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NASA NTRS1998

Advanced Space Propulsion System Flowfield Modeling

Solar thermal upper stage propulsion systems currently under development utilize small low chamber pressure/high area ratio nozzles. Consequently, the resulting flow in the nozzle is highly viscous, with the boundary layer flow comprising a significant fraction of the total nozzle flow area. Conventional uncoupled flow methods which treat the nozzle boundary layer and inviscid flowfield separately by combining the two calculations via the influence of the boundary layer displacement thickness on the inviscid flowfield are not accurate enough to adequately treat highly viscous nozzles. Navier Stokes models such as VNAP2 can treat these flowfields but cannot perform a vacuum plume expansion for applications where the exhaust plume produces induced environments on adjacent structures. This study is built upon recently developed artificial intelligence methods and user interface methodologies to couple the VNAP2 model for treating viscous nozzle flowfields with a vacuum plume flowfield model (RAMP2) that is currently a part of the Plume Environment Prediction (PEP) Model. This study integrated the VNAP2 code into the PEP model to produce an accurate, practical and user friendly tool for calculating highly viscous nozzle and exhaust plume flowfields.

Smith, Sheldon↗

NASA NTRS2013

Autonomous Cryogenic Load Operations: Knowledge-Based Autonomous Test Engineer

The Knowledge-Based Autonomous Test Engineer (KATE) program has a long history at KSC. Now a part of the Autonomous Cryogenic Load Operations (ACLO) mission, this software system has been sporadically developed over the past 20 years. Originally designed to provide health and status monitoring for a simple water-based fluid system, it was proven to be a capable autonomous test engineer for determining sources of failure in the system. As part of a new goal to provide this same anomaly-detection capability for a complicated cryogenic fluid system, software engineers, physicists, interns and KATE experts are working to upgrade the software capabilities and graphical user interface. Much progress was made during this effort to improve KATE. A display of the entire cryogenic system's graph, with nodes for components and edges for their connections, was added to the KATE software. A searching functionality was added to the new graph display, so that users could easily center their screen on specific components. The GUI was also modified so that it displayed information relevant to the new project goals. In addition, work began on adding new pneumatic and electronic subsystems into the KATE knowledge base, so that it could provide health and status monitoring for those systems. Finally, many fixes for bugs, memory leaks, and memory errors were implemented and the system was moved into a state in which it could be presented to stakeholders. Overall, the KATE system was improved and necessary additional features were added so that a presentation of the program and its functionality in the next few months would be a success.

Schrading, J. Nicolas↗

NASA NTRS1987

Definition and testing of the hydrologic component of the pilot land data system

The specific aim was to develop within the Pilot Land Data System (PLDS) software design environment, an easily implementable and user friendly geometric correction procedure to readily enable the georeferencing of imagery data from the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA series spacecraft. A software subsystem was developed within the guidelines set by the PLDS development environment utilizing NASA Goddard Space Flight Center (GSFC) Image Analysis Facility's (IAF's) Land Analysis Software (LAS) coding standards. The IAS current program development environment, the Transportable Applications Executive (TAE), operates under a VAX VMS operating system and was used as the user interface. A brief overview of the ICARUS algorithm that was implemented in the set of functions developed, is provided. The functional specifications decription is provided, and a list of the individual programs and directory names containing the source and executables installed in the IAF system are listed. A user guide is provided for the LAS system documentation format for the three functions developed.

Ragan, Robert M.↗

NASA NTRS2006

Modular Aero-Propulsion System Simulation

The Modular Aero-Propulsion System Simulation (MAPSS) is a graphical simulation environment designed for the development of advanced control algorithms and rapid testing of these algorithms on a generic computational model of a turbofan engine and its control system. MAPSS is a nonlinear, non-real-time simulation comprising a Component Level Model (CLM) module and a Controller-and-Actuator Dynamics (CAD) module. The CLM module simulates the dynamics of engine components at a sampling rate of 2,500 Hz. The controller submodule of the CAD module simulates a digital controller, which has a typical update rate of 50 Hz. The sampling rate for the actuators in the CAD module is the same as that of the CLM. MAPSS provides a graphical user interface that affords easy access to engine-operation, engine-health, and control parameters; is used to enter such input model parameters as power lever angle (PLA), Mach number, and altitude; and can be used to change controller and engine parameters. Output variables are selectable by the user. Output data as well as any changes to constants and other parameters can be saved and reloaded into the GUI later.

Parker, Khary I.↗

NASA NTRS2018

The InSAR Scientific Computing Environment 3.0: A Flexible Framework for NISAR Operational and User-Led Science Processing

The InSAR Scientific Computing Environment (ISCE) was first developed under the NASA Advanced Information Systems Technology as a flexible, extensible object-oriented framework for Interferometric Synthetic Aperture Radar (InSAR) processing. The ISCE framework uses Python 3 at the workflow level, controlling modules of compiled code for functional processing, and managing inputs, outputs, and other flow control services. The currently released version, called ISCE 2.1, is distributed to the research community through the Western North America InSAR Consortium under a research license. The ISCE team is working on the next generation of the code in order to prepare for the NASAISRO SAR (NISAR) mission operational processing. Innovations in this code include augmentation or conversion of the custom Python framework elements in ISCE with the Pyre framework, new workflows for interferometric and polarimetric stack processing, a more intuitive and graphically based user interface, and flow control for hybrid computing environments including CPU/GPU clusters, logging and error tracking facilities, and new more efficient computational modules that exploit graphical processor units (GPUs) when available. The ISCE 3.0 framework is designed to work in an operational environment as well as on a single user’s laptop or compute cluster, with services to discover capabilities and scale computations accordingly.

Buckley, Sean M.↗

NASA NTRSDate not supplied

Benefits of using Electronic Data Sheets (EDS) with coreFlight Systems (cFS) - A Project Example

Recently there has been interest in the incorporation of core Flight Systems (cFS) with Spacecraft Onboard Interface Services (SOIS) Electronic Data Sheets (EDS) in the spaceflight software community. The Regenerative Fuel Cell project at the Glenn Research Center is using cFS architecture with EDS support for its monitoring and control software. The presentation will outline the benefits to using cFS with EDS support: First, EDS establishes a single source of truth for the definitions of data structures used throughout an entire mission that may otherwise be programmed in different languages and designed with different processor architectures. Not only does this help with inter-application communication via the software bus, but it also greatly simplifies communication between systems. An EDS Application Programming Interface (API) library allows the conversion of EDS data structures to and from native data structures. Second, bindings for other programming languages (e.g. Lua, Python, JSON) have been written to allow the creation and manipulation of EDS data objects within those languages. The RFC project uses Lua scripts to automatically generate binary configuration files at build time to be loaded into our cFS programs. We also use Python bindings in a graphical user interface (GUI) to allow an operator to send commands and view telemetry messages sent from cFS instances. Finally, using Lua scripts we can set up specific simulation scenarios to perform automatic functional testing. During the development of the RFC software, the software team put together a generic python GUI called “cFS-EDS-GroundStation” that provides a basic interface to an instance of cFS with EDS support. The GUI includes a basic telecommand and telemetry system that reads directly from the generated EDS databases. In the telecommand system, dropdown menus are populated with all user commands that are defined in EDS. In the telemetry system, telemetry messages are automatically decoded, written to the screen, and saved to a binary file. Additional Python scripts have been written to convert the binary data files into a comma separated value (CSV) format for further processing. We will demonstrate the basic use of the cFS-EDS-GroundStation software including adding additional commands and telemetry payload values in EDS and see them appear automatically in the cFS-EDS-Groundstation software. About the RFC project: The Regenerative Fuel Cell project is tasked with developing and demonstrating a power system consisting of a fuel cell and electrolyzer to provide power during a lunar day/night cycle. During the night, the fuel cell takes Hydrogen and Oxygen gasses and converts them into electricity, water, and heat. During the day, the electrolyzer takes input power (e.g. from a photovoltaic array) and converts water back into Hydrogen and Oxygen gasses.

Mathew Mccaskey↗

NASA NTRS1994

Mission Operations Centers (MOCs): Integrating key spacecraft ground data system components

In an environment characterized by decreasing budgets, limited system development time, and user needs for increased capabilities, the Mission Operations Division (MOD) at the National Aeronautics and Space Administration Goddard Space Flight Center initiated a new, cost-effective concept in developing its spacecraft ground data systems: the Mission Operations Center (MOC). In the MOC approach, key components are integrated into a comprehensive and cohesive spacecraft planning, monitoring, command, and control system with a single, state-of-the-art graphical user interface. The MOD is currently implementing MOC's, which feature a common, reusable, and extendable system architecture, to support the X-Ray Timing Explorer (XTE), Tropical Rainfall Measuring Mission (TRMM), and Advanced Composition Explorer (ACE) missions. As a result of the MOC approach, mission operations are integrated, and users can, with a single system, perform real-time health and safety monitoring, real-time command and control, real-time attitude processing, real-time and predictive graphical spacecraft monitoring, trend analysis, mission planning and scheduling, command generation and management, network scheduling, guide star selection, and (using an expert system) spacecraft monitoring and fault isolation. The MOD is also implementing its test and training simulators under the new MOC management structure. This paper describes the MOC concept, the management approaches used in developing MOC systems, the technologies employed and the development process improvement initiatives applied in implementing MOC systems, and the expected benefits to both the user and the mission project in using the MOC approach.

Harbaugh, Randy↗

NASA NTRS1998

Six axis force feedback input device

The present invention is a low friction, low inertia, six-axis force feedback input device comprising an arm with double-jointed, tendon-driven revolute joints, a decoupled tendon-driven wrist, and a base with encoders and motors. The input device functions as a master robot manipulator of a microsurgical teleoperated robot system including a slave robot manipulator coupled to an amplifier chassis, which is coupled to a control chassis, which is coupled to a workstation with a graphical user interface. The amplifier chassis is coupled to the motors of the master robot manipulator and the control chassis is coupled to the encoders of the master robot manipulator. A force feedback can be applied to the input device and can be generated from the slave robot to enable a user to operate the slave robot via the input device without physically viewing the slave robot. Also, the force feedback can be generated from the workstation to represent fictitious forces to constrain the input device's control of the slave robot to be within imaginary predetermined boundaries.

Ohm, Timothy↗

NASA NTRS2012

The Mobile Chamber

A document discusses a simulation chamber that represents a shift from the thermal-vacuum chamber stereotype. This innovation, currently in development, combines the capabilities of space simulation chambers, the user-friendliness of modern-day electronics, and the modularity of plug-and-play computing. The Mobile Chamber is a customized test chamber that can be deployed with great ease, and is capable of bringing payloads at temperatures down to 20 K, in high vacuum, and with the desired metrology instruments integrated to the systems control. Flexure plans to lease Mobile Chambers, making them affordable for smaller budgets and available to a larger customer base. A key feature of this design will be an Apple iPad-like user interface that allows someone with minimal training to control the environment inside the chamber, and to simulate the required extreme environments. The feedback of thermal, pressure, and other measurements is delivered in a 3D CAD model of the chamber's payload and support hardware. This GUI will provide the user with a better understanding of the payload than any existing thermal-vacuum system.

Scharfstein, Gregory↗

NASA NTRS2015

Tactile Data Entry System

The patent-pending Glove-Enabled Computer Operations (GECO) design leverages extravehicular activity (EVA) glove design features as platforms for instrumentation and tactile feedback, enabling the gloves to function as human-computer interface devices. Flexible sensors in each finger enable control inputs that can be mapped to any number of functions (e.g., a mouse click, a keyboard strike, or a button press). Tracking of hand motion is interpreted alternatively as movement of a mouse (change in cursor position on a graphical user interface) or a change in hand position on a virtual keyboard. Programmable vibro-tactile actuators aligned with each finger enrich the interface by creating the haptic sensations associated with control inputs, such as recoil of a button press.

Adams, Richard J.↗

NASA NTRS2018

Miniature Exercise Device-2 (MED-2): Preliminary ISS Evaluation Results for a Compact Motorized Resistive and Aerobic Rowing Exercise Device

Future human missions beyond Low Earth Orbit (LEO) will require onboard equipment to provide exercise capabilities for the crew to counter the adverse physiological effects of long-duration microgravity. To accomplish this within the physical constraints of a space vehicle or transit module, a single miniature device that provides both resistive and aerobic exercise modalities is required. To meet this need, Johnson Space Center’s (JSC) Software, Robotics, and Simulation Division (ER) developed the Miniature Exercise Device-2 (MED-2). MED-2 integrates a torque-controlled servomotor and a series-elastic actuator to provide highly-controllable load profiles and a large magnitude output performance in a very small package. This innovative technology is derived from years of JSC/ER design, development and operational experience with cutting-edge robotics, motor controllers, software and actuator/sensor miniaturization, including Robonaut 2 and MED-1. MED-2 was presented at the 2016 ISS R&D Conference. This is an update now that the last of six crewmembers will have completed planned MED-2 sessions on the International Space Station (ISS) in May 2018.Current state-of-the-art ISS exercise equipment consists of two treadmills, a resistive exercise device and two cycle ergometers with a total mass of several thousand pounds and a total volume of several cubic yards. This equipment has proven vital to mitigate the musculoskeletal and cardiovascular degradation effects of microgravity. However, due to the large operational volume and mass of these ISS devices, tailoring them for smaller vehicles, such as Orion, is not possible. In addition, each of the current ISS devices targets a single specific modality. Compared to the existing spaceflight (and even terrestrial) exercise equipment, MED-2 is a new archetype altogether. The combined features of compact size, multi-modality and high-performance is attributable to its innovative series elastic actuator and motor controller. Following its arrival on ISS in 2016, MED-2 was evaluated in two parts. The first and shorter evaluation was an engineering functional checkout of the hardware. As this was a novel exercise device previously never used on ISS, the initial checkout assessed the operation of the hardware and ensured the motion and dynamic range of the crew did not present any collision or other hazards. The second portion of the study collected the heart rates, kinematics and utilized operational volumes of six astronauts to determine the quality of both the resistive and aerobic exercise modalities as delivered by MED-2. Investigators from JSC Biomedical Research and Environmental Science Division (SK) and Glenn Research Center are currently evaluating the data and preparing preliminary results. For the resistive exercise modality, MED-2 demonstrated a range of constant resistive loads from 10-150 lbf. With a displacement range of 84 inches, the MED-2 accommodates users from 5th percentile Japanese female through 95th percentile American male for all of its certified exercises. The displacement measurement accuracy has also been verified within 2.5 percent full range. The crew was able to successfully perform all prescribed resistive exercises, except Goblet Squats which were not feasible with a constant load profile. For the aerobic exercise modality, MED-2 simulated a rowing motion with prescribed and user-selected resistance levels. It has demonstrated rates up to 60 strokes per minute on the ground. MED-2 loads and displacements performance are the same as those cited for the resistive modality. Although each of the crew was able to perform the prescribed aerobic rowing sets, there was considerable variability in the rowing motion among different crewmembers. Also, as expected, the crew was unable to get the full benefits of a typical terrestrial rowing stroke because the current configuration does not allow the user to reach past their feet. These observations have already informed the requirements for other microgravity rowing devices currently in development. One of the unique features of the MED-2 device is the intuitive touch-screen control system. This One Portal graphical user interface (GUI) was developed based on JSC/ER’s heritage knowledge and experience of developing and sustaining the current ISS exercise equipment. Through this interface, the crew easily performed prepared prescriptions as well as had the ability to adjust exercise modality, load and other exercise details such as number of repetitions and number of sets. This touch-screen and GUI fulfilled the MED-2 project goal to simplify the interaction between the user and the device. Furthermore, the extent to which MED-2 utilizes a touchscreen and GUI to control exercise equipment is unmatched among the existing ISS exercise devices. As a motorized device, MED-2 technology can provide a customizable force profile that can be varied as a function of strap displacement, strap velocity or a combination of these and other variables. During 2017, JSC/ER developed and flight-certified a resistive exercise algorithm that mimics the 1-G inertial effects of free-weights and enables adjustable eccentric-to-concentric loading ratios. Subsequent development will explore varying the load profiles and incorporating additional exercises beyond the current list of certified movements.

Exercise↗

NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of trained machine-learning models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a Windows app that has been created to deploy trained machine-learning 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 machine-learning application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). Current version of the app focuses on the performance prediction of conventional turbofans. The app gets user input for a turbofan design, preprocesses the input data, and deploys trained machine-learning models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The machine-learning predictive models were built by employing supervised deep-learning algorithm 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 machine-learning models using the app shows that Aero-Engines AI is an easy-to-use and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage.

machine learning↗

NASA NTRS2007

Imaging Sensor Flight and Test Equipment Software

The Lightning Imaging Sensor (LIS) is one of the components onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, and was designed to detect and locate lightning over the tropics. The LIS flight code was developed to run on a single onboard digital signal processor, and has operated the LIS instrument since 1997 when the TRMM satellite was launched. The software provides controller functions to the LIS Real-Time Event Processor (RTEP) and onboard heaters, collects the lightning event data from the RTEP, compresses and formats the data for downlink to the satellite, collects housekeeping data and formats the data for downlink to the satellite, provides command processing and interface to the spacecraft communications and data bus, and provides watchdog functions for error detection. The Special Test Equipment (STE) software was designed to operate specific test equipment used to support the LIS hardware through development, calibration, qualification, and integration with the TRMM spacecraft. The STE software provides the capability to control instrument activation, commanding (including both data formatting and user interfacing), data collection, decompression, and display and image simulation. The LIS STE code was developed for the DOS operating system in the C programming language. Because of the many unique data formats implemented by the flight instrument, the STE software was required to comprehend the same formats, and translate them for the test operator. The hardware interfaces to the LIS instrument using both commercial and custom computer boards, requiring that the STE code integrate this variety into a working system. In addition, the requirement to provide RTEP test capability dictated the need to provide simulations of background image data with short-duration lightning transients superimposed. This led to the development of unique code used to control the location, intensity, and variation above background for simulated lightning strikes at user-selected locations.

Freestone, Kathleen↗

NASA NTRS2011

Multi-Mission Power Analysis Tool

Multi-Mission Power Analysis Tool (MMPAT) Version 2 simulates spacecraft power generation, use, and storage in order to support spacecraft design, mission planning, and spacecraft operations. It can simulate all major aspects of a spacecraft power subsystem. It is parametrically driven to reduce or eliminate the need for a programmer. A user-friendly GUI (graphical user interface) makes it easy to use. Multiple deployments allow use on the desktop, in batch mode, or as a callable library. It includes detailed models of solar arrays, radioisotope thermoelectric generators, nickel-hydrogen and lithium-ion batteries, and various load types. There is built-in flexibility through user-designed state models and table-driven parameters.

Broderick, Daniel↗

NASA NTRS2003

A Voice and Mouse Input Interface for 3D Virtual Environments

There have been many successful stories on how 3D input devices can be fully integrated into an immersive virtual environment. Electromagnetic trackers, optical trackers, gloves, and flying mice are just some of these input devices. Though we can use existing 3D input devices that are commonly used for VR applications, there are several factors that prevent us from choosing these input devices for our applications. One main factor is that most of these tracking devices are not suitable for prolonged use due to human fatigue associated with using them. A second factor is that many of them would occupy additional office space. Another factor is that many of the 3D input devices are expensive due to the unusual hardware that are required. For our VR applications, we want a user interface that would work naturally with standard equipment. In this paper, we demonstrate applications or our proposed muitimodal interface using a 3D dome display. We also show that effective data analysis can be achieved while the scientists view their data rendered inside the dome display and perform user interactions simply using the mouse and voice input. Though the sphere coordinate grid seems to be ideal for interaction using a 3D dome display, we can also use other non-spherical grids as well.

Kao, David L.↗

NASA NTRS1988

Issues on the use of meta-knowledge in expert systems

Meta knowledge is knowledge about knowledge; knowledge that is not domain specific but is concerned instead with its own internal structure. Several past systems have used meta-knowledge to improve the nature of the user interface, to maintain the knowledge base, and to control the inference engine. More extensive use of meta-knowledge is probable for the future as larger scale problems are considered. A proposed system architecture is presented and discussed in terms of meta-knowledge applications. The principle components of this system: the user support subsystem, the control structure, the knowledge base, the inference engine, and a learning facility are all outlined and discussed in light of the use of meta-knowledge. Problems with meta-constructs are also mentioned but it is concluded that the use of meta-knowledge is crucial for increasingly autonomous operations.

Facemire, Jon↗

NASA NTRS2005

System Developed for Real-Time Blade-Flutter Monitoring in the Wind Tunnel

A real-time system has been developed to monitor flutter vibrations in turbomachinery. The system is designed for continuous processing of blade tip timing data at a rate of 10 MB/sec. A USB 2.0 interface provides uninterrupted real-time processing of the data, and the blade-tip arrival times are measured with a 50-MHz oscillator and a 24-bit pipelined architecture counter. The input stage includes a glitch catcher, which reduces the probability of detecting a ghost blade to negligible levels. A graphical user interface provides online interrogation of any blade tip from any light probe sensor. Alternatively, data from all blades and all sensors can be superimposed into a single composite scatter plot displaying the vibration amplitude of each blade.

Kurkov, Anatole P.↗

NASA NTRS2006

Analytical Assessment of the Reciprocating Feed System

A preliminary analysis tool has been created in Microsoft Excel to determine deliverable payload mass, total system mass, and performance of spacecraft systems using various types of propellant feed systems. These mass estimates are conducted by inserting into the user interface the basic mission parameters (e.g., thrust, burn time, specific impulse, mixture ratio, etc.), system architecture (e.g., propulsion system type and characteristics, propellants, pressurization system type, etc.), and design properties (e.g., material properties, safety factors, etc.). Different propellant feed and pressurization systems are available for comparison in the program. This gives the user the ability to compare conventional pressure fed, reciprocating feed system (RFS), autogenous pressurization thrust augmentation (APTA RFS), and turbopump systems with the deliverable payload, inert mass, and total system mass being the primary comparison metrics. Analyses of several types of missions and spacecraft were conducted and it was found that the RFS offers a performance improvement, especially in terms of delivered payload, over conventional pressure fed systems. Furthermore, it is competitive with a turbopump system at low to moderate chamber pressures, up to approximately 1,500 psi. Various example cases estimating the system mass and deliverable payload of several types of spacecraft are presented that illustrate the potential system performance advantages of the RFS. In addition, a reliability assessment of the RFS was conducted, comparing it to simplified conventional pressure fed and turbopump systems, based on MIL-STD 756B; these results showed that the RFS offers higher reliability, and thus substantially longer periods between system refurbishment, than turbopump systems, and is competitive with conventional pressure fed systems. This is primarily the result of the intrinsic RFS fail-operational capability with three run tanks, since the system can operate with just two run tanks.

Eddleman, David E.↗