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At least 1,063 records · Page 59

UAS-Systems Integration, Validation, and Diagnostics Simulation Capability

As part of the Phase 1 efforts of NASA's UAS-in-the-NAS Project a task was initiated to explore the merits of developing a system simulation capability for UAS to address airworthiness certification requirements. The core of the capability would be a software representation of an unmanned vehicle, including all of the relevant avionics and flight control system components. The specific system elements could be replaced with hardware representations to provide Hardware-in-the-Loop (HWITL) test and evaluation capability. The UAS Systems Integration and Validation Laboratory (UAS-SIVL) was created to provide a UAS-systems integration, validation, and diagnostics hardware-in-the-loop simulation capability. This paper discusses how SIVL provides a robust and flexible simulation framework that permits the study of failure modes, effects, propagation paths, criticality, and mitigation strategies to help develop safety, reliability, and design data that can assist with the development of certification standards, means of compliance, and design best practices for civil UAS.

Buttrill, Catherine W.↗

Diagnostic modeling of dimethylsulfide production in coastal water west of the Antarctic Peninsula

The rate of gross biological dimethylsulfide (DMS) production at two coastal sites west of the Antarctic Peninsula, off Anvers Island, near Palmer Station, was estimated using a diagnostic approach that combined field measurements from 1 January 2006 through 1 March 2006 and a one-dimensional physical model of ocean mixing. The average DMS production rate in the upper water column (0-60 m) was estimated to be 3.1 +/- 0.6 nM/d at station B (closer to shore) and 2.7 +/- 0.6 nM/d1 at station E (further from shore). The estimated DMS replacement time was on the order of 1 d at both stations. DMS production was greater in the mixed layer than it was below the mixed layer. The average DMS production normalized to chlorophyll was 0.5 +/- nM/d)/(mg cubic m) at station B and 0.7 +/- 0.2 (nM/d)/(mg/cubic m3) at station E. When the diagnosed production rates were normalized to the observed concentrations of total dimethylsulfoniopropionate (DMSPt, the biogenic precursor of DMS), we found a remarkable similarity between our estimates at stations B and E (0.06 +/- 0.02 and 0.04 +/- 0.01 (nM DMS / d1)/(nM DMSP), respectively) and the results obtained in a previous study from a contrasting biogeochemical environment in the North Atlantic subtropical gyre (0.047 =/- 0.006 and 0.087 +/- 0.014 (nM DMS d1)/(nM DMSP) in a cyclonic and anticyclonic eddy, respectively).We propose that gross biological DMS production normalized to DMSPt might be relatively independent of the biogeochemical environment, and place our average estimate at 0.06 +/- 0.01 (nM DMS / d)/(nM DMSPt). The significance of this finding is that it can provide a means to use DMSPt measurements to extrapolate gross biological DMS production, which is extremely difficult to measure experimentally under realistic in situ conditions.

Dimethylsulfide↗

Overview of NASA GRCs Green Propellant Infusion Mission Thruster Testing and Plume Diagnostics

The Green Propellant Infusion Mission (GPIM) is sponsored by NASA's Space Technology Mission Directorate (STMD) Technology Demonstration Mission (TDM) office. The goal of GPIM is to advance the technology readiness level of a green propulsion system, specifically, one using the monopropellant, AF-M315E, by demonstrating ground handling, spacecraft processing, and on-orbit operations. One of the risks identified for GPIM is potential contamination of sensitive spacecraft surfaces from the effluents in the plumes of AF-M315E thrusters. NASA Glenn Research Center (GRC) is conducting activities to characterize the effects of AF-M315E plume impingement and deposition. GRC has established individual plume models of the 22-N and 1-N thrusters that will be used on the GPIM spacecraft. The models describe the pressure, temperature, density, Mach number, and species concentration of the AF-M315E thruster exhaust plumes. The models are being used to assess the impingement effects of the AF-M315E thrusters on the GPIM spacecraft. The model simulations will be correlated with plume measurement data from Laboratory and Engineering Model 22-N, AF-M315E thrusters. The thrusters will be tested in a small rocket, altitude facility at NASA GRC. The GRC thruster testing will be conducted at duty cycles representatives of the planned GPIM maneuvers. A suite of laser-based diagnostics, including Raman spectroscopy, Rayleigh spectroscopy, Schlieren imaging, and physical probes will be used to acquire plume measurements of AFM315E thrusters. Plume data will include temperature, velocity, relative density, and species concentration. The plume measurement data will be compared to the corresponding simulations of the plume model. The GRC effort will establish a data set of AF-M315E plume measurements and a plume model that can be used for future AF-M315E applications.

green Propellants↗

The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Overview and Description of Models, Simulations and Climate Diagnostics

The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.

humidity↗

Verification of Loop Diagnostics

Many different techniques have been used to characterize the plasma in the solar corona: density-sensitive spectral line ratios are used to infer the density, the evolution of coronal structures in different passbands is used to infer the temperature evolution, and the simultaneous intensities measured in multiple passbands are used to determine the emission measure. All these analysis techniques assume that the intensity of the structures can be isolated through background subtraction. In this paper, we use simulated observations from a 3D hydrodynamic simulation of a coronal active region to verify these diagnostics. The density and temperature from the simulation are used to generate images in several passbands and spectral lines. We identify loop structures in the simulated images and calculate the loop background. We then determine the density, temperature and emission measure distribution as a function of time from the observations and compare with the true temperature and density of the loop. We find that the overall characteristics of the temperature, density, and emission measure are recovered by the analysis methods, but the details of the true temperature and density are not. For instance, the emission measure curves calculated from the simulated observations are much broader than the true emission measure distribution, though the average temperature evolution is similar. These differences are due, in part, to inadequate background subtraction, but also indicate a limitation of the analysis methods.

Winebarger, A.↗

The Green Propellant Infusion Mission Thruster Performance Testing for Plume Diagnostics

The Green Propellant Infusion Mission (GPIM) is sponsored by NASA's Space Technology Mission Directorate (STMD) Technology Demonstration Mission (TDM) office. The goal of GPIM is to advance the technology readiness level of a green propulsion system, specifically, one using the monopropellant, AF-M315E, by demonstrating ground handling, spacecraft processing, and on-orbit operations. One of the risks identified for GPIM is potential contamination of sensitive spacecraft surfaces from the effluents in the plumes of AF-M315E thrusters. NASA Glenn Research Center (GRC) is conducting activities to characterize the effects of AF-M315E plume impingement and deposition. GRC has established individual plume models of the 22-N and 1-N thrusters that will be used on the GPIM spacecraft. The model simulations will be correlated with plume measurement data from Laboratory and Engineering Model 22-N, AF-M315E thrusters. The thrusters are currently being tested in a small rocket, altitude facility at NASA GRC. A suite of diagnostics, including Raman spectroscopy, Rayleigh spectroscopy, and Schlieren imaging are being used to acquire plume measurements of AF-M315E thrusters. Plume data will include temperature, velocity, relative density, and species concentration. The plume measurement data will be compared to the corresponding simulations of the plume model. The GRC effort will establish a data set of AF-M315E plume measurements and a plume model that can be used for future AF-M315E applications.

Green Propellants↗

Air Breathing Propulsion Controls and Diagnostics Research at NASA Glenn Under NASA Aeronautics Research Mission Programs

The Intelligent Control and Autonomy Branch (ICA) at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet the goals of the NASA Aeronautics Research Mission Directorate (ARMD) Programs. These efforts are primarily under the various projects under the Fundamental Aeronautics Program (FAP) and the Aviation Safety Program (ASP). The ICA Branch is focused on advancing the state-of-the-art of aero-engine control and diagnostics technologies to help improve aviation safety, increase efficiency, and enable operation with reduced emissions. This paper describes the various ICA research efforts under the NASA Aeronautics Research Mission Programs with a summary of motivation, background, technical approach, and recent accomplishments for each of the research tasks.

aircraft engines↗

Climate Model Diagnostic and Evaluation: With a Focus on Satellite Observations

Each year, we host a summer school that brings together the next generation of climate scientists - about 30 graduate students and postdocs from around the world - to engage with premier climate scientists from the Jet Propulsion Laboratory and elsewhere. Our yearly summer school focuses on topics on the leading edge of climate science research. Our inaugural summer school, held in 2011, was on the topic of "Using Satellite Observations to Advance Climate Models," and enabled students to explore how satellite observations can be used to evaluate and improve climate models. Speakers included climate experts from both NASA and the National Oceanic and Atmospheric Administration (NOAA), who provided updates on climate model diagnostics and evaluation and remote sensing of the planet. Details of the next summer school will be posted here in due course.

climate↗

Air Breathing Propulsion Controls and Diagnostics Research at NASA Glenn Under NASA Aeronautics Research Mission Programs

The Intelligent Control and Autonomy Branch (ICA) at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet the goals of the NASA Aeronautics Research Mission Directorate (ARMD) Programs. These efforts are primarily under the various projects under the Advanced Air Vehicles Program (AAVP), Airspace Operations and Safety Program (AOSP) and Transformative Aeronautics Concepts Program (TAC). The ICA Branch is focused on advancing the state-of-the-art of aero-engine control and diagnostics technologies to help improve aviation safety, increase efficiency, and enable operation with reduced emissions. This paper describes the various ICA research efforts under the NASA Aeronautics Research Mission Programs with a summary of motivation, background, technical approach, and recent accomplishments for each of the research tasks.

Engine Control↗

Feasibility of Rayleigh Scattering Flow Diagnostics in the National Transonic Facility

Laser-based Rayleigh light scattering (RLS) was performed in the National Transonic Facility (NTF) at NASA Langley Research Center. The goal was to determine if the free-stream flow undergoes clustering (early stage of condensation from gas to liquid) or remains in a pure diatomic molecular phase. Data indicate that clusters are not observable down to levels of 10% of the total light scatter for a variety of total pressures at one N2 cryogenic-mode total temperature (Tt = -50 F = 227 K) and one air-mode temperature (Tt = +130 F = 327 K). Thus RLS appears viable as a qualitative or quantitative diagnostic for flow density in NTF in the future. Particles are distinguished from optically unresolvable clusters because they are much larger and individually resolvable in the laser beam image with Mie scattering. The same RLS apparatus was also used, without modification, to visualize naturally occurring particles entrained in the flow for both cryogenic and air-modes. Estimates of the free-stream particle flux are presented, which may be important for interpretation of laminar-to-turbulent boundary-layer transition studies. 1

Herring, Gregory C.↗

Morphological Processing of Ultraviolet Emissions of Electrical Corona Discharge for Analysis and Diagnostic Use

Electron cascades from electrical discharge produce secondary emissions from atmospheric plasma in the ultraviolet band. For a single point of discharge, these emissions exhibit a stereotypical discharge morphology, with latent information about the discharge location. Morphological processing can uncover the location and therefore can have diagnostic utility.

Schubert, Matthew R.↗

Autonomous Diagnostic Imaging Performed by Untrained Operators using Augmented Reality as a Form of "Just-in-Time" Training

We will address the Human Factors and Performance Team, "Risk of performance errors due to training deficiencies" by improving the JIT training materials for ultrasound and OCT imaging by providing advanced guidance in a detailed, timely, and user-friendly manner. Specifically, we will (1) develop an audio-visual tutorial using AR that guides non-experts through an abdominal trauma ultrasound protocol; (2) develop an audio-visual tutorial using AR to guide an untrained operator through the acquisition of OCT images; (3) evaluate the quality of abdominal ultrasound and OCT images acquired by untrained operators using AR guidance compared to images acquired using traditional JIT techniques (laptop-based training conducted before image acquisition); and (4) compare the time required to complete imaging studies using AR tutorials with images acquired using current JIT practices to identify areas for time efficiency improvements. Two groups of subjects will be recruited to participate in this study. Operator-subjects, without previous experience in ultrasound or OCT, will be asked to perform both procedures using either the JIT training with AR technology or the traditional JIT training via laptop. Images acquired by inexperienced operator-subjects will be scored by experts in that imaging modality for diagnostic and research quality; experts will be blinded to the form of JIT used to acquire the images. Operator-subjects also will be asked to submit feedback to improve the training modules used during the scans to improve future training modules. Scanned-subjects will be a small group individuals from whom all images will be acquired.

Martin, D. S.↗

A Review of Recent Developments in X-Ray Diagnostics for Turbulent and Optically Dense Rocket Sprays

Highly efficient mixing and atomization of fuel and oxidizers is an important factor in many propulsion and power generating applications. To better quantify breakup and mixing in atomizing sprays, several diagnostic techniques have been developed to collect droplet information and spray statistics. Several optical based techniques, such as Ballistic Imaging and SLIPI have previously demonstrated qualitative measurements in optically dense sprays, however these techniques have produced limited quantitative information in the near injector region. To complement to these advances, a recent wave of developments utilizing synchrotron based x-rays have been successful been implemented facilitating the collection of quantitative measurements in optically dense sprays.

Radke, Christopher↗

Autonomous Diagnostic Imaging Performed by Untrained Operator Using Augmented Reality as a Form of "Just-in-Time" Training

We will address the Human Factors and Performance Team, "Risk of performance errors due to training deficiencies" by improving the JIT training materials for ultrasound and OCT imaging by providing advanced guidance in a detailed, timely, and user-friendly manner. Specifically, we will (1) develop an audio-visual tutorial using AR that guides non-experts through an abdominal trauma ultrasound protocol; (2) develop an audio-visual tutorial using AR to guide an untrained operator through the acquisition of OCT images; (3) evaluate the quality of abdominal ultrasound and OCT images acquired by untrained operators using AR guidance compared to images acquired using traditional JIT techniques (laptop-based training conducted before image acquisition); and (4) compare the time required to complete imaging studies using AR tutorials with images acquired using current JIT practices to identify areas for time efficiency improvements. Two groups of subjects will be recruited to participate in this study. Operator-subjects, without previous experience in ultrasound or OCT, will be asked to perform both procedures using either the JIT training with AR technology or the traditional JIT training via laptop. Images acquired by inexperienced operator-subjects will be scored by experts in that imaging modality for diagnostic and research quality; experts will be blinded to the form of JIT used to acquire the images. Operator-subjects also will be asked to submit feedback to improve the training modules used during the scans to improve future training modules. Scanned-subjects will be a small group individuals from whom all images will be acquired.

Martin, David S.↗

Diagnostic Techniques to Elucidate the Aerodynamic Performance of Acoustic Liners

In support of Topic A.2.8 of NASA NRA NNH10ZEA001N, the University of Florida (UF) has investigated the use of flow field optical diagnostic and micromachined sensor-based techniques for assessing the wall shear stress on an acoustic liner. Stereoscopic particle image velocimetry (sPIV) was used to study the velocity field over a liner in the Grazing Flow Impedance Duct (GFID). The results indicate that the use of a control volume based method to determine the wall shear stress is prone to significant error. The skin friction over the liner as measured using velocity curve fitting techniques was shown to be locally reduced behind an orifice, relative to the hard wall case in a streamwise plane centered on the orifice. The capacitive wall shear stress sensor exhibited a linear response for a range of shear stresses over a hard wall. PIV over the liner is consistent with lifting of the near wall turbulent structure as it passes over an orifice, followed by a region of low wall shear stress.

June, Jason↗

Global Assessment of the SMAP Level-4 Soil Moisture Product Using Assimilation Diagnostics

The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx. 2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

Reichle, Rolf↗