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Abstract <p>The conceptual phase of aircraft design is characterized by a significant degree of uncertainty in the initial data. This is largely due to the presence of random processes and incomplete information, requiring the use of nondeterministic parameters that cannot be defined by a precise number. These nondeterministic parameters are linked to parametric uncertainty, which is a key factor contributing to the increased risk of design errors. To address this challenge, this paper presents optimization models that formalize the tasks of parametric synthesis in aircraft conceptual design, with a focus on ensuring the reliability of the design solutions. Probability theory and uncertainty theory are employed to represent nondeterministic parameters. The theory of uncertainty provides decision-makers (DMs) with a powerful tool for constructing optimization models that encapsulate the formalized requirements of the designed system.</p>

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Synthesis of Reliable Design Solutions Using Statistical and Expert Information in Conceptual Aircraft Design

  • 期刊论文

  • 发表日期：

    2025年2月1日

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  • G. S. Veresnikov,
  • V. I. Goncharenko

摘要

Abstract

The conceptual phase of aircraft design is characterized by a significant degree of uncertainty in the initial data. This is largely due to the presence of random processes and incomplete information, requiring the use of nondeterministic parameters that cannot be defined by a precise number. These nondeterministic parameters are linked to parametric uncertainty, which is a key factor contributing to the increased risk of design errors. To address this challenge, this paper presents optimization models that formalize the tasks of parametric synthesis in aircraft conceptual design, with a focus on ensuring the reliability of the design solutions. Probability theory and uncertainty theory are employed to represent nondeterministic parameters. The theory of uncertainty provides decision-makers (DMs) with a powerful tool for constructing optimization models that encapsulate the formalized requirements of the designed system.