Augmentation of Cross-Sectional Spray Measurements with Discrete Droplet Model Using Ensemble Kalman Filter
نویسندگان
چکیده
Spray flows containing droplets and particles are used in various industrial fields. In this study, we investigate an efficient reliable way to predict the spray flow of by combining discrete droplet model (DDM) with ensemble data assimilation for application such problems. The aim is augment cross-sectional measurements as particle image velocimetry (PIV) fast DDM simulations droplets. paper, focus on numerical experiment assimilation, which also known twin experiments, discuss how can be integrated Kalman filter. results showed that position velocity nozzle's state were estimated assimilating time-averaged cross-section using a carefully prepared Furthermore, size distribution was indirectly through DDM.
منابع مشابه
Real - Time Reservoir Model Updating Using Ensemble Kalman Filter
This paper was selected for presentation by an SPE Program Committee following review of information contained in a proposal submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum ...
متن کاملEnsemble Kalman filter with the unscented transform
A modification scheme to the ensemble Kalman filter (EnKF) is introduced based on the concept of the unscented transform (Julier et al., 2000; Julier and Uhlmann, 2004), which therefore will be called the ensemble unscented Kalman filter (EnUKF) in this work. When the error distribution of the analysis is symmetric (not necessarily Gaussian), it can be shown that, compared to the ordinary EnKF,...
متن کاملResampling the ensemble Kalman filter
Ensemble Kalman filters (EnKF) based on a small ensemble tend to provide collapse of the ensemble over time. It is shown that this collapse is caused by positive coupling of the ensemble members due to use of one common estimate of the Kalman gain for the update of all ensemble members at each time step. This coupling can be avoided by resampling the Kalman gain from its sampling distribution i...
متن کاملDiscrete Kalman Filter Tutorial
be the set of k observations. Finding xak, the estimate or analysis of the state space xk, given Zk and the initial conditions is called the filtering problem. When the dynamic model for the process, f(·), and for the measurements, h(·), are linear, and the random components x0, wk, vk are uncorrelated Gaussian random vectors, then the solution is given by the classical Kalman filter equations ...
متن کاملMulti-Model Ensemble Approaches to Data Assimilation Using the 4D-Local Ensemble Transform Kalman Filter
Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computational Fluid Dynamics
سال: 2022
ISSN: ['1026-7417', '1061-8562', '1029-0257']
DOI: https://doi.org/10.1080/10618562.2022.2052281