We investigate through computational simulations with a pore network model the formation of patterns caused by erosion-deposition mechanisms. In this model, the geometry of the pore space changes dynamically as a consequence of the coupling between the fluid flow and the movement of particles due to local drag forces. Our results for this irreversible process show that the model is able to repr...

This paper presents the development artificial neural network (ANN) models for three steady state chemical engineering systems, which are 1) a crude oil distillation column for use in real time optimisation, 2) physical properties of palm oil components, and 3) pore size determination for membrane characterization. Although studies on ANN applications in chemical engineering in the literature a...

We describe a poreto reservoir-scale investigation of wettability variation and its impact on waterflooding. We use a three-dimensional pore-scale network model of a Berea sandstone to predict relative permeability and capillary pressure hysteresis. We successfully predict experimentally measured relative permeability data for the water-wet case, and demonstrate that the model captures experime...

this paper presents a hybrid approach to developing a short-term traffic flow prediction model. in thisapproach a primary model is synthesized based on neural networks and then the model structure is optimized throughgenetic algorithm. the proposed approach is applied to a rural highway, ghazvin-rasht road in iran. the obtainedresults are acceptable and indicate that the proposed approach can i...

Nerve signaling in humans and chemical sensing in bacteria both rely on the controlled opening and closing of the ion-conducting pore in pentameric ligand-gated ion channels. With the help of a multiscale simulation approach that combines mixed elastic network model calculations with molecular dynamics simulations, we study the opening and closing of the pore in Gloeobacter violaceus channel GL...

We investigate the capture of particles in soft porous media. Liquid foam constitutes a model system for such a study, allowing the radii of passage in the pore space to be tuned over several orders of magnitude by adjusting the liquid volume fraction. We show how particle capture is determined by the coupling of interstitial liquid flow and network deformation, and present a simple model of th...

A two-dimensional pore-network model based on invasion percolation is used to study the patterns obtained from the release of methane during the dissociation of methane hydrates (without including dissociation kinetics) caused by a sudden pressure reduction in the system below the hydrate equilibrium pressure. The concept of the critical gas saturation S(gc) (volume fraction of the gas phase at...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

[1] Measurements have been made of the effect of compaction on water retention, saturated hydraulic conductivity, and porosity of two English soils: North Wyke (NW) grassland clay topsoil and Broadbalk silty topsoil, fertilized inorganically (PKMg) or with farmyard manure (FYM). As expected, the FYM topsoil had greater porosity and greater water retention than PKMg topsoil, and the NW clay tops...