76 research outputs found

    Applied Mathematics to Mechanisms and Machines

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    This book brings together all 16 articles published in the Special Issue "Applied Mathematics to Mechanisms and Machines" of the MDPI Mathematics journal, in the section “Engineering Mathematics”. The subject matter covered by these works is varied, but they all have mechanisms as the object of study and mathematics as the basis of the methodology used. In fact, the synthesis, design and optimization of mechanisms, robotics, automotives, maintenance 4.0, machine vibrations, control, biomechanics and medical devices are among the topics covered in this book. This volume may be of interest to all who work in the field of mechanism and machine science and we hope that it will contribute to the development of both mechanical engineering and applied mathematics

    Symmetry-based stability theory in fluid mechanics

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    The present work deals with the stability theory of fluid flows. The central subject is the question under which circumstances a flow becomes unstable. Instabilities are a frequent trigger of laminar-turbulent transitions. Stability theory helps to explain the emergence of structures, e.g. wave-like perturbation patterns. In this context, the use of Lie symmetries allows the classification of existing and the construction of new solutions within the framework of linear stability theory. In addition, a new nonlinear eigenvalue problem (NEVP) is presented, whose derivation is completely based on Lie symmetries. In classical linear stability theory, a normal ansatz is used for perturbations. Another ansatz that has been shown in early work is the Kelvin mode ansatz. In the work of Nold and Oberlack (2013) and Nold et al. (2015) it was shown that these ansätze can be traced back to the Lie symmetries of the linearized perturbation equations. Interestingly, knowledge of the symmetries also allows for the construction of new ansatz functions that go beyond the known ansätze. For a plane rotational shear flow, in addition to the normal mode ansatz, an algebraic mode ansatz with algebraic behavior in time t^s (eigenvalue s) can be constructed. The flow is stable according to Rayleigh's inflection point criterion, which is also confirmed by the algebraic mode ansatz. Furthermore, exact solutions of the eigenfunctions can be found and new stable modes can be determined by asymptotic methods. Thereby, spiral-like structures of the vorticity can be recognized, which propagate in the region with time. Another key result of this work is the formulation and solution of an NEVP based on the Lie symmetries of the Euler equation. It can is shown that an NEVP can be formulated for a class of flows with a constant velocity gradient. These include, for example, linear shear flows, strained flows, and rotating flows. The NEVP for linear shear flows shows a relation to experimental data from turbulent shear flows. It can be theoretically shown that the turbulent kinetic energy scales exponentially with the eigenvalue of the NEVP. The eigenvalue is determined numerically using a parallel spectral solver. Initially, nonlinear terms are neglected. The determined eigenvalues are in the range of known literature values for turbulent shear flows. Furthermore, the NEVPs for plane flows with pure rotation and pure strain are solved. It is shown that the flow is invariant to rotation, while oscillatory eigenfunctions are found in the case of strain. In addition, an algorithm to solve the NEVP including the nonlinear terms is presented. The results allow an exciting insight into a new stability theory and form the basis for further investigation and understanding of the full nonlinear dynamics of the fluid flows based on the NEVP

    Attractor selection in nonlinear oscillators by temporary dual-frequency driving

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    This paper presents a control technique capable of driving a harmonically driven nonlinear system between two distinct periodic orbits. A vital component of the method is a temporary dual-frequency driving with tunable driving amplitudes. Theoretical considerations revealed two necessary conditions: one for the frequency ratio of the dual-frequency driving and another one for torsion numbers of the two orbits connected by bifurcation curves in the extended dual-frequency driving parameter space. Although the initial and the final states of the control strategy are single-frequency driven systems with distinct parameter sets (frequencies and driving amplitudes), control of multistability is also possible via additional parameter tuning. The technique is demonstrated on the symmetric Duffing oscillator and the asymmetric Toda oscillator

    Electronic Journal of Qualitative Theory of Differential Equations 2022

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    Symmetry in Modeling and Analysis of Dynamic Systems

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    Real-world systems exhibit complex behavior, therefore novel mathematical approaches or modifications of classical ones have to be employed to precisely predict, monitor, and control complicated chaotic and stochastic processes. One of the most basic concepts that has to be taken into account while conducting research in all natural sciences is symmetry, and it is usually used to refer to an object that is invariant under some transformations including translation, reflection, rotation or scaling.The following Special Issue is dedicated to investigations of the concept of dynamical symmetry in the modelling and analysis of dynamic features occurring in various branches of science like physics, chemistry, biology, and engineering, with special emphasis on research based on the mathematical models of nonlinear partial and ordinary differential equations. Addressed topics cover theories developed and employed under the concept of invariance of the global/local behavior of the points of spacetime, including temporal/spatiotemporal symmetries

    Phase space analysis of nonlinear wave propagation in a bistable mechanical metamaterial with a defect

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    We study the dynamics of solitary waves traveling in a one-dimensional chain of bistable elements in the presence of a local inhomogeneity (“defect”). Numerical simulations reveal that depending upon its initial speed, an incoming solitary wave can get transmitted, captured, or reflected upon interaction with the defect. The dynamics are dominated by energy exchange between the wave and a breather mode localized at the defect. We derive a reduced-order two degree of freedom Hamiltonian model for wave-breather interaction and analyze it using dynamical systems techniques. Lobe dynamics analysis reveals the fine structure of phase space that leads to the complicated dynamics in this system. This work is a step toward developing a rational approach to defect engineering for manipulating nonlinear waves in mechanical metamaterials

    Challenges in nonlinear structural dynamics: New optimisation perspectives

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    nalysis of structural dynamics is of fundamental importance to countless engineering applications. Analyses in both research and industrial settings have traditionally relied on linear or close to linear approximations of the underlying physics. Perhaps the most pervasive framework, modal analysis, has become the default framework for consideration of linear dynamics. Modern hardware and software solutions have placed linear analysis of structural dynamics squarely in the mainstream. However, as demands for stronger and lighter structures increase, and as advanced manufacturing enables more and more intricate geometries, the assumption of linearity is becoming less and less realistic. This thesis envisages three grand challenges for the treatment of nonlinearity in structural dynamics. These are: nonlinear system identification, exact solutions to nonlinear differential equations, and a nonlinear extension to linear modal analysis. Of these challenges, this thesis presents results pertaining to the latter two. The first component of this thesis is the consideration of methods that may yield exact solutions to nonlinear differential equations. Here, the task of finding an exact solution is cast as a heuristic search problem. The structure of the search problem is analysed with a view to motivate methods that are predisposed to finding exact solutions. To this end, a novel methodology, the affine regression tree, is proposed. The novel approach is compared against alternatives from the literature in an expansive benchmark study. Also considered, are nonlinear extensions to linear modal analysis. Historically, several frameworks have been proposed, each of which is able to retain only a subset of the properties of the linear case. It is argued here that retention of the utilities of linear modal analysis should be viewed as the criteria for a practical nonlinear modal decomposition. A promising direction is seen to be the recently-proposed framework of Worden and Green. The approach takes a machine-learning viewpoint that requires statistical independence between the modal coordinates. In this thesis, a robust consideration of the method from several directions is attempted. Results from several analyses demonstrate that statistical-independence and other inductive biases can be sufficient for a meaningful nonlinear modal decomposition, opening the door to a practical, nonlinear extension to modal analysis. The results in this thesis take small but positive steps towards two pressing challenges facing nonlinear structural dynamics. It is hoped that further work will be able to build upon the results presented here to develop a greater understanding and treatment of nonlinearity in structural dynamics and elsewhere

    Efficient sensitivity analysis of chaotic systems and applications to control and data assimilation

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    Sensitivity analysis is indispensable for aeronautical engineering applications that require optimisation, such as flow control and aircraft design. The adjoint method is the standard approach for sensitivity analysis, but it cannot be used for chaotic systems. This is due to the high sensitivity of the system trajectory to input perturbations; a characteristic of many turbulent systems. Although the instantaneous outputs are sensitive to input perturbations, the sensitivities of time-averaged outputs are well-defined for uniformly hyperbolic systems, but existing methods to compute them cannot be used. Recently, a set of alternative approaches based on the shadowing property of dynamical systems was proposed to compute sensitivities. These approaches are computationally expensive, however. In this thesis, the Multiple Shooting Shadowing (MSS) [1] approach is used, and the main aim is to develop computational tools to allow for the implementation of MSS to large systems. The major contributor to the cost of MSS is the solution of a linear matrix system. The matrix has a large condition number, and this leads to very slow convergence rates for existing iterative solvers. A preconditioner was derived to suppress the condition number, thereby accelerating the convergence rate. It was demonstrated that for the chaotic 1D Kuramoto Sivashinsky equation (KSE), the rate of convergence was almost independent of the #DOF and the trajectory length. Most importantly, the developed solution method relies only on matrix-vector products. The adjoint version of the preconditioned MSS algorithm was then coupled with a gradient descent method to compute a feedback control matrix for the KSE. The adopted formulation allowed all matrix elements to be computed simultaneously. Within a single iteration, a stabilising matrix was computed. Comparisons with standard linear quadratic theory (LQR) showed remarkable similarities (but also some differences) in the computed feedback control kernels. A preconditioned data assimilation algorithm was then derived for state estimation purposes. The preconditioner was again shown to accelerate the rate of convergence significantly. Accurate state estimations were computed for the Lorenz system.Open Acces
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