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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Refactoring and Componentizing Legacy Codes: GMI Case Study

As Earth science applications grow increasingly complex over time, maintenance of such software becomes a significant challenge. In general, the software subsystems were designed, implemented and integrated (over an extended period of time) by different groups that did not follow the same software design standard. The objective was understandably to obtain scientific results quickly, but this goal was often achieved at the expense of good software practices. With that pattern of development, the cost of incremental changes to the applications grow ominously large. This increase in effort, tends to squeeze development resources and largely prevent any systematic attempt to reintroduce better software practices and thereby enhance the maintainability of the software. In this paper, we present the process we used to incrementally refactor and componentize the Global Modeling Initiative code to make it more understandable, maintainable, flexible and extensible. The resulting product not only preserves the scientific integrity of the original code but also extends the capabilities of the code for several applications.

Kouatchou, Jules↗
NASA NTRS2011

NASA's UAS NAS Access Project

The vision of the Unmanned Aircraft System (UAS) Integration in the National Airspace System (NAS) Project is "A global transportation system which allows routine access for all classes of UAS." The goal of the UAS Integration in the NAS Project is to "contribute capabilities that reduce technical barriers related to the safety and operational challenges associated with enabling routine UAS access to the NAS." This goal will be accomplished through a two-phased approach based on development of system-level integration of key concepts, technologies and/or procedures, and demonstrations of integrated capabilities in an operationally relevant environment. Phase 1 will take place the first two years of the Project and Phase 2 will take place the following three years. The Phase 1 and 2 technical objectives are: Phase 1: Developing a gap analysis between current state of the art and the Next Generation Air Transportation System (NextGen) UAS Concept of Operations . Validating the key technical areas identified by this Project . Conducting initial modeling, simulation, and flight testing activities . Completing Sub-project Phase 1 deliverables (spectrum requirements, comparative analysis of certification methodologies, etc.) and continue Phase 2 preparation (infrastructure, tools, etc.) Phase 2: Providing regulators with a methodology for developing airworthiness requirements for UAS, and data to support development of certifications standards and regulatory guidance . Providing systems-level, integrated testing of concepts and/or capabilities that address barriers to routine access to the NAS. Through simulation and flight testing, address issues including separation assurance, communications requirements, and human systems integration in operationally relevant environments. The UAS in the NAS Project will demonstrate solutions in specific technology areas, which will address operational/safety issues related to UAS access to the NAS. Since the resource allocation for this Project is limited ($150M over the five years), the focus is on reducing the technical barriers where NASA has unique capabilities. As a result, technical areas, such as Sense and Avoid (SAA) and beyond line of sight command and control will not be addressed. While these are critical barriers to UAS access, currently, there is a great deal of global effort being exercised to address these challenge areas. Instead, specific technology development in areas where there is certainty that NASA can advance the research to high technology readiness levels will be the Project's focus. Specific sub-projects include Separation Assurance, Human Systems Integration, Communications, Certification, and Integrated Test and Evaluation. Each sub-project will transfer technologies to relevant key stakeholders and decision makers through research transition teams, technology forums, or through other analogous means.

Johnson, Charles W.↗
NASA NTRS2008

A Thermal Precipitator for Fire Characterization Research

Characterization of the smoke from pyrolysis of common spacecraft materials provides insight for the design of future smoke detectors and post-fire clean-up equipment on the International Space Station. A thermal precipitator was designed to collect smoke aerosol particles for microscopic analysis in fire characterization research. Information on particle morphology, size and agglomerate structure obtained from these tests supplements additional aerosol data collected. Initial modeling for the thermal precipitator design was performed with the finite element software COMSOL Multiphysics, and includes the flow field and heat transfer in the device. The COMSOL Particle Tracing Module was used to determine particle deposition on SEM stubs which include TEM grids. Modeling provided optimized design parameters such as geometry, flow rate and temperatures. Microscopy results from fire characterization research using the thermal precipitator are presented.

Meyer, Marit↗
NASA NTRS2012

Assessing the Association Between Asthma and Air Quality in the Presence of Wildfires

Asthma hospital/emergency room (patient) data are used as the foundation for creating a health outcome indicator of human response to environmental air quality. Daily U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) fine particulates (PM2.5) ground data and the U.S. National Aeronautical Space Administration (NASA) MODIS aerosol optical depth (AOD) data were acquired and processed for years of 2007 and 2008. Figure 1 shows the PM2.5 annual mean composite of all the 2007 B-spline daily surfaces. Initial models for predicting the number of weekly asthma cases within a Florida county has focused on environmental variables. Weekly maximums of PM2.5, relative humidity, and the proportions of the county with smoke and fire were the environmental variables included in the model. Cosine and sine functions of time were used to account for seasonality in asthma cases. Counties were considered to be random effects, thereby adjusting for differences in socio ]demographics and other factors. The 2007 predictions for Miami ]Dade county when using B ]splines PM2.5 are displayed in Figures 2.

Young, L. J.↗
NASA NTRS2013

Impact of AIRS Thermodynamic Profiles on Precipitation Forecasts for Atmospheric River Cases Affecting the Western United States

This project is a collaborative activity between the NASA Short-term Prediction Research and Transition (SPoRT) Center and the NOAA Hydrometeorology Testbed (HMT) to evaluate a SPoRT Advanced Infrared Sounding Radiometer (AIRS: Aumann et al. 2003) enhanced moisture analysis product. We test the impact of assimilating AIRS temperature and humidity profiles above clouds and in partly cloudy regions, using the three-dimensional variational Gridpoint Statistical Interpolation (GSI) data assimilation (DA) system (Developmental Testbed Center 2012) to produce a new analysis. Forecasts of the Weather Research and Forecasting (WRF) model initialized from the new analysis are compared to control forecasts without the additional AIRS data. We focus on some cases where atmospheric rivers caused heavy precipitation on the US West Coast. We verify the forecasts by comparison with dropsondes and the Cooperative Institute for Research in the Atmosphere (CIRA) Blended Total Precipitable Water product.

Zavodsky, Bradley T.↗
NASA NTRS2014

Global Free Tropospheric NO2 Abundances Derived Using a Cloud Slicing Technique Applied to Satellite Observations from the Aura Ozone Monitoring Instrument (OMI)

We derive free-tropospheric NO2 volume mixing ratios (VMRs) and stratospheric column amounts of NO2 by applying a cloud slicing technique to data from the Ozone Monitoring Instrument (OMI) on the Aura satellite. In the cloud-slicing approach, the slope of the above-cloud NO2 column versus the cloud scene pressure is proportional to the NO2 VMR. In this work, we use a sample of nearby OMI pixel data from a single orbit for the linear fit. The OMI data include cloud scene pressures from the rotational-Raman algorithm and above-cloud NO2 vertical column density (VCD) (defined as the NO2 column from the cloud scene pressure to the top-of-the-atmosphere) from a differential optical absorption spectroscopy (DOAS) algorithm. Estimates of stratospheric column NO2 are obtained by extrapolating the linear fits to the tropopause. We compare OMI-derived NO2 VMRs with in situ aircraft profiles measured during the NASA Intercontinental Chemical Transport Experiment Phase B (INTEX-B) campaign in 2006. The agreement is generally within the estimated uncertainties when appropriate data screening is applied. We then derive a global seasonal climatology of free-tropospheric NO2 VMR in cloudy conditions. Enhanced NO2 in the free troposphere commonly appears near polluted urban locations where NO2 produced in the boundary layer may be transported vertically out of the boundary layer and then horizontally away from the source. Signatures of lightning NO2 are also shown throughout low and middle latitude regions in summer months. A profile analysis of our cloud slicing data indicates signatures of uplifted and transported anthropogenic NO2 in the middle troposphere as well as lightning-generated NO2 in the upper troposphere. Comparison of the climatology with simulations from the Global Modeling Initiative (GMI) for cloudy conditions (cloud optical thicknesses > 10) shows similarities in the spatial patterns of continental pollution outflow. However, there are also some differences in the seasonal variation of free-tropospheric NO2 VMRs near highly populated regions and in areas affected by lightning-generated NOx. Stratospheric column NO2 obtained from cloud slicing agrees well with other independently-generated estimates, providing further confidence in the free-tropospheric results.

NO2↗
NASA NTRS2012

Classification of Ascension Island and Natal Ozonesondes Using Self-Organizing Maps

Ozone profiles from balloon-borne ozonesondes are used for development of satellite algorithms and in chemistry-climate model initialization, assimilation and evaluation. An important issue in the application of these profiles is how best to treat variations where varying photochemical and dynamical influences can cause the ozone mixing ratio in the tropospheric segments of the profile to change by of a factor of 2-3 within a day. Clustering techniques are an ideal way to approach the statistical classification of profile data and we apply self-organizing maps to tropical tropospheric SHADOZ data, hypothesizing that the data will sort according to various influences on ozone, namely anthropogenic sources like biomass burning, meteorological conditions, and stratospheric or extra-tropical intrusions. Self-organizing maps, that use a learning algorithm to reveal the most prominent features of a data set according to a specified number of clusters, have been determined for the 1998-2009 SHADOZ profiles over Ascension Island (512 profiles, 7.98 deg. S, 14.42 deg. W) and Natal, Brazil (425 profiles, 5.42degS, 35.38degW). The 2 × 2 self-organizing map, which creates 4 clusters, reveals that deviations from the average ozone in the free troposphere include both increased ozone resulting from seasonal biomass burning in Africa and locally reduced ozone brought about by convective lifting of unpolluted boundary-layer air. Expanding to a 4 × 4 self-organizing map shows how biomass burning influences the yearly cycle of tropospheric ozone at Ascension Island and captures the seasonality of ozone at both Ascension Island and Natal. Comparing Ascension Island and Natal using a 4 × 4 self-organizing map at each site reveals similarities in mid-tropospheric ozone, but shows differences in lower-tropospheric ozone due to Ascension Island being closer to African biomass burning and more affected by descent from the mean Walker circulation, with less convective activity, than Natal.

algorithms↗
NASA NTRS2014

Modeling for Integrated Science Management and Resilient Systems Development

Many physiological, environmental, and operational risks exist for crewmembers during spaceflight. An understanding of these risks from an integrated perspective is required to provide effective and efficient mitigations during future exploration missions that typically have stringent limitations on resources available, such as mass, power, and crew time. The Human Research Program (HRP) is in the early stages of developing collaborative modeling approaches for the purposes of managing its science portfolio in an integrated manner to support cross-disciplinary risk mitigation strategies and to enable resilient human and engineered systems in the spaceflight environment. In this talk, we will share ideas being explored from fields such as network science, complexity theory, and system-of-systems modeling. Initial work on tools to support these explorations will be discussed briefly, along with ideas for future efforts.

Shelhamer, M.↗
NASA NTRS2014

Global Free-tropospheric NO2 Abundances Derived Using a Cloud Slicing Technique from AURA OMI

We derive free-tropospheric NO2 volume mixing ratios (VMRs) by applying a cloud-slicing technique to data from the Ozone Monitoring Instrument (OMI) on the Aura satellite. In the cloud-slicing approach, the slope of the above-cloud NO2 column versus the cloud scene pressure is proportional to the NO2 VMR. In this work, we use a sample of nearby OMI pixel data from a single orbit for the linear fit. The OMI data include cloud scene pressures from the rotational-Raman algorithm and above-cloud NO2 vertical column density (VCD) (defined as the NO2 column from the cloud scene pressure to the top of the atmosphere) from a differential optical absorption spectroscopy (DOAS) algorithm. We compare OMI-derived NO2 VMRs with in situ aircraft profiles measured during the NASA Intercontinental Chemical Transport Experiment Phase B (INTEX-B) campaign in 2006. The agreement is generally within the estimated uncertainties when appropriate data screening is applied. We then derive a global seasonal climatology of free-tropospheric NO2 VMR in cloudy conditions. Enhanced NO2 in the free troposphere commonly appears near polluted urban locations where NO2 produced in the boundary layer may be transported vertically out of the boundary layer and then horizontally away from the source. Signatures of lightning NO2 are also shown throughout low and middle latitude regions in summer months. A profile analysis of our cloud-slicing data indicates signatures of lightning-generated NO2 in the upper troposphere. Comparison of the climatology with simulations from the global modeling initiative (GMI) for cloudy conditions (cloud optical depth less than10) shows similarities in the spatial patterns of continental pollution outflow. However, there are also some differences in the seasonal variation of free-tropospheric NO2 VMRs near highly populated regions and in areas affected by lightning-generated NOx.

NO2↗
NASA NTRS2012

MSL DSENDS EDL Analysis and Operations

This paper presents the operations experience of the JPL EDL (Entry, Descent, and Landing) trajectory simulation team, focusing on events in the week before landing and EDL itself. A brief description of the EDL trajectory simulation tool used for targeting and simulation verification analysis will be presented, including a high level discussion of the required modeling. Initialization and output interfaces used for landing hazard analysis will also be covered, along with discussion of real-time EDL event detection using radiometric Doppler data.

Entry, descent, and landing (EDL)↗
NASA NTRS2010

Lessons Learned from the Wide Field Camera 3 Flight Correlation

The Wide Field Camera 3 (WFC3) instrument was installed into the Hubble Space Telescope (HST) as part of the activities for STS (Space Transportation System)-125 (HST Servicing Mission 4). Initial model predictions for power and radiator temperature were not in good agreement with flight data during a relatively hot, stable period, with the flight power and temperatures being significantly higher than predictions. Significant efforts were undertaken to identify the causes of the discrepancies and to resolve the flight model correlation problems as the thermal vacuum test correlation indicated good agreement. The WFC3 thermal design performance has proven difficult to accurately predict, since the power dissipation on the radiator typically increases as the radiator temperature increases, due to a Thermo Electric Cooler (TEC) attached to the this radiator. This self beating continues until the radiative emissive capability is met for a given temperature, and only then does the system find a quasi-steady regime. Various other factors may also contribute to the radiator temperature, such as backloadlng from the observatory itself and the planet, local high-absorptivity regions near fasteners/holes, and temperature varying parasitic heat leaks from the instrument itself to the radiator. Each of these effects in turn may increase the radiator temperature, and furthermore the demand on the TEC.

Peabody, Hume L.↗
NASA NTRS2018

GEOS-5 Seasonal Forecast System: ENSO Prediction Skill and Bias

The GEOS-5 AOGCM known as S2S-1.0 has been in service from June 2012 through January 2018 (Borovikov et al. 2017). The atmospheric component of S2S-1.0 is Fortuna-2.5, the same that was used for the Modern-Era Retrospective Analysis for Research and Applications (MERRA), but with adjusted parameterization of moist processes and turbulence. The ocean component is the Modular Ocean Model version 4 (MOM4). The sea ice component is the Community Ice CodE, version 4 (CICE). The land surface model is a catchment-based hydrological model coupled to the multi-layer snow model. The AGCM uses a Cartesian grid with a 1 deg × 1.25 deg horizontal resolution and 72 hybrid vertical levels with the upper most level at 0.01 hPa. OGCM nominal resolution of the tripolar grid is 1/2 deg, with a meridional equatorial refinement to 1/4 deg. In the coupled model initialization, selected atmospheric variables are constrained with MERRA. The Goddard Earth Observing System integrated Ocean Data Assimilation System (GEOS-iODAS) is used for both ocean state and sea ice initialization. SST, T and S profiles and sea ice concentration were assimilated.

GEOS-↗
NASA NTRS2018

Ag Isotopic Evolution of the Mantle During Accretion: New Constraints from Pd and Ag Metal-Silicate Partitioning

Decay of (sup 107) Pd to (sup 107) Ag has a half-life of 6.5 times 10 (sup 6) mega-annums. Because these elements are siderophile but also volatile, they offer potential constraints on the timing of core formation as well as volatile addition. Initial modelling has shown that the Ag isotopic composition of the bulk silicate Earth (BSE) can be explained if accretion occurs with late volatile addition. These arguments were tested for sensitivity for pre-cursor Pd/Ag contents, and for a fixed Pd/Ag ratio of the BSE of 0.1. New Ag and Pd partitioning data has allowed a better understanding of the partitioning behavior of Pd and Ag during core formation. The effects of S, C and Si, and the effect of high temperature and pressure has been evaluated. We can now calculate D(Ag) and D(Pd) over the wide range of PT conditions and variable metallic liquid compositions that are known during accretion. We then use this new partitioning information to revisit the Ag isotopic composition of the BSE during accretion.

Righter, K.↗
NASA NTRS2018

Evaluating the WRF-Hydro Modeling System in Alaska

National Water Model (NWM) implemented operationally in August 2016 to improve hydrological prediction (OWP, 2017). (1) Four operational configurations (2) Only covers contiguous United States (US). NWM is instantiation of Weather Research and Forecasting model hydrological extension package (WRF-Hydro)(Gochis et al., 2013) coupled with Noah Land Surface Model with Multi-Parameterization options (Noah-MP)(Niu et al., 2011). WRF-Hydro is extensible, high-resolution hydrologic routing and streamflow modeling framework, coupling column land surface, terrain routing, and channel routing modules (NCAR, 2017). This project uses experimental version of WRF-Hydro in Alaska mimicking the NWM to: (1) Identify modeling challenges for NWM development in Alaska (2) Assess WRF-Hydro and NWM ability to represent unique hydrological processes of arctic regions and accurately predict high and low flow events (3) Examine impacts of assimilating Surface Water Ocean Topography (SWOT) (Biancamaria et al., 2016) observations to improve model initialization.

Hydrology↗
NASA NTRS2018

Human Automation Teaming: Lessons Learned and Future Directions

Full autonomy seems to be the goal for system developers in almost every area of the economy. However, as we move from automated systems to autonomous systems, designers have needed to insert humans to oversee automation that has traditionally been brittle or incomplete. This creates its own problems as the operator is usually out of the loop when the automation hands over problems that it cannot handle. To better handle these situations, it has been proposed that we develop human automation teams that have shared goals and objectives to support task performance. This paper will describe an initial model of Human Automation Teaming (HAT) which has three elements: transparency, bi-directional communications, and human-directed execution. Transparency in our model is a method for giving insight into the reasoning behind automated recommendations and actions, bi-directional communication allows the operator to communicate directly with the automation, and finally the automation defers execution to the human. The model was implemented through a number of features on an electronic flight bag (EFB) which are described in the paper. The EFB was installed in a mid-fidelity flight simulator and used by 12 airline pilots to support diversion decisions during off-nominal flight scenarios. Pilots reported that working with the HAT automation made diversion decisions easier and reduced their workload. They also reported that the information provided about diversion airports was similar to what they would receive from ground dispatch, thus making coordination with dispatch easier and less time consuming. These HAT features engender more trust in the automation when appropriate, and less when not, allowing improved supervision of automated functions by flight crews.

Human-Autonomy Teaming↗
NASA NTRS2017

Mars Science Laboratory Radiation Assessment Detector (MSLRAD) Modeling Workshop Proceedings

The Radiation Assessment Detector (RAD) (Hassler et al., 2012) onboard the Mars Science Laboratory (MSL) Curiosity rover (Grotzinger et al., 2012) has been making detailed measurements of the radiation environment on the surface of Mars since landing on 6 August 2012 (Hassler et al., 2014; Zeitlin et al., 2016). These measurements are the first of their kind on the surface of another planet and are providing essential measurements of the radiation environment on Mars in preparation for a human mission in the coming decades. The objectives of RAD are; 1) to characterize the energetic particle spectrum on the surface of Mars as a function of time in the solar cycle, including direct (galactic cosmic rays and solar energetic particles) and indirect (neutrons, etc.) radiation created in the atmosphere and regolith, 2) to determine the dose and dose‐equivalent rates as a function of time in the solar cycle, and 3) to use these observations to test and validate space radiation transport models. Initial results of the charged particle spectra (Ehresmann et al., 2014) and neutral particle spectrum (Köhler et al., 2014), as well as dose and dose‐equivalent during cruise (Zeitlin et al., 2013) and on the surface (Hassler et al., 2014) have been reported, and with almost five years of continuous measurements, RAD continues to characterize the radiation environment as solar minimum is approached.

Donald M Hassler↗
NASA NTRS2019

Planetary Science with Small Satellites: Opportunities and Challenges

Small satellites aren't anything particularly new. Earth orbiting small satellites go back 30 years or more. What is new is the proliferation and access to small satellite technologies and flight opportunities. This has been in large part due to the advent of the "cubesat" model, initially a means to develop student's engineering skills, but has since evolved into an industry and accepted method within government space agencies. Until very recently these smallsats were limited to Earth orbiting missions, but with the successful flight of the MarCO spacecraft and the upcoming launch of EM-1 cubesats, the Moon, Mars and beyond are now within reach. While all this is good news, we still have a ways to go before smallsats become true planetary science tools. One could argue that Deep Space 2 was the first planetary smallsat, launched in 1999 and having a mass of 2.3 kg (each probe) it hoped to demonstrate that "real" science could be done with a small (and less expensive) package. The DS2 failure shelved the idea of smallsats (even chilling some to "Class D" planetary missions in general) for nearly two decades. NASA has slowly come back around to smallsats for planetary missions, going so far as to support a range of mission studies (the Planetary Science Deep Space SmallSat Studies, or PSDS3, Program) and the creation of a new Program (SIMPLEx) to developed such missions for opportunistic flights. The MarCO success was hugely important in maintaining (and building) this forward momentum. However, we still have yet to demonstrate "real" science from a planetary smallsat and there are some fundamental disconnects between expectation and reality. This talk will discuss some of the opportunities and challenges that reside with planetary smallsats, focusing on two examples: LunaH-Map (the first SIMPLEx cubesat) and Aeolus (a Mars PSDS3 smallsat concept).

Colaprete, Anthony↗
NASA NTRS2019

Cloud Influence on ERA5 and AMPS Surface Downwelling Longwave Radiation Biases in West Antarctica

The surface downwelling longwave radiation component (LW[down arrow]) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW[down arrow] signal measured at the surface. In this study, we examine the LW[down arrow] model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 reanalysis model relative to observations from the AWARE campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW[down arrow] during clear sky conditions, high error variability (standard deviations > 20 W/m[exp2]) during any type of cloud occurrence, and negative LW biases when LBCLs are observed (bias magnitudes > 15 W/m[exp2] in tenuous LBCL cases; > 43 W/m[exp2] in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for the identified LW[down arrow] biases in both models is the result of excessive ice formation and growth, which could stem from model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.

Israel Silber↗