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This paper presents the status of the long-term experiment using a hybrid GPS/acoustic system to determine strain rates across the Cascadia subduction zone.
This paper presents the system architecture and processing algorithms.
Topics covered include: Crew Activity Analyzer; Distributing Data to Hand-Held Devices in a Wireless Network; Reducing Surface Clutter in Cloud Profiling Radar Data; MODIS Atmospheric Data Handler; Multibeam Altimeter Navigation Update Using Faceted Shape Model; Spaceborne Hybrid-FPGA System for Processing FTIR Data; FPGA Coprocessor for Accelerated Classification of Images; SiC JFET Transistor Circuit Model for Extreme Temperature Range; TDR Using Autocorrelation and Varying-Duration Pulses; Update on Development of SiC Multi-Chip Power Modules; Radio Ranging System for Guidance of Approaching Spacecraft; Electromagnetically Clean Solar Arrays; Improved Short-Circuit Protection for Power Cells in Series; Electromagnetically Clean Solar Arrays; Logic Gates Made of N-Channel JFETs and Epitaxial Resistors; Improved Short-Circuit Protection for Power Cells in Series; Communication Limits Due to Photon-Detector Jitter; System for Removing Pollutants from Incinerator Exhaust; Sealing and External Sterilization of a Sample Container; Converting EOS Data from HDF-EOS to netCDF; HDF-EOS 2 and HDF-EOS 5 Compatibility Library; HDF-EOS Web Server; HDF-EOS 5 Validator; XML DTD and Schemas for HDF-EOS; Converting from XML to HDF-EOS; Simulating Attitudes and Trajectories of Multiple Spacecraft; Specialized Color Function for Display of Signed Data; Delivering Alert Messages to Members of a Work Force; Delivering Images for Mars Rover Science Planning; Oxide Fiber Cathode Materials for Rechargeable Lithium Cells; Electrocatalytic Reduction of Carbon Dioxide to Methane; Heterogeneous Superconducting Low-Noise Sensing Coils; Progress toward Making Epoxy/Carbon-Nanotube Composites; Predicting Properties of Unidirectional-Nanofiber Composites; Deployable Crew Quarters; Nonventing, Regenerable, Lightweight Heat Absorber; Miniature High-Force, Long-Stroke SMA Linear Actuators; "Bootstrap" Configuration for Multistage Pulse-Tube Coolers; Reducing Liquid Loss during Ullage Venting in Microgravity; Ka-Band Transponder for Deep-Space Radio Science; Replication of Space-Shuttle Computers in FPGAs and ASICs; Demisable Reaction-Wheel Assembly; Spatial and Temporal Low-Dimensional Models for Fluid Flow; Advanced Land Imager Assessment System; Range Imaging without Moving Parts.
A class of problems in air traffic management asks for a scheduling algorithm that supplies the air traffic services authority not only with a schedule of arrivals and departures, but also with speed advisories. Since advisories must be finite, a scheduling algorithm must ultimately produce a finite data set, hence must either start with a purely discrete model or involve a discretization of a continuous one. The former choice, often preferred for intuitive clarity, naturally leads to mixed-integer programs, hindering proofs of correctness and computational cost bounds (crucial for real-time operations). In this paper, a hybrid control system is used to model air traffic scheduling, capturing both the discrete and continuous aspects. This framework is applied to a class of problems, called the Fully Routed Nominal Problem. We prove a number of geometric results on feasible schedules and use these results to formulate an algorithm that attempts to compute a collective speed advisory, effectively finite, and has computational cost polynomial in the number of aircraft. This work is a first step toward optimization and models refined with more realistic detail.
Numerical algorithms lie at the heart of many safety-critical aerospace systems. The complexity and hybrid nature of these systems often requires the use of interactive theorem provers to verify that these algorithms are logically correct. Usually, proofs involving numerical computations are conducted in the infinitely precise realm of the field of real numbers. However, numerical computations in these algorithms are often implemented using floating point numbers. The use of a finite representation of real numbers introduces uncertainties as to whether the properties veri ed in the theoretical setting hold in practice. This short paper describes work in progress aimed at addressing these concerns. Given a formally proven algorithm, written in the Program Verification System (PVS), the Frama-C suite of tools is used to identify sufficient conditions and verify that under such conditions the rounding errors arising in a C implementation of the algorithm do not affect its correctness. The technique is illustrated using an algorithm for detecting loss of separation among aircraft.
In order to address the increasing communications needs of modern equipment in space, and to address the increasing number of objects in space, NASA is demonstrating the potential capability of optical communications for both deep space and near-Earth applications. The Integrated Radio Optical Communications (iROC) is a hybrid communications system that capitalizes on the best of both the optical and RF domains while using each technology to compensate for the other's shortcomings. Specifically, the data rates of the optical links can be higher than their RF counterparts, whereas the RF links have greater link availability. The focus of this paper is twofold: to consider the operations of one or more iROC nodes from a networking point of view, and to suggest specific areas of research to further the field. We consider the utility of Disruption Tolerant Networking (DTN) and the Virtual Mission Operation Center (VMOC) model.
NASA continues to advance plans to extend human presence beyond low-Earth orbit leading to human exploration of Mars. The plans being laid out follow an incremental path, beginning with initial flight tests followed by deployment of a Deep Space Gateway (DSG) in cislunar space. This Gateway, will serve as the initial transportation node for departing and returning Mars spacecraft. Human exploration of Mars represents the next leap for humankind because it will require leaving Earth on a long mission with very limited return, rescue, or resupply capabilities. Although Mars missions are long, approaches and technologies are desired which can reduce the time that the crew is away from Earth. This paper builds off past analyses of NASA's exploration strategy by providing more detail on the performance of alternative in-space transportation options with an emphasis on reducing total mission duration. Key options discussed include advanced chemical, nuclear thermal, nuclear electric, solar electric, as well as an emerging hybrid propulsion system which utilizes a combination of both solar electric and chemical propulsion.
Hybrid propulsion is currently favored for a Mars Ascent Vehicle (MAV) concept from a thermal performance and Gross Lift Off Mass standpoint. However, it is at a relatively low level of maturity compared to conventional propulsion options. Technology development efforts are currently underway to bring hybrid propulsion to a technology readiness level that would enable its infusion into potential Mars Sample Return. A new propellant combination is being considered for this design that has excellent low temperature behavior. Preliminary results of two ground test campaigns are currently underway to characterize this propellant combination. Hotfire testing is being carried out in parallel at Parabilis Space Technologies and Space Propulsion Group. In addition to the new propellant combination, several other technologies are being pursued for a potential hybrid MAV: hypergolic ignition and Liquid Injection Thrust Vector Control. Both of these technologies have been applied in other rocket applications, e.g. liquid propulsion commonly uses hypergolic propellants and missiles, such as the Minuteman II, have used LITVC in the past. Hypergolic ignition, when oxidizer and fuel combust upon contact, is highly desirable for multiple starts required by the MAV concept. Therefore, testing at Penn State and Purdue is being completed in this area. An updated hybrid propulsion system design for a Mars Ascent Vehicle concept based on JPL’s current understanding of potential Mars Sample Return requirements will be presented, leveraging the advances in technology development as well as updated understanding of how requirements may evolve.
A Mars Ascent Vehicle (MAV) would be a critical part of a potential Mars sample return campaign. As currently envisioned, the MAV would launch samples from Mars into Mars orbit. Challenging requirements would be placed on a MAV as it would need to be able to survive in the harsh Martian environment which can get as cold as -120°C in the winter. At these cold temperatures, survival heating could be necessary to keep the MAV within the allowable flight temperature range. Estimates for survival heating power show that a fuel capable of operating at low temperature would significantly reduce the total required energy of the MAV. This has led to consideration of a hybrid propulsion system due to its anticipated low temperature capability. A new wax-based fuel, SP7, has been developed for a notional MAV mission. Thermal modeling of the fuel in the Mars environment was completed in order to estimate the temperature response of the fuel during Mars diurnal temperature cycling. Preliminary thermal testing was conducted to determine the max temperature range, radial gradient, and ramp rate the fuel could tolerate without cracking. The modeling and preliminary testing was used to develop a comprehensive, 100-day thermal cycling campaign. A total of 200 cycles are planned that are representative of 200 Martian diurnal cycles, roughly one-third of a Martian year. After 150 cycles, the fuel samples show no signs of cracking that would jeopardize the rocket’s performance. Though not yet complete, this testing is showing that SP7 has the potential to successfully be used on a MAV mission.
Lifetime data is presented for ruggedized commercial NPRO lasers used in the Tropospheric Emission Spectrometer (TES) Instrument on NASA’s Aura Earth-orbiting spacecraft, including 20 years of data from two life test units on the ground, 12 years of on-orbit data from TES Laser A, and 2 years of on-orbit data from TES Laser B. The TES lasers are diode-pumped Non-Planar Ring Oscillator (NPRO) lasers using Nd:YAG crystals. Since accelerated life testing was not possible on the complete laser, early prototype lasers that had gone through thermal cycling and vibration testing were placed on non-accelerated life tests with the hope of gathering at least a couple of years of data before launch. Long-term lifetime data for hybrid laser systems in space applications is not abundant, and out of necessity, accelerated reliability testing is usually done over a relatively short time with a large number of devices. The data presented in this paper is unique as it tracks the optical power output over time of a total of four lasers on the order of decades rather than months or years. Two of the lasers have each been on life test for over 20 years on the ground and are still operating, and the other two lasers have been on-orbit for 14 years. TES Laser A was still operating when the TES Instrument was decommissioned in January 2018. Therefore, the data presented covers over 450,000 non-accelerated device-hours, with 23% of those hours being in space.
NASA's Human Exploration and Operation Mission Directorate is continuing to study different concepts and options to field human Mars missions as part of NASA's Moon2Mars directive. In this study, an update to the Hybrid propulsion system was established with the introduction of nuclear electric propulsion system to replace the solar electric propulsion system in an effort to understand the potential impact of a shorter mission to Mars. For crewed missions to Mars, the transportation system sizing is highly dependent on the type of mission and the mission duration. An integrated trajectory analysis capability has been developed and updated to enable this investigation. Longer duration mission may utilize higher efficiency low thrust propulsion system more, but would require higher payload mass due to increase to crew logistics loading and habitation volume. Conversely, shorter duration mission may have lower payload mass, but will require significant increase to propulsion system performance and/or overall system mass. An overall integrated design trade space is defined in this paper to investigate the tradeoff between these scenarios to illuminate the optimality of the transportation system option from a mass perspective. The sensitivity analysis developed in this study will be crucial to understanding the Mars mission design trade space for crewed Mars missions, and will help inform design decisions and investment strategies.
The Subsonic Single Aft Engine (SUSAN) Electrofan is a new single-aisle regional jet class transport aircraft being studied by NASA, which benefits from reduced fuel consumption through a reduction in the number of hydrocarbon fuel-burning engines from two to one. This is achieved through a hybrid-electric system architecture, where a series of generators are used to extract power from a fuel-consuming tail cone thruster to drive electric propulsors mounted on the wings. To support the development of these propulsion systems, which involve high levels of propulsion-airframe integration, this paper presents high-fidelity analyses through computational fluid dynamics (CFD) simulations provided by the Launch Ascent and Vehicle Aerodynamics (LAVA) framework, which also includes capabilities for modeling the effect of active propulsors. A trade space exploration is performed to investigate the advantages of several wing mounted distributed electric propulsion system configurations, including over-wing, under-wing, and trailing-edge arrangements. For the aft fuselage propulsor, focus is on the sizing of the inlet, core, and bypass ducts. High-fidelity aerodynamic shape optimization is also used to help minimize the inlet distortion intensity experienced by the aft propulsor fan through a reshaping of the fuselage.
This design report summarizes work performed by the Boeing Subsonic Ultra-Green Aircraft Research (SUGAR) team from December 2016 through June 2018. In Phase IV of the SUGAR program, Boeing is working to improve the productivity of a TTBW configuration by updating the Mach 0.745 vehicle concept to operate efficiently at Mach 0.80. Due to the aerodynamic and structural design challenges associated with adapting the design to a higher speed, design tasks have been broken into several subtasks. The information in this report (Volume I) documents the development of a Mach 0.80 vehicle outer mold line, maturation of TTBW structural concepts, and presents a preliminary high-liftsystem assessment. Results from these studies were integrated into an aircraft-level performance code that estimates the benefits of TTBW technology, both on its own and as a part of the SUGAR integrated technology suite. The aerodynamic performance results presented herein detail the high cruise efficiency of the TTBW concept operating at M=0.80. Results from the RANS code OVERFLOW indicate that the TTBW is aerodynamically well suited for operation at the design M=0.80 transonic cruise Mach number. Aircraft-level performance predictions show that the TTBW offers a 7.2% improvement in fuel burn (per seat) for an economic mission of 900nm, and a 9.0% improvement in fuel burn (per seat) for a 3500nm mission with full passenger payload, relative to an aspect ratio 13 conventional tube and wing configuration of equivalent technology. Integration of the TTBW performance benefits into the SUGAR technology suite shows a 55.9% reduction in fuel burn (for the economic mission) relative to the reference (SUGAR Free) aircraft, which is a consistently sized traditional cantilever wing, single-aisle transport typical of the 2008 fleet. This benefit does not include the performance improvement potential of hybrid-electric systems studied in earlier phases of the SUGAR program Structural concept development work completed in Phase IV has identified several strut attachment concepts that are worth additional development activity – an inboard strut attachment swivel joint concept (which enables the strut to carry axial loads while avoiding strut bending induced by wing twist during flight) significantly simplifies the construction of the main strut. An outboard offset strut attachment concept holds significant potential for further reductions in wing-strut interference drag. Based on work performed to date on Phase IV and the previous phases of the SUGAR program, the TTBW concept continues to remain a viable concept for significantly improving the performance of future aircraft. High-fidelity aerodynamic analysis of the Mach 0.80 TTBW aircraft has shown fuel burn improvement that has exceeded initial expectations despite the increase in cruise Mach number. Structural concept maturation has continued to refine the TTBW structure, and has found no obvious ‘show-stoppers’ to date. Therefore, the potential benefit of improved performance through the use of a very high aspect ratio strut-braced wing continues to warrant additional study
Effective deployment of machine-learning (ML) models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a user-friendly app that has been created to deploy trained machine-learning (ML) models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of ML application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). The app gets user input for a turbofan design, preprocesses the input data, and deploys trained ML models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The ML predictive models were built by employing supervised deep-learning and K-nearest neighbor regression algorithms to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these ML models using the app shows that Aero-Engines AI is an easy-touse and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage. Current version of the app focuses on the performance prediction of conventional turbofans. However, the scope of the app can easily be expanded to include other engine types (such as turboshaft and hybrid-electric systems) after their ML models are developed. Overall, the use of a machine-learning app for aircraft engine concept assessment represents a promising area of development in aircraft engine conceptual design.
Runtime assurance is a control framework where a complex controller operates under the observation of a monitor. If the monitor detects the controller exhibiting undesirable behavior, control is passed off to a trusted controller until a desirable state is regained. The runtime assurance architecture provides a layer of assurance to the system being controlled, but special care must be taken that the resulting overall system, consisting of the monitors and controllers, is behaving as intended. This talk aims to formally model and reason about runtime assurance-equipped systems as hybrid programs- which are models that consist of both discrete and continuous components. Using the verification tool Plaidypvs, safety properties of some examples involving RTA architectures is shown.
In support of the Electrified Powertrain Flight Demonstrator and Advanced Air Transport Technologies projects at NASA, a new tool has been developed at NASA’s Ames and Glenn Research Centers to enable coupled engine and airframe optimization and analysis. The new tool combines the engineering-level analysis methods and empirical models of the FORTRAN General Aviation Synthesis Program (GASP) with the Python-based OpenMDAO framework to provide a modular framework for efficient gradient-based optimization with the aim of incorporating new subsystem models for unconventional configurations. The tool has been verified against GASP analyses of several aircraft models and mission formulations. Preliminary efforts have been made to integrate pyCycle, a thermodynamic cycle analysis tool, to enable simultaneous optimization of hybrid propulsion system and vehicle parameters while taking full mission performance and constraints into account. This will improve current capabilities to assess impacts of electrified powertrain technologies on future aircraft designs.
In support of the Electrified Powertrain Flight Demonstrator and Advanced Air Transport Technologies projects at NASA, a new tool has been developed at NASA's Ames and Glenn Research Centers to enable coupled engine and airframe optimization and analysis. The new tool combines the engineering-level analysis methods and empirical models of the FORTRAN General Aviation Synthesis Program (GASP) with the Python-based OpenMDAO framework to provide a modular framework for efficient gradient-based optimization with the aim of incorporating new subsystem models for unconventional configurations. The tool has been verified against GASP analyses of several aircraft models and mission formulations. Preliminary efforts have been made to integrate pyCycle, a thermodynamic cycle analysis tool, to enable simultaneous optimization of hybrid propulsion system and vehicle parameters while taking full mission performance and constraints into account. This will improve current capabilities to assess impacts of electrified powertrain technologies on future aircraft designs.