A Numerical Study of Curved Labyrinth Seals for Steam Turbines

A numerical experiment has been conducted to study and evaluate the structural behavior of newly designed labyrinth seals. Structural analysis was performed to understand, evaluate and compare new seals with a baseline straight seal that is typical of commonly used seals in steam turbines. New configurations of labyrinth seal knives were developed for use in steam turbines [17]. The main objective of this study is to develop a better understanding of selected various labyrinth seals that may be configured to minimize the steam leakage and reduce seal interactions with the shaft. Computational fluid dynamic modeling of the various configurations, from a related study, and preliminary structural analysis led new designs to incorporate curvature into knife geometries including a sharp flat free-edge. Two-dimensional linear elastic static structural analysis was performed on a baseline straight labyrinth seal knife and seven different new configurations incorporating flexible geometries like curved seals, using finite element analysis software ANSYS®. Structural behavior of all new seals was evaluated in comparison with the results obtained for the baseline straight seal knife. Results show that the new geometries are more flexible than the straight seal knife, within the elastic limit of the same material. Of the seven geometries of new curved knives, two (C4 and C5) had higher load bearing capacity than all the others and one of them exceeded the load bearing capacity of the straight knife. The two high performing configurations, CS1 and CS2, have very thin knives compared to the other configurations. These two were found to be the most flexible among all the seven new configurations, considered. The maximum deformation and load bearing capacity of all the seven knives were correlated against a single non-dimensional geometrical parameter that appears to govern such variations and, therefore, define the improved designs

Analysis of Dependencies and Impacts of Metroplex Operations

This report documents research performed by Purdue University under subcontract to the George Mason University (GMU) for the Metroplex Operations effort sponsored by NASA's Airportal Project. Purdue University conducted two tasks in support of the larger efforts led by GMU: a) a literature review on metroplex operations followed by identification and analysis of metroplex dependencies, and b) the analysis of impacts of metroplex operations on the larger U.S. domestic airline service network. The tasks are linked in that the ultimate goal is an understanding of the role of dependencies among airports in a metroplex in causing delays both locally and network-wide. The Purdue team has formulated a system-of-systems framework to analyze metroplex dependencies (including simple metrics to quantify them) and develop compact models to predict delays based on network structure. These metrics and models were developed to provide insights for planners to formulate tailored policies and operational strategies that streamline metroplex operations and mitigate delays and congestion

Hyper-Local Weather Predictions with the Enhanced General Urban Area Microclimate Predictions Tool

This paper presents enhancements to, and the demonstration of, the General Urban area Microclimate Predictions tool (GUMP), which is designed to provide hyper-local weather predictions by combining machine-learning (ML) models and computational fluid dynamic (CFD) simulations. For the further development and demonstration of GUMP, the Embry–Riddle Aeronautical University (ERAU) campus was used as a test environment. Local weather sensors provided data to train ML models, and CFD models of urban- and suburban-like areas of ERAU’s campus were created and iterated through with a wide assortment of inlet wind speed and direction combinations. ML weather sensor predictions were combined with best-fit CFD models from a database of CFD flow fields, providing flight operational areas with a fully expressed wind flow field. This field defined a risk map for uncrewed aircraft operators based on flight plans and individual flight performance metrics. The potential applications of GUMP are significant due to the immediate availability of weather predictions and its ability to easily extend to arbitrary urban and suburban locations

A formulation to analyze system-of-systems problems: A case study of airport metroplex operations

A system-of-systems (SoS) can be described as a collection of multiple, heterogeneous, distributed, independent components interacting to achieve a range of objectives. A generic formulation was developed to model component interactions in an SoS to understand their influence on overall SoS performance. The formulation employs a lexicon to aggregate components into hierarchical interaction networks and understand how their topological properties affect the performance of the aggregations. Overall SoS performance is evaluated by monitoring the changes in stakeholder profitability due to changes in component interactions. The formulation was applied to a case study in air transportation focusing on operations at airport metroplexes. Metroplexes are geographical regions with two or more airports in close proximity to one another. The case study explored how metroplex airports interact with one another, what dependencies drive these interactions, and how these dependencies affect metroplex throughput and capacity. Metrics were developed to quantify runway dependencies at a metroplex and were correlated with its throughput and capacity. Operations at the New York/New Jersey metroplex (NYNJ) airports were simulated to explore the feasibility of operating very large aircraft (VLA), such as the Airbus A380, as a delay-mitigation strategy at these airports. The proposed formulation was employed to analyze the impact of this strategy on different stakeholders in the national air transportation system (ATS), such as airlines and airports. The analysis results and their implications were used to compare the pros and cons of operating VLAs at NYNJ from the perspectives of airline profitability, and flight delays at NYNJ and across the ATS

GT2006-91263 ADVANCED LABYRINTH SEALS FOR STEAM TURBINE GENERATORS

ABSTRACT A new class of knives (C-Shaped) for reduced labyrinth seal discharge has been designed and assessed through two dimensional numerical modeling of the seal's internal flow passages. Modeling procedures used for the analysis have been previously validated by comparison with static labyrinth seal experiments. The objectives of the new seal are to: 1) reduce flow leakage through the seal and 2) introduce structural flexibility in the knives so that design clearances could be maintained even after rub events during startup. The baseline chosen for comparative evaluation is an N2 packing used in GE steam turbines. The new seals have compliant C-shaped knives instead of the straight knives, found in an N2 packing. The best performing configuration has one tall 'C' shaped long knife and three 'C' shaped short knives in each stage. It was found that the best configuration at clearances similar to the baseline seal reduces flow leakage by 42%. Two dimensional numerical structural analyses showed that the new seal knife is more flexible than a straight knife. This is also intuitive by virtue of its geometric profile. A non-dimensional geometric parameter correlates with the degree of flexibility in the knife. These results indicate a potential for design of labyrinth seals that maintain lower design clearances throughout their life time by carefully selecting the knives' geometric parameters and incorporating high performance composite materials. Then, the new design would result in significantly lower steam leakage

Hyper-Local Weather Predictions with the Enhanced General Urban Area Microclimate Predictions Tool

This paper presents enhancements to, and the demonstration of, the General Urban area Microclimate Predictions tool (GUMP), which is designed to provide hyper-local weather predictions by combining machine-learning (ML) models and computational fluid dynamic (CFD) simulations. For the further development and demonstration of GUMP, the Embry–Riddle Aeronautical University (ERAU) campus was used as a test environment. Local weather sensors provided data to train ML models, and CFD models of urban- and suburban-like areas of ERAU’s campus were created and iterated through with a wide assortment of inlet wind speed and direction combinations. ML weather sensor predictions were combined with best-fit CFD models from a database of CFD flow fields, providing flight operational areas with a fully expressed wind flow field. This field defined a risk map for uncrewed aircraft operators based on flight plans and individual flight performance metrics. The potential applications of GUMP are significant due to the immediate availability of weather predictions and its ability to easily extend to arbitrary urban and suburban locations