Knowledge Structuration Based on Cause-and-Effect Relationships between Process Variables and Simulation Procedure

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  • Inoko Kanji
    Department of Chemical Engineering, Tokyo Institute of Technology
  • Matsumoto Hideyuki
    Department of Chemical Engineering, Tokyo Institute of Technology
  • Yoshikawa Shiro
    Department of Chemical Engineering, Tokyo Institute of Technology
  • Kuroda Chiaki
    Department of Chemical Engineering, Tokyo Institute of Technology

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  • プロセス変数間の構造解析とシミュレーション手順に基づく知識構造の抽出
  • プロセス ヘンスウケン ノ コウゾウ カイセキ ト シミュレーション テジュン ニ モトズク チシキ コウゾウ ノ チュウシュツ

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Abstract

Chemical process problems should be solved by a systematic approach in which simulation plays an important role. Simulation software permits the saving of time in problem solving by skipping part of the process of learning model knowledge. However, if the part skipped includes information that is important to understanding the problem, then simulation software obstructs valuable discussion. The object of this paper is to propose a method to clarify the model knowledge of which the learning process is skipped by simulation software. The model knowledge is expressed by a structural graph based on cause-and-effect relationships between process variables. The usefulness of this method is shown for the case of particle settling simulation.

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