A finite element continuous data assimilation framework for a Navier--Stokes--Cahn--Hilliard system

TL;DR

This paper develops a continuous data assimilation framework for a coupled Navier--Stokes--Cahn--Hilliard system, enabling trajectory recovery from coarse observations using a finite element scheme and nudging techniques.

Contribution

It introduces a novel CDA approach with a finite element scheme for the NSCH system, including theoretical analysis and numerical validation.

Findings

Successful recovery from mismatched initial conditions

Dependence of synchronization on observation resolution and feedback strength

Distinct fine-scale evolutions can be distinguished by assimilation

Abstract

This paper studies a coupled two-dimensional Navier--Stokes--Cahn--Hilliard phase-field model augmented by a transported auxiliary field, and develops a continuous data assimilation (CDA) framework for recovering its trajectories from coarse-in-space observations. We formulate a nudging-based CDA system for the coupled NSCH--auxiliary-field model, in which coarse measurements are incorporated through a general linear observation operator. The observation mechanism is described abstractly by an interpolant satisfying an $H^{2}$-type approximation property, which is compatible with coarse spatial observations obtained from mesh coarsening and reconstruction. At the continuous level, we record two structural properties of the model: a formal energy law for the reference system and an evolution law for the phase mean in the assimilated dynamics. At the discrete level, we introduce a capped fully discrete finite element splitting scheme using continuous quadratic elements for the phase, chemical potential, velocity, and auxiliary field, together with continuous linear elements for the pressure. For this scheme, we prove one-step well-posedness and establish a stepwise a priori estimate for the capped method. Numerical experiments illustrate the practical behavior of the proposed CDA approach. They demonstrate recovery from strongly mismatched initial conditions and show how synchronization depends on the observation resolution, boundary forcing, and feedback strength. A coarse-indistinguishability experiment further shows that identical coarse initial information may correspond to distinct fine-scale evolutions, while the assimilated dynamics select the trajectory determined by the supplied time-dependent observations.