The Experts below are selected from a list of 18 Experts worldwide ranked by ideXlab platform

A M Firsov - One of the best experts on this subject based on the ideXlab platform.

  • forecasting of the holes shape accuracy of Thin Walled Body parts through the application of artificial neural networks
    IOP Conference Series: Materials Science and Engineering, 2016
    Co-Authors: V A Kalistru, A G Ovcharenko, A M Firsov
    Abstract:

    In this paper is proposed a method to predict deviations of accuracy of a basic shape of holes due to a thermal deformation (TD) at the design stage of the technological process. Proposed method of control of technological process consists of two stages: the first stage (auxiliary) is based on the finite element method (FEM), the second (main) - on the modeling of artificial neural network (Ann). In this paper is developed an algorithm of calculation of input and output parameters of the network using LS-DYNA. A structure of the Ann to predict and to adjust a trajectory of a movement of a tool at the preparation stage of the technological process for work pieces included in group process is invented in this article.

V A Kalistru - One of the best experts on this subject based on the ideXlab platform.

  • forecasting of the holes shape accuracy of Thin Walled Body parts through the application of artificial neural networks
    IOP Conference Series: Materials Science and Engineering, 2016
    Co-Authors: V A Kalistru, A G Ovcharenko, A M Firsov
    Abstract:

    In this paper is proposed a method to predict deviations of accuracy of a basic shape of holes due to a thermal deformation (TD) at the design stage of the technological process. Proposed method of control of technological process consists of two stages: the first stage (auxiliary) is based on the finite element method (FEM), the second (main) - on the modeling of artificial neural network (Ann). In this paper is developed an algorithm of calculation of input and output parameters of the network using LS-DYNA. A structure of the Ann to predict and to adjust a trajectory of a movement of a tool at the preparation stage of the technological process for work pieces included in group process is invented in this article.

L.n. Erofeeva - One of the best experts on this subject based on the ideXlab platform.

  • Probabilistic Material Efficiency Coefficient and Application Example
    Herald of the Bauman Moscow State Technical University. Series Mechanical Engineering, 2019
    Co-Authors: O.v. Voronkov, L.n. Erofeeva
    Abstract:

    The paper introduces a mathematical derivation of probability density function for a random variable which is a comparative material's mass or cost efficiency coefficient. At early development stage, the coefficient allows a scientifically based selection of material, taking into account its strength or stiffness, weight or cost characteristics. A distinctive feature of the coefficient is the ability to take into account the effect on material efficiency when the material is applied to a Thin-Walled Body structure of an important technological limitation: the discreteness of the standard range of sheet material thicknesses. This function makes it possible to determine with high accuracy the probability of the deviation of the considered random variable from its expectation not further than the limits of a given interval. The use of this function leads to a significant improvement in the developed methodology for selecting an effective material at the development stage of a Thin-Walled product, the methodology being previously based on the application of Chebyshev's inequality. We give an example of selecting an effective material from the list of materials considered for a cover sheet of a sandwich-panel under buckling condition.

A G Ovcharenko - One of the best experts on this subject based on the ideXlab platform.

  • forecasting of the holes shape accuracy of Thin Walled Body parts through the application of artificial neural networks
    IOP Conference Series: Materials Science and Engineering, 2016
    Co-Authors: V A Kalistru, A G Ovcharenko, A M Firsov
    Abstract:

    In this paper is proposed a method to predict deviations of accuracy of a basic shape of holes due to a thermal deformation (TD) at the design stage of the technological process. Proposed method of control of technological process consists of two stages: the first stage (auxiliary) is based on the finite element method (FEM), the second (main) - on the modeling of artificial neural network (Ann). In this paper is developed an algorithm of calculation of input and output parameters of the network using LS-DYNA. A structure of the Ann to predict and to adjust a trajectory of a movement of a tool at the preparation stage of the technological process for work pieces included in group process is invented in this article.

O.v. Voronkov - One of the best experts on this subject based on the ideXlab platform.

  • Probabilistic Material Efficiency Coefficient and Application Example
    Herald of the Bauman Moscow State Technical University. Series Mechanical Engineering, 2019
    Co-Authors: O.v. Voronkov, L.n. Erofeeva
    Abstract:

    The paper introduces a mathematical derivation of probability density function for a random variable which is a comparative material's mass or cost efficiency coefficient. At early development stage, the coefficient allows a scientifically based selection of material, taking into account its strength or stiffness, weight or cost characteristics. A distinctive feature of the coefficient is the ability to take into account the effect on material efficiency when the material is applied to a Thin-Walled Body structure of an important technological limitation: the discreteness of the standard range of sheet material thicknesses. This function makes it possible to determine with high accuracy the probability of the deviation of the considered random variable from its expectation not further than the limits of a given interval. The use of this function leads to a significant improvement in the developed methodology for selecting an effective material at the development stage of a Thin-Walled product, the methodology being previously based on the application of Chebyshev's inequality. We give an example of selecting an effective material from the list of materials considered for a cover sheet of a sandwich-panel under buckling condition.