Searcharxiv⌕ Search

arXiv · 2610.01743

On the transmission of floating-point perturbations in flow-dependent filter-width formulations in Large-Eddy Simulation

Abstract

Heterogeneous high--performance computing architectures expose numerical algorithms to perturbations arising from the non--associativity of floating--point arithmetic. In Large--Eddy Simulation (LES), similar numerical effects may become relevant when they affect the filter--width entering the subgrid scale (SGS) model. This work investigates this mechanism for the least--squares (LSQ) based filter--width formulation, focusing on how floating--point effects are generated, transmitted, and coupled with the resolved flow. We show that, for fixed resolved kinematics, the LSQ filter--width is logarithmically non-expansive but not strictly contractive with respect to perturbations of the mesh metrics. Consequently, small disturbances may be transmitted with little attenuation through strongly directional filter-width responses. To mitigate this sensitivity, we introduce a scalar max--min compression of the directional mesh scales together with a bounded modulation based on the resolved velocity gradient. The resulting formulation reroutes floating--point perturbations through the filter-width operator, improving robustness while preserving the flow--dependent character of the original LSQ construction. The framework is assessed on heterogeneous CPU and GPU architectures for flow past a circular cylinder at Re=3900 and the Taylor--Green vortex at Re=1600. In the former, nearly one--to--one transmission of relative metric disturbances can become relevant when the transmitted perturbations interact with shear-layer transition. By contrast, on orthogonal Taylor--Green vortex grids, the accumulation pathway is structurally absent and no comparable macroscopic response develops. These results suggest floating--point sensitivity matters for LES filter--width formulations in heterogeneous computing environments.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Valerio D'Alessandro, Alessio Piccolo, Matteo Falone, Simone Bnà. 2026-10-01. On the transmission of floating-point perturbations in flow-dependent filter-width formulations in Large-Eddy Simulation. https://arxiv.org/abs/2610.01743

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

KEEP EXPLORING

Related papers

Real-Time Estimation of High-Resolution Flow Fields and Reduced-Order Coordinates from Event-Based Imaging Velocimetry

We propose a data-driven framework to estimate high-resolution (HR) velocity fields and reduced-order flow coordinates from real-time Event-Based Imaging Velocimetry (rt-EBIV). Fast event analysis first provides low-resolution (LR) velocity snapshots on a coarse grid. Offline, paired LR/HR fields are used to identify the LR-to-HR mapping and a linear dynamical model in a POD-based latent space. Online, each LR snapshot is projected onto the LR basis, the corresponding HR coordinates are estimated and temporally regularized, and the HR field is reconstructed from the retained POD modes. Three estimators are compared: a direct Kalman filter (KF), a linear stochastic estimator followed by Kalman filtering (LSE), and a variance-rescaled variant (LSE+VR). The method is tested on two turbulent flows acquired with pulsed EBIV: a submerged water jet and a channel flow over a square rib. All estimators outperform direct cubic interpolation of the LR fields, yielding more consistent HR reconstructions of instantaneous flow states, turbulent kinetic energy, spectra, reduced-order dynamics, and temporal coherence. LSE gives the lowest overall reconstruction error, while LSE+VR achieves similar errors with improved recovery of fluctuation energy and higher-order content. The direct KF is the most computationally efficient and provides the closest agreement with the HR reference in spectral analyses. Since most of the cost is associated with full-field HR reconstruction, the latent-coordinate estimation is negligible compared with LR processing. The framework allows deliberately coarse rt-EBIV processing to be combined with reduced-order refinement, extending real-time operation toward higher update rates while preserving richer and dynamically consistent HR flow representations for diagnostics and future observer-based flow-control applications.

physics.flu-dyn↗

Simulations of Particle-Laden Flows with Large Dispersed-Phase Size Disparities Using Scalable Parallel Adaptive Methods

The numerical simulation of multiphase flows involving dispersed components with large scale disparities, such as the collisions between millimeter-sized bubbles and micron-sized mineral particles in flotation, poses a significant computational challenge. Accurately resolving the thin boundary layers of finite-size objects while tracking massive numbers of small particles within a large turbulent domain is often prohibitively expensive on uniform grids. To address this, we present a parallel scalable computational framework that couples the lattice Boltzmann method with the immersed boundary method on a dynamically adaptive octree grid. A key algorithm is developed for the efficient parallel host-cell searching, which significantly accelerates the tracking of Lagrangian points on distributed unstructured grids. The accuracy and robustness of the code are rigorously validated against canonical benchmarks, including the flow induced by an oscillating cylinder and the sedimentation of a sphere. The framework is applied to the multiscale problem of bubble-particle collisions. In quiescent flow, the simulations accurately capture the hydrodynamic interception mechanism, reproducing the theoretical collision efficiency scaling law proportional to the square of the particle-to-bubble size ratio. Furthermore, the framework is applied to the simulation of fully resolved bubbles interacting with inertial point particles in homogeneous isotropic turbulence.

physics.flu-dyn↗

A conservative micro-continuum-cellular automaton method for multispecies biofilm dynamics in complex flows

We develop a conservative micro-continuum-cellular automaton method for simulating multispecies biofilm dynamics in complex flows. The proposed method couples the Darcy-Brinkman-Stokes equations, reactive transport, suspended bacteria, and biofilm dynamics with a two-stage cellular automaton algorithm for biofilm redistribution and interface evolution. While treating biofilms as evolving porous media, we ensure conservative redistribution of multispecies biomass across partially occupied cells. Donor and recipient cell volumes are explicitly accounted for to conserve biomass and preserve species composition on non-uniform meshes. The proposed method is assessed against diffusion-dominated benchmark cases, including single-species fingering and multispecies stratification, and is further evaluated through a mesh-convergence study for flow and growth over a rectangular bump. The framework is then applied to counter-diffusional biofilms in a membrane-aerated biofilm reactor as a canonical example. The results demonstrate that the framework captures the expected biofilm morphology and stratification in systems involving coupled flow, substrate transport, and biofilm dynamics. The proposed method provides a flexible computational approach for simulating multispecies biofilm dynamics in complex flows and geometries.

physics.flu-dyn↗