High Fidelity Modeling and Simulations for Uncertainty Quantification and Risk-averse Optimization of Structures Under Natural Wind Conditions
- Alternative title
-
High Fidelity Modellierung und Simulationen zur Quantifizierung von Unsicherheiten und risikoaversen Optimierung von Bauwerken in natürlichen Windverhältnissen
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
München, Technische Universität München, Dissertation, 2024
- Keyword
-
Unsicherheit
Computersimulation
Windlast
Monte-Carlo-Simulation
- Event
-
Veröffentlichung
- (where)
-
München
- (who)
-
Universitätsbibliothek der TU München
- (when)
-
2024
- Creator
-
Kodakkal, Anoop
- Contributor
- URN
-
urn:nbn:de:bvb:91-diss-20240311-1703514-1-4
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:27 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Kodakkal, Anoop
- Bletzinger, Kai-Uwe
- Wüchner, Roland
- Römer, Ulrich
- Universitätsbibliothek der TU München
Time of origin
- 2024
Other Objects (12)
Electoral competition with uncertainty averse parties
Objective rationality and uncertainty averse preferences
An Application of Multi-Fidelity Uncertainty Quantification for Computational Wind Engineering
Numerical simulations and uncertainty quantification for cloud simulation
Stochastic material modelling and multi-fidelity uncertainty quantification of macroscopic bone tissue
Optimal Saving Rules for Loss-Averse Agents under Uncertainty
Efficient Uncertainty Quantification for Large-Scale Biomechanical Models Using a Bayesian Multi-Fidelity Approach
Non-intrusive uncertainty quantification with sparse grids for multivariate peridynamic simulations
Topographic uncertainty quantification for flow-like landslide models via stochastic simulations
Uncertainty quantification for expensive simulations : optimal surrogate modeling under time constraints
Multifaceted uncertainty quantification
L’Averse
Electoral competition with uncertainty averse parties
Objective rationality and uncertainty averse preferences
An Application of Multi-Fidelity Uncertainty Quantification for Computational Wind Engineering
Numerical simulations and uncertainty quantification for cloud simulation
Stochastic material modelling and multi-fidelity uncertainty quantification of macroscopic bone tissue
Optimal Saving Rules for Loss-Averse Agents under Uncertainty
Efficient Uncertainty Quantification for Large-Scale Biomechanical Models Using a Bayesian Multi-Fidelity Approach
Non-intrusive uncertainty quantification with sparse grids for multivariate peridynamic simulations
Topographic uncertainty quantification for flow-like landslide models via stochastic simulations
Uncertainty quantification for expensive simulations : optimal surrogate modeling under time constraints
Multifaceted uncertainty quantification
L’Averse
Electoral competition with uncertainty averse parties
Objective rationality and uncertainty averse preferences
An Application of Multi-Fidelity Uncertainty Quantification for Computational Wind Engineering
Numerical simulations and uncertainty quantification for cloud simulation
Stochastic material modelling and multi-fidelity uncertainty quantification of macroscopic bone tissue
Optimal Saving Rules for Loss-Averse Agents under Uncertainty
Efficient Uncertainty Quantification for Large-Scale Biomechanical Models Using a Bayesian Multi-Fidelity Approach
Non-intrusive uncertainty quantification with sparse grids for multivariate peridynamic simulations
Topographic uncertainty quantification for flow-like landslide models via stochastic simulations
Uncertainty quantification for expensive simulations : optimal surrogate modeling under time constraints
Multifaceted uncertainty quantification