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Reliability-Based Multidisciplinary Design Optimization Under Uncertainty for Air Launched Vehicle with an UAV as a Carrier Aircraft

Moradi, Maziyar | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 58213 (45)
  4. University: Sharif University of Technology
  5. Department: Aerospace Engineering
  6. Advisor(s): Fathi, Mohsen
  7. Abstract:
  8. With the advancement in performance and applications of nanosatellites, their utilization capacity has increased. A suitable method for injecting nanosatellites into orbit is the use of air-launched launch vehicles. For the preliminary design of the air-launched launch vehicle, the first and second stages are considered to be Solid Rocket Motors (SRM), and the third stage is considered to be a liquid propellant engine. The mission objective is to inject a 3U cubic nanosatellite with a mass of 3.7 kg into a circular Low Earth Orbit (LEO) at an altitude of 300 km, using an optimized air-launched launch vehicle carried by an MQ-9 Unmanned Aerial Vehicle (UAV) as the carrier aircraft. In this study, the Multidisciplinary Design Optimization (MDO) problem is initially addressed using the All-At-Once (AAO) method to optimize the Gross Lift-Off Weight (GLOW). This optimization involves defining and formulating four disciplines: propulsion, geometry and mass budgeting, aerodynamics, and flight trajectory, with 15 design variables, and is solved using a gradient-based optimizer. Subsequently, the Monte Carlo sampling method is employed to incorporate and investigate epistemic uncertainty in the 15 design variables. To assess the reliability of the obtained optimal design in the mission, the Reliability-Based Multidisciplinary Design Optimization (RBMDO) problem is solved, considering the simultaneous reliability index for achieving orbital velocity and altitude. To enhance the system's reliability in the three stages of the air-launched vehicle, a redundancy approach is implemented to address Single Point of Failure (SPOF) in the engineering design. This involves incorporating an additional turbopump for the third-stage liquid propulsion system and an extra igniter for the first and second-stage solid propulsion systems. Furthermore, the safety factors and margins applied in the design equations are inherently related to the system's reliability. The GLOW was determined to be 1312.3 kg, and the total length of the launch vehicle stages, including the fairing, was calculated to be 6.877 meters. Based on reliability indices, the mission success rate was achieved at %95.5
  9. Keywords:
  10. Multi-Disciplinary Design Optimization ; Uncertainty-Base Multidisciplinary Design Optimization ; Reliability ; Uncertainty ; Monte Carlo Sampling ; Space Aerial Launch ; Reliability-Based Multidisciplinary Design Optimization

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