Computational design exploration of rocket nozzle using deep reinforcement learning
Deep Reinforcement Learning (DRL) has emerged as a powerful tool for solving high-dimensional optimization problems in complex, unexplored domains. This study presents a novel application of DRL for computational design exploration of rocket nozzles, demonstrating its superiority over traditional pa...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025005171 |
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