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Keywords = modified Newton’s formula

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29 pages, 2815 KiB  
Article
Linearly Perturbed Frequency Equation, New Frequency Formula, and a Linearized Galerkin Method for Nonlinear Vibrational Oscillators
by Chein-Shan Liu, Chia-Cheng Tsai and Chih-Wen Chang
Vibration 2025, 8(2), 16; https://doi.org/10.3390/vibration8020016 - 2 Apr 2025
Viewed by 523
Abstract
A new frequency–amplitude formula by improving an ancient Chinese mathematics method results in a modification of He’s formula. The Chinese mathematics method that expresses via a fixed-point Newton form is proven to be equivalent to the original nonlinear frequency equation. We modify the [...] Read more.
A new frequency–amplitude formula by improving an ancient Chinese mathematics method results in a modification of He’s formula. The Chinese mathematics method that expresses via a fixed-point Newton form is proven to be equivalent to the original nonlinear frequency equation. We modify the fixed-point Newton method by adding a term in the denominator, and then a new frequency–amplitude formula including a parameter is derived. Upon using the new frequency formula with the parameter by minimizing the absolute error of the periodicity condition, one can significantly raise the accuracy of the frequency several orders. The innovative idea of a linearly perturbed frequency equation is a simple extension of the original frequency equation, which is supplemented by a linear term to acquire a highly precise frequency for the nonlinear oscillators. In terms of a differentiable weight function, an integral-type formula is coined to expeditiously estimate the frequency; it is a generalized conservation law for the damped nonlinear oscillator. To seek second-order periodic solutions of nonlinear oscillators, a linearized residual Galerkin method (LRGM) is developed whose process to find the second-order periodic solution and the vibrational frequency is quite simple. A hybrid method is achieved through a combination of the linearly perturbed frequency equation and the LRGM; very accurate frequency and second-order periodic solutions can be obtained. Examples reveal high efficacy and accuracy of the proposed methods; the mathematical reliability of these methods is clarified. Full article
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31 pages, 13809 KiB  
Article
Numerical Analysis of Glauert Inflow Formula for Single-Rotor Helicopter in Steady-Level Flight below Stall-Flutter Limit
by Marjan Dodic, Branimir Krstic, Bosko Rasuo, Mirko Dinulovic and Aleksandar Bengin
Aerospace 2023, 10(3), 238; https://doi.org/10.3390/aerospace10030238 - 28 Feb 2023
Cited by 3 | Viewed by 3904
Abstract
This article addresses the numerical computation problem of induced inflow ratio based on the helicopter momentum theory in forward flight. The Glauert inflow formula (equation) is a nonlinear equation usually solved by the Newton–Raphson method in a relatively small number of iterations. However, [...] Read more.
This article addresses the numerical computation problem of induced inflow ratio based on the helicopter momentum theory in forward flight. The Glauert inflow formula (equation) is a nonlinear equation usually solved by the Newton–Raphson method in a relatively small number of iterations. However, many high-order convergence multipoint iterative methods have been developed over the last decade. The study examines several selected methods in terms of finding ones that provide a solution in only one iteration with acceptable accuracy. Furthermore, the influence of initial guesses on the accuracy of the obtained solutions has been investigated. In this regard, the practical range of parameters of the Glauert inflow equation for helicopters in forward flight is roughly determined by simplified modeling of a power and stall-flutter limitation. For these purposes, a basic low-fidelity longitudinal trim model of a single-rotor helicopter in steady-level flight is modified and numerically solved by a symbolic transformation of a system of 20+ nonlinear equations into a single nonlinear equation. Full article
(This article belongs to the Special Issue Advances in Aerospace Sciences and Technology III)
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15 pages, 3034 KiB  
Article
SLAM on the Hexagonal Grid
by Piotr Duszak
Sensors 2022, 22(16), 6221; https://doi.org/10.3390/s22166221 - 19 Aug 2022
Cited by 2 | Viewed by 3130
Abstract
Hexagonal grids have many advantages over square grids and could be successfully used in mobile robotics as a map representation. However, there is a lack of an essential algorithm, namely, SLAM (simultaneous localization and mapping), that would generate a map directly on the [...] Read more.
Hexagonal grids have many advantages over square grids and could be successfully used in mobile robotics as a map representation. However, there is a lack of an essential algorithm, namely, SLAM (simultaneous localization and mapping), that would generate a map directly on the hexagonal grid. In this paper, this issue is addressed. The solution is based on scan matching and solving the least-square problem with the Gauss–Newton formula, but it is modified with the Lagrange multiplier theorem. This is necessary to fulfill the constraints given by the manifold. The algorithm was tested in the synthetic environment and on a real robot and is entirely fully suitable for the presented task. It generates a very accurate map and generally has even better precision than the similar approach implemented on the square lattice. Full article
(This article belongs to the Special Issue Indoor Positioning with Wireless Local Area Networks (WLAN))
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17 pages, 1317 KiB  
Article
An Active Set Limited Memory BFGS Algorithm for Machine Learning
by Hanger Liu, Yan Li and Maojun Zhang
Symmetry 2022, 14(2), 378; https://doi.org/10.3390/sym14020378 - 14 Feb 2022
Cited by 2 | Viewed by 2408
Abstract
In this paper, a stochastic quasi-Newton algorithm for nonconvex stochastic optimization is presented. It is derived from a classical modified BFGS formula. The update formula can be extended to the framework of limited memory scheme. Numerical experiments on some problems in machine learning [...] Read more.
In this paper, a stochastic quasi-Newton algorithm for nonconvex stochastic optimization is presented. It is derived from a classical modified BFGS formula. The update formula can be extended to the framework of limited memory scheme. Numerical experiments on some problems in machine learning are given. The results show that the proposed algorithm has great prospects. Full article
(This article belongs to the Section Mathematics)
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22 pages, 828 KiB  
Article
A Filter and Nonmonotone Adaptive Trust Region Line Search Method for Unconstrained Optimization
by Quan Qu, Xianfeng Ding and Xinyi Wang
Symmetry 2020, 12(4), 656; https://doi.org/10.3390/sym12040656 - 21 Apr 2020
Cited by 4 | Viewed by 3071
Abstract
In this paper, a new nonmonotone adaptive trust region algorithm is proposed for unconstrained optimization by combining a multidimensional filter and the Goldstein-type line search technique. A modified trust region ratio is presented which results in more reasonable consistency between the accurate model [...] Read more.
In this paper, a new nonmonotone adaptive trust region algorithm is proposed for unconstrained optimization by combining a multidimensional filter and the Goldstein-type line search technique. A modified trust region ratio is presented which results in more reasonable consistency between the accurate model and the approximate model. When a trial step is rejected, we use a multidimensional filter to increase the likelihood that the trial step is accepted. If the trial step is still not successful with the filter, a nonmonotone Goldstein-type line search is used in the direction of the rejected trial step. The approximation of the Hessian matrix is updated by the modified Quasi-Newton formula (CBFGS). Under appropriate conditions, the proposed algorithm is globally convergent and superlinearly convergent. The new algorithm shows better performance in terms of the Dolan–Moré performance profile. Numerical results demonstrate the efficiency and robustness of the proposed algorithm for solving unconstrained optimization problems. Full article
(This article belongs to the Special Issue Advance in Nonlinear Analysis and Optimization)
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20 pages, 1050 KiB  
Article
A Modified Equation for Thickness of the Film Fabricated by Spin Coating
by Un Gi Lee, Woo-Byoung Kim, Do Hyung Han and Hyun Soo Chung
Symmetry 2019, 11(9), 1183; https://doi.org/10.3390/sym11091183 - 18 Sep 2019
Cited by 37 | Viewed by 14317
Abstract
According to the equation for Newtonian fluids, the film thickness after spin coating is determined by five parameters: angular velocity, spin coating time, viscosity, density of the coating material, and initial thickness of the material before spin coating. The spin coating process is [...] Read more.
According to the equation for Newtonian fluids, the film thickness after spin coating is determined by five parameters: angular velocity, spin coating time, viscosity, density of the coating material, and initial thickness of the material before spin coating. The spin coating process is commonly controlled by adjusting only the angular velocity parameter and the coating time in the Newtonian expression. However, the measured coating thickness obtained is then compared to the theoretical thickness calculated from the Newtonian fluid equation. The measured coating thickness usually varies somewhat from the theoretical thickness; further details are described in Section 1. Thus, the Newtonian fluid equation must be modified to better represent the actual film thickness. In this paper, we derive a new formula for the spin coating film thickness, which is based on the equation for Newtonian fluids, but modified to better represent film thicknesses obtained experimentally. The statistical analysis is performed to verify our modifications. Full article
(This article belongs to the Special Issue Nonlinear, Convex, Nonsmooth, Functional Analysis in Symmetry)
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