摘要
针对飞机燃油系统方案设计阶段燃油质量特性分析中燃油实体建模效率低、没有统一规范的建模流程,因此导致的建模质量难以保证等问题,应用知识工程的基本思想,提出了针对恒截面燃油实体参数化建模技术。首先,通过分析恒截面飞机油箱的外形特点及强度、刚度等对油箱结构设计的要求,确定驱动燃油实体建模流程和相关参数;其次,通过CATIA二次开发技术,以相关参数为驱动,进行燃油实体建模。实例验证表明,与油箱满油状态时实际所载燃油的实体模型相比,通过该技术创建的燃油实体模型体积误差主要源于油箱内部结构损失,且对重心偏差影响较小。实验结果表明,基于知识工程的参数化建模技术能够保证恒截面燃油实体的建模效率和质量,适用于在飞机燃油系统方案设计阶段创建燃油质量特性分析对象。
For the analysis of fuel quality characteristics in the schematic design stage of the aircraft fuel system, it is difficult to ensure that the resulting modeling is of high quality due to the inefficient fuel entity modeling and non-standard modeling process. A parametric modeling technology based on knowledge engineering is proposed for fuel entity of aircraft fuel tank with stationary cross section to address the problem. Firstly, the parameters and modeling process that drive fuel entity modeling were confirmed by analyzing the shape characteristics of the stationary cross section aircraft fuel tank and the requirements of the tank structure design for strength and stiffness. Secondly, fuel entity modeling was performed which is driven by the relevant parameters through CATIA secondary development technology. The example verification shows that the volume error of the fuel entity model created by this technology is less than the entity model of the actual fuel when the tank is full of oil, mainly because of the tank’s internal structural loss, and it has less influence on the center of gravity deviation. The experimental results show that parametric modeling technology based on knowledge engineering can ensure the modeling efficiency and quality of the stationary cross section fuel entity, and can be applied to create the analysis objects for fuel quality characteristic in the schematic design stage of the aircraft fuel system.
作者
宋伟
钟若瑛
SONG Wei;ZHONG Ruo-ying(College of Aircraft Engineering,Nanchang Hangkong University,Nanchang Jiangxi 330063,China)
出处
《计算机仿真》
北大核心
2020年第10期48-53,共6页
Computer Simulation
关键词
恒截面飞机油箱
燃油实体
燃油质量特性分析
知识工程
参数化建模
Aircraft fuel tank with stationary cross section
Fuel entity
Fuel quality characteristic analysis
Knowledge engineering
Parametric modeling