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Repeatability of the rebound surface hardness of concrete with alteration of concrete parameters
Construction and Building Materials 131 (2017) 317–326
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Repeatability of the rebound surface hardness of concrete with alteration of concrete parameters Abdulkader El Mir ⇑, Salem G. Nehme }egyetem, rkp. 3, Hungary Department of Construction Materials and Technologies, Budapest University of Technology and Economics, 1111, Budapest, Mu
h i g h l i g h t s Concrete type directly affects the response of the repeatability of the rebound index. Ultra-high strength concrete has the lowest coefficient of variation for rebound hammer test. Main concrete parameters influencing the response of the Schmidt hammer are examined. Carbonation dramatically influences the repeatability of the rebound index. EN 13791 basic curve underestimates the mean compressive strength values.
a r t i c l e
i n f o
Article history: Received 28 July 2016 Received in revised form 10 October 2016 Accepted 16 November 2016
Keywords: Concrete Compressive strength Porosity Rebound index Repeatability
a b s t r a c t Diagnostic of concrete structure properties is essential towards assessing the properties of the evaluated element. Since the Schmidt hammer is categorized as an economic and effective non-destructive testing tool, an extensive investigation is applied on several hundred of concrete specimens produced from several types, in order to assess the compressive strength and understand the limitations and boundaries of rebound hardness. From normally vibrated concrete to ultra-high strength concrete, water-binder ratio, water-powder ratio, supplementary cementitious materials and admixtures are relatively affecting the response of rebound index of the Schmidt hammer in terms of repeatability for compressive strength prediction. Additional porosity measurements were performed to enhance this statement. Ó 2016 Elsevier Ltd. All rights reserved.
1. Introduction The evaluation of existing concrete structures is preferably carried out using non-destructive testing (NDT) methods. The Schmidt hammer is classified as one of the most commonly used techniques. Several empirical relationships have been created based on regression analysis, between applied rebound index and actual compressive strength of tested element, in order to predict the actual compressive strength [1,3]. Strength prediction accuracy strongly depends on the correlation between the strength of concrete and the amount of measure in-situ tests. Hence, the validation of such methodology remains a key issue questioning the reliability of the results. A number of earlier studies tried to understand the uncertainty of this testing method by evaluating the concrete itself. The literature provides a connection between rebound index coefficient of variation (COV) and concrete parameters, such ⇑ Corresponding author. E-mail address: [email protected] (A. El Mir). http://dx.doi.org/10.1016/j.conbuildmat.2016.11.085 0950-0618/Ó 2016 Elsevier Ltd. All rights reserved.
as water-cement ratio of the concrete, age of the concrete, the applied cement type for the concrete, the testing conditions and others [2–8]. Over the last decade, several concrete types were created, as well as diagnostic applications, that are not limited only to normally vibrate concrete (NVC). Due to the high paste content and rheological properties, High performance self-compacting concrete (HPSCC) microstructure was considered to be more unified, dense and interconnected [11,12,14]. Therefore, the variability of the rebound hardness index in HPSCC usually brings into question the effectiveness of the Schmidt hammer. In this study, however, the attention is turned on the variation of the rebound index as an effect of several parameters influencing concrete properties. Over the last 20 years, several trials and models have been developed to study the dependence of the mechanical behavior of NVC on the microstructure of the cement paste. In this effort the ‘‘degree of sensitivity concept” has been used, which is based on the pore structure of cement paste [10]. HPSCC, with a growing interest in application, is considered more adequate in terms of homogeneity and sensitivity than
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NVC. Sensitivity represents the degree of dependence of the concrete on its pore structure and related properties. Earlier studies on NVC and high strength concrete, showed that the latter has better behavior with regard to its sensitivity [9,10]. In order to assess the characteristic compressive strength of concrete, mean and standard deviation are calculated based on the strength points of the tested specimen, fitting a type of probability distribution (that is certainly not always a normal distribution). The COV contributes to a better understanding of the margin of variability and dispersion of material properties, as well as their standard deviation. Referring to fib bulletin 1999, Fig. 1 shows the COV of concrete mean compressive strengths ranged between 20 and 70 MPa [13]. To perform the present study, concrete types and compositions should be selected properly in order to obtain an objective comparative evaluation. Therefore, the parameters related to the powder, binders, admixtures and fillers have to be considered with respect to the repeatability of the rebound index. The term repeatability considers the inherent scatter with the NDT method and is often noted as a within test variation. For the characterization of repeatability either the standard deviation or the COV of repeated tests by the same operator on the same material can be suitable. The repeatability for the Schmidt rebound hammer test was found to be appropriately described by the within-test COV, rather than the within-test standard deviation [15]. Fig. 2 illustrates the COV parameter regarding the mean rebound index. The repeatability of the Schmidt rebound hammer analyzed in terms of the COV can range between 10 and 12% of within-test COV. Hence, additional studies are essential for more data relevant to the Schmidt hammer. Input and output are the key terms to understand the behavior of Schmidt hammer towards the tested material. The outcomes of this process depend on what kind of input data is involved. Input in this case is defined as the following: type and constituent of material, quality control and exposures which influence the material properties and the type of Schmidt hammer used. In this research program, several variables and constant parameters were selected in order to evaluate the limitations and boundary conditions of the rebound index of N-type Schmidt hammer on a series of NVC, HPSCC and ultra-high strength concrete (UHSC). This paper aims to evaluate the effect of powder, binder contents, supplementary cementitious materials (SCMs) and admix-
Fig. 2. Coefficient of variation (VR) as a function of the mean rebound index (Rm) [15].
tures on the COV of the rebound index. Further porosity and durability measurements were performed to enrich this investigation. 2. Research objectives The paper focuses on the response of Schmidt hammer rebound index towards different measured parameters in order to understand the limitations of such NDT method. Concrete is a composite material, that has been lately developing with the use of SCMs. Therefore, many types of concrete are produced and classified as NVC, HPSCC and UHSC. Since these classifications are designated based on the provided materials inside the mixture, the paper intends to show a compressive analysis on the repeatability of the surface hardness with respect to the influence of such a selection of parameters. For this purpose, the response of the Schmidt hammer rebound index COV is arranged according to the selected parameter and its relevant conditions. 3. Experimental procedures In order to investigate the relation between the repeatability of the rebound index represented by the COV and the concrete parameters represented by water-binder ratio (w/b), waterpowder ratio (w/p), SCMs, and admixtures, several concrete batches were designed and placed. A wide range of NVC, HPSCC and UHSC series was produced after which the evaluation of the rebound index of the Schmidt hammer and related properties could be completed. 3.1. Materials and mixtures
Fig. 1. Coefficient of variation (VR) as a function of the mean compressive strength (fcm) [13].
The applied cements were supplied by the local Producer, ‘‘LAFARGE”, based on European standards EN 197-1:2011 [16], CEM II A-S 42.5 RS, CEM III A-N 32.5 MSR and CEM III A-R 32.5 MSR. Metakaolin (MK) and silica fume (SF) served as the SCMs implemented independently in the mixtures. Quartz sand and gravel collected from the ‘‘Danube” were used for the preparation of HPSCC and NVC with relative maximum aggregate size (Dmax) of 16 mm. Three nominal grading fractions according to European Standard EN 12620:2002+A1:2008 [17] were used: sand 0/4 mm, small gravel 4/8 mm and medium gravel 8/16 mm. In case of UHSC, natural quartz sand was used as
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aggregate with maximum diameter size of 5 mm. The grading fractions used are of quartz sand ranging, between 0.2/5 mm. Limestone and perlite powder were the fillers used to produce HPSCC. Grinded fine quartz sand was supplied for the UHSC. The term ‘‘powder” is defined by the sum of cement, SCMs and fillers. According to EN 934-2:2009+A1:2012 Standard [18], high range water reducing admixture and air entraining agent represent the added admixtures in several dosages. Workability tests were performed according to concrete type and its relevant standard [19,20]. Measurements were carried out at several time offsets: 2-7-5690-240-400 days. Specimens were tested under saturated surface dry conditions at 2 and 7 days. However, for all other time offsets, the specimens were under air dried atmospheric laboratory conditions. All specimens were demolded after 20–24 h of mixing and cured under water for 7 days and afterwards under laboratory atmospheric conditions. Depending on the classification and concrete type, w/p and w/b ratios were selected to achieve the desired rheological and hardened properties. A total of 104 concrete mixtures data from earlier publications [14,21–23], student’s diploma and current research work were collected together and arranged as the following: 12 NVC, 81 HPSCC and 11 UHSC (Tables 1 and 2 summarize the test parameters with their relative materials). 3.2. Test methods Surface hardness test was performed using N-type Schmidt hammer according to European standard EN 12504-2 [24]. The specimens were put in the compression testing machine and loaded with a constant force of about 20% of their ultimate compressive strength. A total of 10 impact points were applied horizontally on the molded side of the specimen. Striking points were uniformly distributed onto the tested surface of the 150 mm cubic specimen. The mean, standard deviation and COV values were calculated by 10 replicate rebound index readings on the same surface of the concrete specimen. The same specimens were tested in agreement with European Standard EN 12390-3 [25], as to their compressive strength using a universal closed-loop hydraulic testing machine at a constant loading rate of 11.25 kN/s. Total porosity in hardened concrete was evaluated, determined based on the ratio of bulk and particle densities of concrete specimens. Bulk density was measured according to ASTM C 642 standards [26]. Shredded compressive strength specimens were crushed and grounded into fine powder reaching an average diameter size of 0.02 mm in order to evaluate the density of the particles using pycnometers [27]. Note that fluid pycnometer method with oven-dried specimens was adopted. Three specimens for each mixture were tested. Hence total porosity is calculated from the following equation:
PT ¼ 1
qb qp
Table 1 Ranges of water-binder, water-powder and cement-aggregate ratios designed for the relative mixture. Range of ratios
UHSC
HPSCC
NVC
*
0.21–0.24 0.17–0.20 0.25–1.16
0.56–0.41 0.29–0.34 0.17–0.21
0.56–0.41 0.56–0.41 0.17–0.22
w/b ** w/p *** c/a * ** ***
Water to binder ratio (by weight). Water to powder ratio (by weight). CEMENT to aggregates ratio (by weight).
Table 2 Materials applied for producing the selective concrete type. UHSC
HPSCC
NVC
Cement type
CEM II A-S 42.5 R
SCMs Filler type Admixture type
MK, SF Quartz sand Sika ViscoCrete 5
CEM III A-N 32.5 MSR CEM III A-R 32.5 MSR MK, SF Limestone, perlite Sika ViscoCrete 5, Sika Aer
CEM III A-N 32.5 MSR CEM III A-R 32.5 MSR MK, SF – Sika ViscoCrete 5
qb and qp are the bulk and particle densities (g/cm3) respectively. Water absorption by immersion test was applied until the specimens were fully saturated so that it could be checked by no mass variation. It was followed by being oven dried for 24 h under 100 °C. Relative masses were recorded in order to get the water content in V% which corresponds to the atmospheric water saturated condition designated by the apparent porosity. Cylindrical specimens with relative dimensions of Ø100 200 mm were used in this evaluation. Carbonation depth (xc) was computed by spraying phenolphthalein-alcohol solution onto the sliced surface of 150 mm cubic specimen. The carbonation depth which corresponds to the unchanged color thickness layer was measured at the center of each exposed surface and the average value was recorded.
4. Results and discussion 4.1. Analysis based on EN 13791 Validation of empirical relationships connected to (rebound index-compressive strength) represents a crucial issue in concrete structure assessments. Hence from the same batch, concrete samples should be tested for surface hardness and compressive strength in order to obtain a reliable empirical relationship from linear regression analysis. EN 13791 standard states that with the aim of ensuring a reliable assessment, drilled core strength tests must be performed for the calibration of the NDT-strength model. This method is validated according to the acceptable confidence level acquired by drilling n number of cores [28]. Yet still the main benefit of Schmidt hammer application is not achieved by harming the evaluated element. A wide range of experimental laboratory data collecting a total of 795 specimens was evaluated concerning their rebound index and compressive strength. Fig. 3 illustrates the relationship between these properties together with the basic curve given in EN 13791 standard. Mean rebound indices ranged between (Rm = 20.9–64.8) and for mean compressive strength (fcm = 17.12 MPa–139.28 MPa). It can be noticed that EN 13791 curve limited in a range of 20 < Rm < 50 is almost located at the lower boundary of all tested points. It indicates that the basic curve provides a high margin of safety yet underestimating the actual compressive strength values. Therefore, EN 13791 basic curve must be reconsidered for a positive shift along the y-axis in order to reach the actual compressive strength. A positive shift indicates the difference between the actual and the predicted compressive strength values, which is mentioned in EN 13791 Ch. 8.3. Note that the curve provided by EN 13791 is suggested for the prediction of compressive strength of similar batches. Although, the authors aim is only to observe the location of the curve suggested by the EN 13791 with respect to all experimental produced mixtures.
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Fig. 3. Experimental rebound index – compressive strength results (795 test specimens) with respect to the basic curve given in EN 13791.
An extensive analysis was accomplished on the repeatability of 795 data measurements collecting mean rebound indices and compressive strength values. Since there are various concrete types and classifications, statistical characteristics of the rebound index are essential to understand the response of the Schmidt hammer to the tested surface. Figs. 4a and 4b represent the COV of all experimental mixtures with regard to their mean rebound indices and compressive strength values. It can be observed the decreasing tendency of COV with the increase of the mean values of the compressive strength, which confirms the tendency in the behavior illustrated earlier in Fig. 1. Despite that fact, ACI 228.1R-03 Committee
recommendation (Fig. 2) should be reconsidered since no clear tendency is observed in the COV over the mean rebound index values in comparison with Fig. 4b. The latter clearly indicates the decreasing pattern of COV over the increase of mean rebound index. As the evaluated data is not distributed equally concerning mixture types, testing dates and admixtures, a correlation between concrete types and COV cannot be achieved. The paper aims to have a generalized view on the behavior of rebound index and compressive strength over the COV. Moreover, in the following section, concrete mixtures are arranged based on the evaluated property, enabling more objective interpretations that would be reached.
Fig. 4a. Coefficient of variation (VR) as a function of the mean rebound index (Rm).
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Fig. 4b. Coefficient of variation (VR) as a function of the mean compressive strength (fcm).
4.2. Parameters affecting the repeatability of the Schmidt hammer 4.2.1. Concrete type Analysis of batch to batch variation was not the scope of this study. The goal was rather to evaluate the evolution of COV of concrete types over time. Therefore, all experimental data was arranged regarding concrete types. Fig. 5 shows a graphical demonstration of mean within test variation of rebound index values for NVC, HPSCC and UHSC over time. The age of tested concretes varied between 2 day and 400 days. Referring to mean rebound index, UHSC and HPSCC resulted in lower COV over the testing period, compared to references mixtures (NVC). Experiments showed that the COV of the rebound index is very sensitive to the tested concrete type before the age
of 90 days. Differences seem to become more balanced over the age of 90 days. From a practical point of view, as the studied concrete types have different rheological properties in terms of deformability and viscosity, authors claim that rebound index COV is directly affected by the placement method of concrete. 4.2.2. Powder content A comparative analysis was performed on several w/p ratios in order to evaluate the effect of their variation over the COV of the rebound index. The following w/p ratios were selected from the experimental study: w/p = 0.17–0.29–0.31–0.34–0.5. As it can be observed in Fig. 6, it was experimentally proved by the COV values that the rebound index becomes less sensitive with the decrease of w/p ratio. In the first 28 days, almost all cases showed a rapid
Fig. 5. Effect of concrete types on the coefficient of variation of the rebound index in time.
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Fig. 6. Effect the w/p ratio on the coefficient of variation of the rebound index in time.
decrease in the rebound index COV, which can be explained by the hydration reaction. Yet over 90 days, the rate of hydration becomes lower and it has a noticeable influence on rebound index COV values. This behavior is explained by the increase of powder content in the concrete matrix reaching a more homogeneous material in term of particle size and distribution. Also it should be stated out the effect of Dmax on the response of rebound index COV. As it can be noticed in Figs. 6 and 7, lowest rebound index COV values are observed for UHSC mixtures with relative w/p = 0.17 and Dmax = 5 mm. In case of HPSCC and NVC
mixtures, the latter showed higher rebound index COV values despite that they hold the same maximum aggregate size (Dmax = 16 mm). This behavior is deduced by the difference powder content between NVC and HPSCC types. HPSCC contains more powder content, thereby enhancing the concrete microstructure. 4.2.3. Binder content One of the most influential parameters on concrete strength is the w/b ratio [29]. The change of the rebound index response is
Fig. 7. Effect the w/b ratio on the coefficient of variation (VR) of the rebound index in time.
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Fig. 8. Effect of SCMs on the coefficient of variation (VR) of the rebound index in time.
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to analyze the influence of SCMs on the repeatability parameters. The studied categories were: referencce, metakaolin and silica fume mixtures. reference mixtures (R) are the type that do not incorporate any kind of SCMs. Metakaolin mixtures category (MK) only contain MK beside the cement binder as SCMs and the same goes for the third category regarding silica fume mixtures (SF). These mixtures were produced with w/p = 0.29–0.31 and w/ b = 0.562–0.5–0.45–0.41. Fig. 8 shows that the influence of SCMs was quite evident. The age of the examined concretes was at 7 and 28 days. It was found experimentally that the lowest mean COV value for the rebound index could be reached if adding SF into concrete mixtures over reference mixtures. Hence, the differentiation between the influences of distinct hydraulic additives (MK and SF) was evident. MK and SF enhanced the concrete microstructure by decreasing the repeatability of the surface hardness in a range of 6–30% with respect to their relative reference mixtures. Explanation of such behavior is translated by the effect of SCMs on the rate and magnitude of the pozzolonic reaction in improving physical properties of the hardened cement paste [30].
directly related to the binder content. Therefore, higher w/b ratios result in higher values of rebound index COV [4]. According to Fig. 7, the influence of the water-binder ratio was possible to be arranged and studied. Binder in this study is defined as the active materials responsible for hydration (cement, MK and SF). The range of the evaluated w/b ratios from the experimental data was w/ b = 0.22–0.562. It was clearly recognized that the COV of the rebound index reduces with the decrease of w/b ratio. The age of the tested concrete ranged between 2 days and 400 days. Several interpretations can be made. In the first 28 days, a rapid decline in the COV is noticed due to the hydration phenomena. The same pattern is observed from the age of 28 up to 90 days yet at a lower degree. This can be an effect of the low rate of hydration in comparison with earliest 28 days period. A remarkable increase is observed over the age of 90 days in the COV which is directly connected to carbonation effect to the concrete surface. Future information regarding the carbonation phenomena will be discussed later in present paper.
4.2.5. Admixture type The flow ability and viscosity of HPSCC and UHSC are controlled through the HRWRA and viscosity modifying agents. Further types of admixtures such as air entraining admixtures have a significant impact on the concrete pore structure [31]. Consequently, from the basic database mentioned earlier, a comparison between 18 HPSCC mixtures (divided as 9 symmetrical non air entrained (NAE) and air entrained (AE) HPSCC mixtures) was performed. These mixtures were produced with w/p = 0.29 and w/b = 0.562–0.5–0.4 5–0.41. The tested ages were 7, 28 and 56 days. Fig. 9 illustrates the mean rebound index COV of NAE and AE mixture categories over time. First at 7 days, AE category showed an increase of 35% with respect to reference category NAE. Over the age of 7 days, the difference between rebound indices COV of NAE and AE categories was decreasing reaching a more balanced behavior at the age of 56 days. This response of rebound index COV could be explained by AE admixtures which supply air voids into the concrete microstructure.
4.2.4. Supplementary cementitious materials From all earlier mentioned data, 26 HPSCC mixtures were chosen and separated into three concrete categories. The purpose was
4.2.6. Porosity parameters The total porosity measurements were accomplished for 27 HPSCC mixtures at the age of 400 days. Selected water-powder
Fig. 9. Effect of air entrained admixture on the coefficient of variation of the rebound index in time.
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Fig. 10. Coefficient of variation of the rebound index as a function of the mean total porosity provided by different w/p ratios.
Fig. 11. Coefficient of variation of the rebound index as a function of the mean apparent porosity provided by different w/p ratios.
Fig. 12. Coefficient of variation of the rebound index as a function of the mean carbonation depth.
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and water-binder ratios were w/p = 0.29–0.31–0.34 and w/b = 0.5 62–0.5–0.45–0.41. Mean COV of rebound index of examined mixtures over the total porosity is plotted in Fig. 10. It can be observed that COV of rebound index increases along with the total porosity. Water-powder ratios were plotted separately. As it was demonstrated earlier in Fig. 6, at higher water-powder ratios, the increase of rebound index COV was observed. Additional apparent porosity measurements were completed on the HPSCC mixtures (Fig. 11). The same response of rebound index COV over the apparent porosity was observed in Fig. 10. Therefore, it could be concluded that the concrete microstructure, which is directly affected by the pore network, also has an evident influence on the COV of the rebound index.
4.2.7. Carbonation measurements The surface hardness response is related to the properties of the near surface of concrete layer. Within that region, the surface hardness of concrete is higher than the interior region of concrete due to the carbonation effect [32]. In the previous section of binder content, carbonation effect had a significant influence on the COV of the rebound index. Therefore, the carbonation depth of specimens at the age of 400 days was evaluated. A sum of 3 NVC and 27 HPSCC mixtures was designated for evaluation, selected by, water-powder and water-binder ratios, w/p = 0.29–0.5625 and w/ b = 0.562–0.5–0.45–0.41. Carbonation depth (xc) was observed to range between 1.23 mm and 12.02 mm, proportionally increasing with the increase of the water-binder ratio. The same pattern is observed in terms of rebound index COV. These results confirm Szilági et al. work [4] in term of connectivity between repeatability and carbonation depth (Fig. 12).
5. Conclusion In this paper, a series of experimental tests was applied on 795 cubic specimens with the purpose of understanding the repeatability of the rebound index of several concrete types. The applications reveal that EN 13791 underestimates the compressive strength of concrete. Moreover, results obtained in a such large scattering of coefficients of variation had to be separated and organized based on their designated parameters. Hence the response of the Schmidt hammer in relation to the studied parameters, such as waterbinder ratio, water-powder ratio, SCMs and admixtures, proved their dependency on the deviation of coefficient of variation of the rebound index. Nonetheless, the following conclusions can be drawn from this investigation demonstrated from laboratory tests: The COV of the rebound index is inversely proportional to the mean value of the rebound index. Ultra-high strength and high performance self-compacting concretes show lower rebound index COV values compared to normally vibrated concretes. The rebound index COV is inversely proportional to the waterbinder and water-powder ratios, yet directly proportional to the carbonation depth. Mixtures incorporating supplementary cementitious materials such as metakaolin or silica fume enhanced the repeatability of rebound index by resulting in lower rebound index COV values than reference mixtures. The air entrained HPSCC mixtures showed higher values of rebound index COV than non-air entrained mixtures. The rebound index COV increases proportionally to the porosity measurements (both total and apparent porosity). The increase of the COV of the rebound index is influenced by the carbonation depth of concrete.
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6. Future work This present paper addressed the non-destructive evaluation of laboratory specimens in order to assess the compressive strength of concrete. This study provided an extensive analysis on several parameters affecting the repeatability of the surface hardness of the Schmidt hammer. As UHSC resulted in very low rebound index COV, the predication of UHSC actual compressive strength would be reliable. The next logical step is to investigate structural elements produced with the same materials relevant to our laboratory research. Afterwards, an objective comparison between insitu and laboratory results can be completed in order to verify such behavior. Furthermore, the particle size distribution concerning the aggregate needs a deeper study, since this factor directly affects the empirical relationship. As a general remark, further research is needed to improve the reliability of the use of the Schmidt hammer as a tool for compressive strength assessment. Acknowledgments The authors acknowledge the financial support of the Hungarian Scientific Research Fund (OTKA; Project No. OTKA T 109223). Also, they are grateful for ‘‘LAFARGE” and ‘‘Sika” groups for supplying the materials. References [1] K. Szilágyi, 50 years of experience with the Schmidt, Concr. Struct. (2009) 2– 12. [2] A. Masi, L. Chiauzzi, An experimental study on the within-member variability of in situ concrete strength in RC building structures, Constr. Build. Mater. 47 (2013) 951–961, http://dx.doi.org/10.1016/j.conbuildmat.2013.05.102. [3] K. Szilágyi, A. Borosnyói, I. Zsigovics, Rebound surface hardness of concrete: introduction of an empirical constitutive model, Constr. Build. Mater. 25 (2011) 2480–2487, http://dx.doi.org/10.1016/j.conbuildmat.2010.11.070. [4] K. Szilágyi, A. Borosnyói, I. Zsigovics, Extensive statistical analysis of the variability of concrete rebound hardness based on a large database of 60 years experience, Constr. Build. Mater. 53 (2014) 333–347, http://dx.doi.org/ 10.1016/j.conbuildmat.2013.11.113. [5] K. Szilágyi, Static indentation hardness testing of concrete, Epitoanyag (2011) 2–9, http://dx.doi.org/10.14382/epitoanyag-jsbcm.2011.1. [6] M. Alwash, Z.M. Sbartaï, D. Breysse, Non-destructive assessment of both mean strength and variability of concrete: a new bi-objective approach, Constr. Build. Mater. 113 (2016) 880–889, http://dx.doi.org/10.1016/j.conbuildmat. 2016.03.120. [7] D. Breysse, Nondestructive evaluation of concrete strength: an historical review and a new perspective by combining NDT methods, Constr. Build. Mater. 33 (2012) 139–163, http://dx.doi.org/10.1016/j.conbuildmat.2011.12. 103. [8] K. Szilágyi, A. Borosnyói, I. Zsigovics, Understanding the rebound surface hardness of concrete, J. Civ. Eng. Manage. 21 (2015) 185–192, http://dx.doi.org/ 10.3846/13923730.2013.802722. [9] O.N. Oktar, H. Moral, M.A. Tademir, Factors determining the correlations between concrete properties, Cem. Concr. Res. 26 (1996) 1629–1637. [10] H.N. Atahan, O.N. Oktar, M.A. Tademir, Factors determining the correlations between high strength concrete properties, Constr. Build. Mater. 25 (2011) 2214–2222, http://dx.doi.org/10.1016/j.conbuildmat.2010.11.005. [11] I.M. Nikbin, M.H.A. Beygi, M.T. Kazemi, J. Vaseghi Amiri, S. Rabbanifar, E. Rahmani, S. Rahimi, A comprehensive investigation into the effect of water to cement ratio and powder content on mechanical properties of self-compacting concrete, Constr. Build. Mater. 57 (2014) 69–80, http://dx.doi.org/10.1016/ j.conbuildmat.2014.01.098. [12] G. Barluenga, I. Palomar, J. Puentes, Early age monitoring and hardened properties of SCC with limestone filler and active mineral additions, Constr. Build. Mater. 94 (2013) 728–736, http://dx.doi.org/10.1016/j.conbuildmat. 2015.07.072. [13] Fib Bulletin 3, Structural concrete – textbook on behaviour. Design and performance, Fédération internationale du béton (fib) 3 (1999) 247–248. [14] A. El Mir, S.G. Nehme, Porosity of self-compacting concrete, Proc. Eng. 123 (2015) 145–152, http://dx.doi.org/10.1016/j.proeng.2015.10.071. [15] ACI Committee 228, In-Place Methods to Estimate Concrete Strength Reported, ACI Comm. Reports., 2003, p. 41. [16] BS-EN197-1:2011, Cement – Part 1: Composition, Specifications and Conformity Criteria for Common Cements, Br. Stand., 2011. [17] BS-EN12620:2013, Aggregates for Concrete, Br. Stand., 2013. [18] BS EN 934-2:2009, Admixtures for Concrete, Mortar and Grout, Br. Stand., 2012.
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[19] EFNARC, The European Guidelines for Self-Compacting Concrete, Eur. Guidel. Self Compact. Concr. http://www.efnarc.org/pdf/SCCGuidelinesMay2005. pdf2005. 63. [20] MSZ-EN12350-5:2009, Testing Fresh Concrete – Part 5: Flow Table Test, Hun. Stand., 2009. [21] A. El Mir, S. Nehme, Accelerated carbonation effect on rebound index of SCC, CCC Congr., 2015, pp. 4–7, http://dx.doi.org/10.13140/RG.2.1.1677.3841. [22] A. El Mir, S. Nehme, Application of non-destructive test on self-compacting concrete, IABSE Symp. Report, Int. Assoc. Bridg. Struct. Eng., vol. 105, 2015, pp. 1–8.. [23] S. Zoltán, Nagy és ultra nagy szilárdságú betonok tulajdonságai, Diplomamunka. Diplom work n hungarian, 2016. [24] BS-EN12504-2:2012, Testing Concrete in Structures – Part 2: Non-destructive Testing—Determination of Rebound Number, Br. Stand., 2012. [25] BS-EN12390-3:2009, Testing Hardened Concrete – Part 3: Compressive Strength of Test Specimens, Br. Stand., 2009, pp. 420–457. [26] ASTM International, ASTM C 642-97 Standard Test Method for Density, Absorption, and Voids in Hardened Concrete, Annu. B. ASTM Stand., 1997, pp. 1–3.
[27] BSI, ISO/DIS 17892-3, Geotechnical Investigation and Testing – Laboratory Testing of Soil. Part 3: Determination of Particle Size Density, 44, 2014. [28] CEN EN 13791:2007, Assessment of In-situ Compressive Strength in Structures and Precast Concrete Components, Eu. Stand., 2007, p. 30. [29] L. Mlinárik, K. Kopecskó, A. Borosnyói, Properties of cement mortars in fresh and hardened condition influenced by combined application of SCMs, EPA J. Silicon Based Compos. Mater. 68 (2016) 62–66, http://dx.doi.org/10.14382/ epitoanyag-jsbcm.2016.11. [30] A. Borosnyói, Long term durability performance and mechanical properties of high performance concretes with combined use of supplementary cementing materials, Constr. Build. Mater. 112 (2016) 307–324, http://dx.doi.org/ 10.1016/j.conbuildmat.2016.02.224. [31] B. Łaz´niewska-Piekarczyk, Effect of viscosity type modifying admixture on porosity, compressive strength and water penetration of high performance self-compacting concrete, Constr. Build. Mater. 48 (2013) 1035–1044, http:// dx.doi.org/10.1016/j.conbuildmat.2013.07.076. [32] J.K. Kim, C.Y. Kim, S.T. Yi, Y. Lee, Effect of carbonation on the rebound number and compressive strength of concrete, Cem. Concr. Compos. 31 (2009) 139– 144, http://dx.doi.org/10.1016/j.cemconcomp.2008.10.001.
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Construction and Building Materials journal homepage: www.elsevier.com/locate/conbuildmat
Repeatability of the rebound surface hardness of concrete with alteration of concrete parameters Abdulkader El Mir ⇑, Salem G. Nehme }egyetem, rkp. 3, Hungary Department of Construction Materials and Technologies, Budapest University of Technology and Economics, 1111, Budapest, Mu
h i g h l i g h t s Concrete type directly affects the response of the repeatability of the rebound index. Ultra-high strength concrete has the lowest coefficient of variation for rebound hammer test. Main concrete parameters influencing the response of the Schmidt hammer are examined. Carbonation dramatically influences the repeatability of the rebound index. EN 13791 basic curve underestimates the mean compressive strength values.
a r t i c l e
i n f o
Article history: Received 28 July 2016 Received in revised form 10 October 2016 Accepted 16 November 2016
Keywords: Concrete Compressive strength Porosity Rebound index Repeatability
a b s t r a c t Diagnostic of concrete structure properties is essential towards assessing the properties of the evaluated element. Since the Schmidt hammer is categorized as an economic and effective non-destructive testing tool, an extensive investigation is applied on several hundred of concrete specimens produced from several types, in order to assess the compressive strength and understand the limitations and boundaries of rebound hardness. From normally vibrated concrete to ultra-high strength concrete, water-binder ratio, water-powder ratio, supplementary cementitious materials and admixtures are relatively affecting the response of rebound index of the Schmidt hammer in terms of repeatability for compressive strength prediction. Additional porosity measurements were performed to enhance this statement. Ó 2016 Elsevier Ltd. All rights reserved.
1. Introduction The evaluation of existing concrete structures is preferably carried out using non-destructive testing (NDT) methods. The Schmidt hammer is classified as one of the most commonly used techniques. Several empirical relationships have been created based on regression analysis, between applied rebound index and actual compressive strength of tested element, in order to predict the actual compressive strength [1,3]. Strength prediction accuracy strongly depends on the correlation between the strength of concrete and the amount of measure in-situ tests. Hence, the validation of such methodology remains a key issue questioning the reliability of the results. A number of earlier studies tried to understand the uncertainty of this testing method by evaluating the concrete itself. The literature provides a connection between rebound index coefficient of variation (COV) and concrete parameters, such ⇑ Corresponding author. E-mail address: [email protected] (A. El Mir). http://dx.doi.org/10.1016/j.conbuildmat.2016.11.085 0950-0618/Ó 2016 Elsevier Ltd. All rights reserved.
as water-cement ratio of the concrete, age of the concrete, the applied cement type for the concrete, the testing conditions and others [2–8]. Over the last decade, several concrete types were created, as well as diagnostic applications, that are not limited only to normally vibrate concrete (NVC). Due to the high paste content and rheological properties, High performance self-compacting concrete (HPSCC) microstructure was considered to be more unified, dense and interconnected [11,12,14]. Therefore, the variability of the rebound hardness index in HPSCC usually brings into question the effectiveness of the Schmidt hammer. In this study, however, the attention is turned on the variation of the rebound index as an effect of several parameters influencing concrete properties. Over the last 20 years, several trials and models have been developed to study the dependence of the mechanical behavior of NVC on the microstructure of the cement paste. In this effort the ‘‘degree of sensitivity concept” has been used, which is based on the pore structure of cement paste [10]. HPSCC, with a growing interest in application, is considered more adequate in terms of homogeneity and sensitivity than
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NVC. Sensitivity represents the degree of dependence of the concrete on its pore structure and related properties. Earlier studies on NVC and high strength concrete, showed that the latter has better behavior with regard to its sensitivity [9,10]. In order to assess the characteristic compressive strength of concrete, mean and standard deviation are calculated based on the strength points of the tested specimen, fitting a type of probability distribution (that is certainly not always a normal distribution). The COV contributes to a better understanding of the margin of variability and dispersion of material properties, as well as their standard deviation. Referring to fib bulletin 1999, Fig. 1 shows the COV of concrete mean compressive strengths ranged between 20 and 70 MPa [13]. To perform the present study, concrete types and compositions should be selected properly in order to obtain an objective comparative evaluation. Therefore, the parameters related to the powder, binders, admixtures and fillers have to be considered with respect to the repeatability of the rebound index. The term repeatability considers the inherent scatter with the NDT method and is often noted as a within test variation. For the characterization of repeatability either the standard deviation or the COV of repeated tests by the same operator on the same material can be suitable. The repeatability for the Schmidt rebound hammer test was found to be appropriately described by the within-test COV, rather than the within-test standard deviation [15]. Fig. 2 illustrates the COV parameter regarding the mean rebound index. The repeatability of the Schmidt rebound hammer analyzed in terms of the COV can range between 10 and 12% of within-test COV. Hence, additional studies are essential for more data relevant to the Schmidt hammer. Input and output are the key terms to understand the behavior of Schmidt hammer towards the tested material. The outcomes of this process depend on what kind of input data is involved. Input in this case is defined as the following: type and constituent of material, quality control and exposures which influence the material properties and the type of Schmidt hammer used. In this research program, several variables and constant parameters were selected in order to evaluate the limitations and boundary conditions of the rebound index of N-type Schmidt hammer on a series of NVC, HPSCC and ultra-high strength concrete (UHSC). This paper aims to evaluate the effect of powder, binder contents, supplementary cementitious materials (SCMs) and admix-
Fig. 2. Coefficient of variation (VR) as a function of the mean rebound index (Rm) [15].
tures on the COV of the rebound index. Further porosity and durability measurements were performed to enrich this investigation. 2. Research objectives The paper focuses on the response of Schmidt hammer rebound index towards different measured parameters in order to understand the limitations of such NDT method. Concrete is a composite material, that has been lately developing with the use of SCMs. Therefore, many types of concrete are produced and classified as NVC, HPSCC and UHSC. Since these classifications are designated based on the provided materials inside the mixture, the paper intends to show a compressive analysis on the repeatability of the surface hardness with respect to the influence of such a selection of parameters. For this purpose, the response of the Schmidt hammer rebound index COV is arranged according to the selected parameter and its relevant conditions. 3. Experimental procedures In order to investigate the relation between the repeatability of the rebound index represented by the COV and the concrete parameters represented by water-binder ratio (w/b), waterpowder ratio (w/p), SCMs, and admixtures, several concrete batches were designed and placed. A wide range of NVC, HPSCC and UHSC series was produced after which the evaluation of the rebound index of the Schmidt hammer and related properties could be completed. 3.1. Materials and mixtures
Fig. 1. Coefficient of variation (VR) as a function of the mean compressive strength (fcm) [13].
The applied cements were supplied by the local Producer, ‘‘LAFARGE”, based on European standards EN 197-1:2011 [16], CEM II A-S 42.5 RS, CEM III A-N 32.5 MSR and CEM III A-R 32.5 MSR. Metakaolin (MK) and silica fume (SF) served as the SCMs implemented independently in the mixtures. Quartz sand and gravel collected from the ‘‘Danube” were used for the preparation of HPSCC and NVC with relative maximum aggregate size (Dmax) of 16 mm. Three nominal grading fractions according to European Standard EN 12620:2002+A1:2008 [17] were used: sand 0/4 mm, small gravel 4/8 mm and medium gravel 8/16 mm. In case of UHSC, natural quartz sand was used as
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aggregate with maximum diameter size of 5 mm. The grading fractions used are of quartz sand ranging, between 0.2/5 mm. Limestone and perlite powder were the fillers used to produce HPSCC. Grinded fine quartz sand was supplied for the UHSC. The term ‘‘powder” is defined by the sum of cement, SCMs and fillers. According to EN 934-2:2009+A1:2012 Standard [18], high range water reducing admixture and air entraining agent represent the added admixtures in several dosages. Workability tests were performed according to concrete type and its relevant standard [19,20]. Measurements were carried out at several time offsets: 2-7-5690-240-400 days. Specimens were tested under saturated surface dry conditions at 2 and 7 days. However, for all other time offsets, the specimens were under air dried atmospheric laboratory conditions. All specimens were demolded after 20–24 h of mixing and cured under water for 7 days and afterwards under laboratory atmospheric conditions. Depending on the classification and concrete type, w/p and w/b ratios were selected to achieve the desired rheological and hardened properties. A total of 104 concrete mixtures data from earlier publications [14,21–23], student’s diploma and current research work were collected together and arranged as the following: 12 NVC, 81 HPSCC and 11 UHSC (Tables 1 and 2 summarize the test parameters with their relative materials). 3.2. Test methods Surface hardness test was performed using N-type Schmidt hammer according to European standard EN 12504-2 [24]. The specimens were put in the compression testing machine and loaded with a constant force of about 20% of their ultimate compressive strength. A total of 10 impact points were applied horizontally on the molded side of the specimen. Striking points were uniformly distributed onto the tested surface of the 150 mm cubic specimen. The mean, standard deviation and COV values were calculated by 10 replicate rebound index readings on the same surface of the concrete specimen. The same specimens were tested in agreement with European Standard EN 12390-3 [25], as to their compressive strength using a universal closed-loop hydraulic testing machine at a constant loading rate of 11.25 kN/s. Total porosity in hardened concrete was evaluated, determined based on the ratio of bulk and particle densities of concrete specimens. Bulk density was measured according to ASTM C 642 standards [26]. Shredded compressive strength specimens were crushed and grounded into fine powder reaching an average diameter size of 0.02 mm in order to evaluate the density of the particles using pycnometers [27]. Note that fluid pycnometer method with oven-dried specimens was adopted. Three specimens for each mixture were tested. Hence total porosity is calculated from the following equation:
PT ¼ 1
qb qp
Table 1 Ranges of water-binder, water-powder and cement-aggregate ratios designed for the relative mixture. Range of ratios
UHSC
HPSCC
NVC
*
0.21–0.24 0.17–0.20 0.25–1.16
0.56–0.41 0.29–0.34 0.17–0.21
0.56–0.41 0.56–0.41 0.17–0.22
w/b ** w/p *** c/a * ** ***
Water to binder ratio (by weight). Water to powder ratio (by weight). CEMENT to aggregates ratio (by weight).
Table 2 Materials applied for producing the selective concrete type. UHSC
HPSCC
NVC
Cement type
CEM II A-S 42.5 R
SCMs Filler type Admixture type
MK, SF Quartz sand Sika ViscoCrete 5
CEM III A-N 32.5 MSR CEM III A-R 32.5 MSR MK, SF Limestone, perlite Sika ViscoCrete 5, Sika Aer
CEM III A-N 32.5 MSR CEM III A-R 32.5 MSR MK, SF – Sika ViscoCrete 5
qb and qp are the bulk and particle densities (g/cm3) respectively. Water absorption by immersion test was applied until the specimens were fully saturated so that it could be checked by no mass variation. It was followed by being oven dried for 24 h under 100 °C. Relative masses were recorded in order to get the water content in V% which corresponds to the atmospheric water saturated condition designated by the apparent porosity. Cylindrical specimens with relative dimensions of Ø100 200 mm were used in this evaluation. Carbonation depth (xc) was computed by spraying phenolphthalein-alcohol solution onto the sliced surface of 150 mm cubic specimen. The carbonation depth which corresponds to the unchanged color thickness layer was measured at the center of each exposed surface and the average value was recorded.
4. Results and discussion 4.1. Analysis based on EN 13791 Validation of empirical relationships connected to (rebound index-compressive strength) represents a crucial issue in concrete structure assessments. Hence from the same batch, concrete samples should be tested for surface hardness and compressive strength in order to obtain a reliable empirical relationship from linear regression analysis. EN 13791 standard states that with the aim of ensuring a reliable assessment, drilled core strength tests must be performed for the calibration of the NDT-strength model. This method is validated according to the acceptable confidence level acquired by drilling n number of cores [28]. Yet still the main benefit of Schmidt hammer application is not achieved by harming the evaluated element. A wide range of experimental laboratory data collecting a total of 795 specimens was evaluated concerning their rebound index and compressive strength. Fig. 3 illustrates the relationship between these properties together with the basic curve given in EN 13791 standard. Mean rebound indices ranged between (Rm = 20.9–64.8) and for mean compressive strength (fcm = 17.12 MPa–139.28 MPa). It can be noticed that EN 13791 curve limited in a range of 20 < Rm < 50 is almost located at the lower boundary of all tested points. It indicates that the basic curve provides a high margin of safety yet underestimating the actual compressive strength values. Therefore, EN 13791 basic curve must be reconsidered for a positive shift along the y-axis in order to reach the actual compressive strength. A positive shift indicates the difference between the actual and the predicted compressive strength values, which is mentioned in EN 13791 Ch. 8.3. Note that the curve provided by EN 13791 is suggested for the prediction of compressive strength of similar batches. Although, the authors aim is only to observe the location of the curve suggested by the EN 13791 with respect to all experimental produced mixtures.
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Fig. 3. Experimental rebound index – compressive strength results (795 test specimens) with respect to the basic curve given in EN 13791.
An extensive analysis was accomplished on the repeatability of 795 data measurements collecting mean rebound indices and compressive strength values. Since there are various concrete types and classifications, statistical characteristics of the rebound index are essential to understand the response of the Schmidt hammer to the tested surface. Figs. 4a and 4b represent the COV of all experimental mixtures with regard to their mean rebound indices and compressive strength values. It can be observed the decreasing tendency of COV with the increase of the mean values of the compressive strength, which confirms the tendency in the behavior illustrated earlier in Fig. 1. Despite that fact, ACI 228.1R-03 Committee
recommendation (Fig. 2) should be reconsidered since no clear tendency is observed in the COV over the mean rebound index values in comparison with Fig. 4b. The latter clearly indicates the decreasing pattern of COV over the increase of mean rebound index. As the evaluated data is not distributed equally concerning mixture types, testing dates and admixtures, a correlation between concrete types and COV cannot be achieved. The paper aims to have a generalized view on the behavior of rebound index and compressive strength over the COV. Moreover, in the following section, concrete mixtures are arranged based on the evaluated property, enabling more objective interpretations that would be reached.
Fig. 4a. Coefficient of variation (VR) as a function of the mean rebound index (Rm).
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Fig. 4b. Coefficient of variation (VR) as a function of the mean compressive strength (fcm).
4.2. Parameters affecting the repeatability of the Schmidt hammer 4.2.1. Concrete type Analysis of batch to batch variation was not the scope of this study. The goal was rather to evaluate the evolution of COV of concrete types over time. Therefore, all experimental data was arranged regarding concrete types. Fig. 5 shows a graphical demonstration of mean within test variation of rebound index values for NVC, HPSCC and UHSC over time. The age of tested concretes varied between 2 day and 400 days. Referring to mean rebound index, UHSC and HPSCC resulted in lower COV over the testing period, compared to references mixtures (NVC). Experiments showed that the COV of the rebound index is very sensitive to the tested concrete type before the age
of 90 days. Differences seem to become more balanced over the age of 90 days. From a practical point of view, as the studied concrete types have different rheological properties in terms of deformability and viscosity, authors claim that rebound index COV is directly affected by the placement method of concrete. 4.2.2. Powder content A comparative analysis was performed on several w/p ratios in order to evaluate the effect of their variation over the COV of the rebound index. The following w/p ratios were selected from the experimental study: w/p = 0.17–0.29–0.31–0.34–0.5. As it can be observed in Fig. 6, it was experimentally proved by the COV values that the rebound index becomes less sensitive with the decrease of w/p ratio. In the first 28 days, almost all cases showed a rapid
Fig. 5. Effect of concrete types on the coefficient of variation of the rebound index in time.
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Fig. 6. Effect the w/p ratio on the coefficient of variation of the rebound index in time.
decrease in the rebound index COV, which can be explained by the hydration reaction. Yet over 90 days, the rate of hydration becomes lower and it has a noticeable influence on rebound index COV values. This behavior is explained by the increase of powder content in the concrete matrix reaching a more homogeneous material in term of particle size and distribution. Also it should be stated out the effect of Dmax on the response of rebound index COV. As it can be noticed in Figs. 6 and 7, lowest rebound index COV values are observed for UHSC mixtures with relative w/p = 0.17 and Dmax = 5 mm. In case of HPSCC and NVC
mixtures, the latter showed higher rebound index COV values despite that they hold the same maximum aggregate size (Dmax = 16 mm). This behavior is deduced by the difference powder content between NVC and HPSCC types. HPSCC contains more powder content, thereby enhancing the concrete microstructure. 4.2.3. Binder content One of the most influential parameters on concrete strength is the w/b ratio [29]. The change of the rebound index response is
Fig. 7. Effect the w/b ratio on the coefficient of variation (VR) of the rebound index in time.
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Fig. 8. Effect of SCMs on the coefficient of variation (VR) of the rebound index in time.
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to analyze the influence of SCMs on the repeatability parameters. The studied categories were: referencce, metakaolin and silica fume mixtures. reference mixtures (R) are the type that do not incorporate any kind of SCMs. Metakaolin mixtures category (MK) only contain MK beside the cement binder as SCMs and the same goes for the third category regarding silica fume mixtures (SF). These mixtures were produced with w/p = 0.29–0.31 and w/ b = 0.562–0.5–0.45–0.41. Fig. 8 shows that the influence of SCMs was quite evident. The age of the examined concretes was at 7 and 28 days. It was found experimentally that the lowest mean COV value for the rebound index could be reached if adding SF into concrete mixtures over reference mixtures. Hence, the differentiation between the influences of distinct hydraulic additives (MK and SF) was evident. MK and SF enhanced the concrete microstructure by decreasing the repeatability of the surface hardness in a range of 6–30% with respect to their relative reference mixtures. Explanation of such behavior is translated by the effect of SCMs on the rate and magnitude of the pozzolonic reaction in improving physical properties of the hardened cement paste [30].
directly related to the binder content. Therefore, higher w/b ratios result in higher values of rebound index COV [4]. According to Fig. 7, the influence of the water-binder ratio was possible to be arranged and studied. Binder in this study is defined as the active materials responsible for hydration (cement, MK and SF). The range of the evaluated w/b ratios from the experimental data was w/ b = 0.22–0.562. It was clearly recognized that the COV of the rebound index reduces with the decrease of w/b ratio. The age of the tested concrete ranged between 2 days and 400 days. Several interpretations can be made. In the first 28 days, a rapid decline in the COV is noticed due to the hydration phenomena. The same pattern is observed from the age of 28 up to 90 days yet at a lower degree. This can be an effect of the low rate of hydration in comparison with earliest 28 days period. A remarkable increase is observed over the age of 90 days in the COV which is directly connected to carbonation effect to the concrete surface. Future information regarding the carbonation phenomena will be discussed later in present paper.
4.2.5. Admixture type The flow ability and viscosity of HPSCC and UHSC are controlled through the HRWRA and viscosity modifying agents. Further types of admixtures such as air entraining admixtures have a significant impact on the concrete pore structure [31]. Consequently, from the basic database mentioned earlier, a comparison between 18 HPSCC mixtures (divided as 9 symmetrical non air entrained (NAE) and air entrained (AE) HPSCC mixtures) was performed. These mixtures were produced with w/p = 0.29 and w/b = 0.562–0.5–0.4 5–0.41. The tested ages were 7, 28 and 56 days. Fig. 9 illustrates the mean rebound index COV of NAE and AE mixture categories over time. First at 7 days, AE category showed an increase of 35% with respect to reference category NAE. Over the age of 7 days, the difference between rebound indices COV of NAE and AE categories was decreasing reaching a more balanced behavior at the age of 56 days. This response of rebound index COV could be explained by AE admixtures which supply air voids into the concrete microstructure.
4.2.4. Supplementary cementitious materials From all earlier mentioned data, 26 HPSCC mixtures were chosen and separated into three concrete categories. The purpose was
4.2.6. Porosity parameters The total porosity measurements were accomplished for 27 HPSCC mixtures at the age of 400 days. Selected water-powder
Fig. 9. Effect of air entrained admixture on the coefficient of variation of the rebound index in time.
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Fig. 10. Coefficient of variation of the rebound index as a function of the mean total porosity provided by different w/p ratios.
Fig. 11. Coefficient of variation of the rebound index as a function of the mean apparent porosity provided by different w/p ratios.
Fig. 12. Coefficient of variation of the rebound index as a function of the mean carbonation depth.
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and water-binder ratios were w/p = 0.29–0.31–0.34 and w/b = 0.5 62–0.5–0.45–0.41. Mean COV of rebound index of examined mixtures over the total porosity is plotted in Fig. 10. It can be observed that COV of rebound index increases along with the total porosity. Water-powder ratios were plotted separately. As it was demonstrated earlier in Fig. 6, at higher water-powder ratios, the increase of rebound index COV was observed. Additional apparent porosity measurements were completed on the HPSCC mixtures (Fig. 11). The same response of rebound index COV over the apparent porosity was observed in Fig. 10. Therefore, it could be concluded that the concrete microstructure, which is directly affected by the pore network, also has an evident influence on the COV of the rebound index.
4.2.7. Carbonation measurements The surface hardness response is related to the properties of the near surface of concrete layer. Within that region, the surface hardness of concrete is higher than the interior region of concrete due to the carbonation effect [32]. In the previous section of binder content, carbonation effect had a significant influence on the COV of the rebound index. Therefore, the carbonation depth of specimens at the age of 400 days was evaluated. A sum of 3 NVC and 27 HPSCC mixtures was designated for evaluation, selected by, water-powder and water-binder ratios, w/p = 0.29–0.5625 and w/ b = 0.562–0.5–0.45–0.41. Carbonation depth (xc) was observed to range between 1.23 mm and 12.02 mm, proportionally increasing with the increase of the water-binder ratio. The same pattern is observed in terms of rebound index COV. These results confirm Szilági et al. work [4] in term of connectivity between repeatability and carbonation depth (Fig. 12).
5. Conclusion In this paper, a series of experimental tests was applied on 795 cubic specimens with the purpose of understanding the repeatability of the rebound index of several concrete types. The applications reveal that EN 13791 underestimates the compressive strength of concrete. Moreover, results obtained in a such large scattering of coefficients of variation had to be separated and organized based on their designated parameters. Hence the response of the Schmidt hammer in relation to the studied parameters, such as waterbinder ratio, water-powder ratio, SCMs and admixtures, proved their dependency on the deviation of coefficient of variation of the rebound index. Nonetheless, the following conclusions can be drawn from this investigation demonstrated from laboratory tests: The COV of the rebound index is inversely proportional to the mean value of the rebound index. Ultra-high strength and high performance self-compacting concretes show lower rebound index COV values compared to normally vibrated concretes. The rebound index COV is inversely proportional to the waterbinder and water-powder ratios, yet directly proportional to the carbonation depth. Mixtures incorporating supplementary cementitious materials such as metakaolin or silica fume enhanced the repeatability of rebound index by resulting in lower rebound index COV values than reference mixtures. The air entrained HPSCC mixtures showed higher values of rebound index COV than non-air entrained mixtures. The rebound index COV increases proportionally to the porosity measurements (both total and apparent porosity). The increase of the COV of the rebound index is influenced by the carbonation depth of concrete.
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6. Future work This present paper addressed the non-destructive evaluation of laboratory specimens in order to assess the compressive strength of concrete. This study provided an extensive analysis on several parameters affecting the repeatability of the surface hardness of the Schmidt hammer. As UHSC resulted in very low rebound index COV, the predication of UHSC actual compressive strength would be reliable. The next logical step is to investigate structural elements produced with the same materials relevant to our laboratory research. Afterwards, an objective comparison between insitu and laboratory results can be completed in order to verify such behavior. Furthermore, the particle size distribution concerning the aggregate needs a deeper study, since this factor directly affects the empirical relationship. As a general remark, further research is needed to improve the reliability of the use of the Schmidt hammer as a tool for compressive strength assessment. Acknowledgments The authors acknowledge the financial support of the Hungarian Scientific Research Fund (OTKA; Project No. OTKA T 109223). Also, they are grateful for ‘‘LAFARGE” and ‘‘Sika” groups for supplying the materials. References [1] K. Szilágyi, 50 years of experience with the Schmidt, Concr. Struct. (2009) 2– 12. [2] A. Masi, L. Chiauzzi, An experimental study on the within-member variability of in situ concrete strength in RC building structures, Constr. Build. Mater. 47 (2013) 951–961, http://dx.doi.org/10.1016/j.conbuildmat.2013.05.102. [3] K. Szilágyi, A. Borosnyói, I. Zsigovics, Rebound surface hardness of concrete: introduction of an empirical constitutive model, Constr. Build. Mater. 25 (2011) 2480–2487, http://dx.doi.org/10.1016/j.conbuildmat.2010.11.070. [4] K. Szilágyi, A. Borosnyói, I. Zsigovics, Extensive statistical analysis of the variability of concrete rebound hardness based on a large database of 60 years experience, Constr. Build. Mater. 53 (2014) 333–347, http://dx.doi.org/ 10.1016/j.conbuildmat.2013.11.113. [5] K. Szilágyi, Static indentation hardness testing of concrete, Epitoanyag (2011) 2–9, http://dx.doi.org/10.14382/epitoanyag-jsbcm.2011.1. [6] M. Alwash, Z.M. Sbartaï, D. Breysse, Non-destructive assessment of both mean strength and variability of concrete: a new bi-objective approach, Constr. Build. Mater. 113 (2016) 880–889, http://dx.doi.org/10.1016/j.conbuildmat. 2016.03.120. [7] D. Breysse, Nondestructive evaluation of concrete strength: an historical review and a new perspective by combining NDT methods, Constr. Build. Mater. 33 (2012) 139–163, http://dx.doi.org/10.1016/j.conbuildmat.2011.12. 103. [8] K. Szilágyi, A. Borosnyói, I. Zsigovics, Understanding the rebound surface hardness of concrete, J. Civ. Eng. Manage. 21 (2015) 185–192, http://dx.doi.org/ 10.3846/13923730.2013.802722. [9] O.N. Oktar, H. Moral, M.A. Tademir, Factors determining the correlations between concrete properties, Cem. Concr. Res. 26 (1996) 1629–1637. [10] H.N. Atahan, O.N. Oktar, M.A. Tademir, Factors determining the correlations between high strength concrete properties, Constr. Build. Mater. 25 (2011) 2214–2222, http://dx.doi.org/10.1016/j.conbuildmat.2010.11.005. [11] I.M. Nikbin, M.H.A. Beygi, M.T. Kazemi, J. Vaseghi Amiri, S. Rabbanifar, E. Rahmani, S. Rahimi, A comprehensive investigation into the effect of water to cement ratio and powder content on mechanical properties of self-compacting concrete, Constr. Build. Mater. 57 (2014) 69–80, http://dx.doi.org/10.1016/ j.conbuildmat.2014.01.098. [12] G. Barluenga, I. Palomar, J. Puentes, Early age monitoring and hardened properties of SCC with limestone filler and active mineral additions, Constr. Build. Mater. 94 (2013) 728–736, http://dx.doi.org/10.1016/j.conbuildmat. 2015.07.072. [13] Fib Bulletin 3, Structural concrete – textbook on behaviour. Design and performance, Fédération internationale du béton (fib) 3 (1999) 247–248. [14] A. El Mir, S.G. Nehme, Porosity of self-compacting concrete, Proc. Eng. 123 (2015) 145–152, http://dx.doi.org/10.1016/j.proeng.2015.10.071. [15] ACI Committee 228, In-Place Methods to Estimate Concrete Strength Reported, ACI Comm. Reports., 2003, p. 41. [16] BS-EN197-1:2011, Cement – Part 1: Composition, Specifications and Conformity Criteria for Common Cements, Br. Stand., 2011. [17] BS-EN12620:2013, Aggregates for Concrete, Br. Stand., 2013. [18] BS EN 934-2:2009, Admixtures for Concrete, Mortar and Grout, Br. Stand., 2012.
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