Research
involving
the
application
of
waste
materials
in
concrete
has
gained
prominence
academic
community,
aiming
to
promote
cleaner
management
while
enhancing
properties.
This
study
reviews
publications
that
have
assessed
influence
recycled
synthetic
fibers
on
concrete,
observing
improvements
their
main
The
analysis
results
reported
articles
revealed
that,
for
any
type
fiber,
there
is
a
significant
loss
workability
worsens
as
fiber
dosage
increases.
Additionally,
compressive,
flexural,
and
tensile
strengths
are
observed
up
2%
volume
added
concrete.
can
be
attributed
"bridging"
effect
caused
by
adhesion
friction
matrix,
delaying
initiation
propagation
cracks
microcracks
under
mechanical
stress
or
drying
shrinkage.
It
was
also
modulus
elasticity
not
significantly
affected.
Furthermore
demonstrated
performance
compatible
with
commercially
available
virgin
fibers,
indicating
they
serve
effective
replacements,
witch
contributes
mitigation
natural
resource
extraction,
energy
consumption,
CO2
generation
from
production
well
promoting
circular
economy.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Фев. 28, 2025
Physics-informed
modeling
(PIM)
using
advanced
machine
learning
(ML)
represents
a
paradigm
shift
in
the
field
of
concrete
technology,
offering
potent
blend
scientific
rigor
and
computational
efficiency.
By
harnessing
synergies
between
physics-based
principles
data-driven
algorithms,
PIM-ML
not
only
streamlines
design
process
but
also
enhances
reliability
sustainability
structures.
As
research
continues
to
refine
these
models
validate
their
performance,
adoption
promises
revolutionize
how
materials
are
engineered,
tested,
utilized
construction
projects
worldwide.
In
this
work,
an
extensive
literature
review,
which
produced
global
representative
database
for
splitting
tensile
strength
(Fsp)
recycled
aggregate
concrete,
was
indulged.
The
studied
components
such
as
C,
W,
NCAg,
PL,
RCAg_D,
RCAg_P,
RCAg_wa,
Vf,
F_type
were
measured
tabulated.
collected
257
records
partitioned
into
training
set
200
(80%)
validation
57
(20%)
line
with
more
reliable
partitioning
database.
Five
techniques
created
"Weka
Data
Mining"
software
version
3.8.6
applied
predict
Fsp
Hoffman
&
Gardener
method
performance
metrics
used
evaluate
sensitivity
variables
ML
models,
respectively.
results
show
Kstar
model
demonstrates
highest
level
among
achieving
exceptional
accuracy
R2
0.96
Accuracy
94%.
Its
RMSE
MAE
both
low
at
0.15
MPa,
indicating
minimal
deviations
predicted
actual
values.
Additional
WI
(0.99),
NSE
(0.96),
KGE
(0.96)
further
confirm
model's
superior
efficiency
consistent
making
it
most
dependable
tool
practical
applications.
Also
analysis
shows
that
Water
content
(W)
exerts
significant
impact
40%,
demonstrating
amount
water
mix
is
critical
factor
optimal
strength.
This
underscores
need
careful
management
balance
workability
sustainable
production.
Coarse
natural
(NCAg)
has
substantial
38%,
its
essential
role
maintaining
structural
integrity
mix.
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Ноя. 8, 2024
This
study
explores
the
mechanical
and
durability
properties
of
Plastic-Fibre
Reinforced
Concrete,
incorporating
hand-shredded
plastic
fibers
sourced
from
polyethylene
bags
PET
bottles.
Evaluations,
including
compressive
split
tensile
strength
tests,
were
conducted
on
M40
grade
mixes
containing
100%
treated
Construction
Demolition
Waste
(CDW),
comparing
them
with
conventional
concrete.
The
results
demonstrate
a
significant
enhancement
in
addition
0.25%,
0.5%,
0.75%,
1%
plastic-fibres,
alongside
complete
replacement
coarse
aggregate
CDW,
particularly
noticeable
at
both
7
28-day
curing
ages.
Although
higher
fiber
dosages
led
to
slight
reduction
by
7%
optimum
percentage
0.25%
PE
0.5%
PET,
flexural
strengths
exhibited
proportional
increase
11.7%
18%.
Surface
analysis
via
Scanning
Electron
Microscopy
(SEM)
elemental
composition
determination
using
Energy
Dispersive
Spectroscopy
(EDS)
revealed
minimal
damage
post-exposure,
confirming
its
efficiency
contribution
reduced
weight
loss
mix.
novel
approach
combines
manually
recycled
waste
as
enhancing
concrete
while
promoting
sustainability.
Sustainability
indicates
that
utilizing
CDW
contributes
energy
consumption,
lower
carbon
emissions,
economic
benefits.
These
findings
underscore
potential
integrating
non-degradable
plastics
into
mixtures,
combined
offering
environmental
sustainability
enhanced
performance
advantages
construction
materials.
Fullerenes Nanotubes and Carbon Nanostructures,
Год журнала:
2024,
Номер
unknown, С. 1 - 17
Опубликована: Дек. 27, 2024
This
article
deals
with
the
combined
application
of
MWCNTs
and
GFs
to
improve
mechanical
property
durability
concrete.
were
dispersed
by
sonication
added
in
dosages
0.05,
0.10,
0.15%
cement
weight,
while
at
0.5,
1.0,
1.5%
mixture
weight.
Compressive,
flexural,
tensile
strengths,
as
well
modulus
elasticity,
rebound
number,
ultrasonic
pulse
velocity,
tested
various
curing
ages.
Accordingly,
addition
0.10%
1.0%
resulted
enhancement
compressive
strength
improving
elasticity
up
14%.
In
addition,
improved
owing
reduced
sorptivity
aid
pore
refinement
crack-bridging
GFs.
Scanning
electron
microscopy
showed
that
optimum
mix
developed
a
denser
microstructure;
however,
mixtures
higher
exhibited
agglomeration,
influencing
their
performance
adversely.
economic
assessment
pointed
out
best
improvement-cost
ratio
corresponded
benefit-cost
equal
0.104.
The
present
research
provides
an
insight
into
development
high-performance
concrete
materials
delivers
practical
recommendations
on
how
could
be
GF
order
create
durable
yet
economically
viable
concretes.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Апрель 3, 2025
This
research
investigates
the
compressive
strength
behavior
of
basalt
fiber-reinforced
concrete
(BFRC)
using
machine
learning
models
to
optimize
predictions
and
enhance
its
practical
applications.
The
study
incorporates
various
modeling
techniques,
including
Artificial
Neural
Networks
(ANN),
k-Nearest
Neighbors
(KNN),
Support
Vector
Machines
(SVM),
Decision
Trees,
Random
Forest
(RF),
evaluate
their
predictive
capabilities.
Basalt
Fiber
Reinforced
Concrete
is
a
composite
material
that
fibers
into
traditional
mechanical
durability
properties.
use
fibers,
derived
from
natural
volcanic
rocks,
aligns
with
sustainability
goals
due
eco-friendliness,
cost-effectiveness,
high
performance.
BFRC
combines
structural
excellence
sustainability,
making
it
an
ideal
for
modern
construction
practices.
Its
ability
performance,
reduce
environmental
impact,
ensure
long-term
positions
as
pivotal
solution
sustainable
infrastructure
development.
developed
were
used
predict
fiber
(Cs_bf)
mixture
contents,
age,
dimensions.
All
created
"Orange
Data
Mining"
software
version
3.36.
A
total
three
hundred
nine
(309)
records
collected
literature
different
mixing
ratios
at
ages.
Each
record
contains
following
data:
C-Cement
content
(Kg/m3),
FA-Fly
ash
W-Water
SP-Super-plasticizer
CAg-Coarse
aggregates
FAg-Fine
Age-The
age
testing
(days),
L_b-length
(mm),
d_bf-Diameter
(µm),
V_bf-Volume
(%)
Cs_bf-Compressive
fibre
(MPa).
divided
training
set
(249
records≈80%)
validation
(60
records≈
20%).
At
end
process,
can
be
shown
present
work
outclassed
other
ML
techniques
applied
in
previous
paper,
which
reported
utilization
same
size
data
entries
reinforced
constituents.
Taylor
chart
measured
predicted
ANN,
KNN,
SVM,
Tree
RF
presented
comparing
performance
by
illustrating
key
statistical
measures
simultaneously:
correlation
coefficient
(R),
normalized
standard
deviation
(σ),
root-mean-square
error
(RMSE).
Finally,
deduced
after
considering
indices
selected
ensemble
classification
utilized
this
all
modes
have
almost
excellent
level
accuracy
95%,
but
SVR
produced
R2
0.98
each
KNN
producing
MAE
1.4
MPa,
MSE
2.5
MPa
outperform
ANN
1.55
MPa/MSE
4.1
1.6
3.85
respectively.
Three
estimate
impact
input
on
strength,
namely
matrix,
sensitivity
analysis
relative
importance
chart.
