This
study
presents
a
novel
lifetime
assessment
technique
that
may
be
used
in
cargo
vessel
transportation
marine
engineering
applications.
onboard
measured
4400
TEU
container
ship
panel
stress
data
was
analyzed,
the
during
numerous
trans-Atlantic
crossings.
The
risk
of
loss
caused
by
excessive
whipping
loads
is
one
key
issues
with
transportation.
It
challenging
to
predict
accuracy
deck
stresses
due
complex
nonlinear
and
nonstationary
properties
wave
motions.
2nd
higher
order
motion
effects
are
typically
observed
when
sailing
severe,
stormy
environment,
influence
nonlinearity
grows
noticeably.
Depending
on
flow
characteristics
similarity
ratios
employed,
laboratory
testing
also
dispute.
Because
this,
information
acquired
from
ships
operating
extreme
weather
conditions
offers
unique
insight
into
risks
evaluation,
as
whole.
highlights
multidimensional
reliability
approach,
based
inherent
qualities
multivariate
raw
underlying
dataset
itself.
main
objective
current
had
been
benchmark
Gaidai
using
areal
pressure
dynamic
system
dataset.
evaluation
methodology
enabled
efficient
failure,
hazard
or
damage
for
variety
non-linear
hull
systems.
Scientific Reports,
Год журнала:
2023,
Номер
13(1)
Опубликована: Сен. 28, 2023
Abstract
Fatigue
damage
prediction
is
essential
for
safety
of
contemporary
offshore
energy
industrial
projects,
like
wind
turbines,
that
are
to
be
designed
sufficiently
long
operational
period
time,
with
minimal
disruptions.
Offshore
structures
being
withstand
environmental
loadings
due
winds
and
waves.
Due
accumulated
fatigue
damage,
floating
turbines
may
develop
material
cracks
in
their
critical
locations
sooner
than
expected.
Dataset
needed
an
accurate
assessment
produced
by
either
extensive
numerical
modeling,
or
direct
measurements.
However,
reality,
temporal
length
the
underlying
dataset
typically
too
short
provide
calculation
life.
Hence,
objective
this
work
contribute
development
novel
methods,
making
better
use
limited
dataset.
In
study,
in-situ
conditions
were
incorporated
assess
FWT
tower
base
stresses;
then
structural
cumulative
has
been
assessed.
Novel
deconvolution
extrapolation
method
introduced
it
was
shown
able
accurately
predict
long-term
damage.
The
latter
technique
validated,
using
artificially
reduced
dataset,
resulted
close
calculated
from
full
original
Recommended
utilize
available
much
more
efficiently,
compared
estimation.
Accurate
turbine
characteristics
reliability,
design,
safety.
Sustainable Energy Research,
Год журнала:
2023,
Номер
10(1)
Опубликована: Окт. 26, 2023
Abstract
Modern
offshore
and
onshore
green
energy
engineering
includes
harvesting—as
a
result,
extensive
experimental
investigations,
as
well
safety
reliability
analysis
are
crucial
for
design
engineering.
For
this
study,
several
wind-tunnel
experiments
under
realistic
in
situ
wind
speed
conditions
have
been
conducted
to
examine
the
performance
of
galloping
harvester.
Next,
novel
structural
approach
is
presented
here
that
especially
suited
multi-dimensional
harvesting
systems
either
numerically
simulated
or
analog
observed
during
representative
time
lapse,
yielding
an
ergodic
system
record.
As
demonstrated
advocated
methodology
may
be
used
risk
assessment
dynamic
damage
failure.
Furthermore,
traditional
methodologies
dealing
with
series
do
not
easily
cope
system’s
high
dimensionality,
along
nonlinear
cross-correlations
between
components.
This
study’s
objective
was
assess
state-of-the-art
method,
allowing
efficient
extraction
relevant
statistical
information,
even
from
limited
underlying
dataset.
The
described
study
aims
assist
designers
when
assessing
multidimensional
failure
hazard
risks.
Journal of Shipping and Trade,
Год журнала:
2024,
Номер
9(1)
Опубликована: Янв. 2, 2024
Abstract
Modern
cargo
vessel
transport
constitutes
an
important
part
of
global
economy;
hence
it
is
paramount
importance
to
develop
novel,
more
efficient
reliability
methods
for
ships,
especially
if
onboard
recorded
data
available.
Classic
methods,
dealing
with
timeseries,
do
not
have
the
advantage
efficiently
system
high
dimensionality
and
cross-correlation
between
different
dimensions.
This
study
validates
novel
structural
method
suitable
multi-dimensional
systems
versus
a
well-established
bivariate
statistical
method.
An
example
this
was
chosen
container
ship
subjected
large
deck
panel
stresses
during
sailing.
Risk
losing
containers,
due
extreme
motions
primary
concern
transport.
Due
non-stationarity
complicated
nonlinearities
both
waves
motions,
challenging
model
such
phenomenon.
In
case
role
dramatically
increases,
activating
effects
second
higher
order.
Moreover,
laboratory
tests
may
also
be
questioned.
Therefore,
measured
on
actual
ships
their
voyages
in
harsh
weather
provides
unique
insight
into
statistics
motions.
aimed
at
benchmarking
validation
state-of-the-art
method,
which
enables
extraction
necessary
information
about
dynamics
from
time
histories.
The
proposed
opens
up
broad
possibilities
predicting
simply,
yet
potential
failure
or
damage
risks
nonlinear
dynamic
as
whole.
Note
that
advocated
can
used
wide
range
complex
engineering
systems,
thus
limited
only.
International Journal of Low-Carbon Technologies,
Год журнала:
2024,
Номер
19, С. 63 - 72
Опубликована: Янв. 1, 2024
Abstract
Wind
turbines
are
designed
to
withstand
extreme
wind-
and
wave-induced
loads,
hence
a
reliability
study
is
vital.
This
presents
bivariate
approach,
suitable
for
accurate
assessment
of
critical
forces
moments,
occurring
within
the
wind
turbine’s
mechanical
parts,
such
as
drivetrain.
A
ecently
developed
modified
Weibull
method
has
been
utilized
in
this
study.
Multivariate
statistical
analysis
more
appropriate
than
univariate
one,
it
accounts
cross-correlations
between
different
system
components.
employed
estimate
operational
loads
acting
on
10-mega
watt
(MW)
semi-submersible
type
floating
turbine
(FWT).
Longitudinal,
bending,
twisting,
cyclic
being
among
typical
load
types
that
FWTs
associated
parts
susceptible
to.
Furthermore,
environmental
an
operating
FWT
impacted
by
incoming
wind’s
stochastic
behavior
terms
speed,
direction,
shear,
vorticity,
necessitates
nonlinear
Appropriate
numerical
methods
were
used
model
dynamic,
structural,
aerodynamic,
control
aspects
system.
Bending
moments
drivetrain
have
obtained
from
SIMPACK
(Multibody
Simulation
Method),
given
realistic
in-situ
conditions.
For
5-year
return
period
interest,
offered
robust
FWT’s
coupled
drivetrain’s
bending
moments.
Urban Planning and Transport Research,
Год журнала:
2024,
Номер
12(1)
Опубликована: Март 11, 2024
Contemporary
cargo
vessel
transport
constitutes
a
vital
part
of
the
global
trade
and
economy.
Thus,
it
is
primary
engineering
design
importance
to
further
develop
more
efficient
novel
risk
analysis
assessment
methods
for
large
ships.
Classical
methodsmay
not
always
have
advantages
efficiently
dealing
with
dynamic
system's
high
dimensionality
along
cross-correlations
between
various
critical
dimensions.
Current
study
benchmarks
state-of-art
Gaidai
spatiotemporal
structural
method,
suitable
multivariate
systems
versus
well-established
bivariate
method.
As
an
example,
this
study,
operating
container
has
been
selected.
The
hull
had
subjected
deck
panel
stresses
accelerations
during
cross-Atlantic
sailing.
Risks
losing
containers
are
caused
by
extreme
dynamics
being
one
concerns
transport.
methodology,
advocated
here,
opens
up
new
possibilities
predicting
efficiently,
yet
simply
potential
damage/failure
risks
nonstationary,
nonlinear,
ship
systems,
as
whole.
Note
that
method
may
be
applied
wide
range
complex
marine
offshore
systems.
Results in Engineering,
Год журнала:
2024,
Номер
22, С. 102326 - 102326
Опубликована: Май 27, 2024
Current
study
advocates
novel
Gaidai
hazards
assessment
methodology
that
may
be
utilized
for
excessive
wave-heights
spatiotemporal
risk
analysis,
thus
advancing
climate
change
studies.
being
particularly
suitable
multivariate
dynamic
environmental
ocean
systems,
have
been
MC
(i.e.,
Monte
Carlo)
numerically
simulated,
either
physically
measured
across
a
representative
time
period,
resulting
in
synchronous
quasi-ergodic
timeseries.
Offshore
waves
affect
reliable
production
and
operational
safety
of
offshore
marine
structures.
presents
two
reliability
methods:
first,
state-of-the-art
methodology,
designed
multi-dimensional
to
presented
the
current
study;
second,
deconvolution
extrapolation
technique
follow.
Primary
target
accurate
system's
hazard
assessment.
Classic
methods,
dealing
with
timeseries
not
always
possess
advantages
efficiently
high
dimensionality,
along
nonlinear
cross-correlation
patterns
between
various
components.
In-situ
significant
wave-height
dataset,
different
areas,
analyzed
by
means
application
advocated
methodology.
representing
complex
highly-nonlinear,
cross-correlated
system.
Global
also
an
important
factor,
affecting
wave-heights.
purpose
had
benchmark
while
utilizing
underlying
raw
dataset.
Methods
put
forth
assessments
large
variety
dimensional
systems.
