Random generation of irregular natural flow or pore networks
نویسندگان
چکیده
منابع مشابه
Numerical Simulation of Random Irregular Waves for Wave Generation in Laboratory Flumes
Understanding of wave hydrodynamics and its effects are important for engineers and scientists. Important insights may be gained from laboratory studies. Often the waves are simulated in laboratory flumes do not have the full characteristics of real sea waves. It is then necessary to present reliable methods of wave generation in wave flumes. In this paper, the results of numerically simulate...
متن کاملEvaluating transport in irregular pore networks.
A general approach for investigating transport phenomena in porous media is presented. This approach has the capacity to represent various kinds of irregularity in porous media without the need for excessive detail or computational effort. The overall method combines a generalized effective medium approximation (EMA) with a macroscopic continuum model in order to derive a transport equation wit...
متن کاملFlow Resistance in Sinuous or Irregular Channels
Part 1. The problem and the experiments. General statement-_________________________________ Flow in irregular open channels__________________. Design of experiment_____________._...______ Experimental conditions. ______________________ Experimental results._________________________ Character of the flow; deformation of the free surface. _ _ Conditions below threshold____________________ Condit...
متن کاملAn Irregular Lattice Pore Network Model Construction Algorithm
Pore network modeling uses a network of pores connected by throats to model the void space of a porous medium and tries to predict its various characteristics during multiphase flow of various fluids. In most cases, a non-realistic regular lattice of pores is used to model the characteristics of a porous medium. Although some methodologies for extracting geologically realistic irregular net...
متن کاملRandom Generation of Bayesian Networks
This paper presents new methods for generation of random Bayesian networks. Such methods can be used to test inference and learning algorithms for Bayesian networks, and to obtain insights on average properties of such networks. Any method that generates Bayesian networks must first generate directed acyclic graphs (the “structure” of the network) and then, for the generated graph, conditional ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Advances in Water Resources
سال: 2021
ISSN: 0309-1708
DOI: 10.1016/j.advwatres.2021.103936