相关论文: Mathematical Modeling on Open Limestone Channel
We explore progress in understanding the behaviour of cation conducting glasses, within the context of an evolving ''dynamic structure model'' (DSM). This behaviour includes: in single cation glasses a strong dependence of ion mobility on…
This work describes a new 1D hybrid approach for modeling atmospheric pressure discharges featuring complex chemistry. In this approach electrons are described fully kinetically using Particle-In-Cell/Monte-Carlo (PIC/MCC) scheme, whereas…
Neural network (NN) model chemistries (MCs) promise to facilitate the accurate exploration of chemical space and simulation of large reactive systems. One important path to improving these models is to add layers of physical detail,…
Water scarcity is a reality in our world, and scenarios predicted by leading scientists in this area indicate that it will worsen in the next decades. However, new technologies based in low-cost seawater desalination can prevent the worst…
The paper presents a model for liquid uranium dioxide, obtained by improving a simplified ionic model, previously adopted to describe the equation of state of this substance [1]. A "chemical picture" is used for liquid UO2 of stoichiometric…
The mass physical and dynamic properties of marine mud deposits are a function of the interaction among a maximum of four sediment Phases as follows: (1) clay mineral solids that often include silt and sand size particles of different…
Rapid solidification leads to unique microstructural features, where a less studied topic is the formation of various crystalline defects, including high dislocation densities, as well as gradients and splitting of the crystalline…
Carbonated water flooding (CWI) increases oil production due to favorable dissolution effects and viscosity reduction. Accurate modeling of CWI performance requires a simulator with the ability to capture the true physics of such process.…
Calcium oxalate crystals are the most common biominerals found in plants. They also make their presence known as painful kidney stones in humans and animals. Their function in plants is extraordinarily versatile and encompasses calcium…
Bitumen extraction for the production of synthetic crude oil in Canada's Athabasca Oil Sands industry has recently come under spotlight for being a significant source of greenhouse gas emission. A major cause of concern is methane, a…
Kinetic Monte Carlo (KMC) is a powerful method for simulation of diffusion processes in various systems. The accuracy of the method, however, relies on the extent of details used for the parameterization of the model. Migration barriers are…
Pitting corrosion is a much-studied and technologically relevant subject. However, the fundamental mechanisms responsible for the breakdown of the passivating oxide layer are still subjects of debate. Chloride anions are known to accelerate…
We develop a lattice-based Monte Carlo simulation method for charged mixtures capable of treating dielectric heterogeneities. Using this method, we study oil-water mixtures containing an antagonistic salt, with hydrophilic cations and…
Anti-money laundering (AML) actions and measurements are among the priorities of financial institutions, for which machine learning (ML) has shown to have a high potential. In this paper, we propose a comprehensive and systematic approach…
Mathematical modeling is an important theoretical tool which provides researchers with quantification of the permeability of dialyzing systems in renal replacement therapy. In the paper we provide a short review of the most successful…
Displacement experiments carried out in microfluidic porous media analogs show that reduced surface tension leads to a more stable displacement, opposite to the process in Hele-Shaw cells where surface tension stabilizes the displacement of…
Combining machine learning (ML) with computational fluid dynamics (CFD) opens many possibilities for improving simulations of technical and natural systems. However, CFD+ML algorithms require exchange of data, synchronization, and…
The alkali metal ions in aqueous electrolyte solutions have strong influence on the surrounding network structure of water formed through hydrogen bonds. The extent of ionic perturbation to the structure of water depends on the nature of…
Dissipative particle dynamics (DPD) and multi-particle collision (MPC) dynamics are powerful tools to study mesoscale hydrodynamic phenomena accompanied by thermal fluctuations. To understand the advantages of these types of mesoscale…
Modeling hydrogen diffusion and its absorption in traps is a fundamental first step towards the understanding and prediction of hydrogen embrittlement. In this study, a multiscale approach which includes DFT simulations, OkMC, and…