Trajectory Optimization of Launch Vehicles Using Object-oriented Programming

Mota, Fábio Antônio da Silva; Hinckel, J. N.; Rocco, Evandro Marconi; Schlingloff, Hanfried

doi:10.5028/jatm.v10.948

Cited by 3 publications

(3 citation statements)

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“…The importance of selecting a relevant OF for use in multidisciplinary design studies cannot be overemphasized. Da Mota et al [15] tried to minimize the Gross Lift-Off Weight (GLOW), the structural mass (SM) and the expected total cost to investigate the effect of changing the OF using a single optimization technique. Dresia et al [33] investigated the effect of minimizing GLOW or Structural Mass (SM) on a GG cycle using GA techniques and Akhtar et al [13] studied the effect of GLOW using GA on a pressure-fed cycle.…”

Section: Optimizationmentioning

confidence: 99%

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Comparison of Optimization Techniques and Objective Functions Using Gas Generator and Staged Combustion LPRE Cycles

et al. 2022

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This paper compares various optimization techniques and objective functions to obtain optimum rocket engine performances. This research proposes a modular optimization framework that provides an optimum design for Gas Generator (GG) and Staged Combustion (SC) Liquid Propellant Rocket Engines. This process calculates the ideal rocket engine performance by applying seven different optimization techniques: Simulated Annealing (SA), Nelder Mead (NM), Cuckoo Search Algorithm (CSA), Particle Swarm Optimization (PSO), Pigeon-Inspired Optimization (PIO), Genetic Algorithm (GA) and a novel hybrid GA-PSO technique named GA-Swarm. This new technique combines the superior search capability of GA with the efficient constraint matching capability of PSO. This research also compares objective functions to determine the most suitable function for GG and SC cycle rocket engines. Three single objective functions are used to minimize the Gross Lift-Off Weight and to maximize Specific Impulse and the Thrust-to-Weight ratio. A fourth multiobjective function is used to simultaneously maximize both Specific Impulse and Thrust-to-Weight ratio. This framework is validated against a pump-fed rocket, and results are within 1% of the actual rocket engine mass. The results of this research indicate that PSO and GA-Swarm produce optimum results for all objective functions. Finally, the most suitable objective function to use while comparing these two cycles is the Gross Lift-Off Weight.

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Section: Optimizationmentioning

confidence: 99%

“…Akhtar et al and Bayley et al [13,14] used GA-based techniques to optimize a single-stage and a four-stage LV, respectively. Da mota [15] utilized SQP to optimize two LPRE cycles with the objective of maximizing payloads. He concluded that algorithms such as Particle Swarm Optimization (PSO) should also be studied.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Optimization Techniques and Objective Functions Using Gas Generator and Staged Combustion LPRE Cycles

et al. 2022

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“…Thanks to the continuous advancement in more efficient and higher performing computational platforms, combined with the availability of fast and reliable optimization codes and in novel mathematical formulations of the problem, the closed-loop online guidance starts to be appealing. Indeed, online closedloop guidance can improve the performance of the vehicle by recomputing the optimal trajectory from the knowledge of the current external conditions [1], [2], [3], [4]. This approach allows to cope with the uncertainties encountered during the entry, descent and landing phases.…”

mentioning

confidence: 99%