Channels - Flow Decomposition by Optimal Balance With Time‐Averaging :: FRELIP Discovery

Similar Items: Flow Decomposition by Optimal Balance With Time‐Averaging

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Experimental study of time-averaged flow and turbulence over asymmetric tidal dunes
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Dynamic mode decomposition of extreme events
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Boosting ensembles for statistics of tails at conditionally optimal advance split times
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Seasonal Ice Dynamics Control the Timing of Crevasse Drainage at a Fast‐Flowing Outlet Glacier
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Projected elevation-dependent warming in the Alps: contrasting free-atmosphere and surface trends with surface energy balance drivers
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Listening, in Times of Noise
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The Fate of Western Headwaters: Climate Controls on Base‐Flow Decline
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Stacking ensemble model for rainfall prediction using hyperparameter optimization
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On transversality and the characterization of finite time hyperbolic subspaces in chaotic attractors
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On the criticality of return flows in viscous accretionary wedges and its implications for deep-crustal exhumation in subduction zones
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Optimization of blast design to improve fragmentation of limestone at Dire-Dawa Quarry, Eastern Ethiopia
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Supercritical‐flow structures in a Cretaceous submarine channel–lobe transition zone, Point Loma Formation, California
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Tide of the Time: Global tidal characteristics observed from in-situ measurements
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Timing of the reproductive cycle of waved whelk, on the U.S. Mid-Atlantic Bight
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Ocean salinity across space-time scales: from water cycle indicator to dynamical driver
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Safeguarding Cultural Heritage: Integrating laser scanning, InSAR, vibration monitoring and rockfall/granular flow runout modelling at the Temple of Hatshepsut, Egypt
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A multi-chain surrogate-assisted hybrid optimization framework for joint identification of groundwater contaminant sources and hydrogeological parameters
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Application of swarm intelligence optimization techniques and explainable data-driven methods in predicting the shear strength of serrated jointed rock masses
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Basic Earth Parameters from VLBI observations using Bayesian inversions in the time domain: updated insights of the Earth's interior
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Predicting intact rock strength for mechanical excavation in dry and saturated condition using multivariate statistics and artificial neural networks optimized using genetic algorithm