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Design Methods for Reducing Failure Probabilities with Examples from Electrical Engineering : Doctoral Thesis accepted by Technische Universität Darmstadt, Germany / Mona Fuhrländer
Design Methods for Reducing Failure Probabilities with Examples from Electrical Engineering : Doctoral Thesis accepted by Technische Universität Darmstadt, Germany / Mona Fuhrländer
Autore Fuhrländer, Mona
Pubbl/distr/stampa Cham, : Springer, 2023
Descrizione fisica xxii, 153 p. : ill. ; 24 cm
Soggetto non controllato Adaptive Newton-Monte Carlo method
Design and Optimization of Electrotechnical Devices
Gaussian process regression
Hermite BOBYQA
Hermite Least Squares Optimization
Hybrid Monte Carlo Method
Manufacturing Uncertainties
Maxwell’s equations
Mixed Gradient Optimization
Modeling Electromagnetic Phenomena
Multi-objective Yield Optimization
Permanent Magnet Synchronous Machine
Robust Design Optimization
Stochastic Collocation
Uncertainty Quantification
Yield Optimization
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNICAMPANIA-VAN0279424
Fuhrländer, Mona  
Cham, : Springer, 2023
Materiale a stampa
Lo trovi qui: Univ. Vanvitelli
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Design Methods for Reducing Failure Probabilities with Examples from Electrical Engineering : Doctoral Thesis accepted by Technische Universität Darmstadt, Germany / Mona Fuhrländer
Design Methods for Reducing Failure Probabilities with Examples from Electrical Engineering : Doctoral Thesis accepted by Technische Universität Darmstadt, Germany / Mona Fuhrländer
Autore Fuhrländer, Mona
Pubbl/distr/stampa Cham, : Springer, 2023
Descrizione fisica xxii, 153 p. : ill. ; 24 cm
Soggetto topico 00A79 (77-XX) - Physics [MSC 2020]
62-XX - Statistics [MSC 2020]
90-XX - Operations research, mathematical programming [MSC 2020]
Soggetto non controllato Adaptive Newton-Monte Carlo method
Design and Optimization of Electrotechnical Devices
Gaussian process regression
Hermite BOBYQA
Hermite Least Squares Optimization
Hybrid Monte Carlo Method
Manufacturing Uncertainties
Maxwell’s equations
Mixed Gradient Optimization
Modeling Electromagnetic Phenomena
Multi-objective Yield Optimization
Permanent Magnet Synchronous Machine
Robust Design Optimization
Stochastic Collocation
Uncertainty Quantification
Yield Optimization
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNICAMPANIA-VAN00279424
Fuhrländer, Mona  
Cham, : Springer, 2023
Materiale a stampa
Lo trovi qui: Univ. Vanvitelli
Opac: Controlla la disponibilità qui
Empowering Materials Processing and Performance from Data and AI
Empowering Materials Processing and Performance from Data and AI
Autore Chinesta Francisco
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 online resource (156 p.)
Soggetto topico Technology: general issues
Soggetto non controllato additive manufacturing
analytical model
artificial neural networks
Code2Vect
computational modeling
constitutive modeling
data driven
data mining
data-driven
data-driven mechanics
effective properties
elasto-visco-plasticity
FE-beam model
feature engineering
finite element model
Gaussian process
Gaussian process regression
GENERIC
hardness
high-throughput experimentation
hyperelasticity
laser shock peening
machine learning
manifold learning
mechanical properties
microcompression
microstructures
model calibration
model correction
multiscale
n/a
nanoindentation
nanoporous metals
neural networks
nonlinear
nonlinear regression
open-pore foams
physics based
plasticity
principal component analysis
residual stresses
sensitivity analysis
soft living tissues
spherical indentation
statistical analysis
stochastics
structure-property relationship
TDA
Ti-Mn alloys
topological data analysis
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557717703321
Chinesta Francisco  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Integration and Control of Distributed Renewable Energy Resources
Integration and Control of Distributed Renewable Energy Resources
Autore Nazaripouya Hamidreza
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 online resource (148 p.)
Soggetto topico History of engineering & technology
Technology: general issues
Soggetto non controllato composite control strategy
DG
diesel generator
different PV technologies
distributed generation
distribution networks
distribution system
energy independence
energy storage system (ESS)
Gaussian process regression
green communities
HOMER
intraday forecasting
machine learning
microgrids
min-max optimisation
model-based predictive control
Monte Carlo simulations
n/a
off-grid system
permanent magnet brushless DC machine (PMBLDCM)
photovoltaics
PLO's profit
power losses
power quality
power quality improvement
power system management
power system optimization
power system reliability
PV curves
PV hosting capacity
robustness
smart grid paradigm
smart grids
solar photovoltaic panel
solar-powered electric vehicle parking lots
synchronous machine (SM)
TSA/SCA
uncertainties
wind turbine
wind turbines
worst-case scenario
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910566463203321
Nazaripouya Hamidreza  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Kernel Mode Decomposition and the Programming of Kernels / Houman Owhadi, Clint Scovel, Gene Ryan Yoo
Kernel Mode Decomposition and the Programming of Kernels / Houman Owhadi, Clint Scovel, Gene Ryan Yoo
Autore Owhadi, Houman
Pubbl/distr/stampa Cham, : Springer, 2021
Descrizione fisica x, 118 p. : ill. ; 24 cm
Altri autori (Persone) Scovel, Clint
Yoo, Gene Ryan
Soggetto topico 68T10 - Pattern recognition, speech recognition [MSC 2020]
62J02 - General nonlinear regression [MSC 2020]
62-XX - Statistics [MSC 2020]
62G07 - Density estimation [MSC 2020]
62J12 - Generalized linear models (logistic models) [MSC 2020]
62R07 - Statistical aspects of big data and data science [MSC 2020]
62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020]
62G08 - Nonparametric regression and quantile regression [MSC 2020]
68T09 - Computational aspects of data analysis and big data [MSC 2020]
Soggetto non controllato Additive models
Empirical mode decomposition
Gaussian process regression
Kernel methods
Time-frequency decomposition
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNICAMPANIA-VAN0274859
Owhadi, Houman  
Cham, : Springer, 2021
Materiale a stampa
Lo trovi qui: Univ. Vanvitelli
Opac: Controlla la disponibilità qui
Kernel Mode Decomposition and the Programming of Kernels / Houman Owhadi, Clint Scovel, Gene Ryan Yoo
Kernel Mode Decomposition and the Programming of Kernels / Houman Owhadi, Clint Scovel, Gene Ryan Yoo
Autore Owhadi, Houman
Pubbl/distr/stampa Cham, : Springer, 2021
Descrizione fisica x, 118 p. : ill. ; 24 cm
Altri autori (Persone) Scovel, Clint
Yoo, Gene Ryan
Soggetto topico 62-XX - Statistics [MSC 2020]
62G07 - Density estimation [MSC 2020]
62G08 - Nonparametric regression and quantile regression [MSC 2020]
62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020]
62J02 - General nonlinear regression [MSC 2020]
62J12 - Generalized linear models (logistic models) [MSC 2020]
62R07 - Statistical aspects of big data and data science [MSC 2020]
68T09 - Computational aspects of data analysis and big data [MSC 2020]
68T10 - Pattern recognition, speech recognition [MSC 2020]
Soggetto non controllato Additive models
Empirical mode decomposition
Gaussian process regression
Kernel methods
Time-frequency decomposition
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNICAMPANIA-VAN00274859
Owhadi, Houman  
Cham, : Springer, 2021
Materiale a stampa
Lo trovi qui: Univ. Vanvitelli
Opac: Controlla la disponibilità qui
Modeling and Simulation of Metallurgical Processes in Ironmaking and Steelmaking
Modeling and Simulation of Metallurgical Processes in Ironmaking and Steelmaking
Autore Echterhof Thomas
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 online resource (286 p.)
Soggetto topico History of engineering & technology
Technology: general issues
Soggetto non controllato arc gap
arc impingement
artificial neural network
blast furnace ironmaking
bubble deformation
bubble generation
bubble size distribution
carbon composite briquette
coke saving
computational fluid dynamic
computational fluid dynamics
continuous casting
continuous charging
direct current
direct reduction
drag force
drying
electric arc
electric arc furnace
energy consumption
energy demand
estimation
evaluation model
evolving modelling
fuzzy modelling
gas density
Gaussian process regression
heat exchanger
heat recovery technology
horizontal single belt casting
HYL
inflow condition
Köhle formula
lift force
liquid metals
machine learning
magneto hydrodynamics
mass transfer coefficient
mathematical modeling
mathematical modelling
Midrex
model application
model predictive control
model validation
modelling
n/a
near net shape casting
numerical simulation
porous plugs
pre-reduction
profile optimization
quantitative relationship
RANS/LES/DNS
reaction kinetics
real-time model
RecHeat
reduction process
regression
Rist diagram
rotary kiln
scrap melting
scrap preheating
slag energy content
slag heat recovery
steel refining
steelmaking
steelmaking process
turbulence modelling
twin roll (Bessemer) casting
ISBN 3-0365-5154-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910619471103321
Echterhof Thomas  
MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Sensor Networks in Structural Health Monitoring: From Theory to Practice
Sensor Networks in Structural Health Monitoring: From Theory to Practice
Autore Chatzi Eleni
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 online resource (164 p.)
Soggetto topico Technology: general issues
Soggetto non controllato adjacent buildings
autoregressive with exogenous inputs
Bayesian inference
Bayesian model updating
bridges
computation time
damage detection and localization
damage identification
distributed sensor network
error-domain model falsification
evolutionary optimisation
frequency of entrainment
Gaussian process regression
inertial sensor fusion
instrumented particle
Internet of Things (IoT)
iterative asset-management
MEMS
modal identification
mode shape curvatures
model updating
mutual information
n/a
practical applicability
probabilistic data-interpretation
sediment entrainment
semi-active control
sensor calibration
sensor placement optimisation
soil-structure interaction (SSI)
structural dynamics
structural health monitoring
swarm-based parallel control (SPC)
varying environmental and operational conditions
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Sensor Networks in Structural Health Monitoring
Record Nr. UNINA-9910557504303321
Chatzi Eleni  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui