Interval-stochastic thermal processes in electronic systems: Modeling in practice

Mathematical and computer modeling of thermal processes, applied presently in thermal design of electronic systems, is based on the assumption that the factors determining the thermal processes are completely known and uniquely determined, that is, they are deterministic. Meanwhile, practice shows that the determining factors are of indeterminate interval-stochastic character. Moreover, thermal processes in electronic systems are nonstationary and nonlinearly depend on both the stochastic determining factors and the temperatures of electronics elements and environment. At present, the literature does not present methods of mathematical modeling of nonstationary, stochastic, nonlinear, interval-stochastic thermal processes in electronic systems to model thermal processes, which satisfy all the above-listed requirements to modeling adequacy. The present paper develops a method of mathematical and computer modeling of the nonstationary interval-stochastic nonlinear thermal processes in electronic systems. The method is based on obtaining equations describing the dynamics of time variation of statistical measures (expectations, variances, covariances) of temperature of electronic systemelements with given statistical measures of the initial interval-stochastic determining factors. A practical example of applying the developed approach to a the real electronic system is given.     

Responses of discretized systems under narrow band nonstationary random excitations. Part 2: nonlinear problems

In a companion paper, the extended stochastic central difference (ESCD) method was presented for computation of responses of linear multi-degrees-of-freedom (mdof) systems under narrow band stationary and nonstationary random excitations. The present paper is concerned with the generalization of the ESCD method for computation of nonlinear mdof systems. The generalization is based on a combination of the ESCD method with statistical linearization (SL) technique, modified adaptive time scheme (ATS), and time coordinate transformation (TCT). Unlike the conventional SL technique, the generalized ESCD method is applicable to mdof systems with large nonlinearities. Comparison is made of the computed results applying the generalized ESCD method to those obtained by the Monte Carlo simulation (MCS). Excellent agreements were obtained. It was observed that the proposed method is very efficient compared with the MCS.     

Probabilistic evaluation of interconnectable capacity for wind power generation

We propose a novel framework for probabilistic evaluation of interconnectable capacity for wind power generation. This is based on mathematical modeling of load frequency control systems, which captures their nonlinear (saturation and rate limiting) dynamical characteristics, and stochastic uncertainty of wind power output deviation. The method called stochastic linearization is used to analyze resulting power quality. The effectiveness of the proposed method is examined by numerical simulation.     

On the theory of nonlinear thermal conductivity

A nonlinear differential equation of thermal conductivity is derived phenomenologically from the general principles of construction of functional Q invariant to the inversion operation I(r →–r), and the temperature evolution dynamics is analyzed in the nonstationary case. The proposed method makes it possible to reveal some general regularities in the physical behavior of such systems for describing irreversible phenomena in self-organization processes. It is noted that an analogous situation may take place, for example, in strongly inhomogeneous structures with stochastic internal heat fluxes.     

Cellular Biology in Terms of Stochastic Nonlinear Biochemical Dynamics: Emergent Properties,Isogenetic Variations and Chemical System Inheritability

Based on a stochastic, nonlinear, open biochemical reaction system perspective, we present an analytical theory for cellular biochemical processes. The chemical master equation (CME) approach provides a unifying mathematical framework for cellular modeling. We apply this theory to both self-regulating gene networks and phosphorylation-dephosphorylation signaling modules with feedbacks. Two types of bistability are illustrated in mesoscopic biochemical systems: one that has a macroscopic, deterministic counterpart and another that does not. In certain cases, the latter stochastic bistability is shown to be a “ghost” of the extinction phenomenon. We argue the thermal fluctuations inherent in molecular processes do not disappear in mesoscopic cell-sized nonlinear systems; rather they manifest themselves as isogenetic variations on a different time scale. Isogenetic biochemical variations in terms of the stochastic attractors can have extremely long lifetime. Transitions among discrete stochastic attractors spend most of the time in “waiting”, exhibit punctuated equilibria. It can be naturally passed to “daughter cells” via a simple growth and division process. The CME system follows a set of nonequilibrium thermodynamic laws that include non-increasing free energy F(t) with external energy drive Q _hk ≥0, and total entropy production rate e _p =−dF/dt+Q _hk ≥0. In the thermodynamic limit, with a system’s size being infinitely large, the nonlinear bistability in the CME exhibits many of the characteristics of macroscopic equilibrium phase transition.     

A Refutation of Finite-State Language Models through Zipf’s Law for Factual Knowledge

We present a hypothetical argument against finite-state processes in statistical language modeling that is based on semantics rather than syntax. In this theoretical model, we suppose that the semantic properties of texts in a natural language could be approximately captured by a recently introduced concept of a perigraphic process. Perigraphic processes are a class of stochastic processes that satisfy a Zipf-law accumulation of a subset of factual knowledge, which is time-independent, compressed, and effectively inferrable from the process. We show that the classes of finite-state processes and of perigraphic processes are disjoint, and we present a new simple example of perigraphic processes over a finite alphabet called Oracle processes. The disjointness result makes use of the Hilberg condition, i.e., the almost sure power-law growth of algorithmic mutual information. Using a strongly consistent estimator of the number of hidden states, we show that finite-state processes do not satisfy the Hilberg condition whereas Oracle processes satisfy the Hilberg condition via the data-processing inequality. We discuss the relevance of these mathematical results for theoretical and computational linguistics.     

Approximate Gaussian representation of evolution equations I. Single degree of freedom nonlinear equations

We have developed a generalization of the method of statistical linearization to enable us to describe transient and other nonstationary phenomena obeying stochastic nonlinear differential equations. This approximation technique provides an optimal Gaussian representation with time-dependent parameters. The algorithm specifies a set of ordinary differential equations for the Gaussian parameters in terms of the time-dependent average nonlinearities. We apply the general formalism developed herein for single degree of freedom dissipative systems to a particular example.     

On the theory of metastable states

It is shown that the stationary states of stochastic systems are stable. Therefore one cannot use the stationary probability distributions for describing the stochastic systems in metastable states. It is shown that the nonstationary stochastic processes can have sample paths with stationary parts. It is proposed to consider these stationary parts as the metastable states.     

Numerical modeling of high-temperature heat and mass transfer at laser nitriding of titanium

Numerical modeling of the processes of heat and mass transfer under the action of laser radiation on a titanium surface in a nitrogen medium has been performed. The problem statement includes a system of two-dimensional nonstationary nonlinear equations of heat conduction and diffusion with the corresponding initial and boundary conditions. The problem was solved taking into account the laser beam motion. The character of the distribution of the alloying elements in the zone of laser heating has been investigated. The results obtained make it possible to conclude that the concentrations of the alloying component are essentially inhomogeneous.     

Nonstationary stochastic resonance viewed through the lens of information theory

In biological systems, information is frequentlytransferred with Poisson like spike processes (shot noise) modulatedin time by information-carrying signals. How then to quantifyinformation transfer by such processes for nonstationary inputsignals of finite duration? Is there some minimal length of theinput signal duration versus its strength? Can such signals bebetter detected when immersed in noise stemming from thesurroundings by increasing the stochastic intensity? These are somebasic questions which we attempt to address within an analyticaltheory based on the Kullback-Leibler information concept applied torandom processes.     

Polynomial chaos expansions for optimal control of nonlinear random oscillators

The polynomial chaos decomposition of stochastic variables and processes is implemented in conjunction with optimal polynomial control of nonlinear dynamical systems. The procedure is demonstrated on a base-excited system whereby ground motion is modeled as a stochastic process with a specified correlation function and is approximated by its Karhunen-Loeve expansion. An adaptive scheme for stochastic approximation with polynomial chaos bases is proposed which is based on a displacement-velocity norm and is applied to the identification of phase orbits of nonlinear oscillators. This approximation is then integrated in the design of an optimal polynomial controller, allowing for the efficient estimation of statistics and probability density functions of quantities of interest. Numerical investigations are carried out employing the polynomial chaos expansions and the Lyapunov asymptotic stability condition based control policy. The results reveal that the performance, as gaged by probabilistic quantities of interest, of the controlled oscillators is greatly improved. A comparative study is also presented against the classical stochastic optimal control, whereby statistical linearization based LQG is employed to design the optimal controller. It is remarked that the proposed polynomial chaos expansion is a preferred approach to the optimal control of nonlinear random oscillators.     

Stochastic joint time–frequency response analysis of nonlinear structural systems

A novel approximate analytical approach for determining the response evolutionary power spectrum (EPS) of nonlinear/hysteretic structural systems subject to stochastic excitation is developed. Specifically, relying on the theory of locally stationary processes and utilizing a recently proposed representation of non-stationary stochastic processes via wavelets, a versatile formula for determining the nonlinear system response EPS is derived; this is done in conjunction with a stochastic averaging treatment of the problem and by resorting to the orthogonality properties of harmonic wavelets. Further, the nonlinear system non-stationary response amplitude probability density function (PDF), which is required as input for the developed approach, is determined either by utilizing a numerical path integral scheme, or by employing a time-dependent Rayleigh PDF approximation technique. A significant advantage of the approach relates to the fact that it is readily applicable for treating not only separable but non-separable in time and frequency EPS as well. The hardening Duffing and the versatile Preisach (hysteretic) oscillators are considered in the numerical examples section. Comparisons with pertinent Monte Carlo simulations demonstrate the reliability of the approach.     

Mathematical problems of modeling stochastic nonlinear dynamic systems

The purpose of this report is to introduce the engineer to the area of stochastic differential equations, and to point out the mathematical techniques and pitfalls in this area. Topics discussed include continuous-time Markov processes, the Fokker-Planck-Kolmogorov equations, the Ito and Stratonovich stochastic calculi, and the problem of modeling physical systems.     

An electronic technique for measuring phase space dimension from chaotic time series

An instrument for determining the number of independent variables involved in chaotic dynamical systems is described. The elaborated technique allows to obtain this measure in real time from a single observable. It has been used for the quantitative characterization of strange attractors underlying chaotic oscillations in anumber of nonlinear electronic circuits. This technique is found to be fairly insensitive to stochastic noise inherent in real experimental systems.     

The theory of nonstationary thermophoresis of a solid spherical particle

The theory of nonstationary thermophoresis of a solid spherical particle in a viscous gaseous medium is presented. The theory is constructed on the solutions of fluid-dynamics and thermal problems, each of which is split into stationary and strictly nonstationary parts. The solution of the stationary parts of the problems gives the final formula for determining the stationary component of the thermophoretic velocity of this particle. To determine the nonstationary component of the thermophoretic velocity of the particle, the corresponding formula in the space of Laplace transforms is derived. The limiting value theorems from operational calculus are used for obtaining the dependence of the nonstationary component of the thermophoretic velocity of the spherical particle on the strictly nonstationary temperature gradient for large and small values of time. The factors determining the thermophoretic velocity of the particle under investigation are determined.     

Dynamical chaos in the Lorentz lattice gas

This paper provides an introduction to the applications of dynamical systems theory to nonequilibrium statistical mechanics, in particular to a study of nonequilibrium phenomena in Lorentz lattice gases with stochastic collision rules. Using simple arguments, based upon discussions in the mathematical literature, we show that such lattice gases belong to the category of dynamical systems with positive Lyapunov exponents. This is accomplished by showing how such systems can be expressed in terms of continuous phase space variables. Expressions for the Lyapunov exponent of a one-dimensional Lorentz lattice gas with periodic boundaries are derived. Other quantities of interest for the theory of irreversible processes are discussed.     

Responses of discretized systems under narrow band nonstationary random excitations. Part 1: linear problems

The extended stochastic central difference (ESCD) method is proposed as a viable alternative for computing linear responses of discretized multi-degrees-of-freedom (mdof) systems under narrow band stationary and nonstationary random disturbances. The method provides a means of controlling the center frequencies and bandwidths of narrow band stationary and nonstationary random excitation processes. It is suitable for larger-scale random response analysis of complicated structures idealized by the finite element method. Its additional important feature is that application of normal mode or complex normal mode analysis or direct numerical integration algorithms such as the fourth-order Runge-Kutta scheme is not required. Examples, including one of flow-induced vibration of a pipe containing a moving fluid are included to demonstrate: (1) the capability of the proposed method and difference between responses of discretized systems under narrow band and wide band random excitations, and (2) its accuracy and efficiency by way of comparison to the Monte Carlo simulation data. Generalization of the ESCD method for computation of responses of nonlinear mdof systems is presented in a companion paper.     

Diffractive optical elements with a double identical microstructure for determination of statistical parameters of random phase objects

Physical processes of interference pattern formation in partially coherent and coherent optical systems containing special diffractive optical elements with a double identical microstructure are studied in the case when a thin scattering object is present in the optical system. Methods for determining the spatial coherence function of the light field, the autocorrelation function of transmission of random phase screens, and the statistical parameters of the screens are considered.