Organizational Unit:

Daniel Guggenheim School of Aerospace Engineering

Permanent Link

https://hdl.handle.net/1853/70742

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Organizational Unit

College of Engineering

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Organizational Unit

Aerospace Design Group

Organizational Unit

Aerospace Systems Design Laboratory (ASDL)

Organizational Unit

Air Transportation Laboratory

Organizational Unit

Cognitive Engineering Center

Organizational Unit

Space Systems Design Laboratory (SSDL)

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https://finding-aids.library.gatech.edu/agents/corporate_entities/106

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Publication Search Results

Now showing 1 - 10 of 359

Wall-models for large eddy simulation based on a generic additive-filter formulation

(Georgia Institute of Technology, 2008-12-19) Sánchez Rocha, Martín

In this work, the mathematical implications of merging two different turbulence modeling approaches are addressed by deriving the exact hybrid RANS/LES Navier-Stokes equations. These equations are derived by introducing an additive-filter, which linearly combines the RANS and LES operators with a blending function. The equations derived predict additional hybrid terms, which represent the interactions between RANS and LES formulations. Theoretically, the prediction of the hybrid terms demonstrates that the hybridization of the two approaches cannot be accomplished only by the turbulence model equations, as it is claimed in current hybrid RANS/LES models. The importance of the exact hybrid RANS/LES equations is demonstrated by conducting numerical calculations on a turbulent flat-plate boundary layer. Results indicate that the hybrid terms help to maintain an equilibrated model transition when the hybrid formulation switches from RANS to LES. Results also indicate, that when the hybrid terms are not included, the accuracy of the calculations strongly relies on the blending function implemented in the additive-filter. On the other hand, if the exact equations are resolved, results are only weakly affected by the characteristics of the blending function. Unfortunately, for practical applications the hybrid terms cannot be exactly computed. Consequently, a reconstruction procedure is proposed to approximate these terms. Results show, that the model proposed is able to mimic the exact hybrid terms, enhancing the accuracy of current hybrid RANS/LES approaches. In a second effort, the Two Level Simulation (TLS) approach is proposed as a near-wall model for LES. Here, TLS is first extended to compressible flows by deriving the small-scale equations required by the model. The full compressible TLS formulation and the hybrid TLS/LES approach is validated simulating the flow over a flat-plate turbulent boundary layer. Overall, results are found in reasonable agreement with experimental data and LES calculations.
Stochastic dynamical system identification applied to combustor stability margin assessment

(Georgia Institute of Technology, 2008-12-16) Cordeiro, Helio de Miranda

A new approach was developed to determine the operational stability margin of a laboratory scale combustor. Applying modern and robust techniques and tools from Dynamical System Theory, the approach was based on three basic steps. In the first step, a gray-box thermoacoustical model for the combustor was derived. The second step consisted in applying System Identification techniques to experimental data in order to validate the model and estimate its parameters. The application of these techniques to experimental data under different operating conditions allowed us to determine the functional dependence of the model parameters upon changes in an experimental control parameter. Finally, the third step consisted in using that functional dependence to predict the response of the system at different operating conditions and, ultimately, estimate its operational stability margin. The results indicated that a low-order stochastic non-linear model, including two excited modes, has been identified and the combustor operational stability margin could be estimated by applying a continuation method.
Parametric Analysis and Targeting Capabilities for the Planetary Entry Systems Synthesis Tool

(Georgia Institute of Technology, 2008-12-05) Smith, Patrick J.

Modeling and simulation has led to major advances in the design of complex systems largely because it provides designers with an affordable method of testing new ideas. This report describes recent improvements to a modeling and simulation tool, known as the Planetary Entry Systems and Synthesis Tool or PESST, that allow a designer to quickly conduct parametric and targeting studies. PESST has been used in several conceptual design studies and the improvements to this tool allow a user to complete several cases quickly and gain valuable insight to a larger region of the design space. It would be impossible for designers to create truly robust systems without the ability to fully grasp the design space. By testing the effect of many different input variable values, the designer gains valuable insight to overall system response. As an example of the improvements added to PESST, hypothetical parametric and targeting studies have been completed for the Orion Crew Entry Vehicle.
Status of Safety WG Products and Activities

(Georgia Institute of Technology, 2008-11-18)
Overview of NextGen Institute Project

(Georgia Institute of Technology, 2008-11-18) Cointin, Rebecca
Flight Deck Merging and Spacing and Advanced FMS Operations

(Georgia Institute of Technology, 2008-11-18) Williams, David H.
Overview of ICAO CAEP WGT-TG3 Operational Measures Work Program

(Georgia Institute of Technology, 2008-11-18)
A probabilistic and multi-objective conceptual design methodology for the evaluation of thermal management systems on air-breathing hypersonic vehicles

(Georgia Institute of Technology, 2008-11-18) Ordaz, Irian

This thesis addresses the challenges associated with thermal management systems (TMS) evaluation and selection in the conceptual design of hypersonic, air-breathing vehicles with sustained cruise. The proposed methodology identifies analysis tools and techniques which allow the proper investigation of the design space for various thermal management technologies. The design space exploration environment and alternative multi-objective decision making technique defined as Pareto-based Joint Probability Decision Making (PJPDM) is based on the approximation of 3-D Pareto frontiers and probabilistic technology effectiveness maps. These are generated through the evaluation of a Pareto Fitness function and Monte Carlo analysis. In contrast to Joint Probability Decision Making (JPDM), the proposed PJPDM technique does not require preemptive knowledge of weighting factors for competing objectives or goal constraints which can introduce bias into the final solution. Preemptive bias in a complex problem can degrade the overall capabilities of the final design. The implementation of PJPDM in this thesis eliminates the need for the numerical optimizer which is required with JPDM in order to improve upon a solution. In addition, a physics-based formulation is presented for the quantification of TMS safety effectiveness corresponding to debris impact/damage and how it can be applied towards risk mitigation. Lastly, a formulation loosely based on non-preemptive Goal Programming with equal weighted deviations is provided for the resolution of the inverse design space. This key step helps link vehicle capabilities to TMS technology subsystems in a top-down design approach. The methodology provides the designer more knowledge up front to help make proper engineering decisions and assumptions in the conceptual design phase regarding which technologies show greatest promise, and how to guide future technology research.
Methodology for the conceptual design of a robust and opportunistic system-of-systems

(Georgia Institute of Technology, 2008-11-18) Talley, Diana Noonan

Systems are becoming more complicated, complex, and interrelated. Designers have recognized the need to develop systems from a holistic perspective and design them as Systems-of-Systems (SoS). The design of the SoS, especially in the conceptual design phase, is generally characterized by significant uncertainty. As a result, it is possible for all three types of uncertainty (aleatory, epistemic, and error) and the associated factors of uncertainty (randomness, sampling, confusion, conflict, inaccuracy, ambiguity, vagueness, coarseness, and simplification) to affect the design process. While there are a number of existing SoS design methods, several gaps have been identified: the ability to modeling all of the factors of uncertainty at varying levels of knowledge; the ability to consider both the pernicious and propitious aspects of uncertainty; and, the ability to determine the value of reducing the uncertainty in the design process. While there are numerous uncertainty modeling theories, no one theory can effectively model every kind of uncertainty. This research presents a Hybrid Uncertainty Modeling Method (HUMM) that integrates techniques from the following theories: Probability Theory, Evidence Theory, Fuzzy Set Theory, and Info-Gap theory. The HUMM is capable of modeling all of the different factors of uncertainty and can model the uncertainty for multiple levels of knowledge. In the design process, there are both pernicious and propitious characteristics associated with the uncertainty. Existing design methods typically focus on developing robust designs that are insensitive to the associated uncertainty. These methods do not capitalize on the possibility of maximizing the potential benefit associated with the uncertainty. This research demonstrates how these deficiencies can be overcome by identifying the most robust and opportunistic design. In a design process it is possible that the most robust and opportunistic design will not be selected from the set of potential design alternatives due to the related uncertainty. This research presents a process called the Value of Reducing Uncertainty Method (VRUM) that can determine the value associated with reducing the uncertainty in the design problem before a final decision is made by utilizing two concepts: the Expected Value of Reducing Uncertainty (EVRU) and the Expected Cost to Reducing Uncertainty (ECRU).
Airline Involvement in Procedure Development

(Georgia Institute of Technology, 2008-11-17)