We are modelling multiscale, multi-physics uncertainty in wave-current interaction (WCI). To model uncertainty in WCI, we introduce stochasticity into the wave dynamics of two classic models of WCI, namely the generalised Lagrangian mean (GLM) model and the Craik-Leibovich (CL) model. The key idea for the GLM approach is the separation of the Lagrangian (fluid) and Eulerian (wave) degrees of freedom in Hamilton's principle. This is done by coupling an Euler-Poincaré for the current flow and a for the wave field. WCI in the GLM model involves the nonlinear Doppler shift in frequency of the Hamiltonian wave subsystem, which arises because the waves propagate in the frame of motion of the Lagrangian-mean velocity of the current. In contrast, WCI in the CL model arises because the fluid velocity is defined relative to the frame of motion of the Stokes mean drift velocity, which is usually taken to be prescribed, time independent and driven externally. We compare the GLM and CL theories by placing them both into the general framework of a stochastic Hamilton's principle for a 3D Euler-Boussinesq (EB) fluid in a rotating frame. In other examples, we also apply the GLM and CL methods to add wave physics and stochasticity to the familiar 1D and 2D shallow water flow models. The differences in the types of stochasticity which arise for GLM and CL models can be seen by comparing the Kelvin circulation theorems for the two models. The GLM model acquires stochasticity in its Lagrangian transport velocity for the currents and also in its group velocity for the waves. However, the CL model is based on defining the Eulerian velocity in the integrand of the Kelvin circulation relative to the Stokes drift velocity induced by waves driven externally. Thus, the Kelvin theorem for the stochastic CL model can accept stochasticity in its both its integrand and in the Lagrangian transport velocity of its circulation loop. In an "Appendix", we also discuss dynamical systems analogues of WCI.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749098PMC
http://dx.doi.org/10.1007/s00332-020-09665-2DOI Listing

Publication Analysis

Top Keywords

glm model
12
wave-current interaction
8
model
8
wci model
8
hamilton's principle
8
frame motion
8
velocity
8
stokes drift
8
drift velocity
8
driven externally
8

Similar Publications

Purpose: Artificial Intelligence models based on medical (imaging) data are increasingly developed. However, the imaging software on which the original data is generated is frequently updated. The impact of updated imaging software on the performance of AI models is unclear.

View Article and Find Full Text PDF

Background And Objective: This study delves into the parenting cognition perspectives on COVID-19 in children, exploring symptoms, transmission modes, and protective measures. It aims to correlate these perspectives with sociodemographic factors and employ advanced machine-learning techniques for comprehensive analysis.

Method: Data collection involved a semi-structured questionnaire covering parental knowledge and attitude on COVID-19 symptoms, transmission, protective measures, and government satisfaction.

View Article and Find Full Text PDF

Many machine learning techniques have been used to construct gene regulatory networks (GRNs) through precision matrix that considers conditional independence among genes, and finally produces sparse version of GRNs. This construction can be improved using the auxiliary information like gene expression profile of the related species or gene markers. To reach out this goal, we apply a generalized linear model (GLM) in first step and later a penalized maximum likelihood to construct the gene regulatory network using Glasso technique for the residuals of a multi-level multivariate GLM among the gene expressions of one species as a multi-levels response variable and the gene expression of related species as a multivariate covariates.

View Article and Find Full Text PDF

Panicle elongation length (PEL), which determines panicle exsertion, is an important outcrossing-related trait. Mining genes controlling PEL in rice (Oryza sativa L.) has great practical significance in breeding cytoplasmic male sterility (CMS) lines with increased PEL and simplified, high-efficiency seed production.

View Article and Find Full Text PDF

Objectives: Rheumatoid arthritis (RA) is a chronic, destructive autoimmune disorder predominantly targeting the joints, with gut microbiota dysbiosis being intricately associated with its progression. The aim of the present study was to develop of effective early diagnostic methods for early RA based on gut microbiota.

Methods: A cohort comprising 262 RA patients and 475 healthy controls (HCs) was recruited.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!