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Bivariate “Cut-Glue” Approximation of Strongly Nonlinear Mathematical Models Based on Experimental Data

机译:基于实验数据的强烈非线性数学模型的近距离生成“切割”近似

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Researchers meet the difficulties of experimental and computer modeling of a statics and dynamics of aircrafts connected with their essential nonlinearity. This is due to the fact that the aerodynamic effects of the interaction complex aircraft designs or their models with air environment generate abrupt changes of the character of the some dependencies. Aerodynamic coefficients in the model of interaction can be obtained only or by full-scale tests or by computer simulations. Therefore, the construction of mathematical models of the objects is associated with the mathematical processing of the points of the experimental data. In this case, the experimentally obtained dependence is usually essentially nonlinear up to piecewise, or even discontinuous nature. Approximation of such dependencies, even with the use of spline functions, is very difficult and is associated with large errors. The solution to this problem was proposed by the author and was reported to the ASME Congress in November 2014 and published in the Proceedings of the Congress in its final form. In that work possibility of “approximating&multiplicative&additive” processing of dot experimental data for creation of unified mathematical model of the studied object or the phenomenon completely is mathematically proved. The offered method is called Cut-glue approximation as it is based on “cutting” of the well approximated intervals of the modelled dependence and their “gluing” in the one analytical function. However, this problem has been solved only for the univariate functions case. In this paper the author presents the solution of a problem of the bivariate Cut-glue approximation, which significantly expands the scope of application of the method. The creation examples of mathematical models are given. Fragments of the flying devices using the aerostatic flight principle are modeled. Examples show that models even piecewise dependences represent the unified analytical functions. However we can approximate their forms to piecewise so, how it is necessary for the accuracy of the description of experimental data. It is shown that combined application of the “Cut-glue” method of approximation and the piecewise description of separate intervals of the modelled experimental dependence by methods of the regression analysis considerably increases the accuracy of the mathematical dependence description in general. For bivariate models the effect of application of a method becomes stronger, because the error of the description of the significantly nonlinear bivariate dependences by regression methods much more, than univariate dependences.
机译:研究人员符合与其基本非线性相连的飞机静态和动态的实验性和计算机建模困难。这是由于相互作用复杂飞机设计的空气动力学效应或空气环境的模型产生了一些依赖性的特征的突然变化。可以仅获得交互模型中的空气动力学系数,或通过满量程测试或通过计算机模拟获得。因此,对象的数学模型的构造与实验数据点的数学处理相关联。在这种情况下,实验获得的依赖通常基本上是非线性的,甚至是不连续性的。即使使用样条函数的近似,这种依赖性也非常困难,并且与大错误相关联。本问题的解决方案是由作者提出的,并于2014年11月向Asme大会报告,并以最终形式发表在国会的诉讼程序中。在这种工作中,“近似和乘法和添加剂”的可能性对学习对象的统一数学模型的圆点实验数据的处理完全被证明是在数学上被证明。所提供的方法称为切割胶水近似,因为它基于在一个分析功能中的建模依赖性的良好近似间隔的“切割”和它们的“胶合”。但是,此问题仅用于单变量功能案例。在本文中,作者提出了一项问题的解决方案,即二元化胶水近似的问题,这显着扩展了该方法的应用范围。给出了数学模型的创建示例。使用空气静力学飞行原理的飞行装置的碎片被建模。例如,模型甚至分段依赖性代表统一的分析功能。然而,我们可以将它们的形式近似于分段,因此如何实现实验数据描述的准确性。结果表明,通过回归分析方法的近似的“切胶”方法的近似和分段描述的单独间隔的分段间隔显着提高了数学依赖性描述的准确性。对于生物模型,应用方法的效果变得更强,因为误差是通过回归方法的显着非线性双变化的依赖性的误差,而不是单变量依赖性。

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