Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Jan. 17, 2025
Caving
mining
in
extra-thick
coal
seams
induces
large-scale
overburden
movement,
leading
to
more
intense
fracture
processes
key
strata,
significant
surface
subsidence,
and
frequent
dynamic
disasters
mines.
This
study,
using
the
N34-2
caving
face
of
17th
seam
at
Junde
Mine
as
a
case
aims
investigate
time-varying
linkage
mechanism
between
microseismic
characteristics,
scales
overburden's
strata
under
such
conditions.
Based
on
Timoshenko's
theory,
bearing
mode
for
is
proposed,
corresponding
criteria
are
established.
The
modes
step
distances
working
were
calculated
theoretically
verified
localization
data,
showing
that
higher
prone
failure,
increase
distances.
Numerical
simulations
monitoring
techniques
employed
comprehensively
analyze
main
controlling
factors
subsidence.
To
further
clarify
high-position
full
cycle
divided
into
four
sub-processes:
short-term
fracture,
rapid
compaction
stability,
energy
accumulation.
relationship
subsidence
responses
analyzed
each
sub-process,
establishing
system.
approach
offers
systematic
accurate
method
predict
assess
movement
processes,
providing
new
insights
prevention
control
rock
burst
seams.
Underground Space,
Journal Year:
2024,
Volume and Issue:
19, P. 101 - 118
Published: June 13, 2024
Rockburst
is
a
major
challenge
to
hard
rock
engineering
at
great
depth.
Accurate
and
timely
assessment
of
rockburst
risk
can
avoid
unnecessary
casualties
property
losses.
Despite
the
existence
various
methods
for
assessment,
there
remains
an
urgent
need
comprehensive
reliable
criterion
that
easy
both
apply
interpret.
Developing
new
based
on
simple
parameters
potentially
fill
this
gap.
With
its
advantages,
facilitate
more
effective
efficient
prediction
potential,
thereby
contributing
significantly
enhancing
safety
measures.
In
paper,
combined
with
internal
external
factors
rockburst,
four
control
variables
(i.e.,
integrity
index,
stress
brittleness
elastic
energy
index)
were
selected
be
incorporated
into
rockburstability
index
(RBSI).
Based
116
sets
cases,
potential
was
accurately
quantified
predicted
using
categorical
boosting
(CatBoost)
model
nature-inspired
metaheuristic
African
vultures
optimization
algorithm
(AVOA).
performance
validation,
achieved
highest
accuracy
95.45%,
verifying
reliability
effectiveness
proposed
RBSI
criterion.
Additionally,
interpretive
method
applied
analyze
variable
influence
criterion,
facilitating
explanation
predictions
analysis
formula's
robustness
under
different
conditions.
general,
compared
existing
involving
relevant
indicators,
newly
enhances
prediction,
it
effectively
swiftly
evaluate
preliminary
rockburst.
Lastly,
graphical
user
interface
developed
provide
clear
visualization
potential.
Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(11), P. 4512 - 4512
Published: May 24, 2024
This
study
employs
scientometric
analysis
to
investigate
the
current
trajectory
of
research
on
tunnel
boring
machine
(TBM)
performance
and
collaborative
efforts.
Utilizing
software
tools
like
Pajek
5.16
VOSviewer
1.6.18,
it
scrutinizes
literature
from
2000
2021
sourced
Web
Science
(WOS).
The
findings
illuminate
TBM
as
an
interdisciplinary
intersectoral
field
attracting
increasing
national
institutional
attention.
Notable
contributions
China,
Iran,
United
States,
Turkey,
Australia
underscore
global
significance
research.
recent
upsurge
in
annual
publications,
primarily
driven
by
Chinese
initiatives,
reflects
a
renewed
vigor
exploration.
Additionally,
paper
presents
succinct
evaluation
advantages
drawbacks
compared
conventional
drill
blast
methods,
discussing
key
considerations
excavation
methodology
selection.
Moreover,
comprehensively
reviews
prediction
models,
categorizing
them
into
theoretical,
empirical,
artificial
intelligence-driven
approaches.
Finally,
rooted
metaverse
theory,
discourse
delves
immersive
learning
model
architecture
metaverse.
In
future,
training
diagram
can
be
employed
scenarios
such
employee
promotion
safety
knowledge.
simulate,
monitor,
diagnose,
predict,
control
organization,
management,
service
processes
behaviors
TBMs.
will
enhance
efficient
collaboration
across
various
aspects
project
production
cycle.
forward-looking
perspective
anticipates
future
trends
technology,
emphasizing
societal
impact
enhancement
economic
benefits.
International Journal of Mining Science and Technology,
Journal Year:
2024,
Volume and Issue:
34(1), P. 51 - 64
Published: Jan. 1, 2024
The
scientific
community
recognizes
the
seriousness
of
rockbursts
and
need
for
effective
mitigation
measures.
literature
reports
various
successful
applications
machine
learning
(ML)
models
rockburst
assessment;
however,
a
significant
question
remains
unanswered:
How
reliable
are
these
models,
at
what
confidence
level
classifications
made?
Typically,
ML
output
single
grade
even
in
face
intricate
out-of-distribution
samples,
without
any
associated
value.
Given
susceptibility
to
errors,
it
becomes
imperative
quantify
their
uncertainty
prevent
consequential
failures.
To
address
this
issue,
we
propose
conformal
prediction
(CP)
framework
built
on
traditional
(extreme
gradient
boosting
random
forest)
generate
valid
while
producing
measure
its
output.
proposed
guarantees
marginal
coverage
and,
most
cases,
conditional
test
dataset.
CP
was
evaluated
case
Sanshandao
Gold
Mine
China,
where
achieved
high
efficiency
applicable
levels.
Significantly,
identified
several
"confident"
from
model
as
unreliable,
necessitating
expert
verification
informed
decision-making.
improves
reliability
accuracy
assessments,
with
potential
bolster
user
confidence.
Rock Mechanics and Rock Engineering,
Journal Year:
2024,
Volume and Issue:
57(11), P. 9713 - 9738
Published: July 4, 2024
Abstract
The
rockburst
phenomenon
in
excavation
endeavours
reveals
a
multitude
of
complexities
and
obstacles
that
significantly
impact
both
the
technical
financial
dimensions
project
execution.
Investigating
critical
factors
underground
excavations
is
considerable
importance
for
addressing
pivotal
safety
issues
operational
within
field
projects.
This
research
proposes
an
innovative
approach
based
on
expert-based
fuzzy
cognitive
map
(FCM)
framework,
aiming
to
identify
prioritize
key
prevalent
tunnelling.
A
tailored
parameters
problem
was
constructed,
integrating
56
meticulously
curated
by
team
seasoned
managers,
engineers,
deputy
trainee
engineers
assistant
managers.
structured
developed,
considering
relative
weights
identified
their
intricate
interrelationships—all
informed
invaluable
insights
expertise
field.
Subsequently,
underwent
systematic
solution
process,
whereby
causal
relationships
influences
amongst
were
analysed
factored
in.
outcomes
comprehensive
analysis
unveiled
several
factors:
lack
risk
assessments,
high
situ
stress,
presence
rock
seams
weak
layers,
quality
variations,
geological
heterogeneity
as
most
paramount
concerns
demanding
immediate
attention
strategic
intervention.
By
adopting
proposed
FCM
leveraging
collective
industry
professionals,
this
offers
robust
framework
comprehensively
assessing
challenges
associated
with
events
tunnelling
projects,
thereby
fostering
enhanced
performance
efficacy
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Jan. 6, 2025
In
this
study,
two
novel
hybrid
intelligent
models
were
developed
to
evaluate
the
short-term
rockburst
using
random
forest
(RF)
method
and
meta-heuristic
algorithms,
whale
optimization
algorithm
(WOA)
coati
(COA),
for
hyperparameter
tuning.
Real-time
predictive
of
phenomenon
created
a
database
comprising
93
case
histories,
taking
into
account
various
microseismic
parameters.
The
results
indicated
that
WOA
achieved
highest
overall
performance
in
tuning
RF
model,
outperforming
COA.
RF-WOA
model
accurately
predicted
occurrence
with
an
accuracy
0.944.
Additionally,
precision,
recall
F1-score
obtained
as
0.950,
0.944
0.943,
respectively,
indicating
proposed
is
robust
predicting
damage
severity
deep
underground
projects.
Subsequently,
Shapley
additive
explanations
(SHAP)
was
employed
interpret
explain
prediction
process
assess
influence
input
features
based
on
model.
showed
three
parameters
including
cumulative
seismic
energy,
events,
apparent
volume
have
greatest
impact
events.
This
study
provides
interpretable
transparent
resource
events
real
time.
It
can
facilitate
estimating
project
costs,
selecting
suitable
support
system,
identifying
essential
ways
limit
danger
rockburst.
