Computer-aided many-objective optimization framework via deep learning surrogate models: Promoting carbon reduction in refining processes from a life cycle perspective
Chemical Engineering Science,
Год журнала:
2025,
Номер
unknown, С. 121350 - 121350
Опубликована: Фев. 1, 2025
Язык: Английский
Comparative Study of Hydrogen Storage and Metal Hydride Systems: Future Energy Storage Solutions
Processes,
Год журнала:
2025,
Номер
13(5), С. 1506 - 1506
Опубликована: Май 14, 2025
Hydrogen
is
a
key
energy
carrier,
playing
vital
role
in
sustainable
systems.
This
review
provides
comparative
analysis
of
physical,
chemical,
and
innovative
hydrogen
storage
methods
from
technical,
environmental,
economic
perspectives.
It
has
been
identified
that
compressed
liquefied
are
predominantly
utilized
transportation
applications,
while
chemical
transport
mainly
supported
by
liquid
organic
carriers
(LOHC)
ammonia-based
Although
metal
hydrides
nanomaterials
offer
high
capacities,
they
face
limitations
related
to
cost
thermal
management.
Furthermore,
artificial
intelligence
(AI)-
machine
learning
(ML)-based
optimization
techniques
highlighted
for
their
potential
enhance
efficiency
improve
system
performance.
In
conclusion,
systems
achieve
broader
applicability,
it
recommended
integrated
approaches
be
adopted—focusing
on
material
development,
feasibility,
environmental
sustainability.
Язык: Английский
The multi-objective data-driven approach: A route to drive performance optimization in the food industry
Trends in Food Science & Technology,
Год журнала:
2024,
Номер
152, С. 104697 - 104697
Опубликована: Авг. 31, 2024
Язык: Английский
Foundation Models for the Process Industry: Challenges and Opportunities
Engineering,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 1, 2025
Язык: Английский
Time series prediction of anaerobic digestion yield and carbon emissions from food waste based on iTransformer model
Chemical Engineering Journal,
Год журнала:
2025,
Номер
513, С. 163064 - 163064
Опубликована: Апрель 26, 2025
Язык: Английский
Multi-scale revolution of artificial intelligence in chemical industry
Ying Li,
Quanhu Sun,
Zutao Zhu
и другие.
Frontiers of Chemical Science and Engineering,
Год журнала:
2025,
Номер
19(7)
Опубликована: Май 23, 2025
Maximization of Hydrogen Production via Methane Steam Reforming in a Wavy Microreactor by Optimization of Catalyst Coating: A Combined Computational and Data Analytics Approach
Industrial & Engineering Chemistry Research,
Год журнала:
2024,
Номер
63(43), С. 18599 - 18614
Опубликована: Окт. 21, 2024
This
study
introduces
an
advanced
methodology
for
optimizing
catalytic
coatings
on
microreactor
walls
used
in
the
steam
reforming
of
methane.
By
integrating
computational
fluid
dynamics,
data
analytics,
and
multiobjective
optimization,
this
approach
significantly
intensifies
process,
reduces
catalyst
usage,
improves
economic
environmental
aspects
hydrogen
production.
The
challenge
identifying
ideal
is
addressed
by
employing
surrogate
functions
created
extensive
sets
from
dynamics
machine
learning.
These
are
rigorously
validated,
achieving
99.9%
accuracy
both
total
H2
production
rate
per
coated
surface
area.
optimal
coating
demonstrates
a
65.8%
increase
area,
yet
9%
entropy
generation
compared
to
fully
channel.
findings
underscore
significant
opportunities
enhance
cost-effectiveness
sustainability
future
microreactors
through
optimization
discrete
coatings.
Язык: Английский