Stochastic Modelling of Particle Segregation in a Horizontal Drum Mixer

1992 ◽  
Vol 57 (10) ◽  
pp. 2100-2112 ◽  
Author(s):  
Vladimír Kudrna ◽  
Pavel Hasal ◽  
Andrzej Rochowiecki
Keyword(s):  
Differential Equation ◽  
Diffusion Coefficient ◽  
Stochastic Model ◽  
Diffusion Process ◽  
Stochastic Modelling ◽  
Solid Particles ◽  
Kolmogorov Equation ◽  
Particle Segregation ◽  
Drum Mixer ◽  
Horizontal Drum

A process of segregation of two distinct fractions of solid particles in a rotating horizontal drum mixer was described by stochastic model assuming the segregation to be a diffusion process with varying diffusion coefficient. The model is based on description of motion of particles inside the mixer by means of a stochastic differential equation. Results of stochastic modelling were compared to the solution of the corresponding Kolmogorov equation and to results of earlier carried out experiments.

Description of segregation in a horizontal drum mixer by use of the diffusion equation

1988 ◽  
Vol 53 (4) ◽  
pp. 771-787 ◽  
Author(s):  
Vladimír Kudrna ◽  
Andrzej Rochowiecki
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Equation ◽  
Two Dimensions ◽  
Solid Particles ◽  
Axial Segregation ◽  
Variable Diffusion Coefficient ◽  
Drum Mixer ◽  
Forward Diffusion ◽  
Variable Diffusion ◽  
Horizontal Drum

An attempt has been made to describe the axial segregation of solid particles of two dimensions in a horizontal drum mixer. For this purpose the Kolmogorov's forward diffusion equation with variable diffusion coefficient and zero drift velocity was used. For the case of "pure" segregation this approach has given good results.

Incorporating concepts from physical theory into stochastic modelling of urban runoff pollution

1998 ◽  
Vol 37 (1) ◽  
pp. 179-185
Author(s):  
Morten Grum
Keyword(s):  
Stochastic Model ◽  
Continuous Time ◽  
Measurement Errors ◽  
Physical Theory ◽  
Oxygen Demand ◽  
Stochastic Modelling ◽  
Urban Runoff ◽  
Primary Input ◽  
Deterministic Modelling ◽  
Runoff Pollution

On evaluating the present or future state of integrated urban water systems, sewer drainage models, with rainfall as primary input, are often used to calculate the expected return periods of given detrimental acute pollution events and the uncertainty thereof. The model studied in the present paper incorporates notions of physical theory in a stochastic model of water level and particulate chemical oxygen demand (COD) at the overflow point of a Dutch combined sewer system. A stochastic model based on physical mechanisms has been formulated in continuous time. The extended Kalman filter has been used in conjunction with a maximum likelihood criteria and a non-linear state space formulation to decompose the error term into system noise terms and measurement errors. The bias generally obtained in deterministic modelling, by invariably and often inappropriately assuming all error to result from measurement inaccuracies, is thus avoided. Continuous time stochastic modelling incorporating physical, chemical and biological theory presents a possible modelling alternative. These preliminary results suggest that further work is needed in order to fully appreciate the method's potential and limitations in the field of urban runoff pollution modelling.

CALCULATION OF PARAMETERS OF A DIFFUSION PROCESS WITH A CONCENTRATION-DEPENDENT DIFFUSION COEFFICIENT

2020 ◽  
Author(s):  
Е.Г. СТЕПАНОВА ◽  
Б.Ю. ОРЛОВ ◽  
М.А. ПЕЧЕРИЦА
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Process ◽  
Transfer Problem ◽  
Extraction Process ◽  
Electrochemical Activation ◽  
Calculation Of Parameters ◽  
Sucrose Solutions ◽  
Diffusion Transfer ◽  
Preliminary Preparation ◽  
Series Of Experiments

Приведено решение нелинейной задачи диффузионного переноса с учетом предварительной подготовки экстрагента методом электрохимической активации. Для расчета параметров процесса использована капиллярная модель. Показаны результаты расчета симплекса концентраций от числа Фурье Е = f(Fo). Представлены экстракционные кривые в чистых сахарных растворах с различными видами экстрагентов и температурами процесса 20 и 70°С. Аналитическая обработка кинетических кривых позволила определить основные параметры диффузионного процесса экстрагирования сахарозы. Проведен полный двухфакторный эксперимент lnЕ= f(С; τ), получено уравнение регрессии и построена поверхность отклика, которая исследована методом неопределенных множителей Лагранжа с получением оптимальных значений для проведенной серии опытов С = 15,4% и τ = 750 с. Выполненные расчеты позволяют моделировать внутренний массоперенос экстрагирования концентрационно-зависимого коэффициента диффузии сахарозы при наложении электрического поля при обработке экстрагента. We present a solution to the nonlinear diffusion transfer problem, taking into account the preliminary preparation of the extractant by electrochemical activation (ECHA). A capillary model is used to calculate the process parameters. The results of calculating the concentration simplex from the Fourier number E= f(Fo) are shown. The description of the laboratory installation, the method of the process, and the modes of ECHA preparation of extractants are given. Extraction curves in pure sucrose solutions with different types of extractants and process temperatures are presented. Analytical processing of the kinetic curves of the sucrose extraction process for the regular stage of the process allowed us to determine the main parameters of the diffusion process. A complete two-factor experiment lnE= f(C; τ) was performed. A regression equation was obtained and the response surface was constructed, which was studied by the method of indeterminate Lagrange multipliers to obtain optimal values for the series of experiments С = 15,4% and τ = 750 s. The calculations performed allow us to model the internal mass transfer of extraction of the concentration-dependent sucrose diffusion coefficient when an electric field is applied during processing of the extractant.

An applied mathematics perspective on stochastic modelling for climate

2008 ◽  
Vol 366 (1875) ◽  
pp. 2427-2453 ◽  
Author(s):  
Andrew J Majda ◽  
Christian Franzke ◽  
Boualem Khouider
Keyword(s):  
Stochastic Model ◽  
General Circulation ◽  
Applied Mathematics ◽  
Low Frequency ◽  
Lattice Models ◽  
Stochastic Modelling ◽  
General Circulation Models ◽  
Teleconnection Patterns ◽  
Slowing Down ◽  
Low Dimensional

Systematic strategies from applied mathematics for stochastic modelling in climate are reviewed here. One of the topics discussed is the stochastic modelling of mid-latitude low-frequency variability through a few teleconnection patterns, including the central role and physical mechanisms responsible for multiplicative noise. A new low-dimensional stochastic model is developed here, which mimics key features of atmospheric general circulation models, to test the fidelity of stochastic mode reduction procedures. The second topic discussed here is the systematic design of stochastic lattice models to capture irregular and highly intermittent features that are not resolved by a deterministic parametrization. A recent applied mathematics design principle for stochastic column modelling with intermittency is illustrated in an idealized setting for deep tropical convection; the practical effect of this stochastic model in both slowing down convectively coupled waves and increasing their fluctuations is presented here.

scholarly journals The ruin problem for a Wiener process with state-dependent jumps

2020 ◽  
Vol 16 (1) ◽  
pp. 13-23
Author(s):  
M. Lefebvre
Keyword(s):  
Differential Equation ◽  
Ordinary Differential Equation ◽  
Diffusion Process ◽  
Wiener Process ◽  
Jump Diffusion ◽  
Moment Generating Function ◽  
Continuous Part ◽  
State Dependent ◽  
The Moment ◽  
First Time

AbstractLet X(t) be a jump-diffusion process whose continuous part is a Wiener process, and let T (x) be the first time it leaves the interval (0,b), where x = X(0). The jumps are negative and their sizes depend on the value of X(t). Moreover there can be a jump from X(t) to 0. We transform the integro-differential equation satisfied by the probability p(x) := P[X(T (x)) = 0] into an ordinary differential equation and we solve this equation explicitly in particular cases. We are also interested in the moment-generating function of T (x).

Optical studies on the turbulent motion of solid particles in a pipe flow

1991 ◽  
Vol 231 ◽  
pp. 665-688 ◽  
Author(s):  
James B. Young ◽  
Thomas J. Hanratty
Keyword(s):  
Diffusion Coefficient ◽  
Particle Velocity ◽  
Turbulent Diffusion ◽  
Slip Velocity ◽  
Rate Of Change ◽  
Solid Particles ◽  
Mean Square ◽  
Turbulent Diffusion Coefficient ◽  
Fluid Turbulence ◽  
The Mean

An extension of an axial viewing optical technique (first used by Lee, Adrian & Hanratty) is described which allows the determination of the turbulence characteristics of solid particles being transported by water in a pipe. Measurements are presented of the mean radial velocity, the mean rate of change radial velocity, the mean-square of the radial and circumferential fluctuations, the Eulerian turbulent diffusion coefficient, and the Lagrangian turbulent diffusion coefficient. A particular focus is to explore the influence of slip velocity for particles which have small time constants. It is found that with increasing slip velocity the magnitude of the turbulent velocity fluctuations remains unchanged but that the turbulent diffusivity decreases. The measurements of the average rate of change of particle velocity are consistent with the notion that particles move from regions of high fluid turbulence to regions of low fluid turbulence. Measurements of the root-mean-square of the fluctuations of the rate of change of particle velocity allow an estimation of the average magnitude of the particle slip in a highly turbulent flow, which needs to be known to analyse the motion of particles not experiencing a Stokes drag.

The Smoluchowski–Kramers approximation for the stochastic Liénard equation by mean-field

1991 ◽  
Vol 23 (2) ◽  
pp. 303-316 ◽  
Author(s):  
Kiyomasa Narita
Keyword(s):  
Differential Equation ◽  
Stochastic Differential Equation ◽  
Diffusion Process ◽  
Langevin Equation ◽  
Mean Field ◽  
Two Dimensional ◽  
Large Parameter ◽  
Rigorous Evaluation ◽  
One Dimensional ◽  
Limit Diffusion

The oscillator of the Liénard type with mean-field containing a large parameter α < 0 is considered. The solution of the two-dimensional stochastic differential equation with mean-field of the McKean type is taken as the response of the oscillator. By a rigorous evaluation of the upper bound of the displacement process depending on the parameter α, a one-dimensional limit diffusion process as α → ∞is derived and identified. Then our result extends the Smoluchowski–Kramers approximation for the Langevin equation without mean-field to the McKean equation with mean-field.

Numerical analysis of the convection and diffusion of solutes to roots

Soil Research ◽  
1967 ◽  
Vol 5 (2) ◽  
pp. 149 ◽  
Author(s):  
JB Passioura ◽  
MH Frere
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Porous Medium ◽  
Diffusion Coefficient ◽  
Numerical Analysis ◽  
Average Concentration ◽  
Soil System ◽  
Dry Soil ◽  
The One ◽  
And Diffusion

A numerical method is given for solving a partial differential equation describing the radial movement of solutes through a porous medium to a root. Computer programmes based on the method were prepared and used to obtain solutions of the equation for an idealized root-soil system in which a solute is transported to the root by convection but is not taken up by the root. Various patterns of water uptake were considered, the most complex being a diurnally varying uptake from soil in which the water content is decreasing. The solutions suggest that the maximum build-up of solute at the surface of a root is trivial if the root is growing in a medium such as agar, in which the diffusion coefficient of the solute is high, but may be considerable, with a concentration up to 10 times higher than the average concentration in the soil solution, when the root is growing in a fairly dry soil. The application of the method to systems other than the one considered in detail is discussed.

A diffusion process model for the optimal investment strategies of an R & D project

1980 ◽  
Vol 17 (03) ◽  
pp. 646-653 ◽  
Author(s):  
Dror Zuckerman
Keyword(s):  
Differential Equation ◽  
Diffusion Process ◽  
Process Model ◽  
Compound Poisson Process ◽  
Optimal Investment ◽  
Investment Strategies ◽  
Diffusion Parameters ◽  
Decision Variables ◽  
Expenditure Rate ◽  
Linear Differential

In this article we examine an R &amp; D project in which the project status changes according to a diffusion process. The decision variables include a resource expenditure strategy and a stopping policy which determines when the project should be terminated. The drift and the diffusion parameters of the project status process are assumed to be functions of the resource expenditure rate. The terminal reward from the project is a non-decreasing function of the project status. Our purpose is to select optimal investment strategies under the discounted return criterion. The value of the project is shown to be a solution of a second order, non-linear differential equation. Finally, we derive the optimal investment strategies for an R &amp; D project in which the project status changes according to a non-homogeneous compound Poisson process by using diffusion approximation.

Sign in / Sign up

Export Citation Format

Share Document