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In order to apply physical simulation results to natural gas hydrate reservoir parameters to provide a theoretical framework for the design of a development plan, an analytical equation method was used to obtain the similarity criteria of natural gas hydrate reservoir development by physical simulation, based on a mathematical model of natural gas hydrate development.
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The quality of the new algorithm also has been assessed by physical simulation experiments.
The potential method was studied systematically by both physical and numerical simulations based on parameters of a typical extra-heavy oil reservoir in China.
This behavior was explained by a comprehensive physical model based on metal diffusion mechanism.
For validating the results of the proposed model, an AMESim simulation model based on physical laws and the existing low-order models validated by other researchers through experiments are used to compare with the seventh-order model.
A physical model based optimization scheme by coupling MATLAB genetic algorithm (GA) and 1-D GT-Power simulation models of the Atkinson cycle engine are proposed.
The results demonstrate that simulations based on solid physical ground can reveal the complex reservoir behavior during hydraulic stimulation.
The AI approach is also beneficial whenever computational simulations based on fundamental physical models are too expensive to perform [19, 20].
Based on the conditions of the Huainan coal mining area in China, by combining physical simulation, theoretical analysis and experimental data, the subsidence mechanism induced by underground mining of thick unconsolidated soil layer was studied, and a prediction model for this condition was established (Zhou et al. 2014).
High-performance computer simulations based on advanced mathematical and physical modelling are at present a necessary tool in the development, design, and understanding of nanostructured materials.
Finally, Fukawa [ 10], using a micro-simulation model based on physical disability, rather than age, concluded that estimates of LTC expenditures for the elderly in Japan will increase rapidly, rising to 3-43-4% GPD by 2050.
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