[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-83115":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":15,"stars7d":16,"stars30d":16,"stars90d":15,"forks30d":15,"starsTrendScore":17,"compositeScore":18,"rankGlobal":9,"rankLanguage":9,"license":19,"archived":20,"fork":20,"defaultBranch":21,"hasWiki":22,"hasPages":20,"topics":23,"createdAt":9,"pushedAt":9,"updatedAt":24,"readmeContent":25,"aiSummary":26,"trendingCount":15,"starSnapshotCount":15,"syncStatus":27,"lastSyncTime":28,"discoverSource":29},83115,"PyThrust","Setuav\u002FPyThrust","Setuav","An Open-Source Framework for Electric Propulsion System Analysis and Optimization in UAV Design",null,"Python",138,18,3,1,0,71,4,3.84,"Apache License 2.0",false,"main",true,[],"2026-06-12 02:04:31","![PyThrust Banner](https:\u002F\u002Fraw.githubusercontent.com\u002FSetuav\u002FPyThrust\u002Fmain\u002Fdocs\u002Fimages\u002FPyThrust_banner.png)\n\n# PyThrust\n\nPyThrust is an open-source framework for electric propulsion system analysis, co-design, and parameter optimization in UAV applications. It can be used for multidisciplinary design optimization (MDO) within OpenMDAO. It includes steady-state performance solvers, auto-tuning calibration tools to fit manufacturer test data, and database search tools to map theoretical designs onto real-world brushless motor and propeller catalogs.\n\n## Design and Analysis Visualization\n\n| 1. Propulsion Co-Design Optimization | 2. Propulsion Calibration & Auto-Tuning |\n| :---: | :---: |\n| ![Propulsion Co-Design Optimization](https:\u002F\u002Fraw.githubusercontent.com\u002FSetuav\u002FPyThrust\u002Fmain\u002Fdocs\u002Fimages\u002Foptimize_and_plot_results.png) | ![Propulsion Calibration & Auto-Tuning Results](https:\u002F\u002Fraw.githubusercontent.com\u002FSetuav\u002FPyThrust\u002Fmain\u002Fdocs\u002Fimages\u002Fcalibration_results.png) |\n| **3. Propeller Aerodynamic Coefficients** | **4. Hover Efficiency Heatmap** |\n| ![Propeller Aerodynamic Coefficients](https:\u002F\u002Fraw.githubusercontent.com\u002FSetuav\u002FPyThrust\u002Fmain\u002Fdocs\u002Fimages\u002Fpropeller_coefficients.png) | ![Hover Efficiency Heatmap](https:\u002F\u002Fraw.githubusercontent.com\u002FSetuav\u002FPyThrust\u002Fmain\u002Fdocs\u002Fimages\u002Fefficiency_heatmap.png) |\n\n### 5. PyBaMM Electrochemical Battery Simulation (Dynamic Load)\n![PyBaMM Electrochemical Battery Simulation](https:\u002F\u002Fraw.githubusercontent.com\u002FSetuav\u002FPyThrust\u002Fmain\u002Fdocs\u002Fimages\u002Fpybamm_mission_results.png)\n\n## Documentation\n\nPlease see the [docs\u002F](https:\u002F\u002Fgithub.com\u002FSetuav\u002FPyThrust\u002Ftree\u002Fmain\u002Fdocs) folder for design specifications, core mathematical model descriptions, and database details.\n\n## License\n\nPyThrust is licensed under the Apache License, Version 2.0 (the \"License\"). See [LICENSE](https:\u002F\u002Fgithub.com\u002FSetuav\u002FPyThrust\u002Fblob\u002Fmain\u002FLICENSE) for the full license.\n\n## Copyright\n\nCopyright (c) 2026 Setuav. All rights reserved.","PyThrust 是一个用于无人机电动推进系统分析、协同设计及参数优化的开源框架。它支持在OpenMDAO环境下进行多学科设计优化，提供了稳态性能求解器、自动调校工具以匹配制造商测试数据，以及数据库搜索工具来将理论设计与实际无刷电机和螺旋桨目录相映射。该项目使用Python语言编写，适合需要精确评估和优化无人机电动推进系统的场景，如学术研究、产品开发等。通过PyThrust，用户可以更好地理解并改进其无人机的设计，提高整体性能效率。",2,"2026-06-11 04:10:09","CREATED_QUERY"]