Numerical Investigations for Leakage and Windage Heating in Straight-Through Labyrinth Seals

The ability to quantify leakage flow and windage heating for labyrinth seals with honeycomb lands is critical in understanding gas turbine engine system performance and predicting its component life. Variety of labyrinth seal configurations (number of teeth, stepped or straight, honeycomb cell size) are in use in gas turbines, and for each configuration, there are many geometric factors that can impact a seal's leakage and windage characteristics. This paper describes the development of a numerical methodology aimed at studying the effect of honeycomb lands on leakage and windage heating. Specifically, a three-dimensional computational fluid dynamics (CFD) model is developed utilizing commercial finite volume-based software incorporating the renormalization group (RNG) k-epsilon turbulence model with modified Schmidt number. The modified turbulence model is benchmarked and fine-tuned based on several experiments. Using this model, a broad parametric study is conducted by varying honeycomb cell size, pressure ratio (PR), and radial clearance for a four-tooth straight-through labyrinth seal. The results show good agreement with available experimental data. They further indicate that larger honeycomb cells predict higher seal leakage and windage heating at tighter clearances compared to smaller honeycomb cells and smooth lands. However, at open seal clearances larger honeycomb cells have lower leakage compared to smaller honeycomb cells.

Genetic algorithms: a survey

Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex landscapes. We introduce the art and science of genetic algorithms and survey current issues in GA theory and practice. We do not present a detailed study, instead, we offer a quick guide into the labyrinth of GA research. First, we draw the analogy between genetic algorithms and the search processes in nature. Then we describe the genetic algorithm that Holland introduced in 1975 and the workings of GAs. After a survey of techniques proposed as improvements to Holland's GA and of some radically different approaches, we survey the advances in GA theory related to modeling, dynamics, and deception

Pattern-Formation During Self-organization in Three-Phase Eutectic Solidification

Eutectic growth is an interesting example for exploring the topic of pattern-formation in multi-phase systems, where the growth of the phases is coupled with the diffusive transport of one or more components in the melt. While in the case of binary alloys, the number of possibilities are limited (lamellae, rods, labyrinth etc.), their number rapidly increases with the number of components and phases. In this paper, we will investigate pattern formation during three-phase eutectic solidification using a state-of-the art phase-field method based on the grand-canonical density formulation. The major aim of the study is to highlight the role of two properties, which are the volume fraction of the solid phases and the solid-liquid interfacial energies, in the self-organization of the solid phases during directional growth. Thereafter, we will show representative phase-field simulations of a micro-structure in a real alloy (Ag-Al-Cu) using an asymmetric phase diagram as well as interfacial properties.