Altair > Case Studies > Dynamic Simulation of Tool Drop on Swift020 UAS using RADIOSS®: A Case Study

Dynamic Simulation of Tool Drop on Swift020 UAS using RADIOSS®: A Case Study

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Technology Category
  • Analytics & Modeling - Digital Twin / Simulation
  • Drones - Fixed-Wing Drones
Applicable Industries
  • Aerospace
  • Equipment & Machinery
Applicable Functions
  • Maintenance
  • Product Research & Development
Use Cases
  • Manufacturing Process Simulation
  • Structural Health Monitoring
Services
  • System Integration
  • Testing & Certification
About The Customer
Swift Engineering, Inc., based in San Clemente, California, is a product development company with over 30 years of experience designing, developing, and building high-performance advanced composite vehicles, unmanned systems, full-scale demonstrators, build-to-print, and automated robotics. Swift specializes in the design, development, and manufacturing of lightweight composite structures, components, and vehicles. Founded in 1983 as a leading developer of high-performance racecars, Swift has been applying its depth of composite talent to the aerospace and aviation industries since 1997. Swift has emerged as a premier air vehicle designer and manufacturer, as demonstrated through the successful KillerBee Unmanned Aerial Systems (UAS), the Boeing Sikorsky Joint Multi-Role (JMR) Demonstrator, the Eclipse Concept Jet program, and many other similar aerospace and oceanic build-to-print composite manufacturing projects.
The Challenge
Swift Engineering, Inc., a product development company with over 30 years of experience in designing, developing, and building high-performance advanced composite vehicles, unmanned systems, and automated robotics, faced a challenge with their Swift020 Unmanned Aerial System (UAS). The challenge was to define the specification for the maximum weight of the maintenance tooling used on the Swift020 UAS. The concern arose from the fact that the flight surfaces of the UAS were minimum gauge, and heavy tools dropped on the structure could cause irreparable damage, downtime, and expensive component replacement. The objective was to determine the maximum maintenance tool weight that, if dropped from a nominal height of 0.762 meters, would not cause permanent damage to any part of the Swift020 UAS.
The Solution
To solve this challenge, Swift Engineering utilized RADIOSS Explicit Dynamic Impact Simulation. An explicit model of the UAS was generated in HyperMesh® and impacted by a steel penetrator at defined drop energies. A parametric curve of maximum composite compression strain vs. impact energy and limit strain for the impacted composite material was used to yield the specification for the maximum tool weight. A full-scale model of the Swift020 was generated in HyperMesh. The primary structural components comprised of graphite, fiberglass, and Kevlar® epoxy advanced composite materials were modeled using MAT25 material property in RADIOSS. The penetrator was modeled as a 0.0254-meter diameter hemispherical tip rod. Initial velocity (INIVEL) of 3.867 m/s was imposed on the penetrator to simulate a 0.762-meter drop using Conservation of Energy. The impact energy was modulated using the density of the penetrator in the material card.
Operational Impact
  • The use of RADIOSS Explicit Dynamic Impact Simulation provided Swift Engineering with a precise and cost-effective solution to their challenge. The simulation allowed for the visualization of the effects of tool drop impact on a thin-walled composite UAS wing structure, eliminating the need for expensive high-speed video testing, non-destructive evaluation, and lengthy trial and error efforts. The results of the simulation led to the definition of the maximum tool weight that would not cause permanent damage to the Swift020 UAS, thus increasing the reliability of the system and reducing the risk of structural damage. This solution also reduced maintenance and component replacement time and cost, further enhancing the operational efficiency of Swift Engineering.
Quantitative Benefit
  • Elimination of costly trial and error testing
  • Reduction in maintenance and component replacement time and cost
  • Increased reliability

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