Parameters Of Nonlinear Equations Research Articles

Побудова математичних моделей збудження хрестоподібних поверхневих хвиль у воді в «співаючих бокалах» при випромінюванні бокалами звукових хвиль

The appearance and structure of cross-shaped waves on the free surface of the liquid contained in the ‘singing glass’ is explained. It was found that the main mode of vibration of the glass is a forced wave, with four nodes evenly spaced along the cylindrical glass wall. When such a singing glass is partially filled with a liquid (which changes the frequency of sound), one can observe another amazing feature: a complex pattern of waves on the free surface of the liquid. With sufficient illumination, one can observe waves directly caused by the vibration of the wall in the four-node mode moving in the circumferential direction at the same speed as the moving finger. However, this picture is dominated by so-called ‘cross waves’ or ‘edge waves’, the crests of which are perpendicular to the vibrating glass wall. Although cross-shaped waves were described by Faraday (1831), until now there was no theoretical justification for the possibility of their excitation in a ‘singing glass’. This paper fills this gap: the appearance of cross waves in a ‘singing glass’ has been mathematically described as resonant oscillations. Non-linear parametric equations describing them were obtained for cross-shaped waves. Two mathematical models were built. The first theoretical model describes the appearance of cross-shaped waves, where only one eigenmode is present on the free surface of the liquid, and the second model applies to the situation where at least two or three eigenmodes are present. The oscillations of the free surface in approximations with three eigenmodes reflect the main features of the wave patterns observed experimentally in the ‘singing glass’.

Resonance simulation of the coupled nonlinear Mathieu’s equation

Numerous theoretical physics and chemistry problems can be modeled using Mathieu’s equations (MEs). They are crucial to the theory of potential energy in quantum systems, which is equivalent to the Schrödinger equation. According to the mentioned applications, thus, the current study investigates the stability behavior of the nonlinear-coupled MEs. The analysis of the coupled harmonic resonance cases imposes two coupled solvability conditions, which leads to coupled parametric nonlinear Landau equations. In addition, a super-harmonic nonlinear resonance combination is presented. Solutions and stability criteria are discussed for each case. It is shown that resonance produces an unstable system. The transition curves are derived. Numerical calculations show the excitation of the frequency on the periodic solutions.

Modeling the multifractal dynamics of COVID-19 pandemic

To describe the COVID-19 pandemic, we propose to use a mathematical model of multifractal dynamics, which is alternative to other models and free of their shortcomings. It is based on the fractal properties of pandemics only and allows describing their time behavior using no hypotheses and assumptions about the structure of the disease process. The model is applied to describe the dynamics of the COVID-19 pandemic from day 1 to day 699 from the beginning of the pandemic. The calculated parameters of the model accurately determine the parameters of the trend and the large jump in daily diseases in this time interval. Within the framework of this model and finite-difference parametric nonlinear equations of the reduced SIR (Susceptible-Infected-Removed) model, the fractal dimensions of various segments of daily incidence in the world and variations in the main reproduction number of COVID-19 were calculated based on the data of COVID-19 world statistics.

Damped Mathieu Equation with a Modulation Property of the Homotopy Perturbation Method

In this article, the main objective is to employ the homotopy perturbation method (HPM) as an alternative to classical perturbation methods for solving nonlinear equations having periodic coefficients. As a simple example, the nonlinear damping Mathieu equation has been investigated. In this investigation, two nonlinear solvability conditions are imposed. One of them was imposed in the first-order homotopy perturbation and used to study the stability behavior at resonance and non-resonance cases. The next level of the perturbation approaches another solvability condition and is applied to obtain the unknowns become clear in the solution for the first-order solvability condition. The approach assumed here is so significant for solving many parametric nonlinear equations that arise within the engineering and nonlinear science.

Goal-oriented model reduction for parametrized time-dependent nonlinear partial differential equations

We present a projection-based model reduction formulation for parametrized time-dependent nonlinear partial differential equations (PDEs). Our approach builds on the following ingredients: reduced bases (RB), which provide rapidly convergent approximations of the parameter-temporal solution manifold; reduced quadrature (RQ) rules, which provide hyperreduction of the nonlinear residual; and the dual-weighted residual (DWR) method, which provides an error representation formula for the quantity of interest. To find the RQ rules, we develop an empirical quadrature procedure (EQP) for time-dependent problems; we analyze the output error due to hyperreduction using a space–time DWR framework and identify appropriate constraints so that the output error due to hyperreduction is controlled. We in addition equip our reduced model with an online-efficient DWR a posteriori error estimate for the output; we again analyze the error in the hyperreduced dual problem and DWR expression to find appropriate constraints for the EQP so that the error in the error estimate is controlled. In the offline stage, the RBs and RQs, as well as the finite element mesh, are simultaneously constructed using a POD-greedy algorithm that leverages the online-efficient output error estimate. We demonstrate the framework for parametrized unsteady flows in a lid-driven cavity and over a NACA0012 airfoil. Reduced models achieve over two orders of magnitude reduction in the number of degrees of freedom, number of quadrature points, and wall-clock computational time, while achieving less than 0.5% output error and providing efficient error estimates in predictive settings.

Thermal Effects on the Nonlinear Forced Responses of Hinged-Clamped Beam with Multimodal interaction

Nonlinear analysis of a forced geometrically nonlinear Hinged-Clamped beam involving three modes interactions with internal resonance and submitted to thermal and mechanical loadings is investigated. Based on the extended Hamilton’s principle, the PDEs governing the thermoelastic vibration of planar motion is derived. Galerkin’s orthogonalization method is used to reduce the governing PDEs of motion into a set of nonlinear non-autonomous ordinary differential equations. The system is solved for the three modes involved by the use of the multiple scales method for amplitudes and phases. For steady states responses, the Newton-Raphson shooting technique is used to solve the three systems of six parametric nonlinear algebraic equations obtained. Results are presented in terms of influences of temperature variations on the response amplitudes of different substructures when each of the modes is excited. It is observed for all substructures and independent of the mode excited a shift within the frequency axis of the temperature influenced amplitude response curves on either side of the temperature free-response curve. Moreover, it is found that thermal loads diversely influence the interacting substructures. Depending on the directly excited mode, higher oscillation amplitudes are found in some substructures under negative temperature difference, while it is observed in others under positive temperature change and in some others for temperature free-response curves.

Partial eigenvalue assignment of descriptor fractional discrete-time linear systems by parametric state feedback

In this paper, we present a nonlinear parametric method to stabilize descriptor fractional discrete time linear system practically. Parametric methods with the free parameters can be adjusted to obtain better performance responses like minimum norm in state feedback. The aim is assigning desirable eigenvalues to obtain satisfactory responses by forward state feedback and forward and propositional state feedback in new systems with large matrices. However, finding the solution to nonlinear parametric equations makes some errors. In partial eigenvalue assignment, just a part of the open-loop spectrum of the standard linear systems is reassigned, while leaving the rest of the spectrum invariant. The size of matrices, state, and input vectors are decreased and the stability is kept. At the end, summary and conclusions are proposed and the convergence of state vectors in the descriptor fractional discrete-time system to zero is also shown by figures in a numerical example. Our method is also compared with another method with one of orthogonality relations in our article and example.

Partially reflected waves in water of finite depth

This paper presents a second-order asymptotic solution in the Lagrangian description for nonlinear partial standing wave in the finite water depth. The asymptotic solution that is uniformly valid satisfies the irrotationality condition and zero pressure at the free surface. In the Lagrangian approximation, the explicit nonlinear parametric equations for the particle trajectories are obtained. In particular, the Lagrangian mean level of a particle motion for the partial standing wave is found as a part of the solution which is different from that in an Eulerian system. This solution enables the description of wave profile and particle trajectory, which can be progressive, standing or partial standing waves. The dynamic properties of nonlinear partial standing waves, including mass transport velocity, radiation stress, wave setup and pressure due to reflection are also investigated.

Effect of a breathing crack on the damping changes in nonlinear vibrations of a cracked beam: Experimental and theoretical investigations

The attempts to identify damping changes in a cracked beam can improve the accuracy of the nonlinear crack identification method. For the purpose of this aim, a parametric nonlinear equation of motion is obtained using the Euler–Bernoulli beam theory and parametric nonlinear breathing crack assumptions. Several experiments were conducted to identify the effect of breathing cracks on changing the damping value in nonlinear vibrations of a cracked beam. Experimental tests have revealed that increasing the crack depth and the level of excitation enlarges the damping coefficient in a vibrating beam. For this reason, the effects of the excitation force and crack depth on the structural damping coefficient are investigated. The obtained results indicated that considering the nonlinear response of a cracked beam and measuring the value of the damping changes can significantly improve the accuracy of the nonlinear crack identification method.

Joint set-up of parameters in genetic algorithms and the artificial bee colony algorithm: an approach for cultivation process modelling

In this paper, a Joint set-up procedure for tuning metaheuristic algorithms’ parameters is proposed. The approach is applied to a genetic algorithm (GA) and tested further on the artificial bee colony (ABC) algorithm. The joint influence of parameters (the crossover and mutation probabilities for GA and the number of population and limit for ABC) on the performance of the algorithms is investigated. As a case study, a model parameter identification of an E. coli fed-batch cultivation process is considered. E. coli is one of the most commonly used bacteria for producing medical substances in the pharmaceutical industry. The development of an effective model of a fed-batch cultivation process is very important. The processes in a bioreactor are usually described by a system of parametric nonlinear differential equations. The model parameter identification is a difficult optimization problem, which cannot be solved by applying traditional numerical methods. Feasibilities of GA and ABC for a model parameter identification of a nonlinear fed-batch cultivation process based on real experimental data are presented. The application of the proposed Joint set-up approach leads to a significant improvement in the performance of GA and ABC. As a result, a reasonable enhancement of the E. coli cultivation model accuracy is achieved. The main advantage of the tuning procedure, which searches an optimal set of values of GA and ABC control parameters, focusing on promising intervals of variation of the parameter values and refining their ranges, is that the computational efforts are reduced by more than 60% for the ABC algorithm and more than 90% for GA.

Polynomial Chaos Expansion for Parametric Problems in Engineering Systems: A Review

In engineering systems with uncertain parameters, it is crucial for system analysis and control to analyze the relationship between these uncertain parameters and system outputs (or states). Nevertheless, the acquisition of this parameter-output function, termed parametric problem in this article, is not easy because it is usually a complicated implicit nonlinear function. Polynomial chaos expansion (PCE), based on the generalized Fourier expansion, is a state-of-the-art method for both parametric problems and uncertainty quantification. Its basic idea is to approximate the implicit parameter-output function with a globally optimal explicit polynomial function, which remains accurate in the case of strong nonlinearity compared with the local Taylor expansion. This article provides a review of PCE and its applications in parametric problems. In terms of PCE theory, a rigorous and complete framework of PCE is established and a detailed review of typical PCE methods is presented. In terms of applications, two kinds of general parametric problems, namely parametric nonlinear algebraic equations and parametric differential equations, as well as their examples in some engineering fields, are introduced. Furthermore, some worthwhile future works are presented at the end of this article, which may facilitate the development of PCE.

On fractional quadratic optimization problem with two quadratic constraints

In this paper, we study the problem of minimizing the ratio of two quadratic functions subject to two quadratic constraints in the complex space. Using the classical Dinkelbach method, we transform the problem into a parametric nonlinear equation. We show that an optimal parameter can be found by employing the S-procedure and semidefinite relaxation technique. A key element to solve the original problem is to use the rank-one decomposition procedure. Finally, within the new algorithm, semidefinite relaxation is compared with the bisection method for finding the root on several examples. For further comparison, the solution of fmincon command of MATLAB also is reported.

Parameter estimation using multiparametric programming for implicit Euler’s method based discretization

This work presents a study that aims to compare two discretization methods for solving parameter estimation using multiparametric programming. In our earlier work, parameter estimation using multiparametric programming was presented where model parameters were obtained as an explicit function of measurements. In this method, the nonlinear ordinary equations (ODEs) model was discretized by using explicit Euler’s method to obtain algebraic equations. Then, a square system of parametric nonlinear algebraic equations was obtained by formulating optimality condition. These equations were then solved symbolically to obtain model parameters as an explicit function of measurements. Thus, the online computation burden of solving optimization problems for parameter estimation is replaced by simple function evaluations. In this work, we use implicit Euler’s method for discretization of nonlinear ODEs model and compare with the explicit Euler’s method for parameter estimation using multiparametric programming. Complexity of explicit parametric functions, accuracy of parameter estimates and effect of step size are discussed.

Fault Detection in Wastewater Treatment Systems Using Multiparametric Programming

In this work, a methodology for fault detection in wastewater treatment systems, based on parameter estimation, using multiparametric programming is presented. The main idea is to detect faults by estimating model parameters, and monitoring the changes in residuals of model parameters. In the proposed methodology, a nonlinear dynamic model of wastewater treatment was discretized to algebraic equations using Euler’s method. A parameter estimation problem was then formulated and transformed into a square system of parametric nonlinear algebraic equations by writing the optimality conditions. The parametric nonlinear algebraic equations were then solved symbolically to obtain the concentration of substrate in the inflow, S c i n , inhibition coefficient, K i , and specific growth rate, μ o , as an explicit function of state variables (concentration of biomass, X ; concentration of organic matter, S c ; concentration of dissolved oxygen, S o ; and volume, V ). The estimated model parameter values were compared with values from the normal operation. If the residual of model parameters exceeds a certain threshold value, a fault is detected. The application demonstrates the viability of the approach, and highlights its ability to detect faults in wastewater treatment systems by providing quick and accurate parameter estimates using the evaluation of explicit parametric functions.

Fluid surface waves in a partially filled ‘singing wine glass’

The appearance and the structure of the directly-forced waves and cross-waves at the free surface of a fluid contained in a ‘singing wine glass’ are explained by using the superposition method. Cross-waves have crests perpendicular to a vibrating wall, such as in the case of the ‘singing glass’, driven by a moistened finger moving steadily along the rim of the glass. According to experimental studies, the directly-forced waves have four nodes (i.e. are spanning two wavelengths) in the azimuthal direction. For directly-forced waves a linear model could be derived, while for the cross-waves the nonlinear parametric equations are worked out. A graphical representation of the free surface elevation by three eigenmode approximations shows the main features of the wave patterns observed in a singing wine glass.

Positive solutions for the Robin p-Laplacian problem with competing nonlinearities

Abstract We consider a parametric nonlinear elliptic equation driven by the Robin p-Laplacian. The reaction term is a Carathéodory function which exhibits competing nonlinearities (concave and convex terms). We prove two bifurcation-type results describing the set of positive solutions as the parameter varies. In the process we also prove two strong comparison principles for Robin equations. These results are proved for differential operators which are more general than the p-Laplacian and need not be homogeneous.

Fault location in distribution systems: A Method Considering the Parameter Estimation Using a RNA Online

This paper proposes a new methodology for single-phase short-circuit location in power distribution systems. The feeder behavior during single-phase faults is modeled in terms of the distance of the fault, the network parameters and the currents and voltages measured only at the substation. Thus, the proposed method does not require the installation of any additional measurement equipment in the network. The capacitances of the network were also considered in the model used, making it closer to the real system. The main innovation of the proposed method is the use of a neural network, which does not require prior training, to estimate the unknown parameters of nonlinear equations that model the feeder behavior during faults. The performance of the proposed method was evaluated in the test system IEEE 34 bars through the variation of fault resistance and load feeder. Furthermore, it was also evaluated the influence of the estimated short-circuit current in the determination of the fault location. The good results obtained, combined with simplicity and low cost of implementation, make the proposed method promising for application in a real feeder.

Algorithmic Differentiation of Numerical Methods: Second-order Adjoint Solvers for Parameterized Systems of Nonlinear Equations

Adjoint mode algorithmic (also know as automatic) differentiation (AD) transforms implementations of multivariate vector functions as computer programs into first-order adjoint code. Its reapplication or combinations with tangent mode AD yields higher-order adjoint code. Second derivatives play an important role in nonlinear programming. For example, second-order (Newton-type) nonlinear optimization methods promise faster convergence in the neighborhood of the minimum through taking into account second derivative information. The adjoint mode is of particular interest in large-scale gradient-based nonlinear optimization due to the independence of its computational cost on the number of free variables. Part of the objective function may be given implicitly as the solution of a system of n parameterized nonlinear equations. If the system parameters depend on the free variables of the objective, then second derivatives of the nonlinear system's solution with respect to those parameters are required. The local computational overhead as well as the additional memory requirement for the computation of second-order adjoints of the solution vector with respect to the parameters by AD depends on the number of iterations performed by the nonlinear solver. This dependence can be eliminated by taking a symbolic approach to the differentiation of the nonlinear system.

Thermal Post-Buckling Analysis of Nanoscale Films Based on a Non-Classical Finite Element Approach

A size-dependent finite element (FE) formulation including surface free energy effect is developed in this article to study the post-buckling behavior of nanofilms under the action of thermal loads. The Gurtin-Murdoch surface elasticity theory is utilized to consider the surface effects. Moreover, the principle of virtual work is used so as to derive the equilibrium equations. The proposed FE formulation is based on the first-order shear deformation theory (FSDT). The von Kármán nonlinear relations are also employed to take the geometric nonlinearity into account. After deriving the FE equations, the resulting set of parameterized non-linear equations is solved using the pseudo arc-length continuation algorithm, and bifurcation diagrams of nanofilms are obtained. Selected numerical results are presented for the influences of surface stress on the thermal post-buckling characteristics of nanofilms subject to different types of boundary conditions.

Existence, nonexistence and multiplicity of positive solutions for parametric nonlinear elliptic equations

We consider a parametric nonlinear elliptic equation driven by the Dirichlet $p$-Laplacian. We study the existence, nonexistence and multiplicity of positive solutions as the parameter $\lambda$ varies in $\mathbb{R}^{+}_{0}$ and the potential exhibits a $p$-superlinear growth, without satisfying the usual in such cases Ambrosetti--Rabinowitz condition. We prove a bifurcation-type result when the reaction has ($p-1$)-sublinear terms near zero (problem with concave and convex nonlinearities). We show that a similar bifurcation-type result is also true, if near zero the right hand side is ($p-1$)-linear.