Polymers,
Год журнала:
2025,
Номер
17(4), С. 436 - 436
Опубликована: Фев. 7, 2025
Self-excited
systems
rely
on
stable
external
stimuli
to
initiate
and
sustain
oscillations
via
internal
processes.
However,
these
can
compromise
system
stability
increase
friction,
limiting
their
practical
applications.
To
overcome
this
issue,
we
propose
the
light-fueled
self-rolling
of
a
liquid
crystal
elastomer
(LCE)-based
wheel.
A
photothermal
response
model
based
an
LCE
was
used
analyze
temperature
distribution
within
rods.
The
driving
torque
for
is
generated
by
contraction
resulting
from
LCE's
response,
which
displaces
wheel's
center
mass.
We
then
derived
equilibrium
equations
identified
critical
conditions
achieving
motion.
Through
interaction
between
field
torque,
wheel
achieves
continuous
absorbing
thermal
energy
counteract
damping
dissipation.
Numerical
simulations
revealed
that
velocity
influenced
several
key
parameters,
including
heat
flux,
coefficient,
gravitational
acceleration,
initial
rolling
coefficient.
proposed
LCE-based
enhances
significantly
reduces
frictional
losses.
These
characteristics
make
it
promising
candidate
applications
in
autonomous
drive
systems,
micro-transportation
devices,
conversion
technologies.
Mathematics,
Год журнала:
2024,
Номер
12(7), С. 1019 - 1019
Опубликована: Март 28, 2024
Self-oscillatory
systems
have
great
utility
in
energy
harvesting,
engines,
and
actuators
due
to
their
ability
convert
ambient
directly
into
mechanical
work.
This
characteristic
makes
design
implementation
highly
valuable.
Due
the
complexity
of
motion
process
simultaneous
influence
multiple
parameters,
computing
self-oscillatory
proves
be
challenging,
especially
when
conducting
inverse
parameter
design.
To
simplify
computational
process,
a
combined
approach
o0f
Random
Forest
(RF)
Backpropagation
Neural
Network
(BPNN)
algorithms
is
employed.
The
example
used
self-rotating
skipping
rope
made
liquid
crystal
elastomer
(LCE)
fiber
mass
block
under
illumination.
Numerically
solving
governing
equations
yields
precise
solutions
for
rotation
frequency
LCE
various
system
parameters.
A
database
containing
138,240
sets
conditions
corresponding
frequencies
constructed
train
RF
BPNN
models.
training
outcomes
indicate
that
can
accurately
predict
demonstrating
high
stability
efficiency.
allows
us
discover
influences
distinct
parameters
on
as
well.
Moreover,
it
capable
design,
meaning
derive
desired
combination
from
given
frequency.
Through
this
study,
deeper
understanding
dynamic
behavior
achieved,
offering
new
theoretical
foundation
construction.
