Journal of Physics Conference Series,
Journal Year:
2024,
Volume and Issue:
2903(1), P. 012017 - 012017
Published: Nov. 1, 2024
Abstract
In
thermal
power
plants,
coal
conveyor
belts
pose
significant
risks
that
jeopardize
the
stability
of
energy
supply,
underscoring
need
for
effective
risk
management.
To
address
complexity,
uncertainty,
and
polymorphism
issues
in
belt
systems,
we
introduce
a
BT-UFDBN
analysis
method
specifically
belts.
This
develops
typical
Bow-tie
model,
identifies
potential
factors
unplanned
stoppages,
utilizes
fuzzy
evaluation
methods
an
improved
SAM
to
determine
prior
probabilities.
The
(BT)
model
is
then
mapped
into
Dynamic
Bayesian
Network
(DBN).
manage
uncertainties
within
DBN,
Leaky
Noisy-OR
gate
stationarity,
first-order
Markov
assumptions
are
employed
ensure
model’s
validity
practical
relevance.
paper
uses
system
from
plant
as
case
study
validate
effectiveness
predicting
accident
consequences,
diagnosing
fault
causes,
proposing
targeted
preventive
measures
identified
weak
points.
provides
theoretical
guidance
management
plants.
Journal of Marine Engineering & Technology,
Journal Year:
2025,
Volume and Issue:
unknown, P. 1 - 19
Published: Feb. 13, 2025
This
study
provides
a
systematic
risk
assessment
approach
for
chemical
tanker
loading
operations,
focusing
on
high-risk
scenario
identified
through
operational
data
from
model
vessel.
To
address
the
complexities
of
transportation,
hybrid
methodology
combining
Methodology
Identification
Major
Accident
Hazards
(MIMAH)
and
Fuzzy
Bayesian
Network
(FBN)
analysis
was
developed.
MIMAH's
structured
framework
systematically
identifies
critical
events
using
Bow-Tie
(BT)
diagram,
integrating
Fault
Tree
(FT)
Event
(ET)
providing
thorough
breakdown
potential
accident
pathways.
BT
structure
converted
into
(BN)
to
improve
probability
estimations
by
incorporating
conditional
dependencies
expert-driven
fuzzy
logic,
particularly
where
historical
limited.
The
further
employed
dual-method
sensitivity
analysis,
Fussell-Vesely
(FV)
importance
measures
Improvement
Index
(II),
identify
improvement-prone
basic
(BEs).
Key
findings
highlight
dominance
human
error
in
events,
manifold
connection
failures
incorrect
valve
alongside
mechanical
vulnerabilities
with
significant
improvement
potential.
extends
ARAMIS
principles
maritime
contexts,
reliability-based
fuzzy-based
estimation
methods
detailed
adaptable
that
enhances
safety
resilience
hazardous
transport.
