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Automated Layout with a Python Integrated NDARC Environment

Travis Perry, Andrew Gallaher, U.S. Army Aviation, Missile Research

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Automated Layout with a Python Integrated NDARC Environment

  • Presented at Forum 74
  • 11 pages
  • SKU # : 74-2018-0059
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Automated Layout with a Python Integrated NDARC Environment

Authors / Details: Travis Perry, Andrew Gallaher, U.S. Army Aviation and Missile Research

Abstract
Geometric layout of an aircraft concept is a fundamental aspect of the design process and can often be a primary driver for design choices, and trade space decisions. Most commonly, geometry is either estimated analytically by performance and sizing tools, from in-production aircraft data, or modeled using Computer Aided Design (CAD). Analytic geometry estimates are often not precise, requiring CAD to refine these estimates. Modeling an aircraft design to the fidelity needed to refine these geometric estimates can be a time consuming process. Furthermore, the initial layout design iterations are primarily used to refine prior estimates rather than address layout design choices. There is a need to accomplish these high level layout tasks in a timely manner; allowing for broad trade space analysis, and relying on CAD later in the design process for more detailed geometric layout. This paper will cover the development of the Automated Layout with a Python Integrated NDARC Environment (ALPINE), a Python Application Programming Interface (API) based geometry tool which leverages outputs from NASA Design and Analysis of Rotorcraft (NDARC) and the geometry software OpenVSP to expedite high level layout processes. ALPINE is an object oriented API tool that streamlines the initial conceptual layout process. This is accomplished through mapping NDARC geometry parameters to custom components generated in OpenVSP, and using algorithms native to OpenVSP. Through the use of this tool, the time needed for initial geometric layout is reduced significantly, potential design challenges can be highlighted without a detailed CAD model, geometry can be integrated within closed loop design optimization prob- lems, and analytic geometry estimates from performance sizing codes can be refined and correlated to 3D model-based analyses.

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