Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 1611.04129

Spatial correlations in bed load transport: evidence, importance, and modelling

J. Heyman·H. B. Ma·F. Mettra·C. Ancey
View original source ↗Read source document ↗Export metadata ↓

Abstract

This article examines the spatial {dynamics of bed load particles} in water. We focus particularly on the fluctuations of particle activity, which is defined as the number of moving particles per unit bed {length}. Based on a stochastic model recently proposed by \citet{Ancey2013}, we derive the second moment of particle activity analytically; that is the spatial correlation functions of particle activity. From these expressions, we show that large moving particle clusters can develop spatially. Also, we provide evidence that fluctuations of particle activity are scale-dependent. Two characteristic lengths emerge from the model: a saturation length $\ell_{sat}$ describing the length needed for a perturbation in particle activity to relax to the homogeneous solution, and a correlation length $\ell_c$ describing the typical size of moving particle clusters. A dimensionless Péclet number can also be defined according to the transport model. Three different experimental data sets are used to test the theoretical results. We show that the stochastic model describes spatial patterns of particle activity well at all scales. In particular, we show that $\ell_c$ and $\ell_{sat}$ may be relatively large compared to typical scales encountered in bed load experiments (grain diameter, water depth, bed form wavelength, flume length...) suggesting that the spatial fluctuations of particle activity have a non-negligible impact on the average transport process.

Explore related subjects

physics.geo-phphysics.flu-dyn

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J. Heyman, H. B. Ma, F. Mettra, C. Ancey. 2016-11-13. Spatial correlations in bed load transport: evidence, importance, and modelling. https://doi.org/10.1002/2013jf003003

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Direction-Aware Masked Pretraining for 3D Seismic Representation Learning and Transfer to Cross-Area Acoustic Impedance Inversion

Large archives of unlabeled three-dimensional seismic data offer opportunities for self-supervised representation learning and subsequent transfer to acoustic impedance inversion. However, conventional masked pretraining often treats three axes equivalently, overlooking differences between lateral reflector structure and vertical waveform characteristics. We propose a direction-aware masked autoencoder for three-dimensional post-stack seismic data, combining anisotropic tokenization, direction-aware representation, trace-aligned tube masking, and reconstruction constraints designed for reflector continuity and waveform characteristics. We evaluate reconstruction quality and downstream transferability using field data through masked reconstruction and cross-area acoustic impedance inversion. Reconstruction is more sensitive to lateral token resolution than to moderate changes in vertical patch length. Within the evaluated configurations, increasing encoder capacity does not fully compensate for reconstruction fidelity loss associated with coarser tokenization. Preferred token scales and masking strategies differ between reconstruction and inversion, indicating that reconstruction fidelity alone is not a reliable indicator of transferability. For cross-area inversion, the pretrained model is fine-tuned in the source area and applied to the target area without further parameter updates. With limited target-area well control, the proposed framework reduces normalized root-mean-square error by 20.8% relative to a pretrained conventional masked autoencoder across eight target-area test wells under matched tokenization and downstream settings. These results demonstrate the value of direction-aware masked pretraining for field seismic inversion and show that token scale and masking strategy should be selected according to downstream-task requirements rather than reconstruction accuracy alone.

physics.geo-ph↗
arXiv2026

Predicting the Elastic Properties of a Cemented Granular Material during Chemical Damage (Debonding)

While underground reservoirs emerge as essential elements to face global warming, these systems represent complex multi-physical and multiscale problems. The considered injection of fluids during hydrogen storage, carbon dioxide sequestration, or geothermal energy recovery involves a modification of the chemical equilibrium of the fluid in the porous reservoir. Chemical reactions can induce microstructural changes of the rock matrix, leading to a reduction of elastic properties of the material, and to potential settlement or stress redistribution. Consequently, it becomes pivotal to establish predictive behavior laws to describe the effect of chemical damage on elastic properties. Facing the difficulties to estimate experimentally the impact of chemical damage on mechanical properties, a Digital Rock Physics approach is proposed in this contribution. This numerical homogenization scheme is used to compare two distinct types of microstructure models: the first one consists in a Discrete Element Model, while the second one employs a continuous description. This continuous formulation is based on a Phase-Field description to predict the evolution of the microstructure subjected to chemical alterations and on the Fast Fourier Transform to estimate the macroscopic properties of the material. Finally, these frameworks establish different softening laws that can be used as constitutive ingredients for a cemented material during its weathering.

physics.geo-ph↗
arXiv2026

Determination of Physical Height Differences from Time Transfer via the ACES Mission -- A Simulation Study

The determination of physical height differences using highly stable atomic clocks has emerged as a novel approach in relativistic geodesy, exploiting the gravitational redshift as a direct observable of geopotential differences. In this study, we investigate the feasibility of satellite-based clock comparisons using the Atomic Clock Ensemble in Space (ACES) onboard the International Space Station, which enables time transfer via microwave (MWL) and optical (ELT) links. Since operational optical data are not yet available, a comprehensive full-scale simulation of realistic ACES observation scenarios is performed, including detailed noise models of clocks and links. A slope-based estimation method is applied to time series of clock comparisons in order to extract the relativistic redshift signal and derive height differences between the ground stations. The performance of the approach is evaluated for quasi-common view, non-common view, and split non-common view configurations, where the latter divides the observation period into shorter intervals. The results show that optical links enable faster convergence and can achieve height accuracies at the decimeter level within a few days and at the centimeter level over longer periods, while microwave links are more strongly affected by noise and bias contributions. Non-common view processing significantly increases observation availability with only minor loss in accuracy, and the split approach provides robust solutions for larger networks. These findings demonstrate the strong potential of satellite-based clock comparisons as a remote-sensing technique for determining physical height differences on a continental scale.

physics.geo-ph↗