Metrology,
Journal Year:
2024,
Volume and Issue:
4(3), P. 337 - 363
Published: July 17, 2024
Virtual
experiments
(VEs)
and
digital
twins
(DTs),
pivotal
for
realizing
European
strategic
policies
on
sustainability
digitalization
within
Industry
4.0
the
Green
Deal,
simulate
physical
systems
characteristics
in
a
virtual
environment,
with
DTs
incorporating
dynamic
inputs
from
outputs
to
real-world
counterpart.
To
ensure
confidence
their
use
outcomes,
traceability
methods
evaluate
measurement
uncertainty
are
needed,
topics
that
hardly
covered
by
literature
so
far.
This
paper
provides
harmonized
definition
of
VEs
introduces
framework
evaluating
uncertainty.
Furthermore,
it
discusses
how
propagate
contributions
coming
different
parts
DT.
For
core
part
DT,
derived
can
be
used.
physical-to-virtual
(P2V)
connection
virtual-to-physical
(V2P)
connection,
additional
sources
need
considered.
metrological
taking
all
these
into
account
while
describing
establish
DTs.
Two
case
studies
presented
demonstrate
proposed
methodology
considering
industrially
relevant
measuring
instruments
devices,
namely,
coordinate
machine
(CMM)
collaborative
robot
arm
(cobot).
Developments in the Built Environment,
Journal Year:
2024,
Volume and Issue:
18, P. 100453 - 100453
Published: April 1, 2024
The
global
building
sector
plays
a
pivotal
role
in
addressing
sustainability,
climate
change,
and
carbon
neutrality.
This
study
introduces
the
original
concept
of
virtual
models
(VBMs)
throughout
lifecycle
industry,
considering
unique
characteristics
this
industry.
VBMs
are
defined
as
mathematical
that
represent
physical
behavior
buildings
their
lifecycle.
These
consist
subvirtual
operational
environments
target
building,
encompassing
variables,
equipment,
systems,
indoor
environments,
structural
material
behaviors.
can
contribute
to
achieving
existing
concepts
information
modeling,
digital
twins,
cyber-physical
systems
within
operations,
communities,
environments.
In
study,
categorized
into
five
aspects:
model
types,
interactions,
integrations,
levels
detail
(LODs).
LODs
classified
(LOD100,
LOD200,
LOD300,
LOD350,
LOD400)
depending
on
primary
coverage
across
entire
building.
Virtual
modeling
methodologies
proposed
aspects
achieve
higher
or
intended
LOD
states
from
both
academic
industrial
perspectives.
Finally,
future
research
directions
discussed
drive
shape
industry
through
transformations.
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(21), P. 9275 - 9275
Published: Oct. 25, 2024
This
research
investigates
the
use
of
digital
twin
(DT)
technology
to
improve
building
energy
management
and
analyse
occupant
behaviour.
DTs
perform
function
acting
as
virtual
replicas
physical
assets,
which
facilitates
real-time
monitoring,
predictive
maintenance,
data-driven
decision-making.
Consequently,
performance
comfort
can
be
enhanced.
study
evaluates
efficiency
in
optimising
usage
by
a
mix
systematic
literature
review
scientometric
analysis
466
articles
from
Scopus
database.
Among
main
obstacles
noted
are
interoperability
issues,
privacy
data
quality
difficulties,
requirement
for
more
thorough
integration
interactions.
The
results
highlight
necessity
standardised
frameworks
direct
DT
implementations
suggest
areas
further
study,
especially
improving
cybersecurity
incorporating
behaviour
into
models.
makes
practical
recommendations
using
increase
sustainability
built
environment.
Applied Energy,
Journal Year:
2024,
Volume and Issue:
375, P. 124080 - 124080
Published: Aug. 5, 2024
Smart
building
digital
twins
represent
a
significant
paradigm
shift
to
optimize
operations,
thereby
reducing
their
substantial
energy
consumption
and
emissions
through
digitalization.
The
objective
is
virtually
replicate
existing
buildings'
static
dynamic
aspects,
leveraging
data,
information,
models
spanning
the
entire
life
cycle.
virtual
replica
can
then
be
employed
for
intelligent
functions,
including
real-time
monitoring,
autonomous
control,
proactive
decision-making
operations.
To
enable
decisions,
within
twin
must
continually
evolve
with
changes
in
physical
building,
aligning
outputs
measurements
calibration.
This
continuous
updating
requires
of
model
inputs.
However,
challenges
arise
uncertain
conditions
buildings
marked
by
sensor
absence,
malfunctions,
inherent
limitations
measuring
certain
variables.
study
introduces
novel
calibration
framework
physics-based
models,
addressing
smart-building
while
considering
environment
buildings.
Within
this
framework,
generative
model-based
architecture
proposed.
enables
fast
scalable
solution
quantifying
uncertainty
reliable
Furthermore,
procedure
presented
based
on
pre-trained
calibrator
model.
A
comprehensive
evaluation
was
conducted
via
case
employing
multiple
experiments.
experimental
results
demonstrated
that
proposed
effectively
addresses
twins.
accurately
quantified
uncertainties
its
predictions
solved
single
problem
an
average
time
0.043
second.
For
facility-level
electricity
consumption,
Coefficient
Variation
Root
Mean
Squared
Error
(CVRMSE)
values
6.33%,
10.18%,
10.97%
were
achieved
under
observations
without
noise
or
missing
noise,
respectively.
Similarly,
gas
corresponding
18.75%,
20.53%,
20.7%.
CVRMSE
scores
both
cases
met
standard
hourly
thresholds
