Page 42 - MSAM-1-3
P. 42
Materials Science in Additive Manufacturing Optimization of chemical admixtures for 3DCP
rheological test , in which Bingham model can also 3. Materials, mixture design, and properties
[11]
be expressed as the following formula (Equation II) for characterization
convenience of experiment design and data analysis:
3.1. Materials and mixture design
T = G + hN (II)
Material mixture in this study consists of ordinary
Equation II describes the correlation between the Portland cement (OPC, ASTM type I, Grade 42.5), silica
measured torque T (N·m) and rotational speed N (rpm). fume (SF, undensified, Grade 940, Elkem company),
The parameter G (N·m) is flow resistance, representing the fine sand, fly ash (FA, Class F), water, superplasticizer
minimum torque required to initiate or maintain the flow of (MasterPozzolith-R168, BASF Pte. Ltd.), accelerator
a material. The parameter h (N·m·min) is torque viscosity. (MasterRoc SA160, BASF Pte. Ltd.), and retarder
Similar to the k in Equation I, the parameter h describes (MasterReobuild1000, BASF Pte. Ltd.). Particle size
the change of applied torque with altering rotational speed. distribution is illustrated in Figure 2, and the chemical
Buildability and pumpability can be characterized composition of all the raw ingredients used is shown in
by a build-up model and a pumping pressure model, Table 1. The mixtures used in this study follow the same
respectively. The built-up model can be adopted to predict mixture proportion, as shown in Table 2.
the printed height of structures with static yield stress of The dosage of chemical admixtures was designed by
material, and the model is expressed in Equation III : the CCD, and the coded and actual values used in the
[31]
experiment are presented in Table 3. The relationship
H t () (III) between coded and actual values is expressed in
g s Equation VI .
[8]
Where H (m) and α are the printed height (buildability) Coded value Actual valueFactor mean /
and the geometric factor of printed structures, respectively;
ρ (kg/m ) and g (m/s ) are the density of materials and Range of factorial vvalue / 2 (VI)
3
2
gravitational constant, respectively. Equation III implies
that the printed height is positively proportional to the 3.2. Mixing process and properties characterization
static yield stress for a given material and structure. A Hobart mixer X200L was used for mixing. The
pumpability, generally characterized by pumping pressure, rheological properties of cement slurries are influenced by
is positively related to dynamic viscosity that measures a several factors, such as speed, time, and temperature. Thus,
fluid’s resistance to flow when an external force is applied .
[32]
mixing procedures in this study were fixed to minimize
2.2.2. Time-dependent effect of rheological properties the difference among batches. First, the powders of all
solid ingredients were dry mixed for 1 min in stir speed
Rheological properties evolve with time due to hydration (33 rpm). Water, superplasticizer, and retarder were then
process. A theoretical model proposed by Roussel et al. added, and the mixing process continued for 1 min in stir
[33]
correlates yield stress with resting time. The model is speed (33 rpm) followed by 1 min in speed I (61 rpm);
expressed in Equation IV:
t() ()0 A t (IV)
s
s
thix
Where t (s) is time at rest; A thix (Pa/s) is thixotropy
parameter, a constant value for a given material; τ (0) is the
s
static yield stress as a function of resting time t = 0. A high
A is required for the 3D printable cementitious material
thix
in printing process to accelerate the increase of static yield
stress to make certain that materials possess appropriate
buildability.
The time effect on the evolution of dynamic viscosity is
expressed in Equation V:
()t (1000 )(/ )t t v n (V)
0
0
Where t (s) is time at rest; t is 1000 Pa∙s. µ is initial
v
0
dynamic viscosity. Generally, dynamic viscosity changes Figure 2. Particle size distribution of ordinary Portland cement, fly ash,
slightly in 30 min after mixing . and silica fume.
[34]
Volume 1 Issue 3 (2022) 3 https://doi.org/10.18063/msam.v1i3.16

