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Model inputs were obtained based on the microstructure information obtained from published literature from the National Institute of Material Science (NIMS, Japan) creep database.
Model inputs were obtained from properties of as-manufactured composite constituents (when possible), literature values of constituent materials, and quantitative microscopy.
To the extent possible, the model inputs were obtained for the specific project in Oklahoma; however, some of this data is proprietary, and thus in situations where data could not be obtained, best available estimates were used.
Other model inputs were obtained from the relevant literature.
Where local data was unavailable, model inputs were obtained from international and regional studies and from focus group discussions.
Forth, some model inputs were obtained from literature published abroad due to a lack of Chinese data, such as the utility values.
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Responses for variable reference inputs are obtained.
Fuel and topography inputs are obtained from LANDFIRE.
These inputs are obtained from neural networks, i.e., scaled from 0 to 1.
The approach is based on utilization of pairs of virtual leaders whose control inputs are obtained in a single optimization process using model predictive control (MPC) methodology.
Information on team inputs was obtained from the basic team questionnaire and from individual questionnaires.
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