2015. március 22., vasárnap

Rebound Surface Hardness of Concrete: Introduction of an Empirical Constitutive Model

Paper published in Construction and Building Materials 25 (2011) 2480-2487

Authors: Katalin Szilágyi PhD; Adorján Borosnyói PhD; István Zsigovics PhD 

Abstract: Surface hardness testing of concrete is a long established NDT method for in-situ strength estimation. Nowadays, the rebound hammer is the surface hardness testing device for concrete of the most widespread use. Based on a comprehensive literature review it was realized that no general theory was developed in the last more than 50 years that could describe the relationship between surface hardness and compressive strength of concrete. The diversity of the numerous empirical proposals that can be found in the technical literature needs to be explained. It can be even found in some publications that the method is suitable only for assessing the uniformity of concrete. There is long a time need for a model that can clarify the rebound surface hardness of concrete. Present paper introduces a phenomenological constitutive model (SBZ-model) that can be formulated for the surface hardness of concrete as a time dependent material property. The generating functions of the model are based on the time dependent development of the capillary pore system of the hardened cement paste in concretes that is characterised by the water-cement ratio as a practical simplification. The modelling assumptions and the use of the model would add to the fundamental understanding of the rebound surface hardness of concrete. An extensive experimental verification study clearly demonstrated the reasonable application possibilities of the SBZ-model.


Keywords: concrete; compressive strength; nondestructive testing; surface hardness; rebound index


1. INTRODUCTION 
In-situ surface hardness testing of materials is an accepted method for strength estimation. Development of surface hardness testing devices goes back more than 100 years. Hardness research was initialized by the pioneering work of Hertz in the 1880’s [1]. Nevertheless, hardness testing was also the first material testing effort from the 1600’s in engineering through scratching hardness testing (1640, Barba; 1722, Réaumur; 1768, Kvist; 1801, Haüy; 1812, Mohs) [2].
In-situ testing of concrete structures was started in the 1930’s. The testing methods at that time covered chisel blow tests, drilling tests, revolver or special design gun shooting tests, splitting tests, pull-out tests, strain measurements from loading tests and the adaptation of the Brinell hardness testing method [3]. This latter technique was found to be the most popular in the European testing practice for decades according to its relatively simple and fast operation [4,5].
Researchers adopted the Brinell method to cement mortar and concrete to find correlations between surface hardness and strength of concrete in the four decades following that Brinell [6] introduced his ball indentation method for hardness testing of steel [7,8,9,10,11]. The first NDT device for in-place testing of the hardness of concrete was introduced in Germany in 1934 which also adopted the ball indentation hardness testing method, however, dynamic load was applied with a spring impact hammer [4]. Similar device was developed in the UK in 1936 by Williams [5]. In the following decades several other NDT instruments were introduced adopting the same method, e.g. pendulum hammer by Einbeck [12] or different methods, e.g. pull-out testing and firearm bullet penetration testing by Skramtajew [3]; drilling method by Forslind [13]; ultrasound pulse velocity method by Long et al. [14].
Nowadays the most widespread method for the surface hardness testing of concrete is the rebound hammer method that is appeared in the 1950’s through the Schmidt rebound hammer (also known as Swiss hammer) [15].
In 1950, Ernst Schmidt developed in Switzerland a spring impact hammer of which handling were found to be superior to the ball penetration tester devices [15]. The hardness testing method of Shore [16] was adopted in the device developed by Schmidt, and the measure of surface hardness is the rebound index rather than the ball penetration. With this development the hardness measurement became much easier, as the rebound index can be read directly on the scale of the device and no measurements on the concrete surface are needed [17]. The original idea and design of the device was further developed in 1952 (using one impact spring instead of two) resulted in simpler use [18,19,20]. Several hundred thousands of Schmidt rebound hammers are in use worldwide [21]. The latest development of the device was finalized in 2007, since the Silver Schmidt hammers are available [22]. The digitally recording Silver Schmidt hammers can also measure coefficient of restitution, CR (or Leeb hardness; see [23]) of concrete not only the original Schmidt rebound index [24].

2. EXPERIENCES OF THE SURFACE HARDNESS OF CONCRETE 
Rebound surface hardness measurements were found to be very popular in the in-situ material testing due to the inexpensive testing devices and their relatively simple use. Numerous publications are available in the technical literature concerning experimental results and analyses.
Aim of rebound hammer tests of concrete is usually to find a relationship between surface hardness and compressive strength with an acceptable error. For the rebound method no general theory was developed that can describe the relationship between measured hardness values and compressive strength, nevertheless, it is deemed in some technical papers that the behaviour is commonly understood. The existence of only empirical relationships was already considered in the earliest publications [19,25] and also recently [26]. In the opinion of the authors of present paper, finding a good fit regression curve does not necessarily mean the understanding of the behaviour.
It should be emphasized that the concrete construction practice needs in-place NDT equipment provided together with simple, easy-to-use, generalized relationships (in the form of equations, graphs or tables) which express the measured value (e.g. rebound index) as a value of the concrete compressive strength of standard specimens. Such generalized relationships, however, usually could not accurately characterize the concrete in the structure being tested.
Generalized relationships are allowed to be used only if their validity has been established by tests carried out on concrete similar to that being investigated and with the same type of testing device that is intended to be used in the investigation.

Fig. 1. Rebound surface hardness vs. compressive strength relationships from the technical literature (represented as standard cube strength).

In Fig. 1 a demonstration is presented regarding the empirical relationships found by several researchers for concrete strength estimation with rebound hardness method in the last 60 years. Due to space limitations only 30 of the available curves are shown, however, more than 60 can be found in the technical literature. Data is given in the graphical representation of Fig. 1 with a correction to provide results for 150 mm standard cubes. For the sake of better visualization results are separated by their relation to the strength estimation curve that is recommended by the manufacturer of the original Schmidt rebound hammers for the N-type rebound hammers [43], as follows:
-     Proposed curves running continuously over the manufacturer’s curve (Fig. 1a),
-     Proposed curves running continuously under the manufacturer’s curve (Fig. 1b),
-     Proposed curves intersecting the manufacturer’s curve coming from below (Fig. 1c),
-     Proposed curves intersecting the manufacturer’s curve coming from above (Fig. 1d).
Compositions of the proposed empirical relationships are linear relationships, power function relationships, polynomial relationships, exponential relationships or logarithm relationships. The proposed curves are usually valid for 28 to 365 days of age, conventional, normal weight concretes under air dry moisture condition. It can be realized that the concrete strength can be estimated at certain rebound indices by a ±40-60 N/mm2 variation. Results clearly demonstrate that the validity of a proposal should be restricted to its testing conditions and an extension of the validity to different types of concretes or testing circumstances is impossible. It is also worth to mention that several linear estimations can be found among the proposals. It is possible when the strength range is chosen to be narrow in the experimental tests, e.g. [53]. Rigorous experiments always resulted in nonlinear relationships since the very beginning of rebound surface hardness testing of concrete. The formulation of a phenomenological constitutive model for the rebound surface hardness of concrete is therefore of high interest.

3. HETEROSCEDASTIC DATA OR MISCOMMUNICATED DATA
The rebound index vs. strength relationship can be determined if the experimental data are available. The usual practice is to consider the average values of the replicate compressive strength and NDT results as one data pair at each strength level. The data pairs are presented in a way that the NDT value is the independent variable (along the X axis) and the compressive strength is the dependent variable (along the Y axis). Regression analysis is performed as a conventional least-squares analysis on the data pairs to obtain the best-fit estimate for the strength relationship. The technical literature calls the attention that the boundary conditions of the conventional least-squares analysis are violated in the case of rebound index vs. strength relationships [54]. The conventional least-squares analysis is not recommended because the uncertainty in the strength relationship could be underestimated.
Statistical analysis of the surface hardness vs. compressive strength relationships usually also indicates heteroscedastic behaviour; i.e. increasing standard deviation in strength (Y variable) for increasing rebound index (X variable). Even the manufacturer of the original design rebound hammers suggests increasing standard deviations to be taken into account for increasing rebound indices [43]. Examples for the heteroscedastic behaviour are indicated in Fig. 2 [18] and Fig. 3 [55].

Fig. 2. Heteroscedastic behaviour of the rebound surface hardness vs. compressive strength relationship (based on [18]). Note: 1 psi = 6,894×10-3 N/mm2.

Fig. 3. Heteroscedastic behaviour of the rebound surface hardness vs. compressive strength relationship (based on [55]). Note: 1 psi = 6,894×10-3 N/mm2.


It should be highlighted that researchers usually do not separate the experimental data of the corresponding rebound index vs. compressive strength results by different influencing parameters in the graphical representations – and the situation has not changed during the last 60 years. Therefore, exclusively the one-parameter regression curves are available in the technical literature that was introduced in Section 2. Surface hardness and compressive strength of concrete, however, are depending on several parameters (e.g. type of cement, amount of cement, type of aggregate, amount of aggregate, compaction of structural concrete, type of formwork, method of curing, quality of concrete surface, age of concrete, carbonation depth in the concrete, moisture content of concrete, mass of the structural element, temperature and state of stress) of which influences may be represented when a two- or more-parameter regression analysis is carried out.
The most significant influencing parameters for the compressive strength of normal weight concretes are the water-cement ratio, the type of cement and the age of the concrete. The amount of cement, the amount of aggregate, the storing method and further concrete technology parameters have only secondary influences. The type and amount of aggregate can have significant influence in the case of lightweight aggregate concretes.
It is shown here as an example that non-separation of experimental data can lead to completely misleading trends of the analysis and the separation of experimental data can clearly uncover the real material behaviour and, therefore, gives the only way to understand the mechanisms of the rebound surface hardness testing of concrete. Two from the earliest publications are referred as examples, i.e. papers by Schmidt and Herzig [17,56]. Both papers are based on detailed laboratory tests carried out at EMPA Laboratories, Switzerland. Schmidt analysed in his paper the experimental results of 550 cube specimens tested both for rebound surface hardness and compressive strength. The non-separated results are adopted in Fig. 4 where the one parameter regression curve power function is represented together with the lower and upper bound curves based on the reported deviations from the mean values. It can be realized that an apparent heteroscedastic behaviour appears when the compressive strength of concrete is represented as a dependent variable of the rebound surface hardness. Herzig presented the experimental results from the same tests but the data were separated by the amount of cement, the storing method and the age of concrete at testing. As a primary influence, the separation by the age of concrete provides high-contrast differences. Three typical curves are indicated in Fig. 5a. Authors of present paper adopted Herzig’s results in Fig. 5b also as one population of data to highlight the possibility to find a false empirical regression curve corresponding to rebound surface hardness vs. compressive strength responses as non-separated data. It can be observed that a strong correlation of a power function resulted. Here, the heteroscedastic behaviour is not pronounced as the data covers only 56 data pairs and not the complete test result of the 550 cubes. It can be realized from Herzig’s original, separated data analysis that further primary influences could come into play besides the age of concrete (e.g. water-cement ratio) not mentioned in his analysis.

Fig. 4. Heteroscedastic behaviour of the rebound surface hardness vs. compressive strength relationship (based on [17]).


Fig. 5. Influences of data separation on the rebound surface hardness vs. compressive strength relationship (based on [56]).
a) selected data separated by cement amount and storage of specimens
b) all data points in non-separated representation


4. GENERATING A PHENOMENOLOGICAL CONSTITUTIVE MODEL
 The primary factor that governs the characteristics of cementitious materials is porosity. It was found experimentally that the development of the porosity in concrete can be described reasonably well by the gel-to-space ratio [57]. It is necessary to know the degree of hydration in the hardened cement paste to work with gel-to-space ratio, therefore, the water-cement ratio (w/c) is a much more practical measure for the porosity of concrete [58]. For practical purposes it can be accepted that the water-cement ratio (w/c) determines the capillary porosity of a properly compacted concrete at any degree of hydration [59]. As a consequence, strength and related properties of concrete can be accepted to depend primarily on the w/c ratio as it was realized more than 100 years ago [60,61]. Surface hardness of concrete is also considerably influenced by the w/c ratio in addition to the modulus of elasticity of the aggregate particles (which is usually considered to be constant in time). The interaction volume (i.e. the volume of hardened cement paste adjacent to the testing device contact) plays the most important role in hardness testing; being several mm in depth for rebound hardness testing. Hydration of clinker minerals in the hardened cement paste makes the per se heterogeneous concrete to be a material with time dependent properties. Transport phenomena (mostly of carbon-dioxide) in the near surface zone of concrete structures have also considerable influence on the rebound hardness characteristics through the chemical reaction referred as carbonation, whenever the hydrated lime content of the hardened cement paste forms limestone due to the chemical reaction with carbon-dioxide [53,62]. Based on the above general behavioural scheme, a phenomenological constitutive model (SBZ-model; the abbreviation is indicating the names of the authors) can be formulated for the surface hardness of concrete as a time dependent material property.
The generation scheme of the SBZ-model as well as the symbolic shapes of the individual functions given by Eq. (1) to Eq. (5) can be studied in Fig. 6


Fig. 6. The generation scheme of the SBZ-model.


The formulation of the model includes the following experimental findings:
A) The compressive strength of concrete at the age of 28 days can be described by an exponential function of the w/c ratio (Eq. 1).

 Eq. (1)
                                                                                
with
a1 > 1
a2 < 0
0 < a3 < 1


B) The development of the compressive strength of concrete with time can be followed by an exponential function of time (Eq. 2).

 Eq. (2)
                                                                    
with
0 < a4 < 1
0 < a5 < 1
and both parameters a4 and a5 are a function of w/c


C) An empirical relationship of a power function can be assumed between the strength of concrete and the rebound index at the age of 28 days (Eq. 3).

                                                                                                 Eq. (3)
with
a6 > 0
a7 ≥ 1


D) The development of the carbonation depth (xc) in concrete with time can be described by models based on Fick’s law of diffusion (Eq. 4).

 Eq. (4)
                                                                                   
with
0 < a8 < 1
0 < a9 < 1
0 < a10 < 1


E) Carbonation of concrete results an increase in the surface hardness that can be assumed to be modelled by a power function of the carbonation depth (Eq. 5).

 Eq. (5)
                                                                                     
with
a11 < 0
a12 > 0

The SBZ-model can provide corresponding compressive strength fc(t) and rebound index R(t) values for any w/c ratio at any age of concrete (t).
A typical fc(t) vs. R(t) relationship is represented in Fig. 7: the output of the model is a set of curves corresponding to different w/c ratios at different ages of the concrete. It should be noted that the shape and curvature of the individual curves are depending on the actual values of the twelve empirical constants a1 to a12 covered in Eqs. (1) to (5) and Fig. 7 indicates a possible general case.
It can be realized that the SBZ-model provides a reasonable depiction of the rebound surface hardness of concrete as a time dependent material property. It should be also noted that the SBZ-model gives a clear explanation for the experimental findings about the apparent heteroscedastic behaviour of the rebound index vs. compressive strength data pairs. The SBZ-model calls the attention that the graphical representation of the experimental results should not be carried out by the simplifying assumption that concretes of different w/c ratios and different ages provide data being in the same population. It can be clearly seen that the simplification could result misleading representation and the influencing parameters should be separated in the graphical visualization as it is suggested by the SBZ-model.

Fig. 7. Typical schematic fc(t) vs. R(t) response as an output of the SBZ-model: a set of curves corresponding to different w/c ratios at different ages of the concrete.


5. EXPERIMENTAL VERIFICATION OF THE SBZ-MODEL
 An extensive experimental study was carried out at the Budapest University of Technology and Economics (BME), Department of Construction Materials and Engineering Geology for the verification of the developed SBZ-model. The tested concrete mixes in the experiments were prepared in accordance with present concrete construction needs, i.e. slightly over-saturated mixes with different admixtures were designed. Danube sand and gravel was used as aggregate. Consistency of the tested concrete mixes was constant: 500±20 mm flow. Design air content of the compacted fresh concrete for the tested concrete mixes was 1.0 V%. The specimens were cast into steel formworks and the compaction of concrete was carried out by a vibrating table. The specimens were stored in water tank for 7 days as curing. After 7 days the specimens were stored at laboratory condition (i.e. 20±3°C temperature and 65±5% relative humidity). Test parameters were:
Water-cement ratio:
0.38 – 0.41 – 0.43 – 0.45 – 0.47 – 0.50 – 0.51 – 0.55 – 0.60
Cement type:
CEM I 42.5 N – CEM II/A-V 42.5 N – CEM III/B 32.5 N
Cement content (kg/m3):
300 – 350 – 400
Mixing water content (kg/m3):
150 – 165 – 180
Cement paste content (litres/m3):
247 – 263 – 278 – 293 – 309
Aggregate-cement ratio:
4.5 – 4.6 – 4.7 – 5.3 – 5.4 – 5.5 – 6.3 – 6.5 – 6.6
Admixture type:
accelerator admixtures (3 types)
Age of concrete at testing (days):
7 – 14 – 28 – 56 – 90 – 180
The experimental programme made possible a detailed verification study to be carried out on a wide range of compressive strengths and ages of concrete at testing. Total number of 864 specimens (150 mm cubes) were tested at six different ages for present verification study. Typical results are indicated in Fig. 8 corresponding to concrete specimens prepared with CEM I 42.5 N cement. Fig. 8 represents test results for only 104 specimens. 


Fig. 8. Experimental verification of the SBZ-model on concrete cube specimens prepared with CEM I 42.5 N cement.
a) data in non-separated representation
b) data separated by the applied water-cement ratios
c) data represented together with the fitted SBZ-model

The following observations can be emphasized:
1) An apparently coherent population of data is resulted if one does not differentiate water-cement ratios and ages of concrete in the graphical representation of test data (Fig. 8a). A completely misleading trend of results is realized and an apparent power function or exponential function relationship can be the output of a regression analysis (usually with considerably good correlation coefficients which further ratifies the misleading direction of the analysis). In Fig. 8a 52 data points are indicated as the pair-averages of the 104 specimens (covering 9 different water-cement ratios and 6 different ages of concrete at testing). Regression curve of an exponential function is also indicated. The correlation coefficient was found to be r2 = 0.84 for this false relationship.
2) An apparent heteroscedastic behaviour of the rebound index vs. compressive strength data pairs is realized if one does not differentiate water-cement ratios and ages of concrete in the graphical representation of test data (Fig. 8a). It can be studied in Fig. 8a that the distance between the lower and upper limit curves corresponding to the increasing rebound index values is increasing that can result the apparent heteroscedasticity (i.e. increasing standard deviation in strength for increasing rebound index).
3) The real performance appears only if one separates the rebound index vs. compressive strength data pairs by the water-cement ratio (Fig. 8b). For the sake of better visualisation only 5 curves are represented in Fig. 8b from the 9 different water-cement ratios studied. It can be realized that the apparently coherent population of data comes loose to separate monotonic curves for the different water-cement ratios.
4) It can be seen in the real performance that rebound index vs. compressive strength relationships are sensitive (but not uniformly) to the water-cement ratio applied (Fig. 8b). The gradients and directions of the responses clearly indicate the influence of the capillary pores of different water-cement ratios on the strength development and carbonation depth development differences. It can be postulated that the water-cement ratio dependent strength development and carbonation depth development behaviour of concretes gives the complete explanation of the observed results. Results of the verification study confirmed that the most significant influencing parameters are the water-cement ratio, the type of cement and the age of the concrete. The cement content, the aggregate content, the cement paste content and further parameters have much less pronounced influences; as it was presumed.
5) The application of the SBZ-model is reasonable for the rebound index vs. compressive strength data (Fig. 8c). A suitable fit of the empirical parameters of the SBZ-model can result an acceptable numerical reproduction of any experimental data. The detailed verification study demonstrated the applicability of the SBZ-model for CEM I 42.5 N, CEM II/A-V 42.5 N and CEM III/B 32.5 N cements on a wide range of water-cement ratios and ages of concrete at testing (further details of the verification is to be presented separately due to the space limitation of present paper). The SBZ-model also provides a clear understanding of the rebound surface hardness of concrete as a time dependent material property. Based on its composition the SBZ-model is deemed to be a unique constitutive model available now for the rebound surface hardness of concrete.


6. FUTURE WORK
 The theoretical considerations covered in the development of the SBZ-model were confirmed by the extensive experimental verification introduced in Section 5. However, further studies are needed for the ratification of the SBZ-model for practical applications. The SBZ-model provides a clear and transparent explanation to the rebound surface hardness of concrete in its introduced form. The observations predict that the general scheme of the SBZ-model allows an extension of the model also for concretes older than 180 days. It was found that the predictions made by the SBZ-model are far more accurate than that was available earlier by simple regression analyses. On the other hand, the number of the empirical constants included in the SBZ-model may result a challenging parameter fitting work before any practical application. Further types of concretes should be studied in the future to be able to find simplification possibilities. Typical form of generating functions should be clarified and the limits of the practical application should be determined. It is to be highlighted, however, that the main purpose of the development of the SBZ-model was to provide a better understanding of the rebound surface hardness of concrete and to explain the experimental findings. The direct practical application of the model is not started yet. Authors are working on further developments and hope that the SBZ-model can be successfully used in practice in the future.


7. CONCLUSIONS
 Rebound surface hardness testing of concrete is one of the most widespread NDT methods for in-situ strength estimation of concrete structures. Rebound surface hardness methods are available in the civil engineering testing practice for more than 60 years. However, understanding and modelling of the rebound surface hardness of concrete as a time dependent material property is not available in the technical literature.
Present paper introduces the SBZ-model developed by the authors of the paper which is a phenomenological constitutive model for the rebound surface hardness of concrete as a time dependent material property. Origination of the SBZ-model is based on the time dependent development of the capillary pore system of the hardened cement paste in concretes that is characterised by the water-cement ratio as a practical simplification. The model covers the following empirical material laws: relationship between the water-cement ratio and the compressive strength of concrete at the age of 28 days; development of the concrete compressive strength in time; relationship between the compressive strength of concrete and the rebound index at the age of 28 days; the development of carbonation depth of concrete in time; the influence of carbonation depth of concrete on the rebound index.
An extensive experimental verification of the SBZ-model clearly demonstrated its reasonable application possibilities for CEM I 42.5 N, CEM II/A-V 42.5 N and CEM III/B 32.5 N cements on a wide range of water-cement ratios (w/c = 0.38 to 0.60) and ages of concrete at testing (7 to 180 days). The transparency of the SBZ-model offers further promising development, however, provides also in its present form the long time missing fill to the gap of knowledge appeared in the last 60 years.


8. ACKNOWLEDGEMENTS
The authors gratefully acknowledge the support of the Bolyai János research scholarship by the Hungarian Academy of Sciences (MTA). Special thanks to Ms. Beáta Horváth, Mr. Tamás Kasza and Mr. Tamás Póka for their valuable help during the laboratory tests. The authors appreciate very much the detailed discussions of Dr. Attila Erdélyi.


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In memoriam of our colleague, mentor and friend, 
István Zsigovics PhD, who has left us so early.
1949-2015
Dear István, thank you for everything.
May your soul rest in peace.

K. Szilágyi, A. Borosnyói


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