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Numerical simulation is a process made up of the six steps summarized in Table 1. These are: (1) identify the objectives of the modeling study, (2) construct a geometrical domain and discretization of the system of interest (i.e. meshing or grid generation), (3) build the simulation model by selecting physical phenomena and applying various physical data (e.g. material properties, boundary conditions), (4) choose numerical parameters to execute the calculations and effect a solution, (5) post‐process the simulation results, and (6) document them and archive the modeling data. Each of these is important, and some are mutually dependent on one another.

Table 1 Summary of simulation process steps.

Step	Process	Description
1	Objective	Identify needed results – quantitative summaries – qualitative insights – comparisons.
2	Geometry and mesh	Construct CAD model and discretize into elements or cells.
3	Physical conditions	Assign materials and properties to regions, boundary conditions, sources, and other abstractions to account for physical behavior. (Can affect Step 2)
4	Solve	Select solver options, such as under‐relaxation coefficients, gradient estimation methods, convergence criteria, etc., and solve. (Can affect Step 2 or 3)
5	Post‐process	Review computed results, prepare contour plots, vector plots, flow pathlines, and other computed values from results.
6	Document and archive	Prepare presentation or report and store all information in appropriate database.

The first step of identifying the objective cannot be overemphasized. It will drive the rest of the process and will lead to key assumptions to be applied along the way. The complexity of the model or its level of detail can very much depend on its purpose. Thus, the second step of geometrically defining the computational domain and discretizing it very much relies on the modeling objectives and requires good judgment in order to resolve the details of interest without adding human and computational effort that are not key to the objectives sought. Therefore, it is crucial to determine a good balance between model accuracy and the effort needed to reach a solution.

Generating a mesh is often the main bottleneck in the modeling process, as it is often rendered difficult by geometrical details which have a negligible effect on the results of interest. Meshing software with de‐featuring options may be helpful, but good guidance at the outset of the modeling project is very valuable. This point is well illustrated in Figure 1a where are sketched two ways to represent a burner block used in a forehearth (i.e. the heated canal lined with refractory material separating the melting furnace from the forming machinery). The geometry shown in Figure 1a more accurately represents the actual shape of the burner block, but it yields highly skewed and undesirable mesh cells. The low‐quality mesh is the result of three surfaces, one of which is curved, intersecting at a point, which will either cause divergence of the computational algorithm or lead to spurious results. Extreme grid refinement thus is required to achieve acceptable mesh quality. An alternative that alleviates the meshing problem, without having a significant effect on computed results, is shown in Figure 1b.

Sound engineering judgment is also needed to build the simulation model, the third step of the simulation process. Many decisions are required. For example, can symmetry be assumed? Another example is linked to the steadiness of the process and whether an assumption of steady state is justified or if transient conditions must be considered. Treating fundamental properties like viscosity (Chapter 4.1) and thermal conductivity (Chapter 4.5) as constant or temperature‐dependent represents another decision that must be made by the numerical analyst. Sometimes, it is advantageous to use constant properties to establish an initial solution, followed by another solution attempt with variable properties. This strategy has been used effectively where the initial constant property solution serves as the initial estimate for the more accurate, variable property simulation. It is recommended to begin a simulation project erring on the side of simplicity, and then to add complexity in subsequent simulations.

It is also the case that the physical modeling decisions will affect the geometrical and meshing procedures. For example, a perforated plate through which a fluid flows could require extremely detailed meshing (Figure 2); or the effects of the hole pattern could be accounted for with a much less refined mesh using a more abstract method, in which the screen is characterized by a permeability which relates velocity and pressure drop. The decision on how to proceed will depend on the objectives of the study.

Post‐processing (Step 5) is also very important, as it requires the analyst to execute good judgment on the results obtained. Before extracting information and insights from the results, the analyst must scrutinize the calculated field variables, as well as checking for balanced conservation laws; that is, checking for sufficient numerical convergence must be performed. Finally, management of simulation data (i.e. electronic model files) should not be overlooked since it determines the efficiency with which the simulation process is executed.

Figure 1 Examples of burner block geometry. (a) Accurate representation with poor mesh quality; (b) slight modification with improved mesh quality.

Figure 2 Example of a screen with small‐scale features requiring a high mesh density to be resolved.