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NASA NTRS2005

Discrete Event Supervisory Control Applied to Propulsion Systems

The theory of discrete event supervisory (DES) control was applied to the optimal control of a twin-engine aircraft propulsion system and demonstrated in a simulation. The supervisory control, which is implemented as a finite-state automaton, oversees the behavior of a system and manages it in such a way that it maximizes a performance criterion, similar to a traditional optimal control problem. DES controllers can be nested such that a high-level controller supervises multiple lower level controllers. This structure can be expanded to control huge, complex systems, providing optimal performance and increasing autonomy with each additional level. The DES control strategy for propulsion systems was validated using a distributed testbed consisting of multiple computers--each representing a module of the overall propulsion system--to simulate real-time hardware-in-the-loop testing. In the first experiment, DES control was applied to the operation of a nonlinear simulation of a turbofan engine (running in closed loop using its own feedback controller) to minimize engine structural damage caused by a combination of thermal and structural loads. This enables increased on-wing time for the engine through better management of the engine-component life usage. Thus, the engine-level DES acts as a life-extending controller through its interaction with and manipulation of the engine s operation.

Litt, Jonathan S.↗

NASA NTRS2006

On-Orbit Testing of Materials and Processes

The Pore Formation and Mobility Investigation (PFMI) and the In-Space Soldering Investigation (ISSI) were conducted aboard the International Space Station (ISS) with the intent of promoting our understanding of materials processing in a low-gravity environment. The numerous experiments were conducted by telescience with the results evaluated by real time video and subsequently returned tapes and samples. In addition to discussing the experimental results and analysis the presentation will include an account of the ISS facilities (Microgravity Science Glovebox and Maintenance Work Area) used as well as some lessons-learned comments.

Grugel, R. N.↗

NASA NTRS2010

Ultra-Rapid dUT1 Measurements on Japan-Fennoscandian Baselines - Application to 24-hour Sessions

GSI, NICT, OSO, and MRO have been engaged in Ultra-rapid dUT1 experiments since 2007 aiming at the technological possibility of real-time dUT1 results using the e-VLBI technique. We have already successfully determined dUT1 in less than four minutes after the end of an experimental Intensive session in 2008, and at present we routinely get the results within 30 minutes for regular Intensives. In 2009 we applied the technique to 24-hour sessions and continuously obtained dUT1 values by processing and analyzing Tsukuba Onsala data in near real-time. It showed a detailed behavior of UT1 variations, which could be very valuable for scientific study as well as for precise prediction of UT1-UTC.

Matsuzaka, Shigeru↗

NASA NTRS2011

Transformation of Air Quality Monitor Data from the International Space Station into Toxicological Effect Groups

The primary reason for monitoring air quality aboard the International Space Station (ISS) is to determine whether air pollutants have collectively reached a concentration where the crew could experience adverse health effects. These effects could be near-real-time (e.g. headache, respiratory irritation) or occur late in the mission or even years later (e.g. cancer, liver toxicity). Secondary purposes for monitoring include discovery that a potentially harmful compound has leaked into the atmosphere or that air revitalization system performance has diminished. Typical ISS atmospheric trace pollutants consist of alcohols, aldehydes, aromatic compounds, halo-carbons, siloxanes, and silanols. Rarely, sulfur-containing compounds and alkanes are found at trace levels. Spacecraft Maximum Allowable Concentrations (SMACs) have been set in cooperation with a subcommittee of the National Research Council Committee on Toxicology. For each compound and time of exposure, the limiting adverse effect(s) has been identified. By factoring the analytical data from the Air Quality Monitor (AQM), which is in use as a prototype instrument aboard the ISS, through the array of compounds and SMACs, the risk of 16 specific adverse effects can be estimated. Within each adverse-effect group, we have used an additive model proportioned to each applicable 180-day SMAC to estimate risk. In the recent past this conversion has been performed using archival data, which can be delayed for months after an air sample is taken because it must be returned to earth for analysis. But with the AQM gathering in situ data each week, NASA is in a position to follow toxic-effect groups and correlate these with any reported crew symptoms. The AQM data are supplemented with data from real-time CO2 instruments aboard the ISS and from archival measurements of formaldehyde, which the AQM cannot detect.

James, John T.↗

NASA NTRS2015

Raven: An On-Orbit Relative Navigation Demonstration Using International Space Station Visiting Vehicles

Since the last Hubble Servicing Mission five years ago, the Satellite Servicing Capabilities Office (SSCO) at the NASA Goddard Space Flight Center (GSFC) has been focusing on maturing the technologies necessary to robotically service orbiting legacy assets-spacecraft not necessarily designed for in-flight service. Raven, SSCO's next orbital experiment to the International Space Station (ISS), is a real-time autonomous non-cooperative relative navigation system that will mature the estimation algorithms required for rendezvous and proximity operations for a satellite-servicing mission. Raven will fly as a hosted payload as part of the Space Test Program's STP-H5 mission, which will be mounted on an external ExPRESS Logistics Carrier (ELC) and will image the many visiting vehicles arriving and departing from the ISS as targets for observation. Raven will host multiple sensors: a visible camera with a variable field of view lens, a long-wave infrared camera, and a short-wave flash lidar. This sensor suite can be pointed via a two-axis gimbal to provide a wide field of regard to track the visiting vehicles as they make their approach. Various real-time vision processing algorithms will produce range, bearing, and six degree of freedom pose measurements that will be processed in a relative navigation filter to produce an optimal relative state estimate. In this overview paper, we will cover top-level requirements, experimental concept of operations, system design, and the status of Raven integration and test activities.

Rendezvous↗

NASA NTRS2015

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Lang, Timothy J.↗

DOE OSTI2023

Asymmetric nanoparticle oxidation observed in-situ by the evolution of diffraction contrast

Abstract The use of transmission electron microscopy (TEM) to observe real-time structural and compositional changes has proven to be a valuable tool for understanding the dynamic behavior of nanomaterials. However, identifying the nanoparticles of interest typically require an obvious change in position, size, or structure, as compositional changes may not be noticeable during the experiment. Oxidation or reduction can often result in subtle volume changes only, so elucidating mechanisms in real-time requires atomic-scale resolution or in-situ electron energy loss spectroscopy, which may not be widely accessible. Here, by monitoring the evolution of diffraction contrast, we can observe both structural and compositional changes in iron oxide nanoparticles, specifically the oxidation from a wüstite-magnetite (FeO@Fe 3 O 4 ) core – shell nanoparticle to single crystalline magnetite, Fe 3 O 4 nanoparticle. The in-situ TEM images reveal a distinctive light and dark contrast known as the ‘Ashby-Brown contrast’, which is a result of coherent strain across the core – shell interface. As the nanoparticles fully oxidize to Fe 3 O 4 , the diffraction contrast evolves and then disappears completely, which is then confirmed by modeling and simulation of TEM images. This represents a new, simplified approach to tracking the oxidation or reduction mechanisms of nanoparticles using in-situ TEM experiments.

36 MATERIALS SCIENCE↗

NASA NTRS1989

The BATSE experiment on the Gamma Ray Observatory: Solar flare hard x ray and gamma-ray capabilities

The Burst and Transient Source Experiment (BATSE) for the Gamma Ray Observatory (GRO) consists of eight detector modules that provide full-sky coverage for gamma-ray bursts and other transient phenomena such as solar flares. Each detector module has a thin, large-area scintillation detector (2025 sq cm) for high time-resolution studies, and a thicker spectroscopy detector (125 sq cm) to extend the energy range and provide better spectral resolution. The total energy range of the system is 15 keV to 100 MeV. These 16 detectors and the associated onboard data system should provide unprecedented capabilities for observing rapid spectral changes and gamma-ray lines from solar flares. The presence of a solar flare can be detected in real-time by BATSE; a trigger signal is sent to two other experiments on the GRO. The launch of the GRO is scheduled for June 1990, so that BATSE can be an important component of the Max '91 campaign.

Fishman, G. J.↗

DOE OSTI2023

ML-based Real-Time Control at the Edge: An Approach Using hls4ml

This study focuses on implementing a real-time control system for a particle accelerator facility that performs high energy physics experiments. A critical operating parameter in this facility is beam loss, which is the fraction of particles deviating from the accelerated proton beam into a cascade of secondary particles. Accelerators employ a large number of sensors to monitor beam loss. The data from these sensors is monitored by human operators who predict the relative contribution of different sub-systems to the beam loss. Using this information, they engage control interventions. In this paper, we present a controller to track this phenomenon in real-time using edge-Machine Learning (ML) and support control with low latency and high accuracy. We implemented this system on an Intel Arria 10 SoC. Optimizations at the algorithm, high-level synthesis, and interface levels to improve latency and resource usage are presented. Our design implements a neural network, which can predict the main source of beam loss (between two possible causes) at speeds up to 575 frames per second (fps) (average latency of 1.74 ms). The practical deployed system is required to operate at 320 fps, with a 3ms latency requirement, which has been met by our design successfully.

Shi, R.↗

NASA NTRS1976

Crew health status and monitoring summary - The second manned Skylab mission

The evaluation of available medical data to determine the health status of the Skylab 3 crew members is discussed. The utilization of raw data from medical experiments during the course of the mission as a source of near-real time criteria for monitoring crew health is described. The percentage change of selected metabolic parameters, including calorie intake, Na intake, K intake, urine output, water intake, and body weight, from their pre-flight values, vectorcardiographic data, and results of the lower body negative pressure experiment provided a core of information upon which clinical judgements could be made. Minor clinical problems occurring during the mission are outlined.

Buchanan, P.↗

DOE OSTI2022

Streaming readout for next generation electron scattering experiments

Current and future experiments at the high-intensity frontier are expected to produce an enormous amount of data that needs to be collected and stored for offline analysis. Thanks to the continuous progress in computing and networking technology, it is now possible to replace the standard ‘triggered’ data acquisition systems with a new, simplified and outperforming scheme. ‘Streaming readout’ (SRO) DAQ aims to replace the hardware-based trigger with a much more powerful and flexible software-based one, that considers the whole detector information for efficient real-time data tagging and selection. Considering the crucial role of DAQ in an experiment, validation with on-field tests is required to demonstrate SRO performance. In this paper, we report results of the on-beam validation of the Jefferson Lab SRO framework. In this work, we exposed different detectors (PbWO-based electromagnetic calorimeters and a plastic scintillator hodoscope) to the Hall-D electron-positron secondary beam and to the Hall-B production electron beam, with increasingly complex experimental conditions. By comparing the data collected with the SRO system against the traditional DAQ, we demonstrate that the SRO performs as expected. Furthermore, we provide evidence of its superiority in implementing sophisticated AI-supported algorithms for real-time data analysis and reconstruction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

A Synoptic System for Capturing Ecosystem Control Points Across Terrestrial‐Aquatic Interfaces

Interconnected landscape features such as terrestrial‐aquatic interfaces play an outsized role in biogeochemical cycles as ecosystem control points, but it is notoriously challenging to characterize these. Here, we document a synoptic sensor network design that is (a) flexible to accommodate diverse ecosystem interfaces and gradients, (b) adaptable to monitoring and modeling needs of small and large projects alike, (c) standardized for intercomparability across sites and field experiments, and (d) adequately replicated to capture heterogeneity of each parameter monitored. This real‐time monitoring of surface water, groundwater, soil, and vegetation supports configuration and evaluation of models that span upland, wetland, open water strata, and transitions between them. We established the network at seven sites along the Chesapeake Bay and Lake Erie coastlines, including large‐scale flood manipulation experiments in both regions. A central design element is “one data logger program to rule them all”—a collection of sensor‐specific modules deployed on 40 loggers controlling ∼2,000 sensors, with the goal of streamlining maintenance, debugging, and reproducible data processing. The network generates ∼6 M observations per month, capturing system dynamics at the broad spatial and fine temporal scales needed to initialize and benchmark models; measurement frequency can be modified remotely to capture events. This network design has also revealed behaviors not represented in Earth system models, such as transient groundwater oxygen pulses. Completely documented and open source, this standardized, flexible, and efficient sensor network design can reduce barriers to understanding environmental changes and ecosystem responses across systems and scales.

Ward, Nicholas D. [Pacific Northwest National Labo↗

NASA NTRS1989

Knowledge based and interactive control for the Superfluid Helium On-orbit Transfer Project

NASA's Superfluid Helium On-Orbit Transfer (SHOOT) project is a Shuttle-based experiment designed to acquire data on the properties of superfluid helium in micro-gravity. Aft Flight Deck Computer Software for the SHOOT experiment is comprised of several monitoring programs which give the astronaut crew visibility into SHOOT systems and a rule based system which will provide process control, diagnosis and error recovery for a helium transfer without ground intervention. Given present Shuttle manifests, this software will become the first expert system to be used in space. The SHOOT Command and Monitoring System (CMS) software will provide a near real time highly interactive interface for the SHOOT principal investigator to control the experiment and to analyze and display its telemetry. The CMS software is targeted for all phases of the SHOOT project: hardware development, pre-flight pad servicing, in-flight operations, and post-flight data analysis.

Castellano, Timothy P.↗

NASA NTRS1974

Medical results of the Skylab program

The Skylab food system, waste management system, operational bioinstrumentation, personal hygiene provisions, in-flight medical support system, and the cardiovascular counterpressure garment worn during reentry are described. The medical experiments program provided scientific data and also served as the basis for real-time decisions on flight duration. Premission support, in-flight operational support, and postflight medical activities are surveyed. Measures devised to deal with possible food spoilage, medical instrument damage, and toxic atmosphere caused by the initial failures on the Orbital Workshop (OWS) are discussed. The major medical experiments performed in flight allowed the study of physiological changes as a function of exposure to weightless flight. The experiments included studies of the cardiovascular system, musculoskeletal and fluid/electrolyte balance, sleep, blood, vestibular system, and time and motion studies.

Johnston, R. S.↗

NASA NTRS1989

JPL control/structure interaction test bed real-time control computer architecture

The Control/Structure Interaction Program is a technology development program for spacecraft that exhibit interactions between the control system and structural dynamics. The program objectives include development and verification of new design concepts - such as active structure - and new tools - such as combined structure and control optimization algorithm - and their verification in ground and possibly flight test. A focus mission spacecraft was designed based upon a space interferometer and is the basis for design of the ground test article. The ground test bed objectives include verification of the spacecraft design concepts, the active structure elements and certain design tools such as the new combined structures and controls optimization tool. In anticipation of CSI technology flight experiments, the test bed control electronics must emulate the computation capacity and control architectures of space qualifiable systems as well as the command and control networks that will be used to connect investigators with the flight experiment hardware. The Test Bed facility electronics were functionally partitioned into three units: a laboratory data acquisition system for structural parameter identification and performance verification; an experiment supervisory computer to oversee the experiment, monitor the environmental parameters and perform data logging; and a multilevel real-time control computing system. The design of the Test Bed electronics is presented along with hardware and software component descriptions. The system should break new ground in experimental control electronics and is of interest to anyone working in the verification of control concepts for large structures.

Briggs, Hugh C.↗

NASA NTRS1979

Adaptive remote sensing technology for feature recognition and tracking

A technology development plan designed to reduce the data load and data-management problems associated with global study and monitoring missions is described with a heavy emphasis placed on developing mission capabilities to eliminate the collection of unnecessary data. Improved data selectivity can be achieved through sensor automation correlated with the real-time needs of data users. The first phase of the plan includes the Feature Identification and Location Experiment (FILE) which is scheduled for the 1980 Shuttle flight. The FILE experiment is described with attention given to technology needs, development plan, feature recognition and classification, and cloud-snow detection/discrimination. Pointing, tracking and navigation received particular consideration, and it is concluded that this technology plan is viewed as an alternative to approaches to real-time acquisition that are based on extensive onboard format and inventory processing and reliance upon global-satellite-system navigation data.

Wilson, R. G.↗

DOE OSTI2022

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, in this paper, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2014

The O/OREOS Mission - Astrobiology in Low Earth Orbit

The O/OREOS (Organism/Organic Exposure to Orbital Stresses) nanosatellite is the first science demonstration spacecraft and flight mission of the NASA Astrobiology Small- Payloads Program (ASP). O/OREOS was launched successfully on November 19, 2010, to a high-inclination (72 deg), 650-km Earth orbit aboard a US Air Force Minotaur IV rocket from Kodiak, Alaska. O/OREOS consists of 3 conjoined cubesat (each 1000 cu cm) modules: (i) a control bus; (ii) the Space Environment Survivability of Living Organisms (SESLO) experiment; and (iii) the Space Environment Viability of Organics (SEVO) experiment. Among the innovative aspects of the O/OREOS mission are a real-time analysis of the photostability of organics and biomarkers and the collection of data on the survival and metabolic activity for microorganisms at 3 times during the 6-month mission. We report on the spacecraft characteristics, payload capabilities, and present operational phase and flight data from the O/OREOS mission. The science and technology rationale of O/OREOS supports NASA0s scientific exploration program by investigating the local space environment as well as space biology relevant to Moon and Mars missions. It also serves as a precursor for experiments on small satellites, the International Space Station (ISS), future free-flyers and lunar surface exposure facilities.

Spectroscopy↗