Organizational Unit:

Aerospace Systems Design Laboratory (ASDL)

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https://hdl.handle.net/1853/70744

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Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1135

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Publication Search Results

Now showing 1 - 10 of 193

Identification of Instantaneous Anomalies in General Aviation Operations using Energy Metrics

(Georgia Institute of Technology, 2019-12) Puranik, Tejas G. ; Mavris, Dimitri N.

Quantification and improvement of safety is one of the most important objectives among the General Aviation community. In recent years, machine learning techniques have emerged as an important enabler in the data-driven safety enhancement of aviation operations with a number of techniques being applied to flight data to identify and isolate anomalous (and potentially unsafe) operations. Energy-based metrics provide measurable indications of the energy state of the aircraft and can be viewed as an objective currency to evaluate various safety-critical conditions across a heterogeneous fleet of aircraft and operations. In this paper, a novel method of identifying instantaneous anomalies for retrospective safety analysis in General Aviation using energy-based metrics is proposed. Each flight data record is processed by a sliding window across the multi-variate time series of evaluated metrics. A Gaussian Mixture Model using energy metrics and their variability within each window is fit in order to predict the probability of any instant during the flight being nominal. Instances during flights that deviate from the nominal are isolated to identify potential increased levels of risk. The identified anomalies are compared with traditional methods of safety assessment such as exceedance detection to highlight the benefits of the developed method. The methodology is demonstrated using flight data records from two representative aircraft for critical phases of flight.
An architecture model of the U.S. air transportation network

(Georgia Institute of Technology, 2019-11-26) Song, Kisun

For almost a century, the U.S. Air Transportation Network (ATN) has continuously and successfully adapted to its changing environment as if it were a living organism. Today, the complexity of the network encompasses various exogenous as well as endogenous factors: fuel price, socioeconomic and political climates, atmospheric conditions, varying interests of stakeholders, and growing dependence on technology, to name a few. Its sophisticated interactions among diverse factors affecting the ATN have captivated many network researchers. Some researchers have attempted to retrieve an order out of seemingly chaotic constructions, while others have analyzed historical variations in its properties to understand the ATN’s behavioral mechanisms. However, its mathematical representation led by the known components and rules is yet to be developed. Thus, this thesis develops an architecture model of the ATN that mathematically represents the components and rules with realism. In the model, the network evolves in a virtual environment comprising three time-variant components – demand, airport, and aircraft technology – built upon extensive realistic datasets. Then the network is constructed by the active agents – airlines – performing multi-tiered network evolutionary processes and evolves into a strong hub-and-spoke (H&S) structure network that mimics the function of its reference: real-world ATN. The validated model provides various opportunities to conduct extensive analyses and studies on the past, current, and future of the ATN. Finally, a case study has been performed: forecasting the future ATN disruption caused by the technological revolution of civil supersonic transports. It provided an opportunity to experience the exploratory and interpretative capability of the architecture model, which shed light on performing future researches with better realism.
A reduced-order modeling methodology for the multidisciplinary design and analysis of boundary layer ingestion configurations

(Georgia Institute of Technology, 2019-11-08) Bozeman, Michael Dwain

In response to the increasingly stringent requirements for subsonic transport aircraft, NASA has established aggressive goals for the noise, emissions, and fuel burn of the next generations of aircraft. This has led to the investigation of a variety of unconventional configurations and new technologies. Boundary Layer Ingestion (BLI) propulsion has been identified as a promising technology to reduce fuel burn. Preliminary studies show that BLI propulsion can offer 3-12% reduction in fuel burn, depending on the configuration. Traditionally, the design and analysis of the airframe and propulsion system has been performed in a decoupled manner. For BLI configurations, the propulsion system is tightly integrated into the airframe resulting in strong interactions between the airframe aerodynamics and propulsion system performance. As a result, the design and analysis of BLI configurations requires coupled multidisciplinary analysis (MDA) consisting of an aerodynamic analysis in an iterative loop with a propulsion system analysis. This is a very expensive analysis considering the requirement for high-fidelity models. Additionally, the design of highly-coupled configurations cannot rely solely on intuition to make design decisions. Advanced methods including Multidisciplinary Analysis and Optimization (MDAO) and design space exploration are needed to allow for the design decisions to be made based directly on a system-level objective (e.g., fuel burn) and to allow for design studies to provide insight into the multidisciplinary trades associated with BLI configurations. However, MDAO and design space exploration using coupled, high-fidelity analysis models are not practical. In this work, reduced-order modeling (ROM) is proposed as a potential solution to reduce the computational cost associated with the coupled MDA of BLI configurations and to enable these advanced design methods. An interpolation-based POD ROM is developed based on the CFD analysis to allow for predictions of the aerodynamics over a range of propulsor operating conditions for a simplified tail-cone thruster (TCT) configuration. The resulting ROM is then coupled to a propulsion model to perform ROM-based, coupled MDA. Finally, the ROM-based, coupled MDA approach is employed for coupled MDAO to assess the performance benefit offered relative to equivalent CFD- and adjoint-based approaches. The results show that the ROM-based, coupled MDA approach offers an improvement in performance relative to the current state of the art. Relative to the equivalent CFD-based approach, the ROM-based, coupled MDA method demonstrated significant computational savings for even a single optimization. However, the ROM-based approach requires multiple optimizations to offer a computational benefit over the adjoint-based approach. This result highlights the benefit of the proposed approach for optimization studies and design space exploration.
Exploring the Design Space of an Electric Ship using a Probabilistic Technology Evaluation Methodology

(Georgia Institute of Technology, 2019-08) McNabb, Jeffrey ; Robertson, Nicole A. ; Steffens, Michael J. ; Sudol, Alicia ; Mavris, Dimitri N. ; Chalfant, Julie

With the advent of new technologies for electric ships, there is a need for a robust methodology to quantitatively evaluate their impact on the performance of a ship, while accounting for the uncertain nature of their parameters. To that end, this paper gives an overview of the Technology Identification, Evaluation, and Selection, or TIES, methodology as applied a 10kton surface combatant. This case study highlights the ability of TIES to aid in a broad exploration of the design space, by giving designers key tools that allow them to show in a traceable manner the tradeoffs involved in infusing technologies and making other design choices, as well as which designs best meet different sets of Figures of Merit. This ultimately allows decision-makers to determine what technologies or design choices to invest in to yield a ship with the performance parameters that will best serve the needs of its stakeholders.
An architecture-based growth approach for industrial gas turbine product development

(Georgia Institute of Technology, 2019-07-30) Fu, Haoyun

In this research, an architecture-based methodology has been developed to understand and interpret the ascending performance trajectory of industrial gas turbines from a growth perspective. Historical data depicting the product evolvement are examined to reveal trends and features that can be tied to the published design philosophy and practices in this industry. Quantifiable growth metrics are introduced and deployed in an established framework that offers a scientific product development environment to emulate the prevalent product development practices. Furthermore, the capability established by this methodology is expected to support performance prediction and planning for future gas turbine products.
Resilience-enhanced control reconfiguration for autonomous systems

(Georgia Institute of Technology, 2019-07-26) Oh, Sehwan

Unmanned systems keep replacing manned systems as a paradigm shift. According to the Unmanned Autonomous Systems (UAS) market forecast reports, the UAS market value is expected to grow two to three times higher in ten years. Considering the economic impacts of UAS application in job markets and component manufacturing industries, the UAS market value may very well exceed, which is predicted in the reports. However, regulations have limited the effective utilization of UAS due to safety concerns. These restrictive regulations significantly delay the potential usefulness of civilian and commercial UAVs. According to the Unmanned Aerial Vehicle (UAV) incidence reports, mechanical failures come out to be one of the top reasons for the incidents except for human errors. Technically, it is impossible to avoid any fault or failure in any systems. However, it can be possible to save the faulty system if the faults are treated properly. In this regard, this research has reviewed the state-of-the-art techniques regarding system safety improvement in the presence of a critical fault mode. Promising concepts are resilience engineering and Active Fault Tolerant Control (AFTCS) systems. Resilience engineering has been more focus on system design and resilience assessment methods. AFTCS mainly contributes to the fast and stable operating point recovery without the consideration of long-term system performances or mission success. Prognostics-enhanced reconfigurable control frameworks have proposed the online prognosis for a Remaining Useful Life (RUL) prediction within the control scheme but do not address comprehensive mission capability trade-offs. The objective of this study is to design a resilience-enhanced reconfigurable control framework for unmanned autonomous systems in the presence of a critical fault mode during the operation. The proposed resilience-enhanced reconfigurable control framework is composed of three fundamental modules: 1) immediate performance recovery by Model Predictive Control (MPC) and Differential Dynamic Programming (DDP) approaches, 2) long-term mission capability trade-offs by an optimization routine, and 3) situational awareness by a particle filtering-based fault diagnosis and Case-Based Reasoning (CBR). Critical development of this thesis is an introduction of an adaptation parameter in an MPC formulation (Module 1) and optimization process to find an optimal value for the adaptation parameter (Module 2). Module 3 enables long-term mission capability reasoning when a new fault growth pattern is observed. In order to test the efficacy of the proposed framework, under-actuated hovercraft as a testbed and an insulation degradation of an electrical thrust motor as a critical fault mode are introduced. The experiments explore the effect of the adaptation parameter on long-term mission capabilities and identify the necessity of the proper trade-offs. Further experiments investigate the efficacy of each module and the integrated framework. The experiment results show that the adaptation parameter adjusts a control strategy, so that mission capabilities are optimized while vulnerable long-term mission capabilities are recovered. The integrated framework presents the improvement to the probability of mission success in the presence of a critical fault mode. Lastly, as a generalization of the design process for the resilience-enhanced reconfigurable control framework, a design methodology suggests a step-by-step design procedure. Assumptions of the research have guided the required steps and limitations of the proposed framework.
A methodology for the prediction of non-volatile particulate matter from aircraft gas turbine engine

(Georgia Institute of Technology, 2019-07-26) Choo, Kyung Hak

There is growing concern about the adverse effects of particulate matter emissions on human health and the environment. New regulation standards on aviation particulate matters are expected in the near future. As particulate emissions become one of the important design constraints, they must be evaluated during the conceptual design of an aircraft engine. Prediction of soot emission from gas turbine combustion is a major subject in this research. Soot is a non-volatile primary particulate matter emitted directly from the combustion chamber. Current soot prediction methods utilize engine-specific information. As the current methods cannot handle engines with different cycles and sizes, they are not suitable for conceptual design. Three hypotheses addressing air partitioning, sizing methodology, and statistical distribution are established to develop the prediction environment, capable of a variety of cycles of engines with different size and thrust. The prediction environment consists of a Combustor Flow Circuit model, Statistical Distribution Model with the unmixedness curve, Chemical Reactor Networks (CRN), and Soot Evaluation Model. The integrated prediction environment developed with the proposed methodology demonstrates good predictability for cycles of different size and thrust engines. As the input of the prediction environment is a cycle, the proposed methodology is adequate for the prediction of non-volatile PM during the conceptual design of an aircraft engine.
An unsteady aerodynamics reduced-order modeling method for maneuvering, flexible flight vehicles

(Georgia Institute of Technology, 2019-07-24) Hiller, Brett R.

Accurate aerodynamic predictions remain a cornerstone of the aircraft design process due to their significance in determining the performance and stability and control (S&C) characteristics of aircraft. Traditional flight dynamics modeling has historically relied on the use of quasi-steady stability derivatives, often calculated using simplified linear aerodynamic methods. These models are inherently incapable of predicting the nonlinear, unsteady aerodynamics encountered by modern flexible aircraft. Inaccurate predictions of such phenomena can lead to suboptimal vehicle performance and/or inaccurate control law design, potentially leading to loss of control of the vehicle. Recent advances in digital computing have motivated interest towards Virtual Flight Simulation (VFS), for which multidisciplinary numerical simulations are used to evaluate an aircraft’s performance and S&C characteristics at full-scale flight Reynolds and Mach numbers. Despite their demonstrated feasibility, these simulations often require thousands of computational hours, limiting their adoption and widespread application for aircraft design and analysis. Reduced-order modeling is viewed as a key enabler for the viable application of VFS methods. Reduced-order models (ROMs) are mathematical models aimed at accurately predicting the fundamental dynamics of a system at a computational cost much less than what is required in solving the original governing equations. These methods approximate the full-order numerical simulations of a system by extracting and reconstructing pertinent dynamic data solutions, without any limiting physical model assumptions. Significant progress in reduced-order modeling has been made over the past two decades with the development of a variety of reduced-order models for efficient unsteady aerodynamic predictions. However, most unsteady aerodynamic ROMs have been primarily used for either predicting the aerodynamic response of rigid maneuvering vehicles or identifying aeroelastic instabilities, such as a flutter. Multidisciplinary ROMs for virtual flight simulations remain a desirable, yet relatively unexplored area of research. The objective of this dissertation was to develop a ROM capable of providing quantitatively accurate, yet computationally efficient predictions of the nonlinear, unsteady aerodynamics encountered by maneuvering flexible flight vehicles. Indicial response theory is a nonintrusive ROM approach, which characterizes a system’s dynamics through identification of the system response due to numerically simulated unit step changes in a system’s inputs. A CFD-based dynamic modal aeroelastic analysis was proposed for identification of indicial responses with respect to the vehicle motion parameters. Linear and nonlinear indicial response ROMs, based on the mathematical principle of convolution, were extended to predict the unsteady aerodynamic response of flexible flight vehicles subject to arbitrary vehicle maneuvers. The aeroelastic ROM is tested through comparisons to dynamic aeroelastic simulations of NASA’s X-56A Multi-Utility Technology Testbed (MUTT) aircraft performing a series of harmonic forced oscillations and a right turn flight test maneuver. Once identified, the aeroelastic indicial response ROM method is shown to accurately capture the entire frequency spectrum of the system, resolving the unsteady aerodynamic response of flexible flight vehicles at any feasible motion rate. Quantified assessments of the computational cost and accuracy of the aeroelastic ROM demonstrate rapidly increasing performance benefits relative to high fidelity aeroelastic simulations as multiple maneuver are considered. Furthermore, traditional stability-derivative models are efficiently extracted from aeroelastic indicial responses and are shown to accurately predict slowly-varying maneuvers with reduced computational costs. For more dynamic motions, the ROM is shown to accurately resolve the complex fluid-structure interactions present for maneuvering, flexible flight vehicles that are incapable of being modeled by quasisteady models.
A Framework for Electrified Propulsion Architecture and Operation Analysis

(Georgia Institute of Technology, 2019-07) Cinar, Gokcin ; Garcia, Elena ; Mavris, Dimitri N.

Purpose – The purpose of this paper was to create a generic and flexible framework for the exploration, evaluation and side-by-side comparison of novel propulsion architectures. The intent for these evaluations was to account for varying operation strategies and to support architectural design space decisions, at the conceptual design stages, rather than single-point design solutions. Design/methodology/approach – To this end, main propulsion subsystems were categorized into energy, power and thrust sources. Two types of matrices, namely, the property and interdependency matrices, were created to describe the relationships and power flows among these sources. These matrices were used to define various electrified propulsion architectures, including, but not limited to, turboelectric, series-parallel and distributed electric propulsion configurations. Findings – As a case study, the matrices were used to generate and operate the distributed electric propulsion architecture of NASA’s X-57 Mod IV aircraft concept. The mission performance results were acceptably close to the data obtained from the literature. Finally, the matrices were used to simulate the changes in the operation strategy under two motor failure scenarios to demonstrate the ease of use, rapidness and automation. Originality/value – It was seen that this new framework enables rapid and analysis-based comparisons among unconventional propulsion architectures where solutions are driven by requirements.
Power Management Optimization for Off-Design Performance Assessment of Ducted Electric Fan with Boundary Layer Ingestion

(Georgia Institute of Technology, 2019-06) Brucculeri, Joseph ; Salas Nunez, Luis ; Gladin, Jonathan ; Mavris, Dimitri N.

This work consists on the examination of the system level benefits of a partially turboelectric propulsion architecture with Boundary Layer Ingestion (BLI) in a 150-pax class size commercial aircraft. This propulsion system consists of an electric ducted fan that ingests the boundary layer from the aft-end of the fuselage. The power for this aft-fan is extracted from two underwing turbofan engines. The BLI effects are quantified in CFD using the power balance method, which are then integrated using surrogate models into an aircraft sizing and mission analysis environment to obtain mission performance metrics. With the overarching goal of minimizing fuel consumption, an approach to optimize the motor power during off-design analysis is presented. The effect that different power management strategies have on system performance are also analyzed. The results showed that such novel propulsion architecture not only presents benefits with respect to a conventional system, but also that the application of an optimized power schedule offers additional fuel burn reductions.