A model, utilizing inputs from published studies, was constructed.
The DEX model operated with linguistic statements derived from numerical values, while the fuzzy model utilized numeric input.
The techno-economic model utilizes reservoir simulation inputs and results such as production rate and composition, injection fluid rate and composition, and bottomhole pressure to provide detailed costs and revenue of injection, production, and CO2 recycling, according to defined scenarios.
Inasmuch as the Pareto-optimal MGGP model utilizes a lower number of input parameters to yield comparatively higher performance than the conventional regression models, it can be used as a parsimonious model for self-cleansing design of large sewers in practice.
The model utilizes electrochemical, metallurgical, and physical inputs.
One model utilizes the source line of code as input variable to estimate the effort; while the second model utilizes the inputs, outputs, files, and user inquiries to estimate the function points.
We developed a model utilizing publicly available inputs, and tested the robustness of the outcome estimates in multivariate analyses.
First, the dynamic model utilizes kinetic equations to predict the substrate uptakes and additional flux constraints which are then used as inputs for the stoichiometric model analysis.
Our model utilized monthly discontinuation rates.
To predict the CO2 production rate and CO2 capture level, eight parameters in the process were utilized as model input variables: inlet gas flow rate, CO2 concentration in inlet flow gas, inlet gas temperature, inlet gas pressure, lean solvent flow rate, lean solvent temperature, lean loading and reboiler duty.
