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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Data Automata in Scala

The field of runtime verification has during the last decade seen a multitude of systems for monitoring event sequences (traces) emitted by a running system. The objective is to ensure correctness of a system by checking its execution traces against formal specifications representing requirements. A special challenge is data parameterized events, where monitors have to keep track of the combination of control states as well as data constraints, relating events and the data they carry across time points. This poses a challenge wrt. efficiency of monitors, as well as expressiveness of logics. Data automata is a form of automata where states are parameterized with data, supporting monitoring of data parameterized events. We describe the full details of a very simple API in the Scala programming language, an internal DSL (Domain-Specific Language), implementing data automata. The small implementation suggests a design pattern. Data automata allow transition conditions to refer to other states than the source state, and allow target states of transitions to be inlined, offering a temporal logic flavored notation. An embedding of a logic in a high-level language like Scala in addition allows monitors to be programmed using all of Scala's language constructs, offering the full flexibility of a programming language. The framework is demonstrated on an XML processing scenario previously addressed in related work.

runtime verification↗
NASA NTRS2014

Monitoring with Data Automata

We present a form of automaton, referred to as data automata, suited for monitoring sequences of data-carrying events, for example emitted by an executing software system. This form of automata allows states to be parameterized with data, forming named records, which are stored in an efficiently indexed data structure, a form of database. This very explicit approach differs from other automaton-based monitoring approaches. Data automata are also characterized by allowing transition conditions to refer to other parameterized states, and by allowing transitions sequences. The presented automaton concept is inspired by rule-based systems, especially the Rete algorithm, which is one of the well-established algorithms for executing rule-based systems. We present an optimized external DSL for data automata, as well as a comparable unoptimized internal DSL (API) in the Scala programming language, in order to compare the two solutions. An evaluation compares these two solutions to several other monitoring systems.

log analysis↗
NASA NTRS2012

Interactive robot control system and method of use

A robotic system includes a robot having joints, actuators, and sensors, and a distributed controller. The controller includes command-level controller, embedded joint-level controllers each controlling a respective joint, and a joint coordination-level controller coordinating motion of the joints. A central data library (CDL) centralizes all control and feedback data, and a user interface displays a status of each joint, actuator, and sensor using the CDL. A parameterized action sequence has a hierarchy of linked events, and allows the control data to be modified in real time. A method of controlling the robot includes transmitting control data through the various levels of the controller, routing all control and feedback data to the CDL, and displaying status and operation of the robot using the CDL. The parameterized action sequences are generated for execution by the robot, and a hierarchy of linked events is created within the sequence.

Sanders, Adam M.↗
NASA NTRS2006

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Adler, Robert F.↗
NASA NTRS2008

VML Sequencing: Growing Capabilities over Multiple Missions

Virtual Machine Language (VML) is an award-winning advanced procedural sequencing language in use on NASA deep-space missions since 1997. Missions featuring VML include Spitzer Space Telescope, Mars Odyssey, Stardust, Genesis, Mars Reconnaissance Orbiter, Phoenix, Dawn and Juno. The latest deployed version, VML 2.0, features parameterized functions, conditionals, polymorphism, a rich set of control directives and data types, event detection and response, and on-the-fly creation of spacecraft commands. This feature set is used to simplify spacecraft operations and science gathering activities. A new 2.1 version is being prototyped for use as an executive within flight instruments, and may be deployed on Juno.

Dawn↗
NASA NTRS2011

TraceContract: A Scala DSL for Trace Analysis

In this paper we describe TRACECONTRACT, an API for trace analysis, implemented in the SCALA programming language. We argue that for certain forms of trace analysis the best weapon is a high level programming language augmented with constructs for temporal reasoning. A trace is a sequence of events, which may for example be generated by a running program, instrumented appropriately to generate events. The API supports writing properties in a notation that combines an advanced form of data parameterized state machines with temporal logic. The implementation utilizes SCALA's support for defining internal Domain Specific Languages (DSLs). Furthermore SCALA's combination of object oriented and functional programming features, including partial functions and pattern matching, makes it an ideal host language for such an API.

log file analysis↗
NASA NTRS2018

Dressing the Coronal Magnetic Extrapolations of Active Regions with a Parameterized Thermal Structure

The study of time-dependent solar active region (AR) morphology and its relation to eruptive events requires analysis of imaging data obtained in multiple wavelength domains with differing spatial and time resolution, ideally in combination with 3D physical models. To facilitate this goal, we have undertaken a major enhancement of our IDL-based simulation tool, GX_Simulator, previously developed for modeling microwave and X-ray emission from flaring loops, to allow it to simulate quiescent emission from solar ARs. The framework includes new tools for building the atmospheric model and enhanced routines for calculating emission that include new wavelengths. In this paper, we use our upgraded tool to model and analyze an AR and compare the synthetic emission maps with observations. We conclude that the modeled magneto-thermal structure is a reasonably good approximation of the real one.

Nita, Gelu M.↗
NASA NTRS2007

An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM, topography-derived hydrologic parameters such as flood direction. flow accumulation, basin, and river network etc.; 3) spatially distributed hydrological models to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay thc input data to the models and display the flood inundation results to the users and decision-makers. Early results appear reasonable in terms of location and frequency of events. Case studies of this experimental system are evaluated with surface runoff data and other river monitoring systems. such as Dartmouth Flood Observatory's "Surface Water Watch" array of river reaches that are measured daily via other satellite remote sensing data. A major outcome of this progress will be the availability of a global overview of flood alerts that should consequently improve the performance of Decision Support System. We expect these developments in utilization of satellite remote sensing technology to offer a practical solution to the challenge of building a cost-effective early warning system for data scarce and under-developed areas.

Adler, Robert↗
NASA NTRSDate not supplied

An Approach to Shape Parameterization Using Laboratory Hypervelocity Impact Experiments

NASA’s Orbital Debris Program Office relies on laboratory-based impact tests to supplement the measurement data of on-orbit events that defines the orbital debris environment. These experiments provide information that is essential to interpreting the radar and optical measurements of orbital fragmentation events into useful metrics, such as characteristic size of the debris, and to providing a better understanding of the distributions of fragment populations in terms of their masses, material constituents, fragment densities, cross-sectional areas, area-to-mass ratios, shapes, etc. The Satellite Orbital Debris Characterization Impact Test (SOCIT) was a notable laboratory impact experiment conducted in 1992 using a surplus U.S. Navy Transit navigation satellite of the 1960s. The data from this ground-based experiment were combined with on-orbit measurements to develop the NASA Standard Satellite Breakup Model (SSBM). To account for advancements in satellite design and construction since, a new impact test series – DebriSat – was conducted in 2014. This test utilized a high-fidelity mock-up spacecraft that better represents the materials and construction techniques used to design and manufacture modern spacecraft. Together, these tests offer valuable data to model an orbital debris environment composed of legacy and modern spacecraft. This paper presents an overview of the two laboratory impact tests, comparing their fragment parameter distributions with each other and with relevant distributions from the NASA SSBM. The categorization and descriptions of fragment shapes are of significant interest for future work, yet there are marked differences in the definitions of shape categories between each dataset. The categorizations of constituent materials, and the measurement techniques employed to populate these two datasets, are also different. New rubrics simplify and equate the categorizations between datasets to aid comparative analyses and to facilitate the potential use of both datasets in tandem with future environmental debris models. A preferred approach to classifying shape across disparate datasets uses the characteristic-length dimensions, and a simplified shape classification based on physical, solid-body dimensions, to mathematically construct an encapsulating right-circular cylinder that represents the fragment. The ratio of cylinder length-to-diameter (L:D) then provides a single continuum value for shape that is strongly correlated with its designated shape and size. This metric can then be used to further assess the distribution of shape with populations of other fragment characteristics within these datasets. The shape parameterization using the L:D ratios of right-circular cylinders is discussed.

John H. Seago↗
NASA NTRSDate not supplied

An Approach to Shape Parameterization Using Laboratory Hypervelocity Impact Experiments

NASA’s Orbital Debris Program Office relies on laboratory-based impact tests to supplement the measurement data of on-orbit events that defines the orbital debris environment. These experiments provide information that is essential to interpreting the radar and optical measurements of orbital fragmentation events into useful metrics, such as characteristic size of the debris, and to providing a better understanding of the distributions of fragment populations in terms of their masses, material constituents, fragment densities, cross-sectional areas, area-to-mass ratios, shapes, etc. The Satellite Orbital Debris Characterization Impact Test (SOCIT) was a notable laboratory impact experiment conducted in 1992 using a surplus U.S. Navy Transit navigation satellite of the 1960s. The data from this ground-based experiment were combined with on-orbit measurements to develop the NASA Standard Satellite Breakup Model (SSBM). To account for advancements in satellite design and construction since, a new impact test series – DebriSat – was conducted in 2014. This test utilized a high-fidelity mock-up spacecraft that better represents the materials and construction techniques used to design and manufacture modern spacecraft. Together, these tests offer valuable data to model an orbital debris environment composed of legacy and modern spacecraft. This paper presents an overview of the two laboratory impact tests, comparing their fragment parameter distributions with each other and with relevant distributions from the NASA SSBM. The categorization and descriptions of fragment shapes are of significant interest for future work, yet there are marked differences in the definitions of shape categories between each dataset. The categorizations of constituent materials, and the measurement techniques employed to populate these two datasets, are also different. New rubrics simplify and equate the categorizations between datasets to aid comparative analyses and to facilitate the potential use of both datasets in tandem with future environmental debris models. A preferred approach to classifying shape across disparate datasets uses the characteristic-length dimensions, and a simplified shape classification based on physical, solid-body dimensions, to mathematically construct an encapsulating right-circular cylinder that represents the fragment. The ratio of cylinder length-to-diameter (L:D) then provides a single continuum value for shape that is strongly correlated with its designated shape and size. This metric can then be used to further assess the distribution of shape with populations of other fragment characteristics within these datasets. The shape parameterization using the L:D ratios of right-circular cylinders is discussed.

John H Seago↗
NASA NTRS1995

Geomagnetic transmission of solar energetic protons during the geomagnetic disturbances of October 1989

Orbit-averaged geomagnetic transmission measurements during the large solar energetic particle events of October 1989 are presented using proton data from the NOAA-10 and GOES-7 satellies. The measurements are compared to geomagnetic transmission calculations determined by tracing particle trajectories through the combination of the International Geomagnetic Reference Field (IGRF) model and the 1989 Tsyganenko magnetospheric magnetic field model. The effective 'ring current' parameter in the 1989 Tsyganenko model based on the Dst data. Results are compared to calculations employing only the IGRF and to a parameterization of geomagnetically quiet-time cutoff rigidities derived from Cosmos/intercosmos observations. The 3-hour orbit-averaged results have approximately 15% accuracy during the October 1989 events.

Boberg, P. R.↗
NASA NTRS1992

The particle background of the Rosat PSPC

In order to permit quantitative studies of the diffuse cosmic X-ray background and of extended X-ray sources, the particle induced background of the Roentgen Satellite, Rosat, Position Sensitive Proportional Counter (PSPC) is parameterized. Data collected during 210,000 s of PSPC operation have been analyzed and the temporal, spectral, and spatial distributions investigated. About 77 percent of the residual events originate within the detector while the remainder enter through the counter window. During typical conditions, the count rate of the residual events is well correlated with the Master Veto (MV) count rate. The spectrum of these events is well described by a flat component plus a soft power law and an Al K-alpha line at 1.5 keV. Also during typical conditions, the ratio between the power law and flat components remains constant to +/- 4 while the relative Al K-alpha contribution increases with increasing MV count rate. The distribution of the counts over the field of view is uniform except for a slight radial dependence and shadowing caused by blockage of the externally produced component by the window support structure.

Snowden, S. L.↗
NASA NTRS2021

Concurrent Runtime Verification of Data Rich Events

This paper presents the open source runtime verification tool MESA (MEssage-based System Analysis), implemented in Scala, which supports concurrent monitors using the Actor model. Furthermore, the tool supports indexing (slicing) on the data values occurring in data-carrying events, for each individual monitor. The tool is generic in the sense that any monitoring system can be used for creating monitors. In this paper, we use the internal Scala DSL Daut for programming such in data parameterized state machines and temporal logic. To illustrate MESA/Daut, we present a case study that monitors flights from live U.S. airspace data streams, verifying that they conform to planned routes. With base in the case study, we then perform an extensive empirical study of the potential benefits from monitoring slices of a single property in concurrently executing actors. Due to the overhead of scheduling “small” actors (one for each slice or a small number of slices), it is not obvious that concurrent execution of such is beneficial. However, as a main result, we demonstrate that concurrent monitoring of slices to handle data-carrying events can provide considerable speed gains.

finite state machines↗
DOE OSTI2025

Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California

Mesoscale model predictions of wind, turbulence, and wind energy capacity factors are evaluated in the Altamont Pass Wind Resource Area of California (APWRA), where the diurnal regional sea breeze and associated terrain-driven speedup flows drive wind energy production during the summer months. Results from the Weather Research and Forecasting model version 4.4 using a novel three-dimensional planetary boundary layer (3D PBL) scheme, which treats both vertical and horizontal turbulent mixing, are compared to those using a well-established one-dimensional (1D) scheme that treats only vertical turbulent mixing. Each configuration is evaluated over a nearly 3-month-long period during the Hill Flow Study, and due to the recurring nature of the observed speedup flows, diurnal composite averaging is used to capture robust trends in model performance. Both model configurations showed similar overall skill. The general timing and direction of the speedup flows is captured, but their magnitude is overestimated within a typical wind turbine rotor layer. Both also fail to capture a persistent observed near-surface jet-like flow, likely due to the limited grid resolution that is typical of mesoscale models. However, the 3D PBL configuration shows several minor improvements over the 1D PBL configuration, including improved wind speed and turbulence kinetic energy profiles during the accelerating phase of the speedup events, as well as reduced positive wind speed bias at surface stations across the APWRA region. Using a mesoscale wind farm parameterization, modeled capacity factors are also compared to monthly data reported to the US Energy Information Administration (EIA) during the study period. Although the monthly trend in the data is captured, both model configurations overestimate capacity factors by roughly 7 %–11 %. Through model evaluation, this study provides confidence in the 3D PBL scheme for wind energy applications in complex terrain and provides guidance for future testing.

17 WIND ENERGY↗
NASA NTRS2013

The MJO Transition from Shallow to Deep Convection in CloudSat/CALIPSO Data and GISS GCM Simulations

The relationship between convective penetration depth and tropospheric humidity is central to recent theories of the Madden-Julian oscillation (MJO). It has been suggested that general circulation models (GCMs) poorly simulate the MJO because they fail to gradually moisten the troposphere by shallow convection and simulate a slow transition to deep convection. CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are analyzed to document the variability of convection depth and its relation to water vapor during the MJO transition from shallow to deep convection and to constrain GCM cumulus parameterizations. Composites of cloud occurrence for 10MJO events show the following anticipatedMJO cloud structure: shallow and congestus clouds in advance of the peak, deep clouds near the peak, and upper-level anvils after the peak. Cirrus clouds are also frequent in advance of the peak. The Advanced Microwave Scanning Radiometer for EarthObserving System (EOS) (AMSR-E) columnwater vapor (CWV) increases by;5 mmduring the shallow- deep transition phase, consistent with the idea of moisture preconditioning. Echo-top height of clouds rooted in the boundary layer increases sharply with CWV, with large variability in depth when CWV is between;46 and 68 mm. International Satellite Cloud Climatology Project cloud classifications reproduce these climatological relationships but correctly identify congestus-dominated scenes only about half the time. A version of the Goddard Institute for Space Studies Model E2 (GISS-E2) GCM with strengthened entrainment and rain evaporation that produces MJO-like variability also reproduces the shallow-deep convection transition, including the large variability of cloud-top height at intermediate CWV values. The variability is due to small grid-scale relative humidity and lapse rate anomalies for similar values of CWV. 1.

DelGenio, Anthony G.↗
NASA NTRS1983

Recurrent pulse trains in the solar hard X-ray flare of 1980 June 7

This study presents a detailed examination of the solar hard X-ray and gamma-ray flare of 1980 June 7 as seen by the Hard X-Ray Burst Spectrometer on SMM. The hard X-ray profile is most unusual in that it is characterized by an initial pulse train of seven intense hard X-ray spikes. However, the event is unique among the 6300 events observed by HXRBS in that the temporal signature of this pulse train recurs twice during the flare. Examinations of the hard X-ray data in conjunction with radio and gamma-ray observations show that the 28-480 keV X-ray emission is simultaneous with the 17 GHz microwave fluxes within 128 ms and that the 3.5-6.5 MeV prompt gamma-ray line emission is coincident with secondary maxima of the microwave and X-ray fluxes. Although the absence of spatially resolved hard X-ray observations leaves other possibilities open, a parameterization of the event as a set of seven sequentially firing loops is presented that offers many satisfying explanations of the observations.

Kiplinger, A. L.↗
NASA NTRS2013

KINEROS2-AGWA: Model Use, Calibration, and Validation

KINEROS (KINematic runoff and EROSion) originated in the 1960s as a distributed event-based model that conceptualizes a watershed as a cascade of overland flow model elements that flow into trapezoidal channel model elements. KINEROS was one of the first widely available watershed models that interactively coupled a finite difference approximation of the kinematic overland flow equations to a physically based infiltration model. Development and improvement of KINEROS continued from the 1960s on a variety of projects for a range of purposes, which has resulted in a suite of KINEROS-based modeling tools. This article focuses on KINEROS2 (K2), a spatially distributed, event-based watershed rainfall-runoff and erosion model, and the companion ArcGIS-based Automated Geospatial Watershed Assessment (AGWA) tool. AGWA automates the time-consuming tasks of watershed delineation into distributed model elements and initial parameterization of these elements using commonly available, national GIS data layers. A variety of approaches have been used to calibrate and validate K2 successfully across a relatively broad range of applications (e.g., urbanization, pre- and post-fire, hillslope erosion, erosion from roads, runoff and recharge, and manure transport). The case studies presented in this article (1) compare lumped to stepwise calibration and validation of runoff and sediment at plot, hillslope, and small watershed scales; and (2) demonstrate an uncalibrated application to address relative change in watershed response to wildfire.

Erosion↗
NASA NTRS2014

The Experimental Regional Ensemble Forecast System (ExREF): Its Use in NWS Forecast Operations and Preliminary Verification

The Experimental Regional Ensemble Forecast (ExREF) system is a tool for the development and testing of new Numerical Weather Prediction (NWP) methodologies. ExREF is run in near‐realtime by the Global Systems Division (GSD) of the NOAA Earth System Research Laboratory (ESRL) and its products are made available through a website, an ftp site, and via the Unidata Local Data Manager (LDM). The ExREF domain covers most of North America and has 9‐km horizontal grid spacing. The ensemble has eight members, all employing WRF‐ARW. The ensemble uses a variety of initial conditions from LAPS and the Global Forecasting System (GFS) and multiple boundary conditions from the GFS ensemble. Additionally, a diversity of physical parameterizations is used to increase ensemble spread and to account for the uncertainty in forecasting extreme precipitation events. ExREF has been a component of the Hydrometeorology Testbed (HMT) NWP suite in the 2012‐2013 and 2013‐2014 winters. A smaller domain covering just the West Coast was created to minimize band‐width consumption for the NWS. This smaller domain has and is being distributed to the National Weather Service (NWS) Weather Forecast Office and California Nevada River Forecast Center in Sacramento, California, where it is ingested into the Advanced Weather Interactive Processing System (AWIPS I and II) to provide guidance on the forecasting of extreme precipitation events. This paper will review the cooperative effort employed by NOAA ESRL, NASA SPoRT (Short‐term Prediction Research and Transition Center), and the NWS to facilitate the ingest and display of ExREF data utilizing the AWIPS I and II D2D and GFE (Graphical Software Editor) software. Within GFE is a very useful verification software package called BoiVer that allows the NWS to utilize the River Forecast Center's 4 km gridded QPE to compare with all operational NWP models 6‐hr QPF along with the ExREF mean 6‐hr QPF so the forecasters can build confidence in the use of the ExREF in preparing their rainfall forecasts. Preliminary results will be presented.

Reynolds, David↗