Computational Fluid Dynamics Modeling

Current aerospace and aero-propulsion systems design process trends lead to the inclusion of computational fluid dynamics (CFD) to reduce prototyping and testing costs and accelerate system design. It allows understanding of the complex physical features of flow fields associated with various components at a system level.
Sest, Inc. has extensive capability and experience in computational fluid dynamics modeling and simulation to analyze fluid flow, thermodynamics, and heat transfer for many different applications. With this background, Sest works with customers to determine the best approach to addressing their specific need. Along with CFD analysis we provides clear interpretation of the results so the analysis is meaningful to the customer.

Sest, Inc. recognizes the challenge of balancing model complexity and detail with accuracy, speed of execution, and ease of use. As with any simulation, model validation is an important part of the process. We work with customers to develop the right approach to meet their specific needs. Some examples of the different kinds of CFD analysis Sest can perform include:

Combustion Modeling
Optimization of Flow in Manifold System
Identification of Losses

Combustion Modeling

Our engineers have modeled and simulated the three-dimensional, viscous, turbulent, reacting and non-reacting flow characteristics of a model gas turbine combustor operating on air/methane. A numerical model of the experimental gaseous combustor is built to simulate the experimental model (For more details see: Davouzadech, F., Liu, N-S. Numerical Predictions of Non-reacting and Reacting Flow in a Model Gas Turbine Combustor. NASA TM 2005-213898).

The constructed numerical geometry includes the flow development sections for air annulus and fuel pipe, twenty-four-channel air and fuel swirlers, hub, combustor, and tail pipe. Various topologies for construction of a grid for the whole combustor were considered and finally a grid was generated for the whole domain using Gridgen Code developed by Pointwise, Inc.

The final grid is a multi-block grid, constructed with approximately 1.6 million gird points, encompassing 3-levels of multi-grid using hexahedron elements. The computational grid includes the whole flow regime starting from the fuel pipe and the air annulus through the twelve air and twelve fuel channels, in the combustion region and through the tail pipe. Sample grid patterns are show in Figure 1. National Combustion Code (NCC) developed at NASA GRC was used to simulate many complex physical processes that occur simultaneously such as combustion, turbulence, turbulence chemistry, interaction, reaction kinetics, turbulence spray interaction, heat transfer, and radiation in gas turbine combustion.

Typical results include the pattern and extent of the re-circulation zone and that of the vortical structures is shown in Figure 2. The particle traces are colored by the magnitude of the velocity vector.There is a large reversed flow that extends almost more than two combustors radius, and there is also a very dense and long vortical structure in the central region. These vertical structures are created from the swirl created in the flow via the fuel and air swirlers, upstream in the two co-annular tubes. The computed temperature field distribution, on a constant Y-plane is shown in Figure 3.

Fig. 1 - Combustor computational grids

Fig. 2 - Predicted swirlers             Fig. 3 - Temperature distribution

Optimization of Flow in Manifold System

Sest, Inc. has developed CFD model of a manifold system for pressure drop testing through a Stirling engine manifold which includes a porous medium. The CAD models were incorporated into the CFD model and flow simulations identified areas where flow was not uniform. Accordingly the flow fixture was modified iteratively to optimize flow conditions before fabricating hardware.

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Identification of Losses

Sest, Inc. has developed a CFD model of a Stirling engine to better understand the fluid flow and heat transfer phenomena inside the engine. The Stirling engine contains oscillating, non-steady-state flow, and thus is difficult to analyze via other methods.

The CFD model can be used for parasitic loss budgeting for component optimization. Parasitics can occur from heat transfer inefficiencies and flow losses due to abrupt changes in geometry. Lost available work or 2nd Law losses are also very interesting to system designers to improve engine performance.

CFD
Combustion Modeling
Optimization of Flow in Manifold System