- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
In: Environmental Earth Sciences, 84, 3, S. 1-6
- Ereignis
-
Veröffentlichung
- (wo)
-
Berlin
- (wer)
-
Bundesanstalt für Materialforschung und -prüfung (BAM)
- (wann)
-
2025
- Urheber
-
Nagel, Thomas
Rühaak, Wolfram
Amann, Florian
Bracke, Guido
Buske, Stefan
Kowalski, Julia
Reiche, Sönke
Schäfer, Thorsten
Scheytt, Traugott
Stumpf, Thorsten
Völzke, Holger
Wellmann, Florian
Kolditz, Olaf
- DOI
-
10.1007/s12665-024-12075-2
- URN
-
urn:nbn:de:kobv:b43-624955
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:25 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Nagel, Thomas
- Rühaak, Wolfram
- Amann, Florian
- Bracke, Guido
- Buske, Stefan
- Kowalski, Julia
- Reiche, Sönke
- Schäfer, Thorsten
- Scheytt, Traugott
- Stumpf, Thorsten
- Völzke, Holger
- Wellmann, Florian
- Kolditz, Olaf
- Bundesanstalt für Materialforschung und -prüfung (BAM)
Entstanden
- 2025
Ähnliche Objekte (12)
OpenFOAM-avalanche 2312: Depth-integrated Models Beyond Dense Flow Avalanches
Deep geological disposal
Topographic uncertainty quantification for flow-like landslide models via stochastic simulations
Elements of future snowpack modeling – part 2: A modular and extendable Eulerian–Lagrangian numerical scheme for coupled transport, phase changes and settling processes
A unified Bayesian model selection workflow for geophysical free-surface flow
Bayesian active learning for parameter calibration of landslide run-out models
OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches
Bayesian active learning for parameter calibration of landslide run-out models
Elements of future snowpack modeling – Part 1: A physical instability arising from the nonlinear coupling of transport and phase changes
Elements of future snowpack modeling – Part 2: A modular and extendable Eulerian–Lagrangian numerical scheme for coupled transport, phase changes and settling processes
From Dense Flows to Powder Cloud Simulations: The OpenFOAM Avalanche Module
Development of electromagnetic induction measurement and inversion methods for soil electrical conductivity investigations
OpenFOAM-avalanche 2312: Depth-integrated Models Beyond Dense Flow Avalanches
Deep geological disposal
Topographic uncertainty quantification for flow-like landslide models via stochastic simulations
Elements of future snowpack modeling – part 2: A modular and extendable Eulerian–Lagrangian numerical scheme for coupled transport, phase changes and settling processes
A unified Bayesian model selection workflow for geophysical free-surface flow
Bayesian active learning for parameter calibration of landslide run-out models
OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches
Bayesian active learning for parameter calibration of landslide run-out models
Elements of future snowpack modeling – Part 1: A physical instability arising from the nonlinear coupling of transport and phase changes
Elements of future snowpack modeling – Part 2: A modular and extendable Eulerian–Lagrangian numerical scheme for coupled transport, phase changes and settling processes
From Dense Flows to Powder Cloud Simulations: The OpenFOAM Avalanche Module
Development of electromagnetic induction measurement and inversion methods for soil electrical conductivity investigations
OpenFOAM-avalanche 2312: Depth-integrated Models Beyond Dense Flow Avalanches
Deep geological disposal
Topographic uncertainty quantification for flow-like landslide models via stochastic simulations
Elements of future snowpack modeling – part 2: A modular and extendable Eulerian–Lagrangian numerical scheme for coupled transport, phase changes and settling processes
A unified Bayesian model selection workflow for geophysical free-surface flow
Bayesian active learning for parameter calibration of landslide run-out models
OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches
Bayesian active learning for parameter calibration of landslide run-out models
Elements of future snowpack modeling – Part 1: A physical instability arising from the nonlinear coupling of transport and phase changes
Elements of future snowpack modeling – Part 2: A modular and extendable Eulerian–Lagrangian numerical scheme for coupled transport, phase changes and settling processes
From Dense Flows to Powder Cloud Simulations: The OpenFOAM Avalanche Module