To be
published in Proceedings of the 12th International Congress on the
Chemistry of Cement,
Verification, Validation, and
Variability of Virtual Standards
D. P. Bentz1
1National
As the potential of computer modeling of hydration
and microstructure development of cement-based materials approaches realization,
the development of virtual standard
test methods becomes a viable possibility.
In creating these virtual standards, just as with the development of any
physical standard test method, verification, validation (calibration), and
variability must all be considered.
These three issues will be discussed in reference to the ongoing
development of a prototype virtual test method for the heat of hydration of
ordinary portland cement within ASTM subcommittee C 01.26. The virtual test method employs the CEMHYD3D
v3.0 cement hydration and microstructure development model and an early-age
physical measurement of chemical shrinkage (via the ASTM C 1608 test method),
to predict the 7-day and 28-day heat of hydration values in comparison to those
measured via the ASTM C 186 Heat of Hydration test method in recent Cement and
Concrete Reference Laboratory cement proficiency sample programs.
1. Introduction
Test methods for the physical properties of
cement-based materials are one central component of the longstanding and
successful application of these materials in building and construction. Physical test methods exist for the
characterization of the starting materials (fineness, chemical composition), their
properties in the "fresh" state (setting time by Vicat needle, air content,
normal consistency), their properties in the hardened state (compressive
strength, sorptivity), and their durability (freeze/thaw testing, sulfate
attack). Especially in the latter two
cases, the aging times of the specimens prior to or during testing can be quite
long (typically 28 d for compressive strength or heat of hydration, 1 year or
longer for some durability test exposures).
One impetus for the development of virtual test methods is to achieve a
reduction in testing time by predicting the longer term performance from a
virtual test method, alone or in concert with an early age physical test method
[1]. Virtual test methods should also
result in a reduction in material and labor costs, as the amount of physical
testing could be optimized and focused in problematic or promising arenas as
opposed to the mundane but necessary day-to-day quality control type testing.
Computer models that predict physical properties such as heat release,
hydration rates, chemical shrinkage, setting time, compressive strength, and
ionic diffusion coefficients have been developed and integrated into
Internet-accessible packages, such as the Virtual Cement and Concrete Testing
Laboratory (VCCTL) [1-3]. As these
computer models are transformed into virtual standards, appropriate attention
must be paid to their verification, validation, and variability [4-7].
Simply put, verification and validation refer to
"building the model right" and "building the right model", respectively [4, 5].In more formal terms, verification is defined
as "the process of determining that a
model implementation accurately represents the developer's conceptual
description of the model and the solution to the model"[6].
Validation is defined
as "the process of determining the degree
to which a model is an accurate representation of the real world from the
perspective of the intended uses of the model"[6].
A concept related to validation is that of
calibration, which is defined as "the
process of adjusting numerical or physical modeling parameters in the
computational model for the purpose of improving agreement with experimental
data" [6].
Mapping these concepts into the world of physical
test method development, one could define verification as "building the physical
test method right" and validation as "building the right physical test
method."A concrete example can be given
by considering the ASTM C 39 Standard Test Method for Compressive Strength of
Cylindrical Concrete Specimens [8].In
this case, verification would be concerned with assuring that the developed
test method accurately assesses the compressive strength of a concrete cylinder
in a repeatable manner.Specimen end
conditions (grinding, capping, etc.), specimen casting and pre-conditioning,
and specimen loading rates must all be specified along with allowable
tolerances to assure that the test method has been "built right". Conversely, validation would be concerned
with whether measurement of compressive strength of concrete cylinders is an
appropriate measure of the quality of field concrete. Measurement of compressive strength is an
interesting example in that both verification and validation have been
re-examined within the past 15 years in light of ongoing developments in high
strength and high performance concretes.
For example, Carino et al. have considered the effects of a variety of
testing parameters on the measured strengths of high-strength concretes [9-11],
part of the verification process.
Concurrently, the appropriateness of using compressive strength to
characterize a high performance concrete mixture versus using a transport
property or durability test that may be more relevant to long term concrete performance,
such as rapid chloride permeability or freeze/thaw durability, has also been
debated [12] as part of the validation process.
Extending the above concepts to a virtual standard
that is based on an underlying computer model brings us full circle back to the
original definitions of verification and validation, "building the (computer)
model right" and "building the right (computer) model". Verification is now the process of
determining whether the computer model correctly implements the underlying conceptual
model on which it is based. Thus, one of
the major steps in verification is commonly the "debugging" of the computer software. Validation is then the process of determining
whether the implemented and verified computer model accurately represents the
real world, at least for its intended uses.
When a corresponding accepted physical test method already exists,
validation may simply consist of validating that the virtual test method
produces computational results that are statistically indistinguishable from
the measured results of the physical test [7].
Validation may proceed to calibration when one or more model parameters
are adjusted to obtain better agreement between the computational and the
measured results. In this paper, the
development of a prototype virtual test method for the heat of hydration of
portland cement will be presented, with regard being given to verification,
validation, and variability.
2. Experimental
and Modeling
2.1 Verification
In CEMHYD3D v3.0, the conceptual model for heat of
hydration is that the cumulative heat of hydration can be obtained at any age
by multiplying the mass of each phase that has reacted by its enthalpy of
hydration value, summing the results, and dividing by the total mass of
cementitious material. The enthalpies of
hydration employed in the model, as taken from the literature [13-15], are
summarized in Table 1. For this part of
the computer model, verification tasks have included verifying that the correct
coefficients from Table 1 are used with the correct phases in the computer
program and that the executable software does indeed produce the "correct" heat
of hydration values according to the conceptual model for a cement of known
composition.
Table 1. Enthalpy of
Hydration for Major Portland Cement Phases [13-15]
|
Phase |
Enthalpy
(kJ/kg phase) |
|
C3S |
517 |
|
C2S |
262 |
|
C3A |
908, 1672, 1144A |
|
C4AF |
418, 725B |
|
Anhydrite (to gypsum) |
187 |
|
Hemihydrate (to gypsum) |
132 |
A For C3A hydration, values are for
conversion to C3AH6, ettringite, and monosulfate (Afm)
phase, respectively.
B For C4AF hydration, values are for
conversion to C3AH6 and ettringite, respectively.
2.2 Validation
For validating the virtual test method, experimental
data previously generated in the Cement and Concrete Reference Laboratory
(CCRL) proficiency sample program has been employed [16]. Specifically, five different CCRL cements
issued between 1995 and 2004 have been examined.The properties of these cements are
summarized in the cements database included in the VCCTL [2]. Their phase composition, as provided in Table
2, has been determined using a scanning electron microscopy (SEM)/X-ray imaging
technique [17]. For cements 141 and 152,
estimates of the proportions of the various calcium sulfate components (gypsum,
hemihydrate, and anhydrite) have been obtained from X-ray diffraction
analysis. In addition, the particle size
distribution (PSD) of each cement has been measured using a laser diffraction
technique.
Table 2. Composition of CCRL proficiency sample
program
|
Phase |
CCRL 115 |
CCRL 116 |
CCRL 135 |
CCRL 141 |
CCRL 152 |
|
C3S |
0.596 |
0.627 |
0.634 |
0.632 |
0.690 |
|
C2S |
0.218 |
0.207 |
0.162 |
0.106 |
0.088 |
|
C3A |
0.031 |
0.067 |
0.066 |
0.115 |
0.123 |
|
C4AF |
0.095 |
0.034 |
0.078 |
0.073 |
0.038 |
|
Gypsum |
0.060 |
0.065 |
0.060 |
0.026 |
0.027 |
|
Hemihydrate |
Not meas. |
Not meas. |
Not meas. |
0.048 |
0.031 |
|
Anhydrite |
Not meas. |
Not meas. |
Not meas. |
0.000 |
0.003 |
Using the five cements shown in Table 2, the
following prototype virtual test methodology has been examined:
1) obtain a physical sample of the cement of interest
and characterize it with respect to PSD and volumetric phase composition based on
SEM/X-ray image analysis or X-ray diffraction (standards for the PSD and phase
characterization methods are currently being pursued in the ASTM C01.25 and
ASTM C01.23 subcommittees, respectively),
2) prepare a w/c=0.4
(23 oC) cement paste specimen and measure its chemical shrinkage
according to the ASTM C 1608 test method [18], during at least the first 8 h of
hydration; use the measured response to calibrate the kinetics factor, β, that connects to time in the
CEMHYD3D v3.0 computer model [19] for this cement,
3) using the same calibrated kinetics factor, conduct
a virtual heat of hydration experiment (w/c=0.4,
sealed hydration at 23 oC) with CEMHYD3D v3.0 to obtain the 7 d and
28 d (and other) heat of hydration values for comparison to the experimentally
measured values from the ASTM C 186 test method [20],
4) optionally, conduct adiabatic hydrations, etc. to
estimate the adiabatic temperature rise of concrete mixtures of interest
produced with this cement, (beyond the scope of this paper, but illustrated in
a previous publication [21]).
All virtual tests (chemical shrinkage and heat of
hydration) were conducted using the freely available CEMHYD3D version 3.0
software for modeling cement hydration and microstructure development [19]. The CEMHYD3D simulations were conducted under
two sets of starting conditions. In the
first case, the simulations were conducted using the complete available
characterization of the cements, including their phase composition, phase
surface area fractions, and phase correlation functions [2, 17, 19, 22], as
determined from the SEM/X-ray imaging analysis.
In the second case, it was assumed that only their volumetric phase
compositions were available, as would be the case if solely the more widely
available X-ray diffraction were used for cement phase characterization. In the second case, for each of the five
cements, it was assumed that each individual phase's surface area fraction was
equivalent to its volume fraction and the correlation functions from a
previously characterized CCRL cement (cement 133) were used as being
characteristic of each cement. The total
alkali contents of the cements were taken directly from the CCRL summary
reports. For three of the cements (see
Table 3), the readily soluble alkalis (sodium and potassium) were measured in
the NIST laboratory for 1 h old filtered pore solutions; for the other two, the
readily soluble alkalis were assumed to be 80 % of their respective total
alkali values [13]. The measured and
assumed activation energies for the hydration reactions for each cement are
also provided in Table 3.
In general, the simulation of the chemical shrinkage
test (w/c=0.4, T=20 oC to 25 oC, saturated curing) was
executed with a default kinetics factor of 0.00035 [19]. This parameter was then adjusted using a
spreadsheet to provide the best agreement between the model and experimentally
measured chemical shrinkages in the 8 h to 10 h time range, as will be
demonstrated in the Results section. The
adjusted kinetics factors obtained in this manner are also provided in Table 3. This adjusted kinetics factor value was then
used for the subsequent simulation of hydration under sealed conditions for the
heat of hydration virtual test method (w/c=0.4
at 23 oC). In the case of
CCRL cement 152, three separate simulations with independently generated random
starting microstructures were executed to provide some indication of the
variability of the prototype virtual test method when executed as outlined
above.
Table 3.
Parameters used in the CEMHYD3D v3.0 modeling of the hydration reactions
of the five different CCRL cements.
|
CCRL Cement |
CEMHYD3D
(complete characterization) kinetics factor |
CEMHYD3D
(volume only) kinetics factor |
Activation
Energy (kJ/mol) |
Readily-soluble
(1 h)
alkalis |
|
115 |
0.00022 |
0.00023 |
41.3* |
Assumed as 80 % |
|
116 |
0.00043 |
0.00050 |
40.0 * |
Assumed as 80 % |
|
135 |
0.00035 |
0.00035 |
40.0+ |
Measured |
|
141 |
0.00035 |
0.00035 |
40.0+ |
Measured |
|
152 |
0.00027 |
0.00027 |
45.5* |
Measured |
|
152 rep1 |
0.00030 |
0.00032 |
45.5 |
Measured |
|
152 rep2 |
0.00030 |
0.00030 |
45.5 |
Measured |
*Activation
energy measured at NIST by isothermal hydration at 2 or more temperatures [22,
23].
+Activation
energy assumed to be 40.0 kJ/mol based on ASTM C 1074 [24].
3. Results
and Discussion
3.1 Validation
(Calibration)
Fourteen sets of simulations were conducted to
validate the use of the prototype virtual test method for predicting 7 d and 28
d heat of hydration. As stated above, the
chemical shrinkage simulations were compared to experimental results in order
to calibrate the kinetics factor of the CEMHYD3D model. The obtained heat of hydration results in
comparison to those measured in the CCRL proficiency sample testing program are
summarized in Table 4, while representative curves for the experimental and
model chemical shrinkage and heat of hydration are provided in Figures 1 and 2,
respectively. In this preliminary study,
the agreement between calibrated model data and the measured values is quite
reasonable, both for the chemical shrinkage measured according to ASTM C 1608
and the heat of hydration measured according to ASTM C 186, even for the cases
where only the measured phase volume fractions were used as input for the
simulations. It can be observed that better
predictions are obtained when the readily-soluble (1 h) alkalis are directly
measured (cements 135, 141, and 152) than when they are assumed to be 80 % of
the total alkalis (cements 115 and 116).
The worst case agreement between virtual and measured C 186 heat of
hydration is found for the 28 d prediction for cement 116, where the virtual
values based on a complete characterization or a "volume only" characterization
differ from the measured average value by 1.11 and 1.33 (CCRL measured) standard
Table 4. CCRL
measured and CEMHYD3D predicted heats of hydration at 7 d and 28 d for five
different cements from the CCRL proficiency sample program.
|
CCRL
cement |
Age (d)
(# of labs) |
CCRL C186
heat of hyd. (J/g) |
CCRL std. dev. (J/g) |
CEMHYD3D (complete) heat of hyd. (J/g) |
(Meas. dev.) |
CEMHYD3D (volume
only) heat of
hyd. (J/g) |
|Model-Meas.|/ (Meas.
dev.) |
|
115 |
7 (27) |
310.9 |
27.6 |
305.3 |
0.20 |
303.8 |
0.26 |
|
115 |
28 (16) |
368.6 |
21.8 |
346.3 |
1.02 |
345.0 |
1.08 |
|
116 |
7 (27) |
359.8 |
25.9 |
339.6 |
0.78 |
331.3 |
1.1 |
|
116 |
28 (16) |
402.1 |
17.2 |
383.0 |
1.11 |
379.3 |
1.33 |
|
135 |
7 (22) |
326.4 |
21.8 |
327.4 |
0.05 |
327.4 |
0.05 |
|
135 |
28 (15) |
360.2 |
19.2 |
375.0 |
0.77 |
371.6 |
0.59 |
|
141 |
7 (18) |
351.1 |
30.96 |
344.2 |
0.22 |
344.7 |
0.21 |
|
141 |
28 (11) |
380.7 |
36.4 |
399.6 |
0.52 |
398.4 |
0.49 |
|
152 |
7 (22) |
362.8 |
30.96 |
373.6 |
0.35 |
371.5 |
0.28 |
|
152 |
415 |
23.85 |
419.0 |
0.17 |
416.9 |
0.08 |
|
|
152-1 |
7 (22) |
362.8 |
30.96 |
374.2 |
0.37 |
370.8 |
0.26 |
|
152-1 |
28 (18) |
415 |
23.85 |
416.6 |
0.07 |
415.5 |
0.02 |
|
152-2 |
7 (22) |
362.8 |
30.96 |
369.2 |
0.21 |
371.6 |
0.28 |
|
152-2 |
28 (18) |
415 |