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At least 721 records · Page 40

Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

Daigle, Matthew John↗

Dynamical Model for the Zodiacal Cloud and Sporadic Meteors

The solar system is dusty, and would become dustier over time as asteroids collide and comets disintegrate, except that small debris particles in interplanetary space do not last long. They can be ejected from the solar system by Jupiter, thermally destroyed near the Sun, or physically disrupted by collisions. Also, some are swept by the Earth (and other planets), producing meteors. Here we develop a dynamical model for the solar system meteoroids and use it to explain meteor radar observations. We find that the Jupiter Family Comets (JFCs) are the main source of the prominent concentrations of meteors arriving to the Earth from the helion and antihelion directions. To match the radiant and orbit distributions, as measured by the Canadian Meteor Orbit Radar (CMOR) and Advanced Meteor Orbit Radar (AMOR), our model implies that comets, and JFCs in particular, must frequently disintegrate when reaching orbits with low perihelion distance. Also, the collisional lifetimes of millimeter particles may be longer (approx. > 10(exp 5) yr at 1 AU) than postulated in the standard collisional models (approx 10(exp 4) yr at 1 AU), perhaps because these chondrule-sized meteoroids are stronger than thought before. Using observations of the Infrared Astronomical Satellite (IRAS) to calibrate the model, we find that the total cross section and mass of small meteoroids in the inner solar system are (1.7-3.5) 10(exp 11) sq km and approx. 4 10(exp 19) g, respectively, in a good agreement with previous studies. The mass input required to keep the Zodiacal Cloud (ZC) in a steady state is estimated to be approx. 10(exp 4)-10(exp 5) kg/s. The input is up to approx 10 times larger than found previously, mainly because particles released closer to the Sun have shorter collisional lifetimes, and need to be supplied at a faster rate. The total mass accreted by the Earth in particles between diameters D = 5 micron and 1 cm is found to be approx 15,000 tons/yr (factor of 2 uncertainty), which is a large share of the accretion flux measured by the Long Term Duration Facility (LDEF). Majority of JFC particles plunge into the upper atmosphere at <15 km/s speeds, should survive the atmospheric entry, and can produce micrometeorite falls. This could explain the compositional similarity of samples collected in the Antarctic ice and stratosphere, and those brought from comet Wild 2 by the Stardust spacecraft. Meteor radars such as CMOR and AMOR see only a fraction of the accretion flux (approx 1- 10% and approx 10-50%, respectively), because small particles impacting at low speeds produce ionization levels that are below these radars detection capabilities.

Nesvorny, David↗

The Extreme Ultraviolet (EUV) Instrument for the MAVEN Mission

The Mars Atmosphere and Volatile Evolution Mission (MAVEN) will explore the variability in the planet's upper atmosphere and ionosphere that is dominated by interactions with the sun, specifically the high-energy photons in the soft X-ray and extreme ultraviolet wavelengths as well as interactions with the solar wind. Scientists will use MAVEN data to determine the current loss rate of volatile compounds from the Mars atmosphere, then extrapolate back in time in order to give historical estimations of state of the Mars atmosphere and climate, its ability to sustain liquid water, and the potential for the Martian habitability. The EUV instrument is critical in measuring the Space Weather driver of this atmospheric variability. It will directly observe a three EUV wavelength ranges and their variability due to solar flares (time scales of seconds to hours) as well as active region evolution (months), which will then act as proxies for a model to determine the entire 0.1-200 nm solar spectrum at all times during the MAVEN mission. These EUV measurements and models results will compliment the other instruments that will provide direct in-situ as well as remote sensing observations of the Martian atmospheric response to this solar driver. This presentation will be an introduction of this instrument and its science measurements and goals to the larger community, as well as a status report on its progress.

Chamberlin, Phillip C.↗

GCR Environmental Models I: Sensitivity Analysis for GCR Environments

Accurate galactic cosmic ray (GCR) models are required to assess crew exposure during long-duration missions to the Moon or Mars. Many of these models have been developed and compared to available measurements, with uncertainty estimates usually stated to be less than 15%. However, when the models are evaluated over a common epoch and propagated through to effective dose, relative differences exceeding 50% are observed. This indicates that the metrics used to communicate GCR model uncertainty can be better tied to exposure quantities of interest for shielding applications. This is the first of three papers focused on addressing this need. In this work, the focus is on quantifying the extent to which each GCR ion and energy group, prior to entering any shielding material or body tissue, contributes to effective dose behind shielding. Results can be used to more accurately calibrate model-free parameters and provide a mechanism for refocusing validation efforts on measurements taken over important energy regions. Results can also be used as references to guide future nuclear cross-section measurements and radiobiology experiments. It is found that GCR with Z>2 and boundary energies below 500 MeV/n induce less than 5% of the total effective dose behind shielding. This finding is important given that most of the GCR models are developed and validated against Advanced Composition Explorer/Cosmic Ray Isotope Spectrometer (ACE/CRIS) measurements taken below 500 MeV/n. It is therefore possible for two models to very accurately reproduce the ACE/CRIS data while inducing very different effective dose values behind shielding.

Slaba, Tony C.↗

Cauchy Drag Estimation For Low Earth Orbiters

Recent work on minimum variances estimators based on Cauchy distributions appear relevant to orbital drag estimation. Samples form Cauchy distributions which are part of a class of heavy-tailed distributions, are characterized by long stretches of fairly small variation, punctuated by large variations that are many times larger than could be expected from a Gaussian. Such behavior can occur when solar storms perturb the atmosphere. In this context, the present work describes an embedding of the scalar Idan-Speyer Cauchy Estimator to estimate density corrections, within an Extended Kalman Filter that estimates the state of a low Earth orbiter. In contrast to the baseline Kalman approach, the larger formal errors of the present approach fully and conservatively bound the predictive error distribution, even in the face of unanticipated density disturbances of hundreds of percent.

Low Earth↗

Improving the Monitoring of Crop Productivity Using Spaceborne Solar-Induced Fluorescence

Large-scale monitoring of crop growth and yield has important value for forecasting food production and prices and ensuring regional food security. A newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll, provides for the first time a direct measurement related to plant photosynthetic activity (i.e. electron transport rate). Here, we provide a framework to link SIF retrievals and crop yield, accounting for stoichiometry, photosynthetic pathways, and respiration losses. We apply this framework to estimate United States crop productivity for 2007-2012, where we use the spaceborne SIF retrievals from the Global Ozone Monitoring Experiment-2 satellite, benchmarked with county-level crop yield statistics, and compare it with various traditional crop monitoring approaches. We find that a SIF-based approach accounting for photosynthetic pathways (i.e. C3 and C4 crops) provides the best measure of crop productivity among these approaches, despite the fact that SIF sensors are not yet optimized for terrestrial applications. We further show that SIF provides the ability to infer the impacts of environmental stresses on autotrophic respiration and carbon-use-efficiency, with a substantial sensitivity of both to high temperatures. These results indicate new opportunities for improved mechanistic understanding of crop yield responses to climate variability and change.

Guan, Kaiyu↗

The MSFC Solar Activity Future Estimation (MSAFE) Model

The Natural Environments Branch of the Engineering Directorate at Marshall Space Flight Center (MSFC) provides solar cycle forecasts for NASA space flight programs and the aerospace community. These forecasts provide future statistical estimates of sunspot number, solar radio 10.7 cm flux (F10.7), and the geomagnetic planetary index, Ap, for input to various space environment models. For example, many thermosphere density computer models used in spacecraft operations, orbital lifetime analysis, and the planning of future spacecraft missions require as inputs the F10.7 and Ap. The solar forecast is updated each month by executing MSAFE using historical and the latest month's observed solar indices to provide estimates for the balance of the current solar cycle. The forecasted solar indices represent the 13-month smoothed values consisting of a best estimate value stated as a 50 percentile value along with approximate +/- 2 sigma values stated as 95 and 5 percentile statistical values. This presentation will give an overview of the MSAFE model and the forecast for the current solar cycle.

Suggs, Ron↗

The MSFC Solar Activity Future Estimation (MSAFE) Model

The Natural Environments Branch of the Engineering Directorate at Marshall Space Flight Center (MSFC) provides solar cycle forecasts for NASA space flight programs and the aerospace community. These forecasts provide future statistical estimates of sunspot number, solar radio 10.7 cm flux (F10.7), and the geomagnetic planetary index, Ap, for input to various space environment models. For example, many thermosphere density computer models used in spacecraft operations, orbital lifetime analysis, and the planning of future spacecraft missions require as inputs the F10.7 and Ap. The solar forecast is updated each month by executing MSAFE using historical and the latest month's observed solar indices to provide estimates for the balance of the current solar cycle. The forecasted solar indices represent the 13-month smoothed values consisting of a best estimate value stated as a 50 percentile value along with approximate +/- 2 sigma values stated as 95 and 5 percentile statistical values. This presentation will give an overview of the MSAFE model and the forecast for the current solar cycle.

Suggs, Ron↗

The MSFC Solar Activity Future Estimation (MSAFE) Model

The Natural Environments Branch of the Engineering Directorate at Marshall Space Flight Center (MSFC) provides solar cycle forecasts for NASA space flight programs and the aerospace community. These forecasts provide future statistical estimates of sunspot number, solar radio 10.7 cm flux (F10.7), and the geomagnetic planetary index, Ap, for input to various space environment models. For example, many thermosphere density computer models used in spacecraft operations, orbital lifetime analysis, and the planning of future spacecraft missions require as inputs the F10.7 and Ap. The solar forecast is updated each month by executing MSAFE using historical and the latest month's observed solar indices to provide estimates for the balance of the current solar cycle. The forecasted solar indices represent the 13-month smoothed values consisting of a best estimate value stated as a 50 percentile value along with approximate +/- 2 sigma values stated as 95 and 5 percentile statistical values. This presentation will give an overview of the MSAFE model and the forecast for the current solar cycle.

Suggs, Ron↗

Approach-Phase Precision Landing with Hazard Relative Navigation: Terrestrial Test Campaign Results of the Morpheus/ALHAT Project

The Morpheus Project began in late 2009 as an ambitious e ort code-named Project M to integrate three ongoing multi-center NASA technology developments: humanoid robotics, liquid oxygen/liquid methane (LOX/LCH4) propulsion and Autonomous Precision Landing and Hazard Avoidance Technology (ALHAT) into a single engineering demonstration mission to be own to the Moon by 2013. The humanoid robot e ort was redirected to a deploy- ment of Robonaut 2 on the International Space Station in February of 2011 while Morpheus continued as a terrestrial eld test project integrating the existing ALHAT Project's tech- nologies into a sub-orbital ight system using the world's rst LOX/LCH4 main propulsion and reaction control system fed from the same blowdown tanks. A series of 33 tethered tests with the Morpheus 1.0 vehicle and Morpheus 1.5 vehicle were conducted from April 2011 - December 2013 before successful, sustained free ights with the primary Vertical Testbed (VTB) navigation con guration began with Free Flight 3 on December 10, 2013. Over the course of the following 12 free ights and 3 tethered ights, components of the ALHAT navigation system were integrated into the Morpheus vehicle, operations, and ight control loop. The ALHAT navigation system was integrated and run concurrently with the VTB navigation system as a reference and fail-safe option in ight (see touchdown position esti- mate comparisons in Fig. 1). Flight testing completed with Free Flight 15 on December 15, 2014 with a completely autonomous Hazard Detection and Avoidance (HDA), integration of surface relative and Hazard Relative Navigation (HRN) measurements into the onboard dual-state inertial estimator Kalman lter software, and landing within 2 meters of the VTB GPS-based navigation solution at the safe landing site target. This paper describes the Mor- pheus joint VTB/ALHAT navigation architecture, the sensors utilized during the terrestrial ight campaign, issues resolved during testing, and the navigation results from the ight tests.

Crain, Timothy P.↗

Early Estimation of Solar Activity Cycle: Potential Capability and Limits

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and longterm sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Kitiashvili, Irina N.↗

Using Data Assimilation Methods of Prediction of Solar Activity

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and long-term sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Prediction↗

Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

Adaptive Contro↗

Sextant Navigation on the International Space Station: A Human Space Exploration Demo

Astronauts on board the International Space Station (ISS) tested a hand-held sextant to demonstrate potential use on future human exploration missions such as Orion and Gateway. The investigation, designed to aid in the development of emergency navigation methods for future crewed spacecraft, took place from June-December 2018. A sextant provides manual capability to perform star/planet-limb sightings and estimate vehicle state during loss of communication or other contingencies. Its simplicity and independence from primary systems make it useful as an emergency survival backup or confirming measurement source. The concept of using a sextant has heritage in Gemini, Apollo, and Skylab. This paper discusses the instrument selection, flight certification, crew training, product development, experiment execution, and data analysis. Preflight training consisted of a hands-on session with the instrument and practice in a Cupola mock-up with star field projector dome. The experiment itself consisted of several sessions with sextant sightings in the ISS Cupola module by two crew members. Sightings were taken on star pairs, star/moon limb, and moon diameter. The sessions were designed to demonstrate star identification and acquisition, sighting stability, accuracy, and lunar sights. Results are presented which demonstrate sightings within the accuracy goal of 60 arcseconds, even in the presence of window refraction effects and minimal crew training. The crew members provided valuable feedback on sighting products and microgravity stability techniques.

Exploration↗

NCA-LDAS: Overview and Analysis of Hydrologic Trends for the National Climate Assessment

Terrestrial hydrologic trends over the conterminous United States are estimated for 1980-47 2015 using the National Climate Assessment-Land Data Assimilation System (NCA-LDAS) reanalysis. NCA-LDAS employs the uncoupled Noah Version 3.3 land surface model at 0.125 degreesx0.125 degrees forced with NLDAS-2 meteorology, rescaled Climate Prediction Center precipitation, and assimilated satellite-based soil moisture, snow depth and irrigation products. Mean annual trends are reported using the nonparametric Mann-Kendall test at p<0.1 significance. Results illustrate the interrelationship between regional gradients in forcing trends, and trends in other land energy and water stores and fluxes. Mean precipitation trends range from +3 to +9 mm/yr in the Upper Great Plains and Northeast to -1 to -9 in the West and South; net radiation flux trends range from +0.05 to +0.20 W/m(exp2)/yr in the East to -0.05 to -0.20 in the West; U.S.-wide temperature trends average about +0.03K/yr. Trends in soil moisture, snow cover, latent and sensible heat fluxes and runoff are consistent with forcings, contributing to increasing evaporative fraction trends from West to East. Evaluation of NCA-LDAS trends compared to independent data indicates mixed results. The RMSE of U.S.-wide trends in number of snow cover days improved from 3.13 to 2.89 days/yr while trend detection increased 11%; Trends in latent heat flux were hardly affected, RMSE decreasing only 0.17 to 0.16 W/m(exp 2)/yr, while trend detection increased 2%; NCA-LDAS runoff trends degraded significantly from 2.6 to 16.1 mm/yr while trend detection was unaffected. Analysis also indicated that NCA-LDAS exhibits relatively more skill in low precipitation station density areas, suggesting there are limits to the effectiveness of satellite data assimilation in densely gaged regions. Overall, NCA-LDAS demonstrates capability for quantifying physically consistent, U.S. hydrologic climate trends over the satellite era.

Snow depth↗