Datasets:
akumar33
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manufacturing

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then O
building O
the O
TCN S-CONPRI
in O
a O
layer-by-layer S-CONPRI
manner O
to O
replicate O
the O
PBF S-MANP
process O
. O
In O
comparison O
to O
conventional O
finite B-CONPRI
element I-CONPRI
method E-CONPRI
( O
FEM S-CONPRI
) O
thermal B-CONPRI
modeling E-CONPRI
, O
the O
TCN B-CONPRI
model E-CONPRI
predicts O
the O
temperature S-PARA
history O
of O
metal S-MATE
PBF O
AM B-MACEQ
parts E-MACEQ
with O
more O
than O
two O
orders O
of O
magnitude S-PARA
faster O
computational B-PARA
speed E-PARA
, O
while O
sacrificing O
less O
than O
15 O
% O
accuracy S-CHAR
. O
The O
companion O
manuscript S-CONPRI
illustrates O
how O
the O
temperature S-PARA
history O
is O
integrated O
into O
a O
thermomechanical B-CONPRI
model E-CONPRI
to O
predict O
thermal B-PRO
stress E-PRO
and O
distortion S-CONPRI
. O
Additive B-MANP
manufacturing E-MANP
( O
AM S-MANP
) O
is O
a O
set S-APPL
of O
emerging O
technologies S-CONPRI
that O
can O
produce O
physical O