aci 207.2 R Pdf Free Download
Over the years, many different simplified prediction methods have been developed to predict the temperature development within mass concrete members. This paper compares calculated temperature values from three commonly-used concrete temperature prediction methods to actual temperatures in eight different concrete bridge members measured during construction. A simple temperature calculation method, the graphical method of ACI 207.2R, and a numerical heat transfer method (the Schmidt Method) were used to predict peak temperatures. The Schmidt Method performed the best when semi-adiabatic calorimetry results were used in the analysis. Suggestions are made on ways to improve the best technique, which was the Schmidt Method.
Figures - uploaded by Kevin J. Folliard
Author content
All figure content in this area was uploaded by Kevin J. Folliard
Content may be subject to copyright.
Discover the world's research
- 20+ million members
- 135+ million publications
- 700k+ research projects
Join for free
ACI Materials Journal/September-October 2006 357
ACI MATERIALS JOURNAL TECHNICAL PAPER
ACI Materials Journal, V. 103, No. 5, September-October 2006.
MS No. 05-116 received April 20, 2006, and reviewed under Institute publication
policies. Copyright © 2006, American Concrete Institute. All rights reserved, including
the making of copies unless permission is obtained from the copyright proprietors.
Pertinent discussion including authors' closure, if any, will be published in the
Jul y-A ugu st 2007 ACI Materials Journal if the discussion is received by April 1, 2007.
Over the years, many different simplified prediction methods have
been developed to predict the temperature development within
mass concrete members. This paper compares calculated temperature
values from three commonly-used concrete temperature prediction
methods to actual temperatures in eight different concrete bridge
members measured during construction. A simple temperature
calculation method, the graphical method of ACI 207.2R, and a
numerical heat transfer method (the Schmidt Method) were used to
predict peak temperatures. The Schmidt Method performed the
best when semi-adiabatic calorimetry results were used in the
analysis. Suggestions are made on ways to improve the best
technique, which was the Schmidt Method.
Keywords: heat; mass concrete, temperature.
INTRODUCTION
Cement hydration is an exothermic reaction capable of
generating large amounts of heat. The core of mass concrete
members can become very hot unless internal cooling or
low-heat-producing materials are used. This has historically
been a problem in dams, and numerical methods of
predicting temperatures throughout mass concrete elements
have been available since the 1920s. The current state of the
practice in dams is to perform adiabatic calorimetry testing
on concrete mixtures and use finite element analysis to
predict temperature distributions over time.
Until recently, it was assumed that high temperatures were
not a problem in bridge substructure members, and that this
problem was unique to dams and precast concrete. In recent
years, however, bridge substructure members have become
larger because of new construction methods and aesthetic
interests. At the same time, cement fineness and cement
content in concrete have increased, raising the concrete's
adiabatic temperature. As a consequence, there is increased
concern over thermal cracking in bridge substructure
members, long-term decrease in strength, and delayed
ettringite formation (DEF) (a mechanism that causes
cracking in concrete when ettringite formation is delayed by
high temperatures).1 In response to a survey conducted in
2003, nine state highway agencies (SHAs) had mass
concrete specifications and eight states had mass concrete
special provisions. Seven of the states with mass concrete
specifications limit the maximum concrete temperature
difference to 20 °C (35 °F), and two states limit the
maximum in-place temperature to 71 °C (160 °F). Six of the
eight states with mass concrete special provisions have
maximum concrete temperature difference limits, and three
have maximum in-place temperature limits.2
The Texas Department of Transportation (TxDOT)
Specification 420,3 for example, defines mass concrete as
any member having a least dimension of 1.5 m (5 ft), or as
designated by the engineer. Many bridge substructure
components in Texas now meet that definition. TxDOT
Specification 420 limits mass concrete placement tempera-
ture to 24 °C (75 °F), the maximum in-place temperature to
71 °C (160 °F) (to avoid DEF), and the maximum tempera-
ture difference in the concrete to 20 °C (35 °F). Contractors
are required to submit a temperature control plan for mass
concrete before construction begins. All concrete temperature
prediction calculations in the temperature control plan must
be made using the methods described in Portland Cement
Association's (PCA) Design and Control of Concrete
Mixtures,4 or using the Schmidt Method as described in the
American Concrete Institute's ACI 207.1R.5 The measurement
of temperatures at two separate locations is also required. If
the concrete temperature exceeds any of the specifications,
adjustments to the temperature control plan are required to
ensure compliance with the specification.
Contractors need quick, simple, accurate, up-to-date
methods or software to evaluate the impact of different
viable options for temperature control and to develop their
temperature control plans. Several methods, such as the
Schmidt Method, have been used successfully over the years
to calculate the temperature rise in very large mass concrete
members.5 For these large mass concrete members, the
maximum temperature of the concrete is primarily a function
of the concrete's adiabatic temperature rise potential. In
smaller mass concrete bridge members, the maximum
temperature is a function of the adiabatic temperature
development and heat transfer with the environment.
This paper evaluates the ability of the two temperature
prediction methods allowed by TxDOT (which we will refer
to as the PCA Method and the Schmidt Method), as well as
the graphical method described in ACI 207.2R,6 Section 2,
to predict the maximum temperature in smaller mass
concrete bridge members. The predicted maximum temperature
from each method will be compared against actual temperature
data from mass concrete bridge members recently
constructed in Texas. Various concrete members were
selected for temperature instrumentation based on their location,
environmental exposure condition, size, formwork used,
mixture proportions, and shape. Two columns, two footings,
one pedestal, one dolphin (a mass concrete structure that
protects bridges from ship impact), one rectangular bent cap,
and one T-shaped bent cap were instrumented.
Title no. 103-M40
Evaluation of Temperature Prediction Methods for Mass
Concrete Members
by Kyle A. Riding, Jonathan L. Poole, Anton K. Schindler, Maria C. G. Juenger,
and Kevin J. Folliard
ACI Materials Journal/September-October 2006 358
RESEARCH SIGNIFICANCE
The commonly-used temperature prediction methods
discussed in this paper were developed over 50 years ago.
Construction methods, form types, cement chemistry,
cement fineness, supplementary cementing materials
(SCMs), and chemical admixtures have changed dramatically
since then, suggesting that these methods may no longer be
appropriate or may need to be updated. The use of mass
concrete members has also increased in recent years,
creating a need for accurate temperature prediction. In the
research presented herein, the accuracy of three commonly
used mass concrete temperature calculation methods is
assessed by their ability to predict maximum temperatures in
eight actual mass concrete bridge members.
BACKGROUND INFORMATION
Maximum temperature
The maximum in-place temperature reached in a mass
concrete member can affect the long-term performance of a
structure. Studies have shown that plain cement paste cured
above 50 °C (122 °F) can, in the long term, have lower
strength, larger pores, and increased permeability.7 Delayed
ettringite formation (DEF) has also been shown to cause
durability problems when concrete is cured at elevated
temperatures (for example, temperatures in excess of 70 °C
(158 °F)). The rate of temperature increase, duration of the
induction period, maximum temperature, and cooling rate
are all factors that may determine the extent of damage from
DEF.1 The time reached and magnitude of the maximum
temperature are critical in determining the maximum
temperature difference.
Maximum temperature difference
Large temperature differences can occur when the
concrete core is hot and the ambient temperature is low or
when the forms are removed when the concrete underneath
is hot, typically referred to as "thermal shock."5 The
maximum temperature difference causes a change in volume
because of thermal expansion/contraction and can affect
thermal cracking in concrete when the member is restrained
by adjacent elements or foundations.
The current TxDOT specification 420 is based on guide-
lines developed for mass concrete projects in Europe during
the 1950s.8 Gajda and VangGeem8 suggest that the
maximum allowable temperature differential should
increase with the compressive strength. Bamforth and Price9
developed the following equation to calculate the maximum
allowable temperature differential
(1)
where ΔT is the maximum temperature difference, in °C; εtsc
is the tensile strain capacity; K is a modification factor for
sustained loading and creep; αc is the coefficient of thermal
expansion of the maturing concrete (1/°C); and R is the
restraint factor. Aggregate type, cement content, supplementary
cementing materials, amount of reinforcement, and reinforcement
detailing will all alter the temperature difference that will
cause thermal cracking.9-11 Concrete properties, such as the
coefficient of thermal expansion, tensile strength, and
modulus of elasticity, are all time- and temperature-dependent
and, thus, may affect the concrete's cracking susceptibility as
the concrete matures.
Several researchers have found that simple, temperature-
difference-based specifications are unreliable for controlling
thermal cracking in concrete elements.12-14 The tensile
strength of the concrete is also a function of the concrete's
maturity. The thermal gradient required to produce cracking
is consequently also a function of the concrete's maturity.
Temperature-based specifications fail to take into account
the intrinsic stresses that can develop. Residual stresses at
the concrete surface are less pronounced when the surface is
cooled at a very young age for a sufficient period of time.15
This means that a concrete member could, in some
circumstances, have a low risk of cracking while at the same
time have a high temperature difference, if the large temperature
difference occurs at a late age. The temperature development
during the first day is typically the most critical parameter in
determining the thermal cracking risk.13,15
PCA Method
The Portland Cement Association's (PCA) Design and
Control of Concrete Mixtures4 gives a quick method for
estimating the maximum temperature developed in mass
concrete members. This method will be referred to in this
paper as the "PCA Method." This method calculates the
maximum temperature rise above the concrete placement
temperature, as 12 °C (21.6 °F) for every 100 kg (220.4 lb)
of cement. The PCA Method is only appropriate for concrete
containing between 300 and 600 kg of cement per cubic
meter (506 and 1012 lb per cubic yard) of concrete and
assumes that the least dimension of the concrete member is
at least 1.8 m (6 ft).4 The PCA Method provides no information
on time of maximum temperature and does not allow the
quantification of temperature differences. The PCA Method
treats all ASTM C 15016 Type I cements the same and gives
no guidelines on how to account for slag cement. ACI
Committee 207 suggests that modification to account for
supplementary cementing materials (SCMs) can be made by
presuming that they liberate approximately half the amount
of heat of cement for a given mass.5 Equation (2) shows the
PCA calculation for the maximum concrete temperature
Tmax when altered to account for the initial placement
temperature and SCMs in this manner
ΔT ε tsc
Kα c R
------------- -=
ACI me mber Kyle A. Riding is a PhD Candidate at the University of Texas at Austin,
Austin, Tex. He received his BS from Brigham Young University, Provo, Utah, and his
MS from The University of Texas at Austin.
ACI member Jonathan L. Poole is a PhD Candidate at the University of Texas at
Austin. He received his BS and MS from The University of Texas at Austin.
ACI me mber Anton K. Schindler is an Assistant Professor in the Department of Civil
Engineering at Auburn University, Auburn, Ala. He received his MSE and PhD in
civil engineering from the University of Texa s a t A us t in . He is a member of ACI
Commi ttees 201, Durability of Concrete; 231, Properties of Concrete at Early Ages;
237, Self-Consolidating Concrete; and E 803, Faculty Network Coordinating Committee.
ACI member Maria C. G. Juenger is an Assistant Professor of Civil, Architectural,
and Environmental Engineering at The University of Texas at Austin. She received a
PhD in materials science and engineering from Northwestern University, Evanston,
Ill. She is a member of ACI Committees 201, Durability of Concrete; 236, Material
Science of Concrete; and E 802, Teaching Methods and Educational Materials.
Kevin J. Folliard, FACI, is an Associate Professor in the Department of Civil,
Architectural, and Environmental Engineering at The University of Texas at Austin.
He received his PhD in civil engineering from the University of California at Berkeley,
Berkeley, Calif., in 1995. He is a member of ACI Committees 201, Durability of
Concrete; 236, Material Science of Concrete; and the ACI Publications Committee.
He received the ACI Young Member Award for Professional Achievement in 2002.
ACI Materials Journal/September-October 2006 359
(2)
where Ti is the concrete placement temperature, in °C; Wc is
the weight of cement, kg/m3 ; and Wscm is the weight of
supplementary cementing materials, kg/m3 .4 Significant
modifications have been made by Bamforth and Price,9 who
designed charts to correct for member size of less than 2 m
(6.6 ft) (least dimension) and to account for fly ash and slag
cement contents. The charts show temperature rise curves
per 100 kg (220 lb) of cementitious materials for different fly
ash and slag cement replacement levels as a function of the
placement thickness.
Graphical method of ACI 207.2R
Section 2 of ACI 207.2R6 contains several charts and
equations based on empirical data that can be used to estimate
the maximum temperature in mass concrete, hereafter
referred to as the "Graphical Method of ACI 207.2R."
Adjustments can be made for member size, exposure condition,
cement type, use of fly ash and/or slag cement, and placement
temperature. The adiabatic temperature rise can be
accounted for by Eq. (3).
(3)
where Tr is the cement Turbidimeter (ASTM C 115) fineness
adjusted adiabatic temperature rise for 171 kg (377 lb) of
cement, in °C; TI is the adiabatic temperature rise for a
Type I cement from ACI 207.2R, Fig. 2.1; Tf is the heat
generation in percent of 28-day heat generation for the
measured cement fineness from ACI 207.2R, Fig. 2.2; and
T1800 is the heat generation in percent of 28-day heat generation
for a cement fineness of 1800 cm2 /g (6.15 in.2 /lb) from
ACI 207.2R, Fig. 2.2.6 Detailed examples showing the
correct use of these charts and equations are given within
ACI 207.2R document.
Schmidt Method
Another method for estimating maximum temperature
and maximum temperature differences was developed by
E. Schmidt in the 1920s and is summarized in ACI 207.1R.5
This method will be referred to in this paper as the "Schmidt
Method." It was an important contribution in the precomputer
era because the calculations were relatively simple to perform
by hand. It was developed as a numerical solution to the
Fourier law governing heat transfer, shown in Eq. (4)
(4)
where QH is the heat generation term, W/m3 ; ρ is the density,
in kg/m3 ; Cp is the specific heat, in J/kg/°C; and T is the
temperature, in °C. The Schmidt Method is a simplified
finite difference method. Temperatures are calculated for
discrete nodes at discrete time steps. The time step is calculated
according to Eq. (5)17
(5)
Tmax Ti 12 W c
100
-------- - ⋅
⎝⎠
⎛⎞
6Wscm
100
----------- - ⋅
⎝⎠
⎛⎞
++ =
Tr TI
Tf
T1800
-----------
⋅ =
d
dx
----- -kdT
dx
------ ⋅
⎝⎠
⎛⎞
d
dy
----- -kdT
dy
------ ⋅
⎝⎠
⎛⎞
QH
++ ρCp
dT
dt
------ ⋅⋅ =
Δt Δx ()
2
2α
------------- =
where α is the thermal conductivity of the concrete, in
W/m/°C; Δt is the time step used, in seconds; and Δx is the
node spacing, in m.
ACI 207.1R4 gives guidance on how to handle boundary
conditions using the Schmidt Method, but only for those
boundaries next to the bottom surface of the element. For
instance, Example 6 given in ACI 207.1R5 provides an
example of the use of the Schmidt Method using the case of
a footing on a rock foundation. The example assigns half of
the temperature rise of the concrete under adiabatic temperature
conditions, to the bottom surface. A constant rock temperature is
usually enforced at a depth, which is assumed to extend a
distance equal to one-half of the concrete member height.
Insulation is also modeled by using an equivalent concrete
thickness. Example 6 also describes the common approach
used to account for the heat generation of the cementitious
material. The temperature added at each node for each time
step is the adiabatic temperature rise for that time, minus the
adiabatic temperature rise for the previous time.
EXPERIMENTAL METHODS
Concrete bridge members
Eight mass concrete bridge members were instrumented to
allow for the comparison of actual and predicted concrete
temperatures. The members were selected to obtain a large
variety of size, shape, formwork, environmental exposure
conditions, constituent materials, and mixture proportions.
Table 1 shows the concrete member locations, dimensions,
placement information and formwork type. There are several
items to note with regard to these members. The dimensions
given in Table 1 for the T-shaped bent cap are for the outer-
most dimensions. The corbel dimensions were 0.65 x 0.65 m
(25 x 25 in.). A large quantity of rigid polyurethane foam was
used to create an arch on the middle bottom of the T-shaped
bent cap. The foam was left in place for several days after
removing forms, which reduced the chances of thermal
shock. The rectangular and T-shaped bent cap lengths are not
listed, but were greater than 20 times the member width or
height. To facilitate concrete placement, the bottom two feet
of the dolphin was made using precast concrete panels. All
three columns were rectangular with 0.15 x 0.3 m (6 x 12 in.)
block-outs on the corners for aesthetic purposes. The block-
outs were made from plywood. Column 1 had a 203 mm (8 in.)
diameter drainpipe running down the middle. The top of the
drain pipe was temporarily sealed during construction to
prevent blockage. The rectangular bent cap, T-shaped bent
Table 1—Concrete member construction
information
Member
Placement
Length,
m (ft)
Width,
m (ft)
Height,
m (ft)
Form-
work
removed,
days
Date
(M/D/Y) Time
Pedestal 06/11/04 10:00 a.m. 2.9 (9.5) 3.2 (10.5) 1.7 (5.5) >7
T-s h ap ed
bent cap 06/05/04 8:00 a.m. — 2.2 (7.3) 2.5 (8.3) 2.25
Rectangular
bent cap 03/31/04 8:00 a.m. — 1.0 (3.3) 1.0 (3.3) 5
Dolphin 02/05/04 11:30 a.m. 4.9 (16.0) 4.9 (16.0) 2.7 (9.0) 5
Footing 1 06/17/03 7:00 a.m. 7.3 (24.0) 7.9 (26.0) 2.2 (7.3) >6
Footing 2 08/01/03 8:00 a.m. 3.1 (10.0) 3.1 (10.0) 1.9 (6.2) —
Column 1 06/16/03 8:00 a.m. 1.8 (6.0) 3.1 (10.0) 9.1 (30.0) 2
Column 2 07/10/03 8:00 a.m. 1.8 (6.0) 3.1 (10.0) 20.4
(67.0) 5
360 ACI Materials Journal/September-October 2006
cap, and pedestal were built with wood forms. The rest of the
concrete members were constructed with steel forms.
Table 2 shows the concrete mixture proportions and
concrete properties. The water content includes all mixing
water added, aggregate moisture above the saturated surface-
dry condition, and ice. Air-entraining admixtures were used
in all concrete mixtures. Normal water reducers were used in
all concrete mixtures. Additionally, a mid-range water
reducer was used in the dolphin concrete mixture. Crushed
granite coarse aggregate was used in the rectangular bent cap
project's concrete mixture, siliceous river gravel was used in
the dolphin project's concrete mixture, and crushed limestone
was used in the remaining concrete mixtures. Natural river
sand was used in all concrete mixtures except the rectangular
bent cap project's mixture, which contained crushed granite
sand. An ASTM C 618 Class C fly ash18 was used in the
rectangular bent cap project's mixture, and an ASTM C 618
Class F fly ash18 was used in the rest of the concrete mixtures.
ASTM Type I/II cement16 was used in all concrete mixtures.
Figure 1 shows the temperatures recorded for the interior
core, concrete surface temperature, and ambient temperature
for the dolphin. The recorded core temperatures are very
similar in behavior to those recorded in the other concrete
members. The difference between the temperature recorded on
the outside of the dolphin and the ambient temperature is
typical for values recorded next to steel formwork. Figure 2
shows the dolphin being instrumented and during
concrete placement.
Instrumentation
Weather data during construction of the mass concrete
members were collected using a weather station. Temperature
and relative humidity data were collected using a probe with
a radiation shield. Solar radiation data were collected using
a silicon pyranometer. Wind speed and direction data were
collected using a wind monitor. The weather station was
programmed to measure and record data every hour for each
of the field sites.
Temperature sensors with an internal data logger were
used for temperature instrumentation.19 Each concrete
member was instrumented with multiple temperature sensors
at various depths and locations in the concrete members. To
allow for fast and accurate installation of the temperature
sensors in the concrete members, modified temperature sensors
were pretaped onto cut pieces of 12 mm (1/2 in.) diameter
acrylic dowels or steel reinforcing bars. The prefabricated
temperature bars were installed before concrete placement.
The location of each temperature bar was selected to capture
Table 2—Concrete mixture proportions and properties
Member
Proportions Properties
Cement,
kg/m3 (lb/yd3 )
Fly ash,
kg/m3 (lb/yd3 )
Wat e r,
kg/m3 (lb/yd3 )
Coarse aggregate,
kg/m3 (lb/yd3 )
Fine aggregate,
kg/m3 (lb/yd3 )
Slump,
mm (in.)
Air
content, %
Placement
temperature,
°C (°F)
Blaine fineness,
cm2 /g (in.2 /lb)
Pedestal 298 (502) 107 (180) 166 (279) 1045 (1762) 688 (1160) 110 (4.3) 7.0 23 (74) 3988 (1.36)
T-shaped bent
cap 243 (409) 86 (145.5) 154 (260) 1039 (1752) 803 (1354) 125 (5.0) 6.5 29 (85) 3988 (1.36)
Rectangular
bent cap 251 (423) 63 (107) 126 (212) 1108 (1868) 758 (1277) 75 (3.0 ) 5.5 18 (65) 3635 (1.24)
Dolphin 253 (426) 100 (168) 123 (208) 1112 (1874) 687 (1158) 190 (7.5) 9 .0 20 (68) 3808 (1.30)
Footing 1 313 (528) 80 (135) 157 (265) 1035 (1745) 643 (1084) — — 22 (72) 3988 (1.36)
Footing 2 251 (423) 63 (107) 132 (223) 1035 (1745) 842 (1420) 100 (4.0) 5.25 20 (68) 3988 (1.36)
Column 1 251 (423) 63 (107) 132 (223) 1035 (1745) 842 (1420) 140 (5.5) 6.5 23 (73) 3988 (1.36)
Column 2 251 (423) 63 (107) 132 (223) 1035 (1745) 847 (1427) 180 (7.0) 5.5 23 (73) 3988 (1.36)
Fig. 1—Concrete core, surface, and ambient temperature
data measured for dolphin.
Fig. 2—Dolphin during instrumentation and placement.
ACI Materials Journal/September-October 2006 361
the concrete temperature at the core, within 50 mm (2 in.) of
the outermost edge of the member, and at various points in
between.
TEMPERATURE PREDICTION METHODS
PCA Method
The PCA Method was used to calculate temperatures for all
eight of the instrumented mass concrete members. Some of
the members, however, did not meet the conditions prescribed
by the PCA Method. The pedestal, T-shaped bent cap, and
rectangular bent cap did not meet the size requirements specified
in the PCA Method. The T-shaped bent cap, rectangular bent
cap, Footing 2, Column 1, and Column 2 did not meet the
cement content requirements as specified in the PCA Method.
The heat contribution of supplementary cementing materials
was assumed to be 50% of cement, as per the recommendation
in section 5.3.2 of ACI 207.1R5 (Eq. (2)).
Graphical method of ACI 207.2R
The graphical method of ACI 207.2R for temperature
analysis was performed for all mass concrete members
instrumented. The volume-to-surface ratio of the concrete
member was calculated assuming that every 25 mm (1 in.)
thickness of wood forms was equal to 0.51 m (20 in.) of
concrete, as recommended in Section 2.6 of ACI 207.2R.6
Form-liners were treated in a similar manner and were
assumed to be equal to 0.51 m (20 in.) of concrete per 25 mm
(1 in.) thickness of form-liner. Because of the large amount
of rigid polyurethane foam used for architectural detailing in
the T-shaped bent cap, all surfaces next to the foam were treated
as an unexposed surface in the "volume to exposed surface
area" calculations. When the fine aggregate was a different type
of material than the coarse aggregate, the concrete thermal
diffusivity was calculated as shown in Eq. (6)20
(6)
where h 2 is the weighted concrete diffusivity, in m2 /h; hc 2 is
the concrete diffusivity assuming the concrete is made from
the coarse aggregate mineral type, in m2 /h; hf 2 is the concrete
diffusivity assuming the concrete is made from just the fine
aggregate mineral type, in m2 /h; Wc is the weight of coarse
aggregate per cubic meter of concrete, in kg/m3 ; and Wf is
the weight of fine aggregate per cubic meter of concrete, in
kg/m3 . Values used in the calculations were manually
extracted from charts within ACI 207.2R6 (Charts 2.1, 2.2,
2.4, 2.5, and 2.6). Cement fineness values were tested using
the air permeability method (Blaine) as described in ASTM
C 204.21 Because Wagner Turbidimeter values are rarely
available, equivalent fineness values to the Wagner Turbi-
dimeter Method (ASTM C 115)22 were estimated from the
Blaine fineness values using Eq. (7)23
SW = S B · 0.56 (7)
where SW is the Wagner specific surface,22 and SB is the
Blaine specific surface,21 in m2 /kg. Maximum placement
temperatures were calculated with and without adjustments
for cement fineness.
h2 h c
2W ch f
2W f
⋅ + ⋅ ()
Wc Wf
+ ()
------------------------------------------- -=
Schmidt Method
All eight concrete members were modeled using the
Schmidt Method, as detailed in ACI 207.1R.5 The columns
were idealized as rectangular in all calculations, with little
loss in accuracy expected. An inherent problem in using this
method is that boundary conditions are very difficult to
model. On the surface boundaries, solar radiation and
convection need to be accounted for in the analysis.24 This
was accomplished by using ambient temperature, wind
speed, and solar radiation values that were measured onsite
during construction. The convection coefficient was calculated
using Eq. (8)25
(8)
where c = 10.15 for a bottom horizontal surface hotter than
ambient or a top horizontal surface cooler than ambient;
c = 15.89 for vertical surfaces; and c = 20.40 for a bottom
horizontal surface cooler than ambient or a top horizontal
surface hotter than ambient, where c is a constant; T∞ is the
ambient temperature, in °C; Ts is the surface temperature, in
°C; w is the wind speed, in m/s; and hc is the convection
coefficient, in W/m2 /K. A solar absorptivity value of 0.3 was
used for curing blankets, 0.2 for plywood,26 and 0.6 for
concrete.27 A solar absorptivity value of 0.2 was used for steel
forms to account for the shading provided by the horizontal
stiffeners of the forms.
At the boundary with the ground, constant temperatures
were assumed in the ground at a depth equal to one half the
height of the member as shown in Example 6 within ACI
207.1R.5 The temperature of the ground at the interface with
the concrete was increased by a value assumed to be equal to
half of the temperature increase in the concrete, as is done in
Example 6 of ACI 207.1R5 .
The dolphin, pedestal, Footing 1, and Footing 2 were
analyzed in one dimension using the Schmidt Method. The
rectangular bent cap, T-shaped bent cap, Column 1, and
Column 2 were analyzed using two-dimensional heat
transfer. The concrete equivalent thickness for the wood
formwork, form liners, and cure blanket were assumed equal
to the node spacing used. A thickness equal to the node
spacing resulted in calculated concrete edge temperatures
that were similar to the measured concrete edge temperatures.
The temperature rise for the concrete members was manually
extracted using the Type I cement curve from Chart 5.3.1 in
ACI 207.1R5 because the figure did not have a heat rise
curve for Type I/II cement. Temperature-rise values were
scaled using the ratio of a calculated 3-day temperature rise
to the 3-day temperature rise extracted from Fig. 5.3.1 in ACI
207.1R5 . The 3-day temperature rise was then calculated using
Eq. (9)
(9)
where Tcr is the calculated temperature rise, in °C; Hi is the
3-day isothermal heat of hydration, in cal/g; Wc is the weight
of cement per cubic meter of concrete, in kg/m3 ; Wt is the
hc c0.2782 T ∞ T s
–
2
----------------- 1 7 . 8 +
0.181 –
⋅⋅ =
T∞Ts
– []
0.266 1 2.8566 w ⋅ + []
0.5
⋅⋅
Tcr
Hi Wc
⋅
Cp Wt
⋅
---------------- -=
362 ACI Materials Journal/September-October 2006
total concrete weight per cubic meter, in kg/m3 ; and Cp is the
specific heat of the concrete, in cal/g/°C. Values for Hi were
obtained experimentally using a isothermal calorimeter at
23 °C (73 °F). The isothermal tests were performed using
cement for each concrete member collected at the batch
plant. The cementitious materials in the isothermal tests for
the rectangular bent cap and dolphin were tested using the fly
ash as a cement replacement (by mass). The isothermal tests
for the remaining members were done with only the cement.
The fly ash for those members was accounted for by
assuming a 50% cement equivalent as discussed in the
graphical method of ACI 207.2R. The adiabatic temperature
development curve was also adjusted for placement temperature
using Fig. 2.3 of ACI 207.2R.6 The calculations used in
determining the adiabatic temperature-rise scale factor are
shown in Table A-1 in Appendix A.
The concrete temperatures were also calculated using the
adiabatic temperature development for each concrete
mixture calculated from semi-adiabatic calorimetry tests.
The calorimeter consisted of an insulated 55 gallon steel
drum that uses a 152 x 304 mm (6 x 12 in.) cylindrical
concrete sample. Probes were used to record the concrete
temperature, heat loss through the calorimeter wall, and air
temperature surrounding the test setup. The heat loss through
the calorimeter was determined by a calibration test
performed by using heated water. Once the concrete was
batched, a 152 x 304 mm (6 x 12 in.) cylinder was made and
placed in the calorimeter. Each test was performed over a
period of approximately 7 days. Semi-adiabatic calorimetry
was performed on concrete sampled from the concrete delivered
at the job site. The results from this analysis are referred to
in this paper as the "Schmidt Method using calorimetry."
The adiabatic temperature development of each member
was also calculated. This was done by adding the adiabatic
temperature rise curve for each concrete member to the
placement temperature. The adiabatic temperature development
was calculated, for reference, to evaluate the magnitude of the
heat transferred from the concrete core. The validity of the
conduction heat transfer can be gauged from results obtained
by comparing the predicted concrete core temperature to the
predicted adiabatic temperature.
RESULTS AND DISCUSSION
All of the instrumented mass concrete members showed
high temperature increases at the core. Table 3 shows the
recorded and calculated maximum temperatures for the eight
concrete members. Table 4 shows the measured time to
the peak temperature, the calculated time to the peak
temperature using the graphical method of ACI 207.2R,
and the Schmidt Method.
Figure 3 shows the recorded core temperature, the calculated
adiabatic temperature, and the calculated maximum temperature
for the dolphin using the Schmidt Method. The shape of the
predicted maximum temperature and adiabatic temperature
development curves for the dolphin were similar to those of
most of the other members. Figure 4 shows the recorded core
temperature, the calculated adiabatic temperature, and the
calculated maximum temperature for the T-shaped bent cap
using the Schmidt Method, which were slightly different
from the dolphin.
PCA Method
As seen in Table 3, the PCA Method4 predicted reasonably
well the maximum temperature of the rectangular bent cap,
Footing 2, Column 1, Column 2, and the T-shaped bent cap,
Table 3—Maximum recorded and calculated temperatures for concrete members
Member
Maximum concrete temperature, °C (°F)
Measured
PCA Method
using Eq. (1)
ACI 207.2R method
not corrected for fineness
ACI 207.2R method
corrected for fineness Schmidt Method
Schmidt Method with
calorimetry
Pedestal 74.0 (165.2) 65.4 (149.8) 57.6 (135.7) 64.7 (148.5) 59.0 (138.1) 71.4 (160.6)
T-shaped bent cap 67.5 (153.5) 63.4 (146.2) 54.6 (130.2) 64.4 (148.0) 62.6 (144.7) 72.0 (161.6)
Rectangular bent cap 53.5 (128.3) 52.2 (126.0) 36.3 (97.4) 39.9 (103.7) 53.7 (128.6) 56.9 (134.4)
Dolphin 63.0 (145.4) 56.3 (133.3) 37.6 (99.7) 42.0 (107.7) 61.5 (142.8) 66.7 (152.0)
Footing 1 72.0 (161.6) 64.6 (148.2) 55.6 (132.0) 62.1 (143.9) 69.3 (156.7) 78.0 (172.3)
Footing 2 56.5 (133.7) 53.9 (129.0) 52.9 (127.3) 57.4 (135.3) 49.6 (121.3) 59.2 (138.5)
Column 1 58.0 (136.4) 56.7 (134.0) 48.9 (120.0) 54.0 (129.2) 56.8 (134.1) 57.8 (136.1)
Column 2 58.0 (136.4) 56.7 (134.0) 50.2 (122.4) 55.5 (131.8) 56.2 (133.1) 59.2 (138.6)
Table 4—Time from concrete placement to peak
temperature
Member
Time to peak temperature, hours
Measured
ACI 207.2R
method corrected
for fineness
Schmidt
Method
Schmidt
Method with
calorimetry
results
Pedestal 37 31 98 58
T-shaped bent cap 36 18 41 50
Rectangular bent cap 23 36 43 43
Dolphin 41 24 77 50
Footing 1 50 38 79 77
Footing 2 48 70 82 58
Column 1 47 26 91 70
Column 2 59 26 91 82
Fig. 3—Recorded core temperature, calculated maximum
temperature using Schmidt Method, and calculated adiabatic
development for dolphin.
ACI Materials Journal/September-October 2006 363
in spite of the fact that these members did not meet all of the
requirements for the model as discussed in the previous
section. This method significantly underpredicted the
maximum temperature in the other four concrete members.
For example, the difference in measured and predicted
maximum temperatures for Column 3 was almost 9 °C (16 °F),
an error of 12%. Interestingly, the PCA Method worked best
with the five of the members that did not fully meet this
method's assumptions. Results from this comparison
demonstrate that the PCA Method is generally not accurate
enough to be a reliable predictor of maximum temperature
for mass concrete structures. This method is generally not
robust enough to be used in temperature control plans for
mass concrete members. This method, however, is a useful
tool for quick estimates to show the effect of cement content
on heat development.
Graphical method of ACI 207.2R
The graphical method found in ACI 207.2R6 underestimated
the maximum temperature in the absence of corrections for
cement fineness. This method did slightly better when
corrections were made for fineness, but the reliability of the
method is still quite poor. This method performed the worst
with the large members that exhibited an appreciable
temperature increase. In the dolphin, for example, the
temperature was underestimated by more than 21 °C (38 °F),
an error of 33%. This method also provided a poor prediction
of the time when the maximum concrete temperature was
reached. This is because cements have changed significantly
since the charts in ACI 207.2R6 were developed. Both the
rate of heat generation and total heat-generating capacity of
cements are now very different than the behavior shown in
ACI 207.2R.
Schmidt Method
The two main components of the Schmidt Method are the
heat transfer component and the heat generation component.
The heat transfer component performed satisfactorily. The
heat generation component performed better when the
measured adiabatic temperature development was used. For
example, the calculated maximum temperature in the
pedestal was underestimated by 20% when the calculated
adiabatic temperature development curve was used and was
underestimated by only 3% when the measured adiabatic
temperature development was used. Furthermore, the time to
maximum temperature was overestimated by 165% in the
pedestal, whereas it was overestimated by 55% when the
measured adiabatic temperature development curve was used.
The Schmidt Method of conductive heat transfer
performed satisfactorily based on the amount of concrete
core heat loss when compared to the adiabatic condition. By
comparing the adiabatic temperature rise curve to the core
concrete temperatures, the core heat loss could be determined.
The rate of calculated heat loss in the concrete core was as
expected for mass concrete. The Schmidt Method assumes
that all nodes have the same thermal diffusivity value. This
is why it is necessary to convert formwork and insulation
properties to equivalent concrete thickness values. This
method also assumes constant values of thermal diffusivity
for every node. The thermal conductivity, however, and
specific heat have been shown to decrease with increasing
degree of hydration. The specific heat of concrete also
increases with an increase in temperature.26
The maximum temperature reached in mass concrete
bridge members can be more sensitive to the effect of its
boundary conditions than large mass concrete. For example,
solar radiation values in excess of 900 W/m2 were recorded
for the rectangular bent cap. This dramatically increased the
formwork and insulating blanket temperatures. Because of
these effects, manual calculation made by using the Schmidt
Method should only be performed by an experienced engineer
or by using calibrated software.
The heat generation component of the Schmidt Method
was enhanced by using semi-adiabatic calorimetry results.
Adiabatic temperature curves can be adequate for massive
dams where there is little heat loss and the concrete is placed
at roughly the same temperature. For smaller mass concrete
members, however, some heat loss or gain from the environment
may occur. Because cement hydration is temperature-
dependent, a change in the temperature will result in
deviation from the adiabatic temperature development curve.
If the member is small, and heat is lost, the heat generation rate
will be significantly different from the adiabatic curve. This
may explain why the Schmidt Method tended to underpre-
dict the maximum temperature reached when the adiabatic
temperature development curve was used. It may also help
explain the tendency to overpredict the maximum temperature
reached when the measured adiabatic temperature development
is used. A different method that includes the cement
temperature dependency could be used to improve the
heat generation component of the calculations. Van Breugel 28
found that the degree of hydration should be used as a basis
for all temperature calculations.
The rate of heat generation is critical in determining the
temperature rise in mass concrete. A comparison of the
maximum temperature recorded versus the calculated adiabatic
temperature rise in Fig. 3 and 4 shows how the heat
generation rate can significantly change the shape of the
maximum temperature curve and the time to peak temperature.
The measured maximum temperature curve tends to be a
lower, flatter curve, even though the adiabatic temperature
eventually reaches that of the concrete member temperature.
The calculated time to peak temperature is also considerably
larger than the recorded values. This is because a significant
amount of heat can be lost while the heat generation rate slows
down considerably after 24 to 72 hours. The time to maximum
temperature and the time spent at elevated temperatures are
Fig. 4—Recorded core temperature, calculated maximum
temperature using Schmidt Method, and calculated adiabatic
development for T-shaped bent cap.
ACI Materials Journal/September-October 2006 364
critical parameters in predicting the possibility of DEF
occurrence1 and thermal shock susceptibility.
The Schmidt Method makes many assumptions regarding
the rate of heat generation. Any method that does not use
measured calorimetry curves will not take into account any
retardation from chemical admixtures. ACI 207.1R5
recommends neglecting rate changes from chemical admixtures
for preliminary calculations because they only affect the
temperature increase during the first few hours. For large
mass concrete, this assumption may be true. For mass
concrete bridge members, the contribution of chemical
admixtures to the heat generation rate should not be ignored.
slag cement, fly ash, and other SCMs can affect the rate of
hydration. A correct determination of the temperature rise
during the first few hours is critical to the accuracy of the
analysis when the peak temperature can be reached within as
little as 24 hours.
Fly ash can significantly change not only the magnitude of
the adiabatic temperature rise, but also the rate of heat
generation. Calcium oxide content has been shown to be
a major indicator of the fly ash heat of hydration.26
Further research should be directed at creating a database
of continuous heat of hydration development curves for
different combinations of cements, supplementary
cementing materials, and chemical admixtures.
CONCLUSIONS
The maximum concrete temperature, maximum concrete
temperature difference, time, and duration of the maximum
temperature difference all considerably affect the performance
of a mass concrete bridge member. The time of the maximum
temperature difference is also critical. Based on the work
documented in this paper, the following conclusions can
be made:
1. The maximum error in predicting the maximum
temperature from the PCA Method compared to the measured
concrete core temperature for all concrete members examined
was 12%. The PCA Method of mass concrete temperature
prediction, however, offered no information on the time that
the maximum temperature was reached, limiting the
usefulness of the method. The criteria for using the method
are so narrow that many bridge substructure concrete
members do not satisfy the assumptions of the method;
2. The graphical method of temperature prediction found
in ACI 207.2R did not produce reliable results for the bridge
substructure concrete members discussed in this paper. Both
the predicted peak temperature and the predicted time to
peak temperature did not compare well to recorded concrete
temperatures with errors in some cases of more than 33%;
3. The Schmidt Method adequately models the conductive
heat transfer in the bridge substructure concrete members
discussed in this paper, as long as one uses surface boundary
assumptions that account for conditions that include the
effects of convection and solar radiation. Future numerical
heat transfer methods should include corrections for the
changes in the concrete thermal conductivity and specific
heat as the concrete hardens. The peak temperature reached
in mass concrete can be sensitive to the boundary conditions.
Results will be improved when convection and solar radiation
are fully accounted for in the modeling process;
4. The heat generation component of the Schmidt Method
performed better when measured adiabatic temperature
development curves were used as compared to when
calculated temperature developments obtained from generic
charts were used. The time to peak temperature predictions
could be very different than predicted, with errors on the
order of 165%. Temperatures predicted using this method
could be significantly improved by accounting for the heat
generated in the concrete by more current hydration models
that can account for the effect of modern cements and
various SCMs; and
5. Future research should develop a database of adiabatic
temperature rise curves using common combinations of
various cements, supplementary cementing materials, and
chemical admixtures.
ACKNOWLEDGMENTS
The authors wish to express their gratitude to the Texas Department
of Transportation for funding this work and other on-going research.
The advice and support of R. Browne, T. Yarbrough, and R. Crowson are
greatly appreciated.
REFERENCES
1. Day, R. L., "The Effect of Secondary Ettringite Formation on the
Durability of Concrete: A Literature Analysis," Research and Developmen t
Bulletin RD108T, Portland Cement Association, Skokie, Ill., 1992,
pp. 59, 83-84.
2. Chini, A. R.; Muszynski, L. C.; Acquaye, L.; and Tarkhan, S.,
"Determination of the Maximum Placement and Curing Temperatures in
Mass Concrete to Avoid Durability Problems and DEF," Final Report,
University of Florida, Gainsville, Fla., July 2003, pp. 46-64.
3. Texas Department of Transportation, "Specification 420," June-July
2004, pp. 494-527.
4. Kosmatka, S. H.; Kerkhoff, B.; and Panarese, W. C., Design and
Control of Concrete Mixtures, 14th Edition, Portland Cement Association,
Skokie, Ill., 2003, pp. 323-325.
5. ACI Committee 207, "Mass Concrete (ACI 207.1R-96)," American
Concrete Institute, Farmington Hills, Mich., 1996, pp. 29-37.
6. ACI Committee 207, "Effect of Restraint, Volume Change, and
Reinforcement on Cracking in Massive Concrete (ACI 207.2R-95),"
American Concrete Institute, Farmington Hills, Mich., 1995, pp. 3-8.
7. Detwiler, R. J.; Gjorv, O. E.; and Kjellsen, K. O., "Pore Structure of
Plain Cement Pastes Hydrated at Different Temperature," Cement and
Concrete Research , V. 20, No. 6, 1990, pp. 927-933.
8. Gajda, J., and VanGeem, M., "Controlling Temperatures in Mass
Concrete," Concrete International , V. 24, No. 1, Jan. 2002, pp. 59-62.
9. Bamforth, P. B., and Price, W. F., "Concreting Deep Lifts and Large
Volume Pours," Construction Industry Research and Information Association,
London, 1995, pp. 19-24, 45-48.
10. Thomas, M. D. A; Mukherjee, P. K.; Sato, J. A.; and Everitt, M. F.,
"Effect of Fly Ash Composition on Thermal Cracking in Concrete," Fly
Ash, Silica Fume, Slag, and Natural Pozzolans in Concrete, Proceedings of
the Fifth CANMET/ACI International Conference, SP-153, V. M. Malhotra,
ed., American Concrete Institute, Farmington Hills, Mich., V. 1, 1995,
pp. 81-98.
11. Bamforth, P. B., "Large Pours," letter to the editor, Concrete, Cement
and Concrete Association, Wexham Springs, Slough, England, Feb. 1981,
pp. 19-20.
12. Emborg, M., "Models and Methods for Computation of Thermal
Stresses," Prevention of Thermal Cracking in Concrete at Early Ages, RILEM
Report 15, R. Springenschmid, ed., E&FN Spon, London, 1998, pp. 178-230.
13. Mangold, M., and Springenschmid, R., "Why are Temperature
Related Criteria so Unreliable for Predicting Thermal Cracking at Early
Ages?" Thermal Cracking in Concrete at Early Ages, R. Springenschmid,
ed., E&FN Spon, London, 1994, pp. 361-368.
14. Eberhardt, M.; Lokhorst, S. J.; and Van Breugel, K., "On the
Reliability of Temperature Differenti als as a Criterion for the Risk of
Early-Age Thermal Cracking," Thermal Cracking in Concrete at Early
Ages, R. Springenschmid, ed., E&FN Spon, London, 1994, pp. 353-360.
15. Mangold, M., "Thermal Prestress of Concrete by Surface Cooling,"
Thermal Cracking in Concrete at Early Ages, R. Springenschmid, ed.,
E&FN Spon, London, 1994, pp. 265-272.
16. ASTM C 150, "Standard Specification for Portland Cement," ASTM
International, West Conshohocken, Pa., 2004, 8 pp.
17. Schack, A., Industrial Heat Transfer , translated by H. Goldschmidt
and E. P. Partridge, John Wiley & Sons, Inc., London, 1933, pp. 54-56.
18. ASTM C 618, "Standard Specification for Coal Fly Ash and Raw or
Calcined Natural Pozzolan for Use in Concrete," ASTM International,
West Conshohocken, Pa., 2003, 3 pp.
ACI Materials Journal/September-October 2006 365
19. Ramaiah, S. V.; Dossey, T.; and McCullough, B. F., "An Investigation of
the Thermacron© I-button for Early-Age and Long-Term Temperature," T RB
2002 Annual Meeting, 2002, 19 pp. (CD-ROM)
20. ACI Committee 207, "Cooling and Insulating Systems for Mass
Concrete (ACI 207.R-93)," American Concrete Institute, Farmington Hills,
Mich., 1993, p. 7.
21. ASTM C 204, "Standard Test Method for Fineness of Hydraulic
Cement by Air-Permeability Apparatus," ASTM International, West
Conshohocken, Pa., 2000, 8 pp.
22. ASTM C 115a, "Standard Test Method for Fineness of Portland Cement
by the Turbidimeter," ASTM International, West Conshohocken, Pa., 2003, 7 p p.
23. Mindess, S.; Young, J. F.; and Darwin, D., Concrete, 2nd Edition,
Prentice Hall, Upper Saddle River, N.J., 2003. pp. 47-48.
24. Wojcik, G. S.; Fitzjarrald, D. R.; and Plawsky, J. L., "Modeling the
Interaction Between the Atmosphere and Curing Concrete Bridge Decks
with the SLABS Model," Meteorology Applied, V. 10, 2003, pp. 1-22.
25. ASHRAE, 1993-ASHRAE Handbook , American Society of Heating,
Refrigerating and Air-Conditioning Engineers, Inc., Atlanta, Ga., 1993,
p. 22.17.
26. Schindler, A. K., "Concrete Hydration, Temperature Development,
and Setting at Early Ages," PhD dissertation, University of Texas at Austin,
Austin, Tex., 2002, pp. 86-88, 94, 100, 175-179.
27. Incropera, F. P., and Dewitt, D. P., Fundamentals of Heat and Mass
Transfer , John Wiley & Sons, Inc., New York, 2002, p. 931.
28. Van Breugel, K., "Prediction of Temperature Development in
Hardening Concrete," Prevention of Thermal Cracking in Concrete at
Early Ages, RILEM Report 15, R. Springenschmid, ed., E&FN Spon, London,
1998, pp. 178-230.
APPENDIX A
Table A-1—Calculations used in determining adiabatic scale rise factor
Item Pedestal T-shaped bent cap Rectangular bent cap Dolphin Footing 1 Footing 2 Column 1 Column 2
Specific heat, cal/g/°C5 0.22 0.22 0.19 0.18 0.22 0.22 0.22 0.22
Three-day isothermal test, cal/g 56 56 65 56 56 56 56 56
Calculated 3-day temperature rise, °C (°F) 33 (59) 26 (48) 48 (86) 47 (84) 36 (64) 27 (49) 27 (49) 27 (49)
Type I cement 3-day temperature rise from
Fig. 5.3.1 in ACI 207.1R,5 °C (°F) 31 (55) 31 (55) 31 (55) 31 (55) 31 (55) 31 (55) 31 (55) 31 (55)
Total adiabatic temperature rise scale factor 1.31 1.06 1.56 1.53 1.34 1.04 1.04 1.04
... Heat loss characteristic coefficients were calculated using four temperature measurements in the cubes to calculate the ATR. Riding et al. [13] used semi-adiabatic calorimetry devices at several construction sites under controlled ambient temperature. ...
... The thermal conductivity of the plywood was assumed to be 0.13 W/m/K. The specific heat ( ) and thermal conductivity ( ) of the concrete were considered to be degree of hydration dependent parameters [13], [22]. They were calculated in a user subroutine with Eq. (8) and Eq. ...
... The calculated ATR error would increase if more insulation than the required R-value is used and the ATR would be under predicted using Eq. (13). Furthermore, through FEM analysis, it was found that a smaller size cube (such as 0.5 cubic meter) would have too much heat loss to the environment under the current insulation design, and the heat generation at the center of the cube would be disrupted at an early stage. ...
In this study, measurements of the heat of hydration of mass concrete delivered on-site were proposed. A one-meter concrete cube, cast adjacent to the real structure, was developed as an on-site semi-adiabatic calorimeter. A table was established for the required insulation of the cube in different ambient temperatures. To simplify the measurement process and cost, a method was developed to obtain the concrete adiabatic temperature rise (ATR) by simply using the measured temperature at the center of the cube. The finite element method (FEM) was used to calculate the required insulation for various ambient conditions between −10 to 30 °C so that the ATR could be accurately estimated using only the measured center temperature. The predicted ATR and the actual ATR showed less than 1% error. The proposed heat of hydration measurement was tested during four on-site field castings at three different districts in West Virginia. Two of the field batches contained 50% Grade 100 ground granulated blast furnace slag replacements. The fourth field batch had 30% Class F fly ash replacement. The material collected from each field test was also used to perform laboratory adiabatic and isothermal heat of hydration measurements. The ATR calculated from the on-site cube data compared well with the results from both adiabatic and isothermal calorimetry tests. The heat of hydration parameters were successfully obtained based on the ATR calculated from each on-site casting. Results show that the proposed on-site heat measurement can be a simple and accurate approach to measure the heat of hydration of a delivered concrete batch.
... In large concrete structures, due to concrete's low thermal conductivity, the interior temperature rise can approach the adiabatic temperature rise. The high temperatures can lead to delayed ettringite formation (DEF) and reduce the concrete's strength and durability [1]. Furthermore, the surface of the concrete losses heat to the environment and cools rapidly. ...
... The thermal stresses are directly correlated to the temperature time history of the structure. Riding et al. reviewed the PCA, Schmidt, and ACI 207.2R methods to predict the temperature distribution in mass concrete structures [1]. They found that the PCA and ACI 207.R methods provided poor predictions. ...
In this study, the early age thermal properties of a concrete mix containing ground granulated blast furnace slag (GGBFS) were investigated and incorporated in a finite-element model. A two-term exponential degree of hydration function was proposed to better capture the early age behavior. An FEM program (ABAQUS) was used to predict the temperature time-history of three 1.2-m (4-ft) cubes cast with a mix design containing 50% replacement of the cement by weight with GGBFS. The FEM predictions match well with the experimental temperature measurements. Results show that using the measurements of the thermal properties, an accurate estimation of the temperature difference can be obtained for a concrete mix containing GGBFS, and engineers can use the estimated temperature difference to take preventative measures to minimize the risk of thermal cracking.
... A complete review of the available models lies beyond the scope of this study. Many authors have provided valuable contributions to the subject [ACI 207.1R (ACI 2005b); Riding et al. 2006;ACI 207.2R (ACI 2007); Abeka et al. 2015;Sargam et al. 2019]. ...
-
![Rodrigo Antunes]()
This study aims to provide engineers with a set of equations to evaluate temperature models for massive footings to avoid the use of high-heat mixtures that can induce excessive expansion. The temperatures of a concrete block and 41 massive footings were measured in the laboratory and construction sites. The equations for the peak core temperature (TPC), peak differential temperature (TD), and form removal time (tFR) are proposed for the thermal resistance of 0.029 W/m · K for 12.7-mm-thick expanded polystyrene (EPS) and extruded polystyrene (XPS) boards or equivalent. Semiadiabatic temperature rise (TR) curves from 1.1-m elements can be used to model footings up to 1.8 m thick. The gradient temperature increment (G) of 0.1°C/cm is recommended for limestone concrete. The cooling rate (FCR) range of 2.2°C/day ≤ FCR ≤ 5.6°C/day is suggested. TR, G, and FCR used in the equations should be validated with local concrete mixtures.
... Prediction of the temperature fields of concrete during early hardening should allow for proper control of the construction process to minimize temperature gradients and the peak temperature by either limiting the amount of heat generated in the hydration process or controlled cooling of the structure [7]. Simplified prediction methods, like PCA method, ACI 207.2R graphical method, and Schmidt method, are able to predict the temperature development within mass concrete members only with much-limited accuracy [8]. Thermal analysis of mass concrete is often carried out through finite-element analysis (FEA), while the material parameters are identified using experimental data obtained via semi-adiabatic calorimetry and tests on hardened concrete [9]. ...
The kinetics of heat transfer in hardening concrete is a key issue in engineering practice for erecting massive concrete structures. Prediction of the temperature fields in early age concrete should allow for proper control of the construction process to minimize temperature gradients and the peak temperatures, which is of particular importance for concrete durability. The paper presents a method of identification of the thermophysical parameters of early age concrete such as the thermal conductivity, the specific heat, and the heat generated by cement hydration in time. Proper numerical models of transient heat conduction problems were formulated by means of finite-element method, including two types of heat losses. The developed experimental–numerical approach included the transient temperature measurements in an isolated tube device and an in-house implementation of an evolutionary algorithm to solve the parameter identification task. Parametric Bezier curves were proposed to model heat source function, which allowed for identifying such function as a smooth curve utilizing a small number of parameters. Numerical identification tasks were solved for experimental data acquired on hardening concrete mixes differing in the type of cement and type of mineral aggregate, demonstrating the effectiveness of the proposed method (the mean-squared error less than 1 °C). The proposed approach allows for the identification of thermophysical parameters of early age concrete even for mixtures containing non-standard components while omitting drawbacks typical for classical optimization methods.
... Several studies have found that high slag cement concretes with 36-65% replacement ratios had higher strength compared to Portland cement (PC) concretes after 10 days and that the use of slag can be beneficial without resulting in significant technical problems or adverse construction problems (Hogan and Meusel 1981). An extensive work was carried out to assess the concrete behavior with slag cement in low-heat mass concrete applications (Committee 1996;Riding et al. 2006). In addition, other researchers (Topcu 2013;Geert 1999) assert that the heat generation is reduced during the hydration and maturing of the slag cement concrete. ...
Ground granulated blast furnace slag is an eco-friendly material with regard to its production process and usage. In this study, slag cement (SC) is used to prepare different slag cement mortar (SCM) mixes to study mortar microstructure perspectives, physiochemical properties, mechanical properties and durability performance. The tests also included the evaluation of SC setting time and slag activity index. Test results showed that the used slag cement had a high activity index and prolonged initial setting time. SCM demonstrated positive synergistic effects on late compressive strength, enhanced durability against sulfates and acid attacks. Also, SCMs seem to produce a more stable structure at elevated temperatures. Strength and durability improvement was correlated with an improved microstructure as indicated by scanning electron microscope and X-ray diffraction analyses.
... In bridges it is still common to use concrete mixes with pure Portland cement and crushed coarse aggregate in the concrete mix [36,37] as the most robust method to ensure desired strength, durability and quality of concrete (Table A.1 presents compositions of some exemplary concrete mixes used in construction of concrete bridges in Poland). High amount of hydration heat generated by Portland cement generates high early age Studying the causes of cracks in bridges formed prior to their opening it can be concluded that in case of bridge abutments the hardening-induced strains and ambient temperature are the only loads causing formation of vertical cracks; an exceptional case is that of unequal settlement of supports [40]. ...
This paper is an effect of coordinated efforts of Working Group 7 of RILEM TC 254-CMS: Thermal cracking in massive concrete structures. The paper deals with a negative effect of restrained hardening-induced strains in reinforced concrete wall-on-slab structures which is cracks formed at the stage of construction of the walls. The aim of the paper was to collect real-life examples of wall-on-slab structures in which hardening-induced cracking was reported, and make a comparative study of these cases to observe patterns and trends on the cracking behaviour of such elements. The study covered a set of almost 20 cases with detailed material and technological data as well as observed cracking patterns. Characteristics of these structures which determine the capacity of crack development were indicated. In addition, for chosen cases the expected crack width was calculated and compared with the measured value. The calculations were performed with the use of current standardised guidance (EN 1992-3 and CIRIA C766) using an approach available at the design stage. This investigation showed that the method of CIRIA C766, being less conservative, consistently predicts smaller crack widths for a fixed set of assumptions compared to EN 1992-3, and both methods showed important discrepancies between the predicted and measured values of crack widths. Changes in calculation methods were proposed to improve the predictability of crack width calculations in wall-on-slab structures under restrained hardening-induced strains.
- Nguyen Van My
-
![Hung Duy Vo]()
The effects of hydration heat can cause the potential of cracks in tower-footing. This paper presents a case study in which the construction of mass concrete bridge foundation of Cua-Dai Extradosed Bridge in Quang Ngai, Vietnam was investigated through FEM software. The 3D-simulation will be conducted to predict the thermal performance. The temperature development profile, temperature difference, tensile stress and displacement were predicted in detail. Results showed that the heat of hydration in Cua-Dai Bridge was very high, which can cause early cracks in concrete structure. The investigation also provided clear insight into the temperature development of concrete block with complicated compositions and ambient conditions. In addition, hydration heat induced tensile stress and displacement also investigated thoroughly. Finally, the critical comments will be given.
Recently, the piezoelectric based sensor coupled with electromechanical impedance (EMI) technique is gaining attention on monitoring the mechanical properties changes in cementitious materials. However, the EMI signals obtained from the sensing system are not only influenced by the development of inherent mechanical properties in the host structure but also affected by the variation of temperature. When implementing a piezoelectric based sensor, both the ambient temperature change and the heat release from newly casted concrete would influence the sensing accuracy. In order to eliminate the biases from temperature effect, the mechanisms of EMI technique for strength sensing were investigated. The experiment work was separated in two parts. The piezoelectric sensors were first used to monitor the strength gaining of the newly casted cementitious samples curing under constant temperature. A strength estimation system was developed based on the experiment results. Later, the temperature variation was induced to affect the sensing performance. A temperature compensation technique was proposed to eliminate the temperature effect. It has concluded that the proposed compensation method can improve the strength sensing accuracy. The new understanding should help to promote the practical applicable EMI sensing technique.
The objective of this research is to characterize the heat generation in mass concrete placements typically encountered by GDOT in its construction projects, to create an analytical method for determining the cooling requirements for mass concrete, and to develop a comprehensive guideline for transportation infrastructure applications. This guideline was derived from an extensive review of technical literature and various state DOT's specifications, analytical modeling of heat generation in transportation structures, and laboratory and field research of mass concrete cooling. The guideline can allow GDOT to more efficiently evaluate contractor's proposed mass concrete cooling methods, which would result in improved quality of concrete transportation infrastructures in Georgia.
-
![Steven H. Kosmatka]()
- Beatrix Kerkhoff
- William C. Panarese
This 358 page book presents the properties of concrete as needed in concrete construction, including strength and durability. All concrete ingredients (cementing materials, water, aggregates, admixtures, and fibers) are reviewed for their optimal use in designing and proportioning concrete mixtures. Applicable ASTM, AASHTO, and ACI standards are referred to extensively. The use of concrete from design to batching, mixing, transporting, placing, consolidating, finishing, and curing is addressed. Special concretes, including high-performance concretes, are also reviewed. Available at http://www.cement.org/pdf_files/EB001.14.pdf.
The interaction between atmospheric and construction conditions and the exothermic, temperature-dependent hydration reactions of the concrete's binding components may produce adverse conditions in curing concrete, thereby reducing the quality of that concrete. Accurate model forecasts of concrete temperatures and moisture would help engineers determine an optimal time to pour, an optimal mix design, and/or optimal curing practices. Existing models of curing concrete bridge decks and road surface prediction models lack realistic boundary conditions. The concrete models contain unnecessarily detailed hydration heat generation mechanisms for a simplified field forecast model. In this paper, a new energy balance model (SLABS), which can be easily adapted to predict road surface conditions, is described and applied to predict the temperatures and moisture of curing concrete bridge decks made with New York State Department of Transportation's Class HP concrete. Highest concrete temperatures occurred at high air temperatures, humidities and initial concrete temperatures and at low cloud cover fractions and wind speeds. Peak concrete temperatures can exceed 60°C. To minimise concrete temperatures and temperature gradient magnitudes, concrete should be placed during the late afternoon or early evening. As a field forecast model for which the meteorological inputs are taken from NGM MOS forecasts, the outputs of SLABS include the peak concrete temperature (to within 2°C of the observed in one application), peak temperature gradient, evaporation rate at the time of placement and several warning messages indicating adverse field conditions. Copyright © 2003 Royal Meteorological Society
- Edward A. Abdun-Nur
- Fred A. Anderson
- Howard L. Boggs
- Stephen B. Tatro
This report presents a discussion of the effects of heat generation and volume change on the design and behavior of reinforced mass concrete elements and structures. Particular emphasis is placed on the effects of restraint on cracking and the effects of controlled placing temperatures, concrete strength requirements, and type and fineness of cement on volume change. Formulas are presented for determining the amounts of reinforcing steel needed to control the size and spacing of cracks to specified limits under varying conditions of restraint and volume change.
Concrete outside the laboratory cures at temperatures other than 20°C. This paper describes an investigation of the pore structure of plain cement pastes hydrated at 5°, 20°, and 50°C to reflect a range of temperatures encountered in practice. Parallel specimens of 0.50 water/cement ratio pastes were examined using mercury intrusion porosimetry and backscattered electron image analysis. Increases in curing temperature resulted in increased porosity, particularly for pores of radius 200–1000 Ȧ as measured by mercury intrusion, or 2500–12,500 Ȧ as measured in the backscattered electron images. The difference between the two results indicates the magnitude of the "ink bottle effect" inherent in the mercury intrusion technique. However, both methods suggest that elevated curing temperatures could have a deleterious effect on the durability of plain cement concretes.
Effect of Fly Ash Composition on Thermal Cracking in Concrete," Fly Ash, Silica Fume, Slag, and Natural Pozzolans in Concrete
- M D A Thomas
- P K Mukherjee
- J A Sato
- M F Everitt
Thomas, M. D. A; Mukherjee, P. K.; Sato, J. A.; and Everitt, M. F., "Effect of Fly Ash Composition on Thermal Cracking in Concrete," Fly Ash, Silica Fume, Slag, and Natural Pozzolans in Concrete, Proceedings of the Fifth CANMET/ACI International Conference, SP-153, V. M. Malhotra, ed., American Concrete Institute, Farmington Hills, Mich., V. 1, 1995, pp. 81-98
Source: https://www.researchgate.net/publication/279552488_Evaluation_of_Temperature_Prediction_Methods_for_Mass_Concrete_Members
Posted by: danicadorweilerssza.blogspot.com