Structure and Infrastructure Engineering,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 15
Published: Nov. 13, 2024
Fragility
and
risk
assessment
of
civil
engineering
structures
against
various
design
loads
their
combinations
need
to
be
conducted
evaluate
structural
vulnerability.
This
is
typically
done
at
the
stage.
However,
during
service
(design)
life,
it
important
investigate
change
(increase)
in
posed
structure
on
account
multiple
hazards.
article
discusses
a
holistic
novel
framework
that
considers
aging
effects
addition
major
or
minor
damage
resulting
from
independent
The
illustrated
for
action
earthquake
fire
hazards
reinforced
concrete
(RC)
buildings
with
varied
occupancies
while
considering
continuous
deterioration
chloride-
carbonation-induced
corrosion
over
building's
life.
structure's
performance
its
terms
incident
resistance
period,
evaluated
combination
environmental
multi-hazard
fire.
results
this
study
indicate
there
significant
increase
post-earthquake
if
degradation
due
factors
earthquakes
not
addressed.
Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(9), P. 3908 - 3908
Published: May 3, 2024
Leakage
in
underground
structures,
especially
tunnels,
may
cause
seepage
erosion
the
surrounding
soil,
which
turn
leads
to
ground
subsidence,
posing
a
great
threat
urban
safety.
The
current
literature
mainly
focuses
on
sand
but
lacks
systematic
study
development
process
of
induced
by
tunnel
leakage
different
strata.
To
investigate
modes
stratum
types,
series
reduced-scale
model
tests
were
carried
out.
A
coupled
fluid–solid
numerical
was
further
established
analyze
fine-scale
characteristics
modes.
results
show
that
(1)
soil
can
be
divided
into
three
categories:
no
cave,
unstable
and
stable
cave;
(2)
adopted
based
DEM,
takes
account
degradation
clay
during
erosion,
effectively
simulate
with
modes;
(3)
phenomena
are
development;
(4)
micro-mechanisms
different,
manifested
range,
arching
effect,
displacement.
Engineering With Computers,
Journal Year:
2024,
Volume and Issue:
41(1), P. 723 - 738
Published: Aug. 21, 2024
Abstract
Assessing
the
structural
integrity
of
ageing
structures
that
are
affected
by
climate-induced
stressors,
challenges
traditional
engineering
methods.
The
reason
is
degradation
often
initiates
and
advances
without
any
notable
warning
until
visible
severe
damage
or
catastrophic
failures
occur.
An
example
this,
conventional
inspection
methods
for
prestressed
concrete
bridges
which
fail
to
interpret
large
permanent
deflections
because
causes—typically
tendon
loss—are
barely
measurable.
In
many
occasions,
inspections
discern
these
latent
defects
damage,
leading
need
expensive
continuous
health
monitoring
towards
informed
assessments
enable
appropriate
interventions.
This
a
capability
gap
has
led
fatalities
extensive
losses
operators
have
very
little
time
react.
study
addresses
this
proposing
novel
machine
learning
approach
inform
rapid
non-destructive
assessment
bridge
states
based
on
measurable
deflections.
First,
comprehensive
training
dataset
assembled
simulating
various
plausible
scenarios
associated
with
different
degrees
patterns
losses,
vital
decks.
Second,
General
Regression
Neural
Network
(GRNN)-based
cascade
ensemble
model,
tailored
predicting
three
interdependent
output
attributes
using
limited
datasets,
developed.
proposed
model
optimised
utilising
differential
evolution
method.
Modelling
validation
were
conducted
real
long-span
bridge.
results
confirm
efficacy
in
accurately
identifying
when
compared
existing
developed
demonstrates
exceptional
prediction
accuracy
reliability,
underscoring
its
practical
value
assessment,
can
facilitate
effective
restoration
planning.
