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Daniel Guggenheim School of Aerospace Engineering
Daniel Guggenheim School of Aerospace Engineering
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ItemAerodynamics and aeroacoustic sources of a coaxial rotor(Georgia Institute of Technology, 2018-04-10) Schatzman, Natasha LydiaVehicles with coaxial, contra-rotating rotor systems (CACR) are being considered for a range of applications, including those requiring high speed and operations in urban environments. Community and environmental noise impact is likely to be a concern in these applications. Design parameters are identified that effect the fundamental aerodynamics and fluid dynamic features of a CACR in hover, vertical, and edgewise flight. Particular attention is paid to those features affecting thickness, loading, blade vortex interaction (BVI), and high speed impulsive (HSI) noise. Understanding the fluid dynamic features is a precursor to studying the aeroacoustics of a coaxial rotor. Rotor performance was computed initially using Navier-Stokes solver with prescribed blade section aerodynamic properties, the results validated against generic experimental test cases. The fluid dynamics of blade interactions was simplified and broken into a 2-D blade crossing problem, with crossing locations and velocity fields from the rotor results. Two trains of 8 airfoils passing were simulated to understand the effects due to shed vorticity. The airfoils are displaced vertically by a distance equivalent to the typical spacing between the upper and lower rotors of a coaxial system. A 2D potential flow code and 2D OVERFLOW compressible-flow Navier-Stokes solver were used to investigate the complex coaxial rotor system flow field. One challenge of analyzing the CACR is the difficulty in envisioning all the possible interactions and their possible locations as flight conditions and rotor designs change. A calculation tool has been developed to identify time and location of blade overlap. The tool was then integrated with a wake aerodynamics model to identify locations and instances of upper rotor tip vortex interaction with a lower rotor blade. This tool enables rapid identification of different types of BVI based on relative rotor orientation. Specific aerodynamic phenomena that occur for each noise source relevant to CACR are presented, along with computational tools to predict these occurrences.
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ItemA framework to enable rotorcraft maintenance free operating periods(Georgia Institute of Technology, 2018-04-05) Bellocchio, Andrew T.The British Ultra-Reliable Aircraft Pilot Program of the late 1990s introduced the sustainment concept of a Maintenance Free Operating Period (MFOP) where aircraft become fault tolerant, highly reliable systems that minimizes disruptive failures and maintenance for an extended period of operations. After the MFOP, a single Maintenance Recovery Period (MRP) consolidates repair of accrued faults and inspections to restore an aircraft’s reliability for the next MFOP cycle. The U.S. Department of Defense recently adopted MFOP as a maintenance strategy for the next generation of rotorcraft named Future Vertical Lift. The U.S. military desires the assurance of uninterrupted flight operations that an MFOP strategy provides to enable an expeditionary force. This work develops a framework to balance downtime, dependability, and maintainability of an MFOP rotorcraft. It begins with the hypothesis that metrics using the mean are insufficient in a MFOP strategy and that metrics that include the time history of failure are as important as the rate of failure. It will utilize a Discrete Event Simulation to model the MFOP, MRP, and the success rate as operational metrics. The work will identify which subsystem(s) limit the MFOP of an aircraft and which components drive MRP higher. It will explore a framework to build policies for availability and success rate where preventive component renewals occur at discrete multiples of the MFOP. Finally, it will test the hypothesis that an operator has some control over the MFOP to meet changing operational demands by adapting the MRP through an aggressive lifing policy.
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ItemA framework for the optimization of doctrine and systems in Army Air Defense units using predictive models of stochastic computer simulations(Georgia Institute of Technology, 2017-04-05) Wade, Brian M.This thesis presents a new methodology that can be used to address large-scale raids made up of different types of Theater Ballistic Missiles (TBMs) and Cruise Missiles (CMs) that attempt to overwhelm the Air Defense Artillery (ADA) systems at a particular location. The primary focus will be on how existing ADA systems can adjust their tactics in order to minimize the damage caused by threats that are not shot down and impact friendly forces. Nearly all the literature to date optimizes systems and tactics to reduce the number of leakers — threats not shot down — that impact the ground. However, simply counting the number of leakers does not adequately describe the effects to friendly forces. Instead, the first part of this thesis combines existing methods for external ballistics, concrete penetration, explosive cratering, and weapon blast and fragmentation damage in order to create an integrated program that can describe the damage to an airfield runway, infrastructure, and parked aircraft. The second part of this thesis focuses on modeling the ADA missile engagements using an accredited Department of Defense ADA simulation model called the Extended Air Defense Simulation (EADSIM). Both the airfield damage model and ADA simulation have run times ranging from minutes to hours. They are also stochastic; so a large number of runs are required for each input vector in order to properly understand the output range. In order to reduce the computation time to allow for later optimization, the methods of design of experiments and machine learning were used to create fast running models that predict the outputs of these simulations. The final part of this work uses these prediction algorithms to first optimize the TBM and CM fire plan, then optimize the ADA defense tactics, and finally optimize the ADA defense tactics with a new interceptor missile system.
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ItemA methodology to achieve microscopic/macroscopic configuration tradeoffs in cooperative multi-robot systems design(Georgia Institute of Technology, 2017-04-04) Durand, Jean Guillaume Dominique SebastienThe exponential growth experienced by the robotics sector over the past decade has fostered the proliferation of new architectures. Optimized for specific missions, these platforms are in most cases limited by their embarked computational power and a lack of full situational awareness. More robust, flexible, scalable, and inspired by nature, group robotics represent an interesting approach to overcome some limitations of these single agents and take advantage of the heterogeneity of the current robotics fleet. Their essence lies in accomplishing more complex synergistic behaviors through diversity, simple rules, and local interactions. However, the design of robotic groups is complex as decision-makers have to optimize the group operation as well as the performance of each individual unit, for the group performance. In particular, key questions arise to know whether resources should be allocated to the characteristics of the group, or to the individual capabilities of its agents in order to meet the established requirements. Current methods of swarm engineering tend to perform sequential optimization of the microscopic level (the agents) and then the macroscopic level (the group), which results in suboptimal architectures. In this context, efficiently comparing two different groups or quantifying the superiority of a group versus a single-robot design may prove impossible. Same goes of the determination of an optimal architecture for a given mission. With a special emphasis on aerial vehicles, the present research proposes to establish a methodology to achieve microscopic/macroscopic configuration tradeoffs in the design of cooperative multi-robot systems. The resulting product is the MASDeM: Multi-Agent Systems Design Methodology. A novel multi-level multi-architecture morphological approach is first introduced to facilitate design space exploration, and a mesoscopic level simulation-based design method is used to bridge the gap between microscopic and macroscopic levels. Using these first blocks, an innovative optimization technique is suggested based on two interconnected loops which differs from the classical sequential approach presently used by the research community. Results of this research show that simultaneous optimization can have clear benefits if applied to the design of multi-robot systems and on particular cases, average improvements of 16 percent were observed on the main performance metric. The proposed optimizer proves to be a key enabler for fully heterogeneous swarms, a capability which is not possible in the current paradigm. Moreover, the optimization algorithm was efficiently designed and exhibits a speedup of at least 50 percent when compared to current techniques. Finally, the exploration of the design space is effectively carried out with a combination of morphological reduction, morphological tree representation, and mesoscopic modeling. Indeed, applied to multi-robot systems, such models prove being several times faster than usual simulation approaches while remaining in the same range of accuracy.
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ItemA new rotorcraft design framework based on reliability and cost(Georgia Institute of Technology, 2016-07-26) Scott, Robert C.Helicopters provide essential services in civil and military applications due to their multirole capability and operational flexibility, but the combination of the disparate performance conditions of vertical and cruising flight presents a major compromise of aerodynamic and structural efficiency. In reviewing the historical trends of helicopter design and performance, it is apparent that the same compromise of design conditions which results in rotorcraft performance challenges also affects reliability and cost through vibration and fatigue among many possible factors. Although many technological approaches and design features have been proposed and researched as means of mitigating the rotorcraft affordability deficit, the assessment of their effects on the design, performance, and life-cycle cost of the aircraft has previously been limited to a manual adjustment of legacy trends in models based on regression of historical design trends. A new approach to the conceptual design of rotorcraft is presented which incorporates cost and reliability assessment methods to address the price premium historically associated with vertical flight. The methodology provides a new analytical capability that is general enough to operate as a tool for the conceptual design stage, but also specific enough to estimate the life-cycle effect of any RAM-related design technology which can be quantified in terms of weight, power, and reliability improvement. The framework combines aspects of multiple design, cost, and reliability models – some newly developed and some surveyed from literature. The key feature distinguishing the framework from legacy design and assessment methods is its ability to use reliability as a design input in addition to the flight conditions and missions used as sizing points for the aircraft. The methodology is first tested against a reference example of reliability-focused technology insertion into a legacy rotorcraft platform. Once the approach is validated, the framework is applied to an example problem consisting of a technology portfolio and a set of advanced rotorcraft configurations and performance conditions representative of capabilities desired in near-future joint service, multirole rotorcraft. The framework sizes the different rotorcraft configurations for both a baseline set of assumptions and a tradespace survey of reliability investment to search for an optimum design point corresponding to the level of technology insertion which results in the lowest life-cycle cost or highest value depending on the assumptions used. The study concludes with a discussion of the results of the reliability trade study and their possible implications for the development and acquisition of future rotorcraft.
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ItemRapid determination of mass and stiffness distribution on primary skin-stiffener structures(Georgia Institute of Technology, 2016-07-20) Noevere, August T.In modern conceptual/preliminary design of aerospace vehicles it is common for a large number of concepts and configurations to be rapidly explored. For each configuration, the structures discipline is responsible for determining an internal structural arrangement and detailed component design that minimizes mass while supporting external loads and other requirements. The proposed research presents a methodology suited for rapid design of structures which is capable of optimizing mass while easily meeting these requirements. Specifically, the methodology focuses on the stiffened panel optimization problem for metallic and composites. A change of variables is performed to allow accurate linearization of the design space, thereby greatly increasing optimization efficiency. The stiffened panel design space is recast in terms of equivalent smeared stiffness, using terms from the [ABD] stiffness matrix. This reformulation is enabled by the use of response surface equations to map the panel failure criteria (such as material failure, local buckling, etc.) to be a function of stiffness terms only. The resulting linear design space can be quickly optimized with the Simplex Algorithm. Thus, the approach is able to perform physics-based panel optimization with a level of efficiency appropriate for conceptual design studies. This approach is validated for a metallic and composite I-stiffened panel, as well as a composite laminate. Additionally, the methodology is demonstrated to couple well with the FEM-based design environment of a wing box for both metallic and composite construction. Overall, the methodology was shown to provide significant improvement in stiffened panel optimization efficiency over traditional tools while retaining accuracy within 10% of those tools.
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ItemFuzzy framework for robust architecture identification in concept selection(Georgia Institute of Technology, 2015-11-10) Patterson, Frank H.An evolving set of modern physics-based, multi-disciplinary conceptual design methods seek to explore the feasibility of a new generation of systems, with new capabilities, capable of missions that conventional vehicles cannot be empirically redesigned to perform. These methods provide a more complete understanding of a concept's design space, forecasting the feasibility of uncertain systems, but are often computationally expensive and time consuming to prepare. This trend creates a unique and critical need to identify a manageable number of capable concept alternatives early in the design process. Ongoing efforts attempting to stretch capability through new architectures, like the U.S. Army's Future Vertical Lift effort and DARPA's Vertical Takeoff and Landing (VTOL) X-plane program highlight this need. The process of identifying and selecting a concept configuration is often given insufficient attention, especially when a small subset of favorable concept families is not immediately apparent. Commonly utilized methods for concept generation, like filtered morphological analysis, often identify an exponential number of alternatives. Simple approaches to concept selection then rely on designers to identify a relatively small subset of alternatives for comparison through simple methods regularly related to decision matrices (Pugh, TOPSIS, AHP, etc.). More in-depth approaches utilize modeling and simulation to compare concepts with techniques such as stochastic optimization or probabilistic decision making, but a complicated setup limits these approaches to just a discrete few alternatives. A new framework to identify and select promising, robust concept configurations utilizing fuzzy methods is proposed in this research and applied to the example problem of concept selection for DARPA's VTOL Xplane program. The framework leverages fuzzy systems in conjunction with morphological analysis to assess large design spaces of potential architecture alternatives while capturing the inherent uncertainty and ambiguity in the evaluation of these early concepts. Experiments show how various fuzzy systems can be utilized for evaluating criteria of interest across disparate architectures by modeling expert knowledge as well as simple physics-based data. The models are integrated into a single environment and variations on multi-criteria optimization are tested to demonstrate an ability to identify a non-dominated set of architectural families in a large combinatorial design space. The resulting framework is shown to provide an approach to quickly identify promising concepts in the face of uncertainty early in the design process.An evolving set of modern physics-based, multi-disciplinary conceptual design methods seek to explore the feasibility of a new generation of systems, with new capabilities, capable of missions that conventional vehicles cannot be empirically redesigned to perform. These methods provide a more complete understanding of a concept's design space, forecasting the feasibility of uncertain systems, but are often computationally expensive and time consuming to prepare. This trend creates a unique and critical need to identify a manageable number of capable concept alternatives early in the design process. Ongoing efforts attempting to stretch capability through new architectures, like the U.S. Army's Future Vertical Lift effort and DARPA's Vertical Takeoff and Landing (VTOL) X-plane program highlight this need. The process of identifying and selecting a concept configuration is often given insufficient attention, especially when a small subset of favorable concept families is not immediately apparent. Commonly utilized methods for concept generation, like filtered morphological analysis, often identify an exponential number of alternatives. Simple approaches to concept selection then rely on designers to identify a relatively small subset of alternatives for comparison through simple methods regularly related to decision matrices (Pugh, TOPSIS, AHP, etc.). More in-depth approaches utilize modeling and simulation to compare concepts with techniques such as stochastic optimization or probabilistic decision making, but a complicated setup limits these approaches to just a discrete few alternatives. A new framework to identify and select promising, robust concept configurations utilizing fuzzy methods is proposed in this research and applied to the example problem of concept selection for DARPA's VTOL Xplane program. The framework leverages fuzzy systems in conjunction with morphological analysis to assess large design spaces of potential architecture alternatives while capturing the inherent uncertainty and ambiguity in the evaluation of these early concepts. Experiments show how various fuzzy systems can be utilized for evaluating criteria of interest across disparate architectures by modeling expert knowledge as well as simple physics-based data. The models are integrated into a single environment and variations on multi-criteria optimization are tested to demonstrate an ability to identify a non-dominated set of architectural families in a large combinatorial design space. The resulting framework is shown to provide an approach to quickly identify promising concepts in the face of uncertainty early in the design process.
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ItemAn IPPD approach providing a modular framework to closing the capability gap and preparing a 21st century workforce(Georgia Institute of Technology, 2014-04-09) Zender, FabianThe United States are facing a critical workforce challenge, even though current unemployment is around 6.7%, employers find it difficult to find applicants that can satisfy all job requirements. This problem is especially pronounced in the manufacturing sector where a critical skills gap has developed, a problem that is exasperated by workforce demographics. A large number of employees across the various manufacturing sub-disciplines are eligible to retire now or in the near future. This gray tsunami requires swift action as well as long lasting change resulting in a workforce pipeline that can provide Science, Technology, Engineering, and Mathematics (STEM) majors in sufficient quantity and quality to satisfy not only the needs of STEM industries, but also of those companies outside of the STEM sector that hire STEM graduates. The research shown here will identify overt symptoms describing the capability gap, will identify specific skills describing the gap, educational causes why the gaps has not yet been addressed or is difficult to address, and lastly educational remedies that can contribute to closing the capability gap. A significant body of literature focusing on engineering in higher education has been evaluated and findings will be presented here. A multidisciplinary, collaborative capstone program will be described which implements some of the findings from this study in an active learning environment for students working on distributed teams across the US. Preliminary findings regarding the impact of these measures on the quantity of engineers to the US economy will be evaluated.
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ItemAn integrated product – process development (IPPD) based approach for rotorcraft drive system sizing, synthesis and design optimization(Georgia Institute of Technology, 2013-07-02) Ashok, Sylvester VikramEngineering design may be viewed as a decision making process that supports design tradeoffs. The designer makes decisions based on information available and engineering judgment. The designer determines the direction in which the design must proceed, the procedures that need to be adopted, and develops a strategy to perform successive decisions. The design is only as good as the decisions made, which is in turn dependent on the information available. Information is time and process dependent. This thesis work focuses on developing a coherent bottom-up framework and methodology to improve information transfer and decision making while designing complex systems. The rotorcraft drive system is used as a test system for this methodology. The traditional serial design approach required the information from one discipline and/or process in order to proceed with the subsequent design phase. The Systems Engineering (SE) implementation of Concurrent Engineering (CE) and Integrated Product and Process Development (IPPD) processes tries to alleviate this problem by allowing design processes to be performed in parallel and collaboratively. The biggest challenge in implementing Concurrent Engineering is the availability of information when dealing with complex systems such as aerospace systems. The information is often incomplete, with large amounts of uncertainties around the requirements, constraints and system objectives. As complexity increases, the design process starts trending back towards a serial design approach. The gap in information can be overcome by either “softening” the requirements to be adaptable to variation in information or to delay the decision. Delayed decisions lead to expensive modifications and longer product design lifecycle. Digitization of IPPD tools for complex system enables the system to be more adaptable to changing requirements. Design can proceed with “soft” information and decisions adapted as information becomes available even at early stages. The advent of modern day computing has made digitization and automation possible and feasible in engineering. Automation has demonstrated superior capability in design cycle efficiency [1]. When a digitized framework is enhanced through automation, design can be made adaptable without the requirement for human interaction. This can increase productivity, and reduce design time and associated cost. An important aspect in making digitization feasible is having the availability of parameterized Computer Aided Design (CAD) geometry [2]. The CAD geometry gives the design a physical form that can interact with other disciplines and geometries. Central common CAD database allows other disciplines to access information and extract requirements; this feature is of immense importance while performing systems syntheses. Through database management using a Product Lifecycle Management (PLM) system, Integrated Product Teams (IPTs) can exchange information between disciplines and develop new designs more efficiently by collaborating more and from far [3]. This thesis focuses on the challenges associated with automation and digitization of design. Making more information available earlier goes jointly with making the design adaptable to new information. Using digitized sizing, synthesis, cost analysis and integration, the drive system design is brought in to early design. With modularity as the objective, information transfer is made streamlined through the use of a software integration suite. Using parametric CAD tools, a novel ‘Fully-Relational Design’ framework is developed where geometry and design are adaptable to related geometry and requirement changes. During conceptual and preliminary design stages, the airframe goes through many stages of modifications and refinement; these changes affect the sub-system requirements and its design optimum. A fully-relational design framework takes this into account to create interfaces between disciplines. A novel aspect of the fully-relational design methodology is to include geometry, spacing and volume requirements in the system design process. Enabling fully-relational design has certain challenges, requiring suitable optimization and analysis automation. Also it is important to ensure that the process does not get overly complicated. So the method is required to possess the capability to intelligently propagate change. There is a need for suitable optimization techniques to approach gear train type design problems, where the design variables are discrete in nature and the values a variables can assume is a result of cascading effects of other variables. A heuristic optimization method is developed to analyze this multimodal problem. Experiments are setup to study constraint dependencies, constraint-handling penalty methods, algorithm tuning factors and innovative techniques to improve the performance of the algorithm. Inclusion of higher fidelity analysis in early design is an important element of this research. Higher fidelity analyses such as nonlinear contact Finite Element Analysis (FEA) are useful in defining true implied stresses and developing rating modification factors. The use of Topology Optimization (TO) using Finite Element Methods (FEM) is proposed here to study excess material removal in the gear web region.
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ItemA framework for analyzing unmanned aircraft system integration into the national airspace system using a target level of safety approach(Georgia Institute of Technology, 2013-03-08) Melnyk, Richard V.Unmanned Aircraft Systems (UAS) represent a significant potential for growth in the aerospace industry. Their use in military operations has increased exponentially in the last decade alone, requiring a corresponding increase in training airspace in the United States. In addition to military usage, UAS have the potential to fulfill a myriad of roles for both the public and private sectors. However, the use of UAS has been limited in the National Airspace System (NAS) to military and public applications and only under fairly restrictive Certificates of Authorization or Waiver (COA). The only way to truly realize the potential of UAS is to fully integrate them into the NAS. The desire to integrate UAS was recently codified into law with the 2012 FAA Modernization Act, mandating integration by specific, fairly short timelines. There are several challenges currently preventing the full integration of UAS that range from technological to procedural areas. However, the one common theme in all of these challenges is Safety. Across the literature on this topic there is no consensus on how safe UAS need to be to achieve integration, whether UAS can currently meet specified safety targets, and if not, what is the best way to achieve the safety goals. The purpose of this effort was to demonstrate a comprehensive framework for analyzing UAS integration efforts using a Target Level of Safety (TLS) approach. Using reliability tools, aircraft encounter models, and data from a wide variety of sources ranging from manned aircraft safety, explosives, falling debris and earthquake damage, the primary outcome of the effort was a better understanding of the risk to second and third party persons as a result of UAS operations in the NAS. This framework and associated models are validated using reliability and casualty data from manned aircraft operations. The framework is then applied to several relevant and specific cases to demonstrate the impact of policy decisions on UAS reliability and allowed operational areas. The supporting research and analysis can serve as a baseline for future integration analysis and decision-making efforts, and was designed to allow stakeholders and decision makers in this field to assess UAS safety, and set minimum system reliability requirements and mitigation system effectiveness standards.