Optimization Of Micro Meteoroid And Space Debris Protection Systems.pdf

The goal is to optimize protection systems to minimize both the number of penetrations and added mass.

Challenges:

- Nonlinearity: The optimization problem is highly nonlinear, making classical derivative-based methods unsuitable.
- Local Optima: Numerous local optima make identifying the global optimum difficult.
- Constraints: Incorporating constraints like maximum allowable penetrations and material limitations into a single target function is complex.

Approach:

Three search algorithms were tested:

1. Genetic Algorithm: Uses population-based methods to evolve solutions.
2. Simulated Annealing: Explores the solution space by randomly perturbing current solutions, accepting worse solutions with a probability based on temperature.
3. Hooke-Jeeves Algorithm: Identifies the direction of greatest improvement in the target function and moves iteratively along that direction until no further progress is made.

These algorithms were applied to:

- Single wall structures to establish a suitable optimization procedure.
- Double wall structures, requiring careful consideration of shield thickness effects on penetration calculations.

Results:

The study found that different sets of equations for calculating penetration numbers needed evaluation based on their accuracy in reflecting the influence of shield thickness in double-wall configurations.

Conclusion:

The results highlight the effectiveness of using search algorithms, particularly Hooke-Jeeves, for optimizing spacecraft protection systems against micrometeoroids and orbital debris. The paper concludes with a summary and outlook towards future research.