Local Grand Canonical Monte Carlo Simulation Method for Confined Fluids

2019 ◽  
Vol 15 (12) ◽  
pp. 6944-6957 ◽  
Author(s):  
Phuong Vo ◽  
Hongduo Lu ◽  
Ke Ma ◽  
Jan Forsman ◽  
Clifford E. Woodward
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Method ◽  
Monte Carlo Simulation Method ◽  
Grand Canonical Monte Carlo ◽  
Confined Fluids ◽  
Grand Canonical

scholarly journals Size Effect in Grand-canonical Monte-Carlo Simulation of Solutions of Electrolyte

2019 ◽  
Vol 35 (2) ◽  
Author(s):  
Nguyen Viet Duc
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Size Effect ◽  
Chemical Potential ◽  
Finite Size ◽  
Simulation Method ◽  
Electrolyte Solutions ◽  
Finite Size Effect ◽  
Grand Canonical Monte Carlo ◽  
Grand Canonical

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.

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

Energies ◽  
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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