Journal of Flow Control, Measurement & Visualization

Volume 3, Issue 2 (April 2015)

ISSN Print: 2329-3322   ISSN Online: 2329-3330

A Review of Measurement-Integrated Simulation of Complex Real Flows

HTML  XML Download Download as PDF (Size: 1729KB)  PP. 51-66  
DOI: 10.4236/jfcmv.2015.32006    4,088 Downloads   5,123 Views  Citations
Author(s)

ABSTRACT

In spite of the inherent difficulty, reproducing the exact structure of real flows is a critically important issue in many fields, such as weather forecasting or feedback flow control. In order to obtain information on real flows, extensive studies have been carried out on methodology to integrate measurement and simulation, for example, the four-dimensional variational data assimilation method (4D-Var) or the state estimator such as the Kalman filter or the state observer. Measurement-integrated (MI) simulation is a state observer in which a computational fluid dynamics (CFD) scheme is used as a mathematical model of the physical system instead of a small dimensional linear dynamical system usually used in state observers. A large dimensional nonlinear CFD model makes it possible to accurately reproduce real flows for properly designed feedback signals. This review article surveys the theoretical formulations and applications of MI simulation. Formulations of MI simulation are presented, including governing equations of a flow field observer, those of a linearized error dynamics describing the convergence of the observer, and stabilization of the numerical scheme, which is important in implementation of MI simulation. Applications of MI simulation are presented ranging from fundamental turbulent flows in pipes and Karman vortices in a wind tunnel to clinical application in diagnosis of blood flows in a human body.

Share and Cite:

Hayase, T. (2015) A Review of Measurement-Integrated Simulation of Complex Real Flows. Journal of Flow Control, Measurement & Visualization, 3, 51-66. doi: 10.4236/jfcmv.2015.32006.

Cited by

[1] Real-Time Reconstruction of Fluid Flow under Unknown Disturbance
ACM Transactions on Graphics, 2023
[2] Nudging-based data assimilation of the turbulent flow around a square cylinder
Journal of Fluid …, 2022
[3] Calculation of the Pressure Field for Turbulent Flow around a Surface-Mounted Cube Using the SIMPLE Algorithm and PIV Data
Fluids, 2022
[4] INTEGRATION OF PIV DATA INTO THE SIMPLE ALGORITHM FOR 2D TIME-AVERAGED TURBULENT FLOWS
12th International Symposium on Turbulence and Shear Flow Phenomena, 2022
[5] A Projection-Based Reduced Order Model (PBROM) for Coupled Physical-Numerical Simulations
2018
[6] Data-assimilated computational fluid dynamics modeling of convection-diffusion-reaction problems
Journal of Computational Science, 2017
[7] Grid Convergence Property of Three-Dimensional Measurement-Integrated Simulation for Unsteady Flow behind a Square Cylinder with Karman Vortex …
2016
[8] Grid Convergence Property of Three-Dimensional Measurement-Integrated Simulation for Unsteady Flow behind a Square Cylinder with Karman Vortex Street
2016
[9] Numerical simulation of real-world flows
Fluid Dynamics Research, 2015
[10] A Localised, Ensemble-Based, Data Assimilation Method Applied Across Differentreynolds Numbers in the Laminar Regime
Ensemble-Based

Copyright © 2025 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.