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Stochastic networks

A full analysis of intra-particle and intra-pellet porosity based on stochastic networks remains to be completed 11). For the present, we seek the application of a stochastic network to the intra-particle spaces based upon a discrimination of this porosity via a parallel bundle analysis of the results of Figure 2. [Pg.46]

Parallel bundles of pores (in which all pores of a given size or radius are bound to be equally accessible) are a highly unrealistic structural configuration. Stochastic networks are arrangements of pores into fiilly accessible inter-connected frameworks within which pores are assumed to be distributed randomly. In this way, the size of any pore is taken to be independent of its neighbours. A network may then be constructed to obey any stipulated distribution function by assigning pores from the distribution randomly to positions in the network. Stochastic networks are an attempt to incorporate the elements of randomness and chaos which are implicit to many porous media, in such a way as to retain a feasible computability. Modem computers (and now micro-computers) can readily compute mercury porosimetry into networks comprised of up to millions of pores 11.15). [Pg.46]

R. Mann. J. Almeida, and M. Mugerwa, A random pattern extension to the stochastic network pore model, Chem. Eng. Sci. 47 2663 (1986). [Pg.643]

A.E. Forrest, Stochastic network modelling of convection and diffusion in porous catalysts, M.Sc. thesis, UMIST (1994). [Pg.643]

Vol. 1829 E. Altman, B. Gaujal, A. Hordijk, Discrete-Event Control of Stochastic Networks Multimodularity and R ularity. XIV, 313 p, 2003. [Pg.466]

University, Germany, in collaboration with SAP AG. It is the key component of SAP R/3 s modeling concepts for business engineering and customizing. It is based on the concepts of stochastic networks and Petri nets. Simple versions exclude conditions and messages and include only E(vent)/A(ction) illustrations. [Pg.291]

Kelly, F. P. (1979), Reversibility and Stochastic Networks, John Wiley Sons, New York. [Pg.2171]

Williams, R. J. (1996), On the Approximation of Queueing Networks in Heavy Traffic, in Stochastic Networks Theory and Applications, P. P. Kelly, S. Zachary, and 1. Zeidins, Eds, Oxford University Press, Oxford, pp. 35-56. [Pg.2171]

An algorithm and a discrete-event solver have been developed for repairable stochastic networks with merging flows. The solver provides loss reporting, handles very large networks, multiple failure modes, multi-commodity flows, overlapping failures. [Pg.125]

Stochastic Network Model for the Pore Phase 677 where r is an intercept vector allowing for the possibiHty of non-zero mean... [Pg.677]

One of the few successful attempts, by investigators other than Clarke, to utilize stochastic network analysis was carried out by Eiswirth et al. (1991), who divide the known mechanisms of chemical oscillators into four categories two based on the positive feedback loop, and a threefold division of one of these according to the negative feedback loop. The structure of the classification scheme resembles somewhat the results of the approach described in section 5.4.2, but the analysis is considerably more detailed and rigorous. [Pg.103]

Hidden Markov models (HMMs) are constructed by using concepts such as conditional probability. They are used in a variety of applications, and are classified under a useful class of probabilistic models. HMMs are a special case of neural networks, stochastic networks, and Bayesian networks. The dyad probabilities as a function of reactor monomer composition are given in Table 11.1. The probabilities are calculated using Equations (11.8 11.10). [Pg.245]

The remarkable properties of electrospun CNTs nanocomposites continue to draw attention in the development of multifunctional properties of nanostructures for many applications.. Multiscale model for calculation macroscopic mechanical properties for fibrous sheet is developed. Effective properties of the fiber at microscale determined by homogenization using modified shear-lag model, while on the second stage the point-bonded stochastic fibrous network at macroscale replaced by multilevel finite beam element net. Elastic modulus and Poisson s ratio dependence on CNT volume concentration are calculated. Effective properties fibrous sheet as random stochastic network determined numerically. We conclude that an addition of CNTs into the polymer solution results in significant improvement of rheological and structural properties. [Pg.38]

The theory of cooperative capillary condensation in stochastic network of channels is developed. The corresponding mathematical problem is reduced to a three-component bond percolation problem. At a given relative pressure x in the network of channels three types of bonds are distinguished subundercritlcal channels of equivalent size pp (x)- Here functions p+(x) and p (x) determine the equivalent sizes of pores in which the capillary condensation and desorption are observed at relative pressure x ... [Pg.70]


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