Short communication
Fractional dynamics in the Rayleigh’s piston

https://doi.org/10.1016/j.cnsns.2015.07.009Get rights and content

Highlights

  • Dynamical analysis of the Rayleigh piston.

  • Power law approximation in the Fourier domain.

  • Application of fractional calculus and fractional Brownian motion in the Rayleigh piston dynamical analysis.

Abstract

This paper studies the dynamics of the Rayleigh piston using the modeling tools of Fractional Calculus. Several numerical experiments examine the effect of distinct values of the parameters. The time responses are transformed into the Fourier domain and approximated by means of power law approximations. The description reveals characteristics usual in Fractional Brownian phenomena.

Introduction

During the last decades several papers addressed a conceptual example of statistical mechanics known as the “Rayleigh piston” [1], [2]. This classical prototype system consists of a one-dimensional array of particles separated by means of an adiabatic piston. The particles in the two cylinders have non-zero random velocities and collide sporadically with the piston provoking its motion. While a very simple system, a kind of conceptual paradox occurs and considerable debate took place about the steady state operating conditions. Nevertheless, most of the technical literature addresses the relationship of the system final equilibrium conditions and the study of the complex dynamics has not attracted relevant attention.

This paper focus the dynamics of the Rayleigh piston in the perspective of Fractional Brownian motion (fBm) and Fractional Calculus (FC). The fBm was introduced by Kolmogorov [3]. Later Mandelbrot adopted the concept of fBm to model phenomena with self-similarity and long range effects [4]. The fBm is also called 1/f noise [5], where f denotes frequency, because its spectrum is given by 1/f α, α > 0. The fBm is interpreted as a signature of complexity [6] and has been observed in many distinct areas [7], namely in economics and finance [8], [9], geophysics [10], [11], [12], [13], [14], [15], music and speech [16], [17], [18], biology [19], [20], [21], [22], [23] and others. During the last years the relation between fBm and FC was studied by some researchers [24], [25], [26], [27]. FC emerged with the ideas of Leibniz and several important mathematicians contributed to its development [28], [29], [30], [31], [32]. However, only in the last decades [33], [34] FC was recognized to be an important tool to study systems with long range memory phenomena [35], [36], [37], [38], [39], [40], [41], [42], [43], [44]. FC generalizes the operations of integration and differentiation to non-integer orders and constitutes an efficient mathematical tool for describing natural phenomena with long-range memory effects and power law description. This paper addresses the Rayleigh piston and its characterization by means of fBm and FC concepts.

Having these ideas in mind, this paper focus on the fBm in the perspective of FC and is organized as follows. Section 2 introduces the “Rayleigh piston”, develops the analysis in the Fourier domain, extracting several power-law parameters, and discusses the results in the perspective of dynamical systems. Finally, Section 3 outlines the main conclusions.

Section snippets

Preliminary concepts

The Rayleigh’s piston is a system consisting of two cylinders, to be denoted as 1 and 2, containing some type of fluid, and separated by an adiabatic movable piston (Fig. 1). A brake maintains the piston at rest until time t=0. The two fluids are in equilibrium with pressure, volume and temperature {pi(0), Vi(0), Ti(0)}, i=1,2. The piston with mass M undergoes random one-dimensional collisions with particles of mass m. Furthermore, there are ni, i=1,2, particles per unit volume, with Maxwell

Conclusions

This paper studied the dynamical properties of Rayleigh piston. The novel contribution was in the viewpoint of fBm and FC. Several numerical experiments with distinct values for the system parameters, such as number of particles, their masses and their velocities, were conducted. The transient and steady-state behavior was characterized in the Fourier domain by means of power law approximations. The results demonstrated that fBm and FC are useful tools for investigating the complexity present

References (54)

  • CallenH.B.

    Thermodynamics

    (1963)
  • CallenH.B.

    Thermodynamics and an introduction to thermostatistics

    (1985)
  • KolmogorovA.N.

    Wienersche spiralen und einige andere interessante kurven im hilbertschen raum

    Comptes Rendus (Doklady) Acad Sci l’URSS

    (1940)
  • MandelbrotB.B. et al.

    The fractional Brownian motions, fractional noises and applications

    SIAM Rev

    (1968)
  • KeshnerM.S.

    1/f noise

    Proc IEEE

    (1982)
  • MandelbrotB.B.

    The fractal geometry of nature

    (1983)
  • NourdinI.

    Selected aspects of fractional Brownian motion

    (2012)
  • LoA.W.

    Long term memory in stock market prices

    Econometrica

    (1991)
  • KirályA. et al.

    Stochastic modeling of daily temperature fluctuations

    Phys Rev E

    (1998)
  • MontanariA. et al.

    A seasonal fractional ARIMA model applied to the Nile river monthly flows at Aswan

    Water Resour Res

    (2000)
  • KoutsoyiannisD.

    Climate change, the Hurst phenomenon, and hydrological statistics

    Hydrol Sci J

    (2003)
  • chih ChenC. et al.

    A relationship between Hurst exponents of slip and waiting time data of earthquakes

    Physica A

    (2008)
  • VyushinD.I. et al.

    On the origins of temporal power-law behavior in the global atmospheric circulation

    Geophys Res Lett

    (2009)
  • VossR.F. et al.

    1/f noise in music and speech

    Nature

    (1975)
  • VossR.F. et al.

    “1/f noise” in music: music from 1/f noise

    J Acoust Soc Am

    (1978)
  • PengC.K. et al.

    Long-range correlations in nucleotide sequences

    Nature

    (1992)
  • PengC.-K. et al.

    Mosaic organization of DNA nucleotides

    Phys Rev E

    (1994)
  • Cited by (12)

    • New results on nonlocal functional integro-differential equations via Hilfer fractional derivative

      2020, Alexandria Engineering Journal
      Citation Excerpt :

      Due to its tremendous applications many researchers are working in this field. Initially it was developed by several authors in their monograph [18,19,22,24,27,28,49] and considerable articles have been concerned to review the presence of smooth solutions of fractional systems [1,2,4,7–11,13–16,20,21,26,29–33,34–45,50,51]. This section deals with the basic facts and lemmas which will be used in further sequel.

    • Delay independent robust stability analysis of delayed fractional quaternion-valued leaky integrator echo state neural networks with QUAD condition

      2019, Applied Mathematics and Computation
      Citation Excerpt :

      Indeed, this idea is receiving considerable attention in the scope of fractional calculus. Fractional calculus is as old as the standard calculus, but recently it was verified that it provides superior tools for the modeling and control of complex systems [19–22]. Due to this reason, the study of Fractional Order Recurrent NN (FORNN) attracted the attention of several researchers in the last years.

    • Stability analysis of fractional Quaternion-Valued Leaky Integrator Echo State Neural Networks with multiple time-varying delays

      2019, Neurocomputing
      Citation Excerpt :

      Due to their properties, the ESNN has been successfully applied in a wide range of problems [44–47]. Fractional calculus is an effective tool for modeling and controlling physical systems with memory effects [48–52]. In [51], the robust stability analysis of Fractional order (FO) singular nonlinear systems with the fractional proportional derivative controller was investigated using the Lyapunov function.

    • A novel stability criterion of the time-lag fractional-order gene regulatory network system for stability analysis

      2019, Communications in Nonlinear Science and Numerical Simulation
      Citation Excerpt :

      Therefore, there have been more and more studies on FOs in recent years. Distinct phenomena are successfully modeled in the FOs perspective, such as earthquakes [7], the Rayleighs piston [8], stock markets [9], pendula [10], muscular blood vessels [11], electromagnetism [12] viscoelastic system [13], dielectric polarization [14], electrode-electrolyte polarization [15], electromagnetic waves [16], colored noise [17] and gene regulation network system [18]. Specifically, as the FC can describe memory and hereditary in different ways [19,20], the use of FOs gradually attracted people's attention in the study of biological engineering and genetics.

    • Uniform stability of Fractional Order Leaky Integrator Echo State Neural Network with multiple time delays

      2017, Information Sciences
      Citation Excerpt :

      The dynamic models that involve fractional derivatives and integrals are referred to as fractional-order (FO) systems. Many phenomena were found to be well modeled using fractional calculus [2,29,30]. The rapid developments in the field of FO systems during the last years had a considerable impact in science and engineering [1,8,12] and, in particular, in the study of the fractional-order neural networks (FONNs) [5,45].

    View all citing articles on Scopus
    View full text