adhere to the same boundary conditions as the calculation procedure. In the case of chloride diffusion coefficient tests, these boundary conditions dictate that the influence of alternative chloride transport mechanisms be minimized Since chloride diffusion occurs through the water filled pores in concrete, saturation and minimal water transport are essential conditions for an appropriate test procedure. This requirement is satisfied in the saturated conditions of the chloride flux, migration, and bulk diffusion test methods, but is lacking in the chloride ponding test. The data presented in Table 1 clearly show that the flux, migration, and bulk diffusion methods produce similar parameter estimates, whereas the historical approach of fitting chloride profiles is heavily biased. This bias is most probably caused by chloride ingress through alternative transport modes. Water and chloride transport through concrete is influenced by hydraulic pressure and/or saturation gradients produced by wetting and evaporation fronts. A saturation gradient caused by evaporation near the dry bottom surface of the ponding test pulls both water and chloride through the concrete. This combined water and chloride transport mode is termed wicking. Buenfeld et al. (1995) showed that wicking can be a significant chloride transport mode and should be modeled separate from diffusion. Wicking and other transport mechanisms are included in the apparent diffusion coefficients calculated from both structures and chloride-ponding tests, but are absent in the effective diffusion coefficients calculated in the other methods presented. This disparity is clearly illustrated in Fig. 3. Furthermore, if the test conditions eliminate water transport through wicking and sorption, as in the bulk diffusion test, the apparent diffusion coefficients obtained by fitting chloride profiles are reasonable. For example, Mix 22 has comparable mixture proportions to Mix 11, but the apparent diffusion coefficients do not agree. In contrast, Mix 22 s apparent diffusion coefficient is more in line with the effective diffusion coefficients calculated from the chloride flux and migration methods for Mix 11. This example should not be construed as a general statement of fact, as it is just a single observation. However, the observed response is consistent with the theories advanced above. To draw scientifically correct inferences on the data shown in Table 1, analysis of variance (ANOVA) was used. Because separate mixes were not made when running each test method, there are between-mix and within-mix comparisons for this split-plot design. For example, the evaluation, corrosion inhibitor dose, and silica fume effects are between-mix comparisons. However, the test method effect is a within-mix comparison. Due to the unbalanced nature of this split-plot design detailed discussion of the formal data analysis is beyond the scope of this paper. (Milliken and Johnson 1984).

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12 Table 1: Chloride diffusion coefficient summary table. Measured Diffusion Coefficient (mm 2 /yr) Surface Background Age Eval.# Mix # Mix Code D e - Flux D e - Migr. 1 D e - Migr. 2 D a - Pond Cse (ppm) Co (ppm) t (yr) A A B B B B B B C C C C C C D* D* D* D* E* E* F** F** * The chloride profiles for these evaluations came from specimens in a severe marine exposure ** Bulk diffusion test 28 days in 5M NaCl solution at 40 C; coefficient corrected for 21 C (see Amey et al., 1998)

13 Statistical analysis of the data in Table 1 shows that the estimates obtained using the chloride flux and migration methods are essentially equivalent. The analysis also shows the reduction in the diffusion coefficients from chemical and mineral admixtures are significant. Replacing 4-8% of cement with silica fume produced a dramatic reduction in the diffusion coefficient regardless of the testing method. This reduction was is excess of 50% for 8% replacement. Furthermore, the organic corrosion-inhibiting admixture reduced the diffusion coefficient by 10 to 30%. 6 Conclusions 1. The flux and migration test methods presented produce similar values for the effective chloride diffusion coefficient for concrete. 2. Fitting chloride profiles from ponding or environmental exposure experiments to Fick s second law of diffusion can produce apparent diffusion coefficients 2 to 6 times greater than the effective diffusion coefficient. 3. Statistical analysis of the data presented indicates that all the test methods show a progressive reduction in the diffusion coefficient with increasing silica fume replacement. Also, significant reductions in the diffusion coefficient occur when an organic corrosion-inhibiting admixture was added to the concrete. 7 References Amey, S. L. Johnson, D. A., Miltenberger, M. A., Farzammehr, H., A Methodology for Predicting Service Life of Concrete Structures Exposed to a Marine Environment, ACI Structures Journal, Vol. 95, No. 2, March/April, Andrade, C., Calculation of Chloride Diffusion in Concrete from Ionic Migration Measurements, Cement and Concrete Research, Vol. 23, No. 3, pp , Bamforth, P. B., Prediction of the Onset of Reinforcement Corrosion Due to Chloride Ingress, International Conference on Concrete Across Borders, Danish Concrete Association, Berke, N. S., Hicks, M. C., Predicting Chloride Profiles in Concrete, Corrosion 93, Paper 341, The NACE International Annual Conference. Buenfeld, N. R., Shurafa-Daoudi, M. T., and McLoughlin, I. M., Chloride Transport due to Wick Action in Concrete, Chloride Penetration into Concrete, Proceedings of the RILEM Intl. Workshop, pp , October 15-18, Milliken, G. A., Johnson, D. A., Analysis of Messy Data, Vol. I: Designed Experiments, Lifetime Learning Publications, Belmont, CA, Streicher, P. E., Alexander, M. G., A Chloride Conduction Test for Concrete, Cement and Concrete Research, Vol. 25, No. 6, pp , Weyers, R. E., Fitch, M. G., Larsen, E. P., Al-Qadi, I. L., Chamberlin, W. P., and Hoffman, P. C., Service Life Estimates (SHRP-S-668), Strategic Highway Research Program, National Research Council, 1993.

14 Zhang, T., and Gjorv, O. E., An Electrochemical Method for Accelerated Testing of Chloride Diffusivity in Concrete, Cement and Concrete Research, Vol. 24, No. 8, pp , Zhang, T., and Gjorv, O. E., Effect of Ionic Interaction in Migration Testing of Chloride Diffusivity in Concrete, Cement and Concrete Research, Vol. 25, No. 7, pp , 1995.