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Different models would provide different estimates of indirect effects, and thus produce different conclusions.
In addition, a theoretically-based rational strategy for applying catalytic boundary conditions in turbulent flow models would provide a valuable design tool.
Explanatory models (also referred to as mechanistic or process models) would provide the basis for a more robust system model, as these would be based on an understanding of specific processes.
Current mathematical models would provide the same results for the six case studies presented here (two models by three wind directions), however the measured spatially averaged profiles are quite different from each other.
These enhanced wildland fire spread models would provide land managers and government agencies with better tools to prescribe preventive measures and fuels treatments before a fire, and allocate suppression resources and issue evacuation orders during a fire.
This latter is a region of great practical interest for real applications, in which the flow is chaotic but not fully turbulent, and neither steady-state simulations nor the use of turbulence models would provide satisfactory predictions.
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In this case, the model simulation would provide data for the MCDA (e.g. estimated cost ranges) while simultaneously compensate one of the biggest weaknesses of MCDA methodology, that is considering sediment management as static rather than a dynamic process.
This model would provide significant theory foundation to the design of nozzles.
An ideal model would provide a quantitative mapping between neural and perceptual effects on a trial-by-trial basis.
It was expected that the results from this microscopic model would provide input data for a macroscopic corrosion model.
Here, a good model would provide a set of properties enabling others to relate their schemes to ours.
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Justyna Jupowicz-Kozak
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