发表机构
Indian Institute of Technology Bombay（印度孟买理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过CFD-机器学习框架优化舱体几何并采用分级CD管道，实现超音速真空管道运输从马赫1.6到2.5的无壅塞过渡，总阻力从68,913.7牛降至120.5牛，显著降低气动阻力。
AI 中文摘要
本研究探讨了高速真空管道运输（ETT）的气动可行性，采用集成的CFD-机器学习框架进行舱体几何优化，并采用分级收敛-扩张（CD）管道概念以实现超音速运行。舱体几何通过复合三次贝塞尔曲线参数化，包含七个设计变量。使用拉丁超立方采样在亚音速和超音速范围内生成200种配置，并通过二维轴对称ANSYS Fluent模拟进行评估，模拟结果与已发表的可压缩流数据进行了验证。由此产生的CFD数据集用于训练代理模型以快速预测阻力。XGBoost提供了最佳的整体性能，测试R²达到0.9524，并与差分进化和粒子群优化相结合，以识别低阻力几何形状，随后通过CFD进行验证。研究进一步考察了分级CD管道架构，该架构将受控的面积变化与逐步的压力降低相结合，以缓解超音速加速过程中的壅塞。在理想化的轴对称模拟中，所提出的策略使得从马赫1.6的大气进入过渡到马赫2.5、阻塞比为0.50的近真空巡航，且未形成壅塞的环形流动区域。总阻力从大气超音速条件下的68,913.7牛降至最终近真空阶段的120.5牛，这伴随着从波阻主导到粘性剪切主导的转变。结果表明，结合舱体形状优化和分级压力-面积管理在降低超音速ETT系统气动阻力方面具有潜力。
英文摘要
This study investigates the aerodynamic feasibility of high-speed evacuated tube transport (ETT) using an integrated CFD-machine learning framework for pod geometry optimization and a staged converging-diverging (CD) tube concept for supersonic operation. The pod geometry is parameterized using composite cubic Bezier curves with seven design variables. Latin Hypercube Sampling is used to generate 200 configurations across subsonic and supersonic regimes, which are evaluated using two-dimensional axisymmetric ANSYS Fluent simulations validated against published compressible-flow data. The resulting CFD dataset is used to train surrogate models for rapid drag prediction. XGBoost provides the best overall performance, achieving a test R^2 of 0.9524, and is coupled with Differential Evolution and Particle Swarm Optimization to identify low-drag geometries that are subsequently verified using CFD. The study further examines a staged CD tube architecture combining controlled area variation with gradual pressure reduction to mitigate choking during supersonic acceleration. In the idealized axisymmetric simulations, the proposed strategy enables transition from atmospheric entry at Mach 1.6 to near-vacuum cruise at Mach 2.5 and a blockage ratio of 0.50 without forming a choked annular flow region. Total drag decreases from 68,913.7 N under atmospheric supersonic conditions to 120.5 N in the final near-vacuum stage, associated with a transition from wave-drag-dominated to viscous-shear-dominated resistance. The results demonstrate the potential of combined pod-shape optimization and staged pressure-area management for reducing aerodynamic resistance in supersonic ETT systems.
