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Title: Physically-based interactive Schlieren flow visualization

Abstract

Understanding fluid flow is a difficult problem and of increasing importance as computational fluid dynamics produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph and schlieren imaging for centuries which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraphs and schlieren images of time-varying scalar fields derived from computational fluid dynamics (CFD) data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Results comparing this method to previous schlieren approximations are presented.

Authors:
 [1];  [1];  [2];  [2];  [2]
  1. Los Alamos National Laboratory
  2. UNIV OF UTAH
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
982208
Report Number(s):
LA-UR-09-08318; LA-UR-09-8318
TRN: US201013%%908
DOE Contract Number:
AC52-06NA25396
Resource Type:
Journal Article
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ABUNDANCE; ACCELERATION; APPROXIMATIONS; AUGMENTATION; COMPUTERIZED SIMULATION; DATA; DYNAMICS; FLOW VISUALIZATION; FLUID FLOW; FLUID MECHANICS; GLOBAL ANALYSIS; IMAGES; INTERACTIONS; PROGRAMMING; REFRACTION; SCALAR FIELDS; SHADING; SIMULATION; SOLUTIONS; VISIBLE RADIATION

Citation Formats

Mccormick, Patrick S, Brownlee, Carson S, Pegoraro, Vincent, Shankar, Siddharth, and Hansen, Charles D. Physically-based interactive Schlieren flow visualization. United States: N. p., 2009. Web.
Mccormick, Patrick S, Brownlee, Carson S, Pegoraro, Vincent, Shankar, Siddharth, & Hansen, Charles D. Physically-based interactive Schlieren flow visualization. United States.
Mccormick, Patrick S, Brownlee, Carson S, Pegoraro, Vincent, Shankar, Siddharth, and Hansen, Charles D. 2009. "Physically-based interactive Schlieren flow visualization". United States. doi:. https://www.osti.gov/servlets/purl/982208.
@article{osti_982208,
title = {Physically-based interactive Schlieren flow visualization},
author = {Mccormick, Patrick S and Brownlee, Carson S and Pegoraro, Vincent and Shankar, Siddharth and Hansen, Charles D},
abstractNote = {Understanding fluid flow is a difficult problem and of increasing importance as computational fluid dynamics produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph and schlieren imaging for centuries which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraphs and schlieren images of time-varying scalar fields derived from computational fluid dynamics (CFD) data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Results comparing this method to previous schlieren approximations are presented.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2009,
month = 1
}
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