RANS models such as K-epsilon, RNG K-epsilon, Shear-Stress Transport (SST) K-omega and BSL Reynolds-stress turbulence model were chosen for validation.
The NASA Trapwing model and DLR-F11 model were chosen to research the mesh resolution, turbulence model, transition prediction and Reynolds effect by numerical simulation.
Twelve different orthogonal cases based on the 3-D CFD model were chosen to train and validate the ANN in order to obtain the relationship between the optimal objectives and the design variables.
These criteria, along with the use of a simple surrogate sublaminate buckling model, were chosen to allow analysis of all feasible laminates in the design space without excessive computation time.
Using a computer simulation of the SD model, the variation trends from 2006 to 2030 in population, economy, water supply and demand, and pressure on the water environment were derived for Beijing, from which 12 core variables of the model were chosen as the WRCC evaluation indices.
The designer and model were chosen from Italian professional trained people.
For this experiment the linear and the Freundlich model were chosen.
In our simulation, the traffic flow and channel model were chosen to produce high channels loads and received CAM rates.
The variables tested for significance in the model were chosen for their potential to be related to mortality.
Variables included in the multivariable model were chosen according to univariate analyses, their relevance according to the literature, and the likelihood of collinearity based upon clinical judgment.
In the simulation, values of parameters entering into the model were chosen from their respective probability distributions by Latin hypercube sampling technics and were combined according to functional relationships in the model to determine NPV and IRR project outcome.
