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Mathematical Modelling of Energy Systems and Fluid Machinery

The ongoing digitalization of the energy sector, which will make a large amount of data available, should not be viewed as a passive ICT application for energy technology or a threat to thermodynamics and fluid dynamics, in the light of the competition triggered by data mining and machine learning t...

Повний опис

Збережено в:
Формат: Online
Мова:Англійська
Опубліковано: MDPI - Multidisciplinary Digital Publishing Institute 2022
Предмети:
centrifugal pump
double hidden layer
Levenberg–Marquardt algorithm
performance prediction
thermal energy storage
stratification
dynamic simulation
heating
double-channel sewage pump
critical wall roughness
numerical calculation
external characteristics
axial-flow pump
impeller
approximation model
optimization design
multi-disciplinary
blade slot
orthogonal test
numerical simulation
Francis turbine
anti-cavity fins
draft tube
vortex rope
low flow rates
internal flow characteristics
unsteady pressure
energy recovery
turboexpander
throttling valves
CFD
modelling techniques
Kaplan turbine
draft tube optimization
CFD analysis
DOE
response surface
single-channel pump
CFD-DEM coupling method
particle features and behaviors
solid-liquid two-phase flows
computational fluid dynamics (CFD)
artificial neural network (ANN)
subcooled boiling flows
uncertainty quantification (UQ)
Monte Carlo dropout
deep ensemble
deep neural network (DNN)
intake structures
physical hydraulic model
free surface flow
free surface vortices
vertical pump
design considerations
magnetocaloric effect
coefficient of performance
refrigeration
capacity
mathematical modelling
energy systems
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
Онлайн доступ:ONIX_20220111_9783036505503_114
Теги: Додати тег
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