Maritime electromagnetic (EM)‐based communication and detection systems are strongly influenced by meteorological conditions, as they can cause anomalous electromagnetic propagation within the surface layer. To predict the performance of such systems, detailed knowledge of the refractivity profile is required. In recent years, refractivity from clutter (RFC) methods has been developed to estimate this refractivity profile by measuring radar clutter return from the rough ocean surface. The current work proposes an RFC framework that utilizes a novel surrogate model for EM propagation. The surrogate model is based on an offline created library of sparsely sampled field data of clutter returns, compressed into proper orthogonal bases, and indexed on specific surface layer refractive parameters. By exploiting the Riemannian manifold structure of the space that proper orthogonal bases occur in, we are able to interpolate among them. This, then, enables us to use the surrogate model in an inverse problem setting, whose goal is to uncover in situ maritime EM propagation conditions efficiently. We demonstrate the feasibility of our proposed surrogate model‐based RFC approach for evaporation duct by testing it with field data obtained from an experimental campaign.
An uncertainty quantification framework is developed for Eulerian-Lagrangian models of particle-laden flows, where the fluid is modeled through a system of partial differential equations in the Eulerian frame and inertial particles are traced as points in the Lagrangian frame. The source of uncertainty in such problems is the particle forcing, which is determined empirically or computationally with high-fidelity methods (data-driven). The framework relies on the averaging of the deterministic governing equations with the stochastic forcing and allows for an estimation of the first and second moment of the quantities of interest. Via comparison with Monte Carlo simulations, it is demonstrated that the moment equations accurately predict the uncertainty for problems whose Eulerian dynamics are either governed by the linear advection equation or the compressible Euler equations. In areas of singular particle interfaces and shock singularities significant uncertainty is generated. An investigation into the effect of the numerical methods shows that low-dissipative higher-order methods are necessary to capture numerical singularities (shock discontinuities, singular source terms, particle clustering) with low diffusion in the propagation of uncertainty.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.