Measurement of Three-dimensional Density Distribution with Genetic Algorithm

• OKAMOTO Koji

  "Nuclear Engineering Research Lab., University of Tokyo"

• TSURU Daigo

  "Nuclear Engineering Research Lab., University of Tokyo"

• FENG Jian

  "Nuclear Engineering Research Lab., University of Tokyo"

• FUMIZAWA Motoo

  Japan Atomic Energy Research Institute

Bibliographic Information

Other Title

• 131 3次元密度分布計測へのGAの応用

Abstract

Three-dimensional density distribution can be reconstructed using tomography technique from interferogram images. Conventional tomography techniques have low accuracy with a few interferogram images and truncated images. To improve the accuracy of the reconstruction, a new tomography technique is proposed. In the present method, density distribution is assumed to be mainly effected by diffusion processes, and to be expressed as the summation of elementary density distributions. The tomography is carried out as the optimization of the arrangement of elementary density distributions. As optimization technique, genetic algorithm (GA) is introduced.<BR>The GA usually needs lots of calculation time. In this study, the two-dimensional density distribution in cross sections are stacked, in order to construct the three-dimensional data. As an initial condition of one cross section, the converged data at previous cross section are used, resulting in the less calculation time.<BR>The three-dimensional density distribution is reconstructed using the present method (GA) and conventional Filtered Back Projection method (FBP). The target flow field is density stratified field, which is caused by the downward helium jet into air. Both the GA and FBP can reconstruct the three-dimensional density distributions. The GA shows high effectiveness with reconstructing the three-dimensional data with a few images and truncated images.

Journal

• Journal of the Visualization Society of Japan

  Journal of the Visualization Society of Japan 15 (Supplement1), 173-176, 1995

  The Visualization Society of Japan

Details

• CRID: 1390282679595638656
• NII Article ID: 10002673402
• NII Book ID: AN10374478
• DOI: 10.3154/jvs.15.supplement1_173
• ISSN: 1884037X
• ISSN: 09164731
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed