Recommended Best Practices for Model Based Engineering's Digital Twin: Analysis and Simulation

This paper was produced for the 2019 NAFEMS World Congress in Quebec Canada

Resource Abstract

Model Based Engineering has a digital twin in the engineering analysis and simulation domain. During the development of a physical system (a product), several key characteristics must be defined such that they satisfy the design requirements. Substantiating the satisfactory measure of meeting a design requirement often relies on various means of verification during a physical system’s development.

When the physical system is manufactured it must also be shown to satisfy the design requirements by verification and validation. In most cases, the means of verification and validation involve obtaining physical measurements of key characteristics that are part of the model based design, but the definition of many of the target values of these characteristics is dependent on math and science-based analysis to predict them during development.

The fundamental theory and application of analysis-based predictions have been generated by the fusion of math and science present in the engineering vocation. Many of these analytical methods have been packaged in computer aided engineering (CAE) software, such that the process of modelling the math and science (physics) can produce predicted results that are robust, repeatable and reliable.

The simulation results for a physical system are produced concurrently with the design and development of the product and continue to be produced (as-needed) throughout the lifecycle of the system. These data are used to assist in verification and validation of the physical system’s performance relative to the design objectives and requirements.

Defining best practices for long term archiving and retrieval (LOTAR) of engineering analysis and simulation (EAS) information has been the objective of the authors as part of the LOTAR International EAS Working Group. The means of achieving the goal of LOTAR of EAS information are also suitable for data exchange throughout the lifecycle of a product.

In its initial phases, the focus has been placed on LOTAR of structural engineering analysis of aerospace products using finite element analysis (FEA) via industry standards, such as ISO 10303-409 “Industrial automation systems and integration — Product data representation and exchange Part 409 Application Module: AP209 multidisciplinary analysis and design” (ISO STEP AP209 ed2). The use of ISO STEP AP209 is not limited to aerospace products. Other ISO STEP standards are widely used for data interchange and LOTAR (such as AP203). (International Standards Organization, 2014)

A summary of the recommended best practices is presented that will be captured in prEN 9300-600/620 “Aerospace series — LOTAR — LOng Term Archiving and Retrieval of Structural Analysis information — Part 600: Fundamentals and concepts” and “Part 620: Structural analysis information.” The LOTAR International was established as a joint AIA and ASD-STAN project. While these organizations and project are focused on addressing the needs of aerospace and defence manufacturers, the best practices can be applied to any product requiring LOTAR of EAS data. These practices are also applicable to exchanging EAS data during product development.

The authors will also demonstrate a simulation of a round-trip of structural analysis performed using FEA from packaging the archived model and results data in ISO STEP AP209 ed2 to retrieving the data from archive and rerunning the analysis and validating that the results are equivalent to the original data.

Document Details

AuthorDraper. J
Date 18th June 2019
OrganisationThe Boeing Company


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