Solar Airplane Conceptual Design and Performance Estimation: What Size to Choose and What Endurance to Expect

Solar airplanes exhibit a fascination due to their energy sustainability aspect and the potential for sustained flight lasting several day-night cycles. Resulting monitoring and measurement applications at high altitudes but also close to the Earth surface would be extremely useful and are targeted by several research groups and institutions. The question of how to choose the main design parameters of the airplane for a specific mission, considering the current state-of-the-art technologies involved, however, is not easy to answer. A tool is presented performing such a multi-disciplinary optimization. Solar airplanes using both batteries as energy storage devices as well as their capability of flying performance-optimizing altitude profiles can be sized and evaluated in terms of various performance measures. Simulation results show that sustained flight in the Stratosphere is hard to achieve, if the altitude needs to be kept constant. A simulated Remote Control (RC) model size solar airplane allowed to vary altitude proves to be capable of flying multiple day-night cycles at medium and high latitudes during summe

Multidisciplinary Design Optimization of an Extreme Aspect Ration HALE UAV

Development of High Altitude Long Endurance (HALE) aircraft systems is part of a vision for a low cost communications/surveillance capability. Applications of a multi payload aircraft operating for extended periods at stratospheric altitudes span military and civil genres and support battlefield operations, communications, atmospheric or agricultural monitoring, surveillance, and other disciplines that may currently require satellite-based infrastructure. The central goal of this research was the development of a multidisciplinary tool for analysis, design, and optimization of HALE UAVs, facilitating the study of a novel configuration concept. Applying design ideas stemming from a unique WWII-era project, a pinned wing HALE aircraft would employ self-supporting wing segments assembled into one overall flying wing. When wrapped in an optimization routine, the integrated design environment shows potential for a 17.3% reduction in weight when wing thickness to chord ratio, aspect ratio, wing loading, and power to weight ratio are included as optimizer-controlled design variables. Investigation of applying the sustained day/night mission requirement and improved technology factors to the design shows that there are potential benefits associated with a segmented or pinned wing. As expected, wing structural weight is reduced, but benefits diminish as higher numbers of wing segments are considered. For an aircraft consisting of six wing segments, a maximum of 14.2% reduction in gross weight over an advanced technology optimal baseline is predicted

The HAMMER: High altitude multiple mission environmental researcher

At the equator, the ozone layer ranges from 65,000 to 130,000+ feet which is beyond the capabilities of the ER-2, NASA's current high altitude reconnaissance aircraft. The Universities Space Research Association, in cooperation with NASA, is sponsoring an undergraduate program which is geared to designing an aircraft that can study the ozone layer at the equator. This aircraft must be able to satisfy four mission profiles. Mission one is a polar mission which ranges from Chile to the South Pole and back to Chile, a total range of 6000 n. mi. at 100,000 feet with a 2500 lb. payload. The second mission is also a polar mission with a decreased altitude of 70,000 feet and an increased payload of 4000 lb. For the third mission, the aircraft will take-off at NASA Ames, cruise at 100,000 feet carrying a 2500 lb. payload, and land in Puerto Montt, Chile. The final mission requires the aircraft to take-off at NASA Ames, cruise at 100,000 feet with a 1000 lb. payload, make an excursion to 120,000 feet, and land at Howard AFB, Panama. All three missions require that a subsonic Mach number is maintained due to constraints imposed by the air sampling equipment. The aircraft need not be manned for all four missions. Three aircraft configurations were determined to be the most suitable for meeting the above requirements. The performance of each configuration is analyzed to investigate the feasibility of the project requirements. In the event that a requirement can not be obtained within the given constraints, recommendations for proposal modifications are given

The design of aircraft using the decision support problem technique

The Decision Support Problem Technique for unified design, manufacturing and maintenance is being developed at the Systems Design Laboratory at the University of Houston. This involves the development of a domain-independent method (and the associated software) that can be used to process domain-dependent information and thereby provide support for human judgment. In a computer assisted environment, this support is provided in the form of optimal solutions to Decision Support Problems

Evaluation of Direct Search Algorithms to Trajectory Optimization for a Perpetually Flying Fixed-Wing Solar UAV Providing Network Coverage

Recent advances in battery and solar-cell technology have allowed for small-scale solar-powered fixed-wing aircraft to achieve perpetual-endurance flight, where they harvest enough energy to fly for long periods of time without recharging. We consider how this capability can be utilized in a networking context to enable rapid deployment of wireless Internet coverage in areas where it has been disrupted or is otherwise unavailable, providing a relay between portable ground-based devices such as cell phones and the currently developing Very-Low-Earth-Orbit satellite Internet layer. In particular, we investigate the impact of the aircraft trajectory on the level of service provided and the energy balance of the vehicle. We develop a framework for evaluating and optimizing these trajectories in three-dimensions and compare two optimization methods, Particle Swarm Optimization and the Nelder-Mead method, in optimizing the throughput of the trajectory while respecting the energy constraints implicit to providing perpetual-endurance flight.Master of ScienceComputer ScienceUniversity of Michigan-Flinthttp://deepblue.lib.umich.edu/bitstream/2027.42/167240/1/Miller2021.pdfDescription of Miller2021.pdf : thesi

A Biomimetic, Energy-Harvesting, Obstacle-Avoiding, Path-Planning Algorithm for UAVs

This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class. The results show that, in mountainous regions, substantial energy can be recovered, depending on topography and wind characteristics. For the examples presented, as much as 50% of the energy was recovered for a complex, multi-heading, multi-altitude, 170 km mission in an average wind speed of 9 m/s. The algorithms constitute a Generic Intelligent Control Algorithm (GICA) for autonomous unmanned aerial vehicles that enables an extraction of atmospheric energy while completing a mission trajectory. At the same time, the algorithm automatically adjusts the flight path in order to avoid obstacles, in a fashion not unlike what one would expect from living organisms, such as birds and insects. This multi-disciplinary approach renders the approach biomimetic, i.e. it constitutes a synthetic system that “mimics the formation and function of biological mechanisms and processes.

A methodology for the validated design space exploration of fuel cell powered unmanned aerial vehicles

Unmanned Aerial Vehicles (UAVs) are the most dynamic growth sector of the aerospace industry today. The need to provide persistent intelligence, surveillance, and reconnaissance for military operations is driving the planned acquisition of over 5,000 UAVs over the next five years. The most pressing need is for quiet, small UAVs with endurance beyond what is capable with advanced batteries or small internal combustion propulsion systems. Fuel cell systems demonstrate high efficiency, high specific energy, low noise, low temperature operation, modularity, and rapid refuelability making them a promising enabler of the small, quiet, and persistent UAVs that military planners are seeking. Despite the perceived benefits, the actual near-term performance of fuel cell powered UAVs is unknown. Until the auto industry began spending billions of dollars in research, fuel cell systems were too heavy for useful flight applications. However, the last decade has seen rapid development with fuel cell gravimetric and volumetric power density nearly doubling every 2-3 years. As a result, a few design studies and demonstrator aircraft have appeared, but overall the design methodology and vehicles are still in their infancy. The design of fuel cell aircraft poses many challenges. Fuel cells differ fundamentally from combustion based propulsion in how they generate power and interact with other aircraft subsystems. As a result, traditional multidisciplinary analysis (MDA) codes are inappropriate. Building new MDAs is difficult since fuel cells are rapidly changing in design, and various competitive architectures exist for balance of plant, hydrogen storage, and all electric aircraft subsystems. In addition, fuel cell design and performance data is closely protected which makes validation difficult and uncertainty significant. Finally, low specific power and high volumes compared to traditional combustion based propulsion result in more highly constrained design spaces that are problematic for design space exploration. To begin addressing the current gaps in fuel cell aircraft development, a methodology has been developed to explore and characterize the near-term performance of fuel cell powered UAVs. The first step of the methodology is the development of a valid MDA. This is accomplished by using propagated uncertainty estimates to guide the decomposition of a MDA into key contributing analyses (CAs) that can be individually refined and validated to increase the overall accuracy of the MDA. To assist in MDA development, a flexible framework for simultaneously solving the CAs is specified. This enables the MDA to be easily adapted to changes in technology and the changes in data that occur throughout a design process. Various CAs that model a polymer electrolyte membrane fuel cell (PEMFC) UAV are developed, validated, and shown to be in agreement with hardware-in-the-loop simulations of a fully developed fuel cell propulsion system. After creating a valid MDA, the final step of the methodology is the synthesis of the MDA with an uncertainty propagation analysis, an optimization routine, and a chance constrained problem formulation. This synthesis allows an efficient calculation of the probabilistic constraint boundaries and Pareto frontiers that will govern the design space and influence design decisions relating to optimization and uncertainty mitigation. A key element of the methodology is uncertainty propagation. The methodology uses Systems Sensitivity Analysis (SSA) to estimate the uncertainty of key performance metrics due to uncertainties in design variables and uncertainties in the accuracy of the CAs. A summary of SSA is provided and key rules for properly decomposing a MDA for use with SSA are provided. Verification of SSA uncertainty estimates via Monte Carlo simulations is provided for both an example problem as well as a detailed MDA of a fuel cell UAV. Implementation of the methodology was performed on a small fuel cell UAV designed to carry a 2.2 kg payload with 24 hours of endurance. Uncertainty distributions for both design variables and the CAs were estimated based on experimental results and were found to dominate the design space. To reduce uncertainty and test the flexibility of the MDA framework, CAs were replaced with either empirical, or semi-empirical relationships during the optimization process. The final design was validated via a hardware-in-the loop simulation. Finally, the fuel cell UAV probabilistic design space was studied. A graphical representation of the design space was generated and the optima due to deterministic and probabilistic constraints were identified. The methodology was used to identify Pareto frontiers of the design space which were shown on contour plots of the design space. Unanticipated discontinuities of the Pareto fronts were observed as different constraints became active providing useful information on which to base design and development decisions.Ph.D.Committee Chair: Mavris, Dimitri; Committee Member: Nam, Taewoo; Committee Member: Parekh, David; Committee Member: Soban, Danielle; Committee Member: Volovoi, Vital

Reference Model for Interoperability of Autonomous Systems

This thesis proposes a reference model to describe the components of an Un-manned Air, Ground, Surface, or Underwater System (UxS), and the use of a single Interoperability Building Block to command, control, and get feedback from such vehicles. The importance and advantages of such a reference model, with a standard nomenclature and taxonomy, is shown. We overview the concepts of interoperability and some efforts to achieve common refer-ence models in other areas. We then present an overview of existing un-manned systems, their history, characteristics, classification, and missions. The concept of Interoperability Building Blocks (IBB) is introduced to describe standards, protocols, data models, and frameworks, and a large set of these are analyzed. A new and powerful reference model for UxS, named RAMP, is proposed, that describes the various components that a UxS may have. It is a hierarchical model with four levels, that describes the vehicle components, the datalink, and the ground segment. The reference model is validated by showing how it can be applied in various projects the author worked on. An example is given on how a single standard was capable of controlling a set of heterogeneous UAVs, USVs, and UGVs