Non-linear output frequency response functions of MDOF systems with multiple non-linear components

In engineering practice, most mechanical and structural systems are modelled as multi-degree-of-freedom (MDOF) systems such as, e.g., the periodic structures. When some components within the systems have non-linear characteristics, the whole system will behave non-linearly. The concept of non-linear output frequency response functions (NOFRFs) was proposed by the authors recently and provides a simple way to investigate non-linear systems in the frequency domain. The present study is concerned with investigating the inherent relationships between the NOFRFs for any two masses of non-linear MDOF systems with multiple non-linear components. The results reveal very important properties of the non-linear systems. These properties clearly indicate how the system linear characteristic parameters govern the propagation of the non-linear effect induced by non-linear components in the system. One potential application of the results is to detect and locate faults in engineering structures which make the structures behave non-linearly.     

A frequency-domain FEM approach based on implicit Green’s functions for non-linear dynamic analysis

The present paper describes an efficient algorithm to integrate the equations of motion implicitly in the frequency domain. The standard FEM displacement model (Galerkin formulation) is employed to perform space discretization, and the time-marching process is carried out through an algorithm based on the Green’s function of the mechanical system in nodal coordinates. In the present formulation, mechanical system Green’s functions are implicitly calculated in the frequency domain. Once the Green’s functions related matrices are computed, a time integration procedure, which demands low computational effort when applied to non-linear mechanical systems, becomes available. At the end of the paper numerical examples are presented in order to illustrate the accuracy of the present approach.     

Equations of motion for mechanical systems: A unified approach

This paper presents a unified framework from which emerge the Lagrange equations, the Gibbs-Appell Equations and the Generalized Inverse Equations for describing the motion of constrained mechanical systems. The unified approach extends the applicability of the first two approaches to systems where the constraints are non-linear functions of the generalized velocities and are not necessarily independent. Furthermore, the approach leads to the Explicit Gibbs-Appell Equations.     

On non-linear dynamics of a coupled electro-mechanical system

Electro-mechanical devices are an example of coupled multi-disciplinary weakly non-linear systems. Dynamics of such systems is described in this paper by means of two mutually coupled differential equations. The first one, describing an electrical system, is of the first order and the second one, for mechanical system, is of the second order. The governing equations are coupled via linear and weakly non-linear terms. A classical perturbation method, a method of multiple scales, is used to find a steady-state response of the electro-mechanical system exposed to a harmonic close-resonance mechanical excitation. The results are verified using a numerical model created in MATLAB Simulink environment. Effect of non-linear terms on dynamical response of the coupled system is investigated; the backbone and envelope curves are analyzed. The two phenomena, which exist in the electro-mechanical system: (a)?detuning (i.e. a natural frequency variation) and (b)?damping (i.e. a decay in the amplitude of vibration), are analyzed further. An applicability range of the mathematical model is assessed.     

Averaging method for the solution of non-linear differential equations with periodic non-harmonic solutions

While Krylov and Bogolyubov used harmonic functions in their averaging method for the approximate solution of weakly non-linear differential equations with oscillatory solution, we apply a similar averaging technique using Jacobi elliptic functions. These functions are also periodic and are exact solutions of strongly non-linear differential equations. The method is used to solve non-linear differential equations with linear and non-linear small dissipative terms and/or with time dependent parameters. It is also shown that quite general dissipative terms can be transformed into time-dependent parameters. As a special example, the Langevin (collisional) equation of motion of electrons in a neutralizing ion background under the influence of a time and space-dependent electric field is presented. The method may also be used for non-linear control theory, dynamic and parametric stabilization of non-linear oscillations in plasma physics, etc.     

Exact stationary probability density functions for non-linear systems under Poisson white noise excitation

The paper presents exact stationary probability density functions for systems under Poisson white noise excitation. Two different solution methods are outlined. In the first one, a class of non-linear systems is determined whose state vector is a memoryless transformation of the state vector of a linear system. The second method considers the generalized Fokker-Planck (Kolmogorov-forward) equation. Non-linear system functions are identified such that the stationary solution of the system admits a prescribed stationary probability density function. Both methods make use of the stochastic integro-differential equations approach. This approach seems to have some computational advantages for the determination of exact stationary probability density functions when compared to the stochastic differential equations approach.     

Methods of Identification of Nonlinear Mechanical Vibrating Systems

Methods for determination of the dynamic characteristics and parameters of mechanical vibrating systems by processing experimental data on controlled vibrations are presented. These methods are intended for construction of mathematical models of objects to be identified and classed as parametric and nonparametric methods. The quadrature formulas of the nonparametric-identification method are derived by inverting the integral parameters of approximate analytical solutions of nonlinear differential equations. The parametric-identification method involves setting up and solving systems of linear algebraic equations in the sought-for inertia, stiffness, and dissipation parameters by integrating experimental processes using special weighting functions. Depending on the type of the nonlinearity of the vibrating system and the method of representing experimental processes, the weighting functions can be oriented toward displacement, velocity, or acceleration gauges. The results of studies made mainly at the Institute of Mechanics of the National Academy of Sciences of Ukraine are presented     

Reynolds’ dream?

For many non-linear phenomena, it is necessary to solve infinite systems of equations for correlation functions with a wide range of parameters. This paper can be seen as a first step in addressing this problem. Correlation functions related to the ?³ and to the ?⁴ field theories are described by means of generating Fock space vectors constructed with the help of Cuntz algebra. The equations obtained are easily transformed and general solutions are constructed. Various expansions of these solutions are developed using the explicitly constructed right inverse operators related to linear and non-linear parts of the theory. Based on the idea of information loss and using the language of classical mechanics, a solution to the closure problem for correlation functions is proposed. The method described in this paper can be used to obtain approximated correlation functions with strong and weak non-linearity.     

Identification of physical parameters with memory in non-linear systems

A new technique called ‘Reverse MI/SO’ has been developed that greatly simplifies the identification of parameters in systems with amplitude non-linearities and frequency-dependent coefficients as described by non-linear integro-differential equations of motion. This paper illustrates the technique for single degree-of-freedom (SDOF) non-linear systems where linear and non-linear damping is described by memory functions of an exponential and exponential-cosine analytical form. Comparisons between analytical and numerical simulation results prove that the Reverse MI/SO technique is quite robust. A discussion is included outlining the importance of this new technique as applied to the (non-linear) dynamics of ships and stability studies.     

Post-buckling of a hinged-fixed beam under uniformly distributed follower forces

Based on geometrically non-linear theory for extensible elastic beams, governing equations of statically post-buckling of a beam with one end hinged and the other fixed, subjected to a uniformly distributed, tangentially compressing follower forces are established. They consist of a boundary-value problem of ordinary differential equations with a strong non-linearity, in which seven unknown functions are contained and the arc length of the deformed axis is considered as one of the basic unknown functions. By using shooting method and in conjunction with analytical continuation, the non-linear governing equations are solved numerically and the equilibrium paths as well as the post-buckled configurations of the deformed beam are presented. A comparison between the results of conservative system and that of the non-conservative systems are given. The results show that the features of the equilibrium paths of the beams under follower loads are evidently different from that under conservative ones.     

Identification of stiffness, dissipation and input parameters of randomly excited non-linear systems: Capability of restricted potential models (RPM)

A dynamic identification technique in the time domain for time invariant systems under random external forces is presented. This technique is based on the use of the class of restricted potential models (RPM), which are characterized by a non-linear stiffness and a special form of damping, that is a product of the input power spectral density (PSD) matrix and the velocity gradient of a non-linear function of the total mechanical energy. By applying stochastic differential calculus and by specific analytical manipulations, some algebraic equations, depending on the response statistics and on the mechanic parameters that characterize RPM, are obtained. These equations can be used for the dynamic identification of the above mechanic parameters once the response statistics of the system to be identified are evaluated. The proposed technique allows one to identify single-degree-of-freedom or multi-degrees-of-freedom systems in the case of unmeasurable input. Further, the probabilistic characteristics of the external forces can be completely estimated in terms of PSD matrix.     

Effect of non-linearities in the identification and fault detection of gear-pair systems

This study investigates issues related to parametric identification and health monitoring of dynamical systems with non-linear characteristics. In the first part, a gear-pair system supported on bearings with rolling elements is selected as an example mechanical model and the corresponding equations of motion are set up. This model possesses strongly non-linear characteristics, accounting for gear backlash and bearing stiffness non-linearities. Then, the basic steps of the parametric identification and fault detection procedure employed are outlined briefly. In particular, a Bayesian statistical framework is adopted in order to estimate the optimal values of the gear and bearing model parameters. This is achieved by combining experimental information from vibration measurements with theoretical information built into a parametric mathematical model of the system. In the second part of the study, characteristic numerical results are presented. First, based on the effect of the system parameters on its dynamics, a solid basis is created for explaining some of the peculiar results obtained by applying classical gradient-based optimization methodologies for the strongly non-linear system examined. Some serious difficulties, associated with the existence of irregular response or the coexistence of multiple motions, are first pointed out. A solution to some of these problems, through the application of a suitable genetic algorithm, is then presented. Special problems, related to more classical identification issues associated with the presence of measurement noise and model error, are also investigated.     

COLLATION AND UPWINDING FOR THERMAL FLOW IN PIPELINES: THE LINEARIZED CASE

Simulating thermal effects in pipeline flow involves solving a coupled non-linear system of first-order hyperbolic equations. The advection term has two large eigenvalues of opposite signs, corresponding to the propagation of high-speed sound waves, and one eigenvalue close to or even equal to zero, representing the much slower fluid flow velocity, which transports temperature. Standard collocation methods work well for isothermal flow in pipelines, but the stagnating eigenvalue causes difficulties when thermal effects are included. In a companion paper we formulate and analyse a new numerical method for the non-linear system which arises in thermal modelling. The new method applies to general coupled systems of non-linear first-order hyperbolic partial differential equations with one degenerate eigenvalue. In the present paper we focus on a linearized constant coefficient form of the thermal flow equations. This substantially simplifies presentation of the error analysis for the numerical scheme. We also include numerical results for the method applied to the fully non-linear system. Both the error analysis and the numerical experiments show that the difficulties that come from the application of standard collocation can be overcome by using upwinded piecewise constant functions for the degenerate component of the solution.     

Parameter and state identification in non-linearizable uncertain systems

A dynamical process is modelled by a system of non-linearizable ordinary differential equations with uncertain but bounded state variables and variable parameters. When stochastic identification is not feasible (no assumptions upon random parameters, single run control, etc), the “worst case” design is required. To avoid this penalty, we propose to extend the Liapunov design technique of building adaptive (on-line) identifiers, so far developed for linear systems with constant parameters. The standard study of stability of an error-equation is replaced by investigating convergence to diagonal set in the Cartesian product of state-parameter spaces of the model and the identifier. We also attempt to stabilize the model. Conditions for the above are introduced together with proposing suitable Liapunov functions. The method is illustrated on two examples with wide applicability: a damped Hamiltonian system and the non-linear oscillator.     

Study of a non-linear mechanical system using Boubaker polynomials expansion scheme BPES

Differential equations governing mechanical system behaviours have to be transformed into algebraic equations using the appropriate analytical and numerical tools. This study is concerned with the identification of a non-linear 2-degree-of-freedom mechanical system using the Boubaker polynomials expansion scheme (BPES). Solutions are plotted in the frequency-energy plane and are compared to other results published so far.     

Large free vibrations of a beam carrying a moving mass

The focus of this work is to develop a technique to obtain numerical solution over a long range of time for non-linear multi-body dynamic systems undergoing large amplitude motion. The system considered is an idealization of an important class of problems characterized by non-linear interaction between continuously distributed mass and stiffness and lumped mass and stiffness. This characteristic results in some distinctive features in the system response and also poses significant challenges in obtaining a solution.

In this paper, equations of motion are developed for large amplitude motion of a beam carrying a moving spring–mass. The equations of motion are solved using a new approach that uses average acceleration method to reduce non-linear ordinary differential equations to non-linear algebraic equations. The resulting non-linear algebraic equations are solved using an iterative method developed in this paper. Dynamics of the system is investigated using a time-frequency analysis technique.     

Analysis of the von Karman equations by group methods

One of the systems of equations approximating the large deflection of plates consists of two coupled non-linear fourth order partial differential equations, known as the von Karman equations. The full symmetry group for the steady equations is a finitely generated Lie group with ten parameters. For the time-dependent system the full symmetry group is an infinite parameter Lie group. Several subgroups of the full group are used to generate exact solutions of the time-independent and the time-dependent systems. These include the dilatation group (similar solutions), rotation group, screw group and others. Physical implications and applications are discussed.     

Representation of Normal Cone Inclusion Problems in Dynamics Via Non-linear Equations

Analyzing non-smooth mechanical systems requires often the solution of inclusion problems of normal cone type. These problems arise for example in the event-driven or time-stepping simulation approaches. Such inclusion problems can be written as non-linear equations, which can be solved iteratively. In this paper we discuss three different methods to derive the non-linear equations representing the inclusions arising in the event-driven simulation approach. First, we formulate inclusions describing the individual non-smooth constraints and solve them successively. Secondly, we interpret the non-linear equations as the conditions for the saddle point of the augmented Lagrangian function. As a third possibility we discuss the exact regularization of set-valued force laws. All three methods lead to the same numerical scheme, but give different insight into the problem. Especially the factor r occurring in the non-linear equations is discussed. Two iterative methods for solving the non-linear equations are presented together with some remarks on convergence.     

Non-linear stability problem of an open conical sandwich shell under external pressure and compression

The stability problem of a shallow sandwich shell of conical segment shape, subjected to uniform external pressure and compression along generators is analysed based on the finitedeformation theory. With the help of the Ritz method the system of five non-linear, heterogeneous equations is obtained. They are the basic equations of elastic stability of the shell under consideration. The results of numerical calculations are presented in diagrams, which show the influence of basic mechanical properties and geometric parameters of the shell on the value of the upper and lower critical load.     

Local and nonlocal conserved vectors of the system of two-dimensional generalized inviscid Burgers equations

The concept of non-linear self-adjointness for the construction of conservation laws has attracted a lot of interest in recent years. The most noteworthy aspect of it is the likelihood of explicitly constructing the conservation laws for any arbitrary systems of differential equations, in particular for those for which Noether׳s theorem is not applicable. In this study, we shall use both Noether׳s theorem and the non-linear self-adjoint method to construct local and nonlocal conserved vectors of the system of two-dimensional Burgers equations under consideration. The first integrals obtained not only give more credence to obtained results due to their generality with respect to any arbitrary functions of the velocity components but are also independent, nontrivial and infinitely many.