Grand Potential, Helmholtz Free Energy, and Entropy Calculation in Heterogeneous Cylindrical Pores by the Grand Canonical Monte Carlo Simulation Method

Abstract: A Grand-canonical Monte-Carlo simulation method is investigated. Due to charge neutrality requirement of electrolyte solutions, ions must be added to or removed from the system in groups. It is then implemented to simulate solution of 1:1, 2:1 and 2:2 salts at different concentrations using the primitive ion model. We investigate how the finite size of the simulation box can influence statistical quantities of the salt system. Remarkably, the method works well down to a system as small as one salt molecule. Although the fluctuation in the statistical quantities increases as the system gets smaller, their average values remain equal to their bulk value within the uncertainty error. Based on this knowledge, the osmotic pressures of the electrolyte solutions are calculated and shown to depend linearly on the salt concentrations within the concentration range simulated. Chemical potential of ionic salt that can be used for simulation of these salts in more complex system are calculated. Keywords: GCMC, electrolyte solution simulation, primitive ion model, finite size effect.

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Influence of temperature on water adsorption / desorption hysteresis loop in disordered mesoporous silica glass by Grand Canonical Monte Carlo simulation method

Studies in Surface Science and Catalysis - Characterization of Porous Solids VII - Proceedings of the 7th International Symposium on the Characterization of Porous Solids (COPS-VII), Aix-en-Provence, France, 26-28 May 2005 ◽

10.1016/s0167-2991(07)80069-3 ◽

2007 ◽

pp. 535-541 ◽

Cited By ~ 3

Author(s):

Joël Puibasset ◽

Roland J.-M. Pellenq

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Mesoporous Silica ◽

Simulation Method ◽

Monte Carlo Simulation Method ◽

Influence Of Temperature ◽

Influence Of Temperature On ◽

Desorption Hysteresis ◽

Adsorption Desorption ◽

Grand Canonical

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Uncertainty Cost Functions in Climate-Dependent Controllable Loads in Commercial Environments

Energies ◽

10.3390/en14102885 ◽

2021 ◽

Vol 14 (10) ◽

pp. 2885

Author(s):

Daniel Losada ◽

Ameena Al-Sumaiti ◽

Sergio Rivera

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Simulation Method ◽

Electricity Sector ◽

Cost Functions ◽

Density Estimator ◽

Monte Carlo Simulation Method ◽

Commercial Building ◽

Complementary Method ◽

The Cost

This article presents the development, simulation and validation of the uncertainty cost functions for a commercial building with climate-dependent controllable loads, located in Florida, USA. For its development, statistical data on the energy consumption of the building in 2016 were used, along with the deployment of kernel density estimator to characterize its probabilistic behavior. For validation of the uncertainty cost functions, the Monte-Carlo simulation method was used to make comparisons between the analytical results and the results obtained by the method. The cost functions found differential errors of less than 1%, compared to the Monte-Carlo simulation method. With this, there is an analytical approach to the uncertainty costs of the building that can be used in the development of optimal energy dispatches, as well as a complementary method for the probabilistic characterization of the stochastic behavior of agents in the electricity sector.

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