可扩展性
计算机科学
火箭(武器)
开源
导弹
航空航天工程
一套
风洞
飞行模拟器
系统工程
飞行试验
蒙特卡罗方法
概率逻辑
模拟
软件
航空学
工程类
人工智能
程序设计语言
统计
数学
考古
历史
操作系统
作者
Henry Stoldt,Declan Quinn,Jake Kavanagh,Craig T. Johansen
出处
期刊:AIAA Propulsion and Energy 2020 Forum
日期:2021-07-28
摘要
View Video Presentation: https://doi.org/10.2514/6.2021-3267.vid MAPLEAF is a novel compact, extensible, and open-source rocket flight simulation framework for researchers, amateurs, and startups. MAPLEAF aims to improve on the accuracy and extensibility of existing publically-available simulators. The architectural choices intended to facilitate future extensions and modifications to MAPLEAF are discussed. MAPLEAF's included Monte Carlo, optimization, adaptive time integration, probabilistic wind modelling, automated verification and validation, and control system modelling capabilities are presented. Finally, selected cases from MAPLEAF's test suite are presented, including comparisons to rocket flight data, wind tunnel tests, NASA's flight simulators, Missile Datcom, Aeroprediction, OpenRocket, RockSim, and various CFD solvers.
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