失事后机身摩擦受热与燃烧的数学建模仿真

发布时间：2018-05-24 12:26

本文选题：机身受热摩擦 + 摩擦受热时间　；参考：《计算机仿真》2015年06期

【摘要】：在预定的温度下,飞机失事后机身摩擦受热时间与燃烧的关系很复杂,受到飞行高度、天气状况等综合因素的影响,是一个多变耦合数学问题。针对飞机失事后机身摩擦受热时间与燃烧的数学建模,需要设定大量的约束条件,缺少智能化过程,导致建模结果不准确,提出了一种新的飞机失事后机身摩擦受热时间与燃烧的数学关系模型。依据机身摩擦受热模型,采用Themecmastor-Z型热加工模拟试验机对机身进行不同程度的摩擦受热试验,依次记录各个时间段以及各种温度下相关机身摩擦受热的燃烧数值,将该数值输入神经网络系统中,建立前馈式算法的人工神经网络,并进行优化训练,构造出飞机失事后机身摩擦受热时间与燃烧的数学关系模型。实验结果说明,与传统模型对比,改进的神经网络模型具有一定高效性,将误差缩小到3%,大大提高了模型自身的拟合度,精确地描绘出飞机失事后机身摩擦受热时间与燃烧的数学对应关系。
[Abstract]:At a predetermined temperature, the relationship between the friction heating time of the fuselage and the combustion after the plane crash is very complex, which is influenced by the flight altitude, weather conditions and other comprehensive factors, so it is a multi-variable coupled mathematical problem. In view of the mathematical modeling of friction heating time and combustion of the fuselage after the plane crash, a large number of constraint conditions need to be set up, and the lack of intelligent process leads to inaccurate modeling results. A new mathematical model of friction heating time and combustion after aircraft crash is proposed. According to the friction heating model of the fuselage, the friction heating test of the fuselage was carried out with Themecmastor-Z hot working simulator to record the combustion value of the fuselage friction heating at each time period and at various temperatures. The artificial neural network of feedforward algorithm is established by inputting the numerical value into the neural network system, and the optimization training is carried out, and the mathematical model of the relationship between the friction heating time and the combustion of the fuselage after the plane crash is constructed. The experimental results show that compared with the traditional model, the improved neural network model has a certain efficiency, the error is reduced to 3, and the fitting degree of the model itself is greatly improved. The mathematical relation between the friction heating time and the combustion of the fuselage after the plane crash is accurately described.
【作者单位】：青海师范大学数学系;
【基金】：国家自然科学基金(11301291)基于sieve bootstrap方法的长记忆过程变点研究与应用
【分类号】：V211;V328

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