SEARCH · Engineering Papers

Results for “warning”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,747 records · Page 97

All sources NASA NTRS DOE OSTI

NASA NTRS2020

UAS Pilot Performance Comparisons with Different Low Size, Weight and Power Sensor Ranges

The present study evaluated the performance of UAS pilots under four simulated low size, weight, and power (SwaP) sensor ranges: 1.5nmi, 2.0nmi, 2.5nmi, and 3.0nmi. Nine active-duty UAS pilots responded to scripted DAA conflicts against non-cooperative intruders while flying a simulated RQ-7 Shadow at varied speeds along a pre-filed flight path in Class E airspace. Findings revealed a linear effect of sensor range on alerting time and separation performance, with nearly every DAA well clear (DWC) violation and all Near Mid-Air Collision (NMAC) events occurring below 2.5nmi. Response time differences at these reduced ranges were negligible due to the high frequency of warning-level alerts that require an immediate response. Since caution alert duration was truncated to some degree by each tested declaration range, pilots were often unable to coordinate their avoidance maneuvers with ATC prior to their uploads. Nonetheless, the 2.5nmi range allowed minimum alerting times that were sufficient for acceptable pilot performance. These findings will inform DAA system requirements for UAS with alternative surveillance equipment and aircraft performance capabilities. Implications on DAA display and sensor requirements are discussed.

unmanned aircraft systems↗

NASA NTRS2020

Convection Parametrization and Multi-Nesting Dependence of a Heavy Rainfall Event over Namibia with Weather Research and Forecasting (WRF) Model

Namibia is considered as one of the countries that are most vulnerable to climate change due to its generally dry climate and the percentage of its population that rely on subsistence agriculture for their livelihoods. Early warning systems are an important aspect of adapting to climate change. Weather forecasting relies on the use of numerical weather prediction models and these need to be configured properly. In this study we investigate the effects of using multi-nests and a convection scheme on the simulation of a heavy rainfall event over the Northwestern region of Kunene, Namibia. The event which was associated with a cut-off low system, was short-lived and resulted in over 45 mm of rainfall in one hour. For the multi-nest, a 9 km grid length parent domain is nested within the Global Forecast System (GFS) simulations, which in turn forces a 3 km grid spacing child domain. A different set of simulations are produced using a single nest of 3 km grid spacing, nested directly inside the GFS data. The simulations are produced with the convection scheme switched on and off. The impact of a single versus multi nest is found to be small in general, with slight differences in the location of high rainfall intensity. Switching off the convection schemes results in high rainfall intensity and increased detail in the simulations, including when a grid spacing of 9 km mis used. Using a grid spacing of 3 km with the convection scheme on, results in a loss of detail in the simulations as well as lower rainfall amounts. The study shows a need for different configurations to be tested before an optimum configuration can be selected for operational forecasting. We recommend further tests with different synoptic forcing to be conducted to identify a suitable configuration for Namibia.

flooding↗

NASA NTRS2020

Cryogenic Technologies for the Stratospheric Observatory for Infrared Astronomy (SOFIA) Science Instruments

This work was performed at the request of the Program Chief Engineer for Stratospheric Observatory for Infrared Astronomy (SOFIA). The intended audience for this position paper is the prospective SOFIA Science Instrument (SI) developer, who may not have extensive experience with cryogenics or cryostat design. The objective is to provide an introductory handbook that (1) concisely summarizes SOFIA requirements, (2) describes components and techniques that enable cryostats to reach temperatures ranging from 4 K to 50 mK, and (3) warns of common pitfalls that an SI developer might encounter.

Stratospheric Observatory for Infrared Astronomy↗

NASA NTRS2020

Farm-Level Risk Factors of Increased Abortion and Mortality in Domestic Ruminants during the 2010 Rift Valley Fever Outbreak in Central South Africa

Background:Rift Valley fever (RVF) outbreaks in domestic ruminants have severe socio-economic impacts. Climate-based continental predictions providing early warnings to regions at risk for RVF outbreaks are not of a high enough resolution for ruminant owners to assess their individual risk. (2) Methods: We analyzed risk factors for RVF occurrence and severity at the farm level using the number of domestic ruminant deaths and abortions reported by farmers in central South Africa during the 2010 RVF outbreaks using a Bayesian multinomial hurdle framework. (3) Results: We found strong support that the proportion of days with precipitation, the number of water sources, and the proportion of goats in the herd were positively associated with increased severity of RVF (the numbers of deaths and abortions). We did not find an association between any risk factors and whether RVF was reported on farms. (4) Conclusions: At the farm level we identified risk factors of RVF severity; however, there was little support for risk factors of RVF occurrence. The identification of farm-level risk factors for Rift Valley fever virus (RVFV) occurrence would support and potentially improve current prediction methods and would provide animal owners with critical information needed in order to assess their herd’s risk of RVFV infection.

Melinda K Rostel↗

NASA NTRS2021

Go-Around Criteria Refinement for Transport Category Aircraft

Presently, airline pilots are trained to go around if, when lower than 500 ft above the ground, they are outside of a handful of parameters such as airspeed, position, and rate of descent. At times, pilots do not comply with these criteria, perhaps owing to their conservative nature or complexity. This paper examines potential refinements to the continue-to-land decision from the combined results of three flight simulator experiments. Potential refinements include simplifying the number of parameters and lowering the altitude at which pilots make the decision. First, refinements were developed by evaluating pilots’ touchdown performance and qualitative data in a variety of starting and environmental conditions. Second, 30 of those pilots evaluated the refinements under several induced instabilities during the approach. The results showed little difference in touchdown performance when lowering the decision altitude from 500 to 300 ft; however, significant differences arose when the decision altitude was lowered further to 100 ft. The proposed new criteria include assessments of deviations in airspeed and position, no rate-of-descent audio warning, and having an appropriate engine setting at 1000, 500, and 300 ft height above threshold. Additionally, a recommendation is made that if the proposed criteria are not met at the 1000 or 500 ft height above threshold the pilots may make corrections and continue the approach; however, if the criteria are not met at 300 ft, then a go-around should be performed.

stabilized approach criteria↗

NASA NTRSDate not supplied

Improving Drought Monitoring for the Middle East and North Africa Region via Data Assimilation Using the NASA Land Information System (LIS)

Food and water security become an increasingly pressing concern for countries within the Middle East and North Africa (MENA) region under climate change. Droughts are among the most important issues facing this region in both economic and social terms, which have become much more severe in recent decades. An effective drought monitoring and early warning system is, therefore, critical to support drought impact assessment and risk management. This presentation describes the effort to improve the simulation of hydrological conditions for such semi-arid environment by Noah Multi-parameterization Land Surface Model within the NASA Land Information System (LIS) via assimilating remotely sensed leaf area index and soil moisture in the presence of irrigation. Multi-source satellite evapotranspiration products are used to evaluate the model performance under the impact of the choice of met-forcings, the presence of irrigation and data assimilation. The improved model configuration is aimed to deliver a better soil moisture estimation for the composite drought indicator (CDI) for drought monitoring and to provide a better initial condition in support for hydrological drought forecasting.

Wanshu Nie↗

NASA NTRS2021

Developing a Hydrological Monitoring and Sub-Seasonal to Seasonal Forecasting System for South and Southeast Asian River Basins

South and Southeast Asia is subject to significant hydrometeorological extremes, including drought. Under rising temperatures, growing populations, and an apparent weakening of the South Asian monsoon in recent decades, concerns regarding drought and its potential impacts on water and food security are on the rise. Reliable sub-seasonal to seasonal (S2S) hydrological forecasts could, in principle, help governments and international organizations to better assess risk and act in the face of an oncoming drought. Here, we leverage recent improvements in S2S meteorological forecasts and the growing power of Earth Observations to provide more accurate monitoring of hydrological states for forecast initialization. Information from both sources is merged in a South and Southeast Asia sub-seasonal to seasonal hydrological forecasting system (SAHFS-S2S), developed collaboratively with the NASA SERVIR program and end-users across the region. This system applies the Noah-MultiParameterization (NoahMP) Land Surface Model (LSM) in the NASA Land Information System (LIS), driven by downscaled meteorological fields from the Global Data Assimilation System (GDAS) and Climate Hazards InfraRed Precipitation products (CHIRP and CHIRPS) to optimize initial conditions. The NASA Goddard Earth Observing System Model - sub-seasonal to seasonal (GEOS-S2S) forecasts, downscaled using the National Center for Atmospheric Research (NCAR) General Analog Regression Downscaling (GARD) tool and quantile mapping, are then applied to drive 5-km resolution hydrological forecasts to a 9-month forecast time horizon. Results show that the skillful predictions of root zone soil moisture can be made one to two months in advance for forecasts initialized in rainy seasons and up to 8 months when initialized in dry seasons. The memory of accurate initial conditions can positively contribute to forecast skills throughout the entire 9-month prediction period in areas with limited precipitation. This SAHFS-S2S has been operationalized at the International Centre for Integrated Mountain Development (ICIMOD) to support drought monitoring and warning needs in the region.

Yifan Zhou↗

NASA NTRSDate not supplied

Weather Guidance for UAS Urban Medical Transport Missions

Unmanned aircraft will revolutionize healthcare services by providing efficient and expeditious delivery of life-saving transplant organs and supplies to hospitals in urban environments, where road traffic and congestion can slow delivery times and endanger lives. Bell has developed the Autonomous Pod Transport (APT) vehicle to serve this market, with entry into service in mid-2020s. Adverse weather conditions can introduce risks and inefficiencies in urban environments leading to flight delays and cancellations. In 2018, National Aeronautics and Space Administration (NASA) and Bell entered into a cooperative agreement, under the Systems Integration and Operationalization (SIO) program to tackle key challenges to enable future commercial unmanned aircraft operations. The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) at the University of Massachusetts, Amherst, joined this team to demonstrate weather avoidance technologies for remotely piloted and autonomous vehicles. CASA has developed the ‘City Warn’ hazard alerting platform to gather weather information from various weather sensors and models, and based on user (or mission) preferences for alerting and on user (or unmanned aircraft) locations, the platform shares timely weather intelligence with users and the systems used by them for remote operations. This presentation discusses the weather avoidance solution developed during this project, leading up to the demonstration of the end-to-end system in Fall 2020. The presentation will cover the following topics: 1) goals related to weather avoidance 2) the design requirements process, including the results of pilot interviews, 3) weather observation and avoidance needs 4) selection of regional and national weather data sets 5) design of the weather graphical interface and 6) considerations for real-time weather alerting. The end-to-end system that was developed will be discussed, along with the results from the demonstration flight. The presentation will conclude with insights from the project team on lessons learned and best practices on weather avoidance technologies for the industry going ahead.

weather avoidance↗

NASA NTRS2021

Weather Guidance for UAS Urban Medical Transport Missions

weather avoidance↗

NASA NTRS2021

Detection of Anomalies in the UV/Vis Reflectances from the Ozone Monitoring Instrument

Various instrumental or geophysical artifacts, such as saturation, stray light, or obstruction of light (either coming from the instrument or related to solar eclipses), negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra and downstream retrievals of atmospheric and surface properties derived from these spectra. In addition, excessive noise such as from cosmic ray impacts, prevalent within the South Atlantic Anomaly, can also degrade satellite radiance measurements. Saturation specifically pertains to observations of very bright surfaces such as sun glint over open water or thick clouds. When saturation occurs, additional photoelectric charge generated at the saturated pixel may overflow to pixels adjacent to a saturated area and be reflected as a distorted image in the final sensor output.When these effects cannot be corrected to an acceptable level for science quality retrievals, flagging of the affected pixels is indicated. Here, we introduce a straightforward detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectraover a 10 nm-spectral range; our Decorrelation Index (DI for brevity) is simply defined as DI=1-r. DI increases with anomalous additive effects or excessive noise in either radiances, the most likely cause indata from theOzone Monitoring Instrument (OMI),or irradiances. DI is relatively straight-forward to use and interpret and can be 20computed for different wavelength intervals. We developed a set of DIs for two spectral channelsof the OMI, a hyperspectral pushbroom imaging spectrometer. For each OMI spatial measurement, we define 14 wavelength-dependent DIs within the OMI visible channel (350-498 nm) and 6 DIs in its ultraviolet 2 (UV2) channel (310-370 nm). As defined, DIs reflect a continuous range of deviations of observed spectra from the reference irradiance spectrum that are complementary to the binary Saturation Possibility Warning (SPW) flags currently provided for each individual spectral/spatial pixel in the OMI radiance data set. Smaller values of DI are also caused by a number of geophysical factors; this allows one to obtain interesting physical results on the global distribution of spectral variations.

Space sensor↗

NASA NTRS2021

Vegetation Monitoring Optimization with Normalized Difference Vegetation Index and Evapotranspiration Using Remote Sensing Measurements and Land Surface Models Over East Africa

The majority of people in East Africa rely on the agro-pastoral system for their livelihood, which is highly vulnerable to droughts and flooding. Agro-pastoral droughts are endemic to the region and are considered the main natural hazard that contributes to food insecurity. Drought begins with rainfall deficit, gradually leading to soil moisture deficit, higher land surface temperature, and finally impacts to vegetation growth. Therefore, monitoring vegetation conditions is essential in understanding the progression of drought, potential effects on food security, and providing early warning information needed for drought mitigation decisions. Because vegetation processes couple the land and atmosphere, monitoring of vegetation conditions requires consideration of both water provision and demand. While there is consensus in using either the Normalized Difference Vegetation Index (NDVI) or evapotranspiration(ET) for vegetation monitoring, a comprehensive assessment optimizing the use of both has not yet been done. Moreover, the evaluation methods for understanding the relationships between NDVI and ET for vegetation monitoring are also limited. Taking these gaps into account we have developed a framework to optimize vegetation monitoring using both NDVI and ET by identifying where they perform the best by using triple collocation and cross-correlation methods. We estimated the random error structure in Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI; ET from the Operational Simplified Surface Energy Balance (SSEBop) model; and ET from land surface models (LSMs). LSM ET and SSEBop ET have been found to be better indicators for vegetation monitoring during extreme drought events, while NDVI could provide better information on vegetation condition during wetter than normal conditions. The random error structures of these variables suggest that LSM ET is most likely to provide important information for vegetation monitoring over low and high ends of the vegetation fraction areas. Over moderate vegetative areas, any of these variables could provide important vegetation information for drought characterization and food security assessments. While this study provides a framework for optimizing vegetation monitoring for drought and food security assessments over East Africa, the framework can be adopted to optimize vegetation monitoring over any other drought and food insecure region of the world.

triple collocation↗

NASA NTRS2010

Report of the 1st SMAP Applications Workshop

The NASA Earth Science Division has made a commitment to “discover and demonstrate applications that inform resource management, policy development and decision making” (NASA Earth Science Division Applied Sciences Program, Program Strategy, 2010–2015). The NASA mission teams have the opportunity to take a lead role in meeting this challenge. A primary goal of the SMAP mission is to engage SMAP end users and build broad support for SMAP applications through a transparent and inclusive process. Toward this goal, the SMAP mission formed an open-community SMAP Applications Working Group (ApplWG) with over 150 members. The ApplWG held the first SMAP Applications Workshop on September 9–10, 2009, at the National Oceanic and Atmospheric Administration (NOAA) in Silver Spring, Maryland. Workshop attendees represented state and federal agencies, operational centers focused on natural hazards and disasters, international organizations, and academia. Introductory speakers from NOAA, US Geological Survey (USGS), US Department of Agriculture (USDA), Environment Canada, and US Department of Defense (DoD) addressed applications that included floods and droughts, early famine warning, crop assessments, human health, and defense.

O’Neill, P.↗

NASA NTRS2008

QuikSCAT follow - on concept study

Global, real-time observations of the speed and direction of winds over the oceans ocean surface vector winds [OSVW]) are high priority measurements for National Oceanic and Atmospheric Administration’s (NOAA’s) weather forecasting, prediction, and hazard warning communities. At present, these data are provided by the experimental National Aeronautics and Space Administration (NASA) QuikSCAT satellite sensor, which is operating well beyond its design lifetime. To continue to meet the Nation’s need for operational OSVW observations beyond QuikSCAT, NOAA tasked the Jet Propulsion Laboratory (JPL) to design and provide costs for a set of QuikSCAT Follow-On mission options. Three scenarios were examined: 1) a QuikSCAT Replacement mission with capabilities commensurate to QuikSCAT, 2) a next-generation Extended Ocean Vector Winds Mission (XOVWM), as recommended in the National Research Council’s decadal survey to provide significantly improved all-weather, allwind, high spatial resolution measurements, and 3) an XOVWM Constellation consisting of two XOVWM observatories to provide improved temporal resolution. In parallel, NOAA asked its users to provide a quantitative assessment of each option’s benefit to NOAA. This report presents the JPL design, risk assessment, and cost for each of three options, together with a summary of the NOAA users’ benefit assessment. The report concludes that though all options are technically feasible for immediate implementation and have a risk posture consistent with a NOAA operational mission, the XOVWM options provide significant observational benefits. While a QuikSCAT Replacement option would continue current operational measurement capabilities, there is a strong and clearly defined operational need for improved capabilities in high winds (e.g., hurricanes or extra-tropical cyclones), heavy precipitation, and near coasts to enable significantly improved severe storm and coastal hazard forecasts, which are provided only by the XOVWM options.

Rodriquez, Ernesto↗

NASA NTRS2018

Automated Spacecraft Conjunction Assessment at Mars and the Moon - A Five Year Update

It is well known that the Earth has an ongoing problem with orbiting space debris. Some Earth orbiting missions have regular warnings of close approaches with debris or other satellites. At Mars and the Moon, due to the growing number of orbiter missions and the current inability to track orbital debris in these environments, the creation of a hazardous debris field must be avoided because a debris field would greatly complicate both existing and future operations. Work at the Jet Propulsion Laboratory in the area of automated spacecraft conjunction assessment at Mars and the Moon has been conducted over the past six years using a process called "MADCAP" ("Multimission Automated Deepspace Conjunction Assessment Process"). A paper introducing this work was presented at Space Ops in Stockholm, Sweden in 2012. In that inaugural paper, the then current state of operations was presented along with a number of items that were identified for potential future work. The fundamental design concepts of MADCAP have not materially changed in the last five years, however, since 2012 a number of the changes to MADCAP identified in the previous paper have been implemented. Some other previously planned work has not progressed appreciably; several of these items remain on a "parking lot" list. In addition to the items that were listed as prospective future work, JPL's Mars/Moon conjunction assessment efforts have also been extended in a few unplanned but important areas. This follow-up paper will provide a five year update on MADCAP operations at Mars and the Moon.

Wilson, Roby S.↗

NASA NTRS2021

Landslide Hazard and Exposure Modelling in Data‐Poor Regions: The Example of the Rohingya Refugee Camps in Bangladesh

Landslide hazards significantly affect economies and populations around the world, but locations where the greatest proportional losses occur are in data‐poor regions where capacity to estimate and prepare for these hazards is most limited. Earth observation (EO) data can fill key knowledge gaps, and can be rapidly used in settings with lower analytical capacity. In this study, we describe a novel series of methods designed to analyze landslide susceptibility, hazard and exposure in the region in and around the Rohingya refugee camps in Bangladesh, where limited data is juxtaposed with a major humanitarian crisis. We demonstrate that a high degree of accuracy is possible even when estimating susceptibility of relatively small landslides. In the context of this example, we also explore how estimates of landslide hazard and exposure are most beneficial to decisions made by humanitarian stakeholders relevant to natural hazards and risk. The unique opportunity to work alongside humanitarian end‐users has allowed us to produce focused products that can be tested while in development. In particular, we stress the importance of communicating the difference between a landslide “early warning system”—for which satellite data may be unsuitable at local scales—and a model that provides relative hazard estimates, where EO may be valuable. The toolbox of methods presented here could be used to generate landslide hazard and exposure maps in other data‐poor regions around the globe.

R A Emberson↗

NASA NTRSDate not supplied

Intelligent Control & Autonomy Branch Research Overview Research

The purpose of the subject presentation is to expose engineering students at Ohio University to ongoing work being performed by the Intelligent Control and Autonomy Branch (ICAB) at the NASA Glenn Research Center in Cleveland, Ohio. The presentation will start with some introductory material about the organization. This will be followed by an overview of Electrified Aircraft Propulsion (EAP) controls research and the ICAB’s support for the Space Launch System (SLS). One aspect of EAP is the integration of electrical motor/generators and other power systems components with turbine engine technology to create propulsion & power systems for single-aisle aircraft that are more fuel efficient and have lower emissions. The presentation will introduce some of the controls, systems health management, and modeling technologies developed by the ICAB to help realize EAP. NASA’s SLS is a super-heavy-lift launch vehicle that provides the foundation for human exploration beyond Earth’s orbit. The presentation will introduce capabilities developed by the ICAB to support the SLS Mission and Fault Management function which includes capabilities for abort, caution and warning, redundancy management, and safing. The presentation will conclude with information about internships with the NASA and the ICAB.

propulsion↗

NASA NTRS2019

The Combustion Product Monitor instrument for the spacecraft fire safety demonstration project

The Combustion Product Monitor (CPM) instrument is a six-channel tunable laser absorption spectrometer capable of measuring ambient gas-phase concentrations of CO, HCl, HCN, HF, CO2, and O2 in spacecraft environments. Monitoring of these compounds can provide early warning detection of combustion events and can also facilitate safe post-fire cleanup. Here, we will describe the development of a CPM instrument optimized for operation as part of the Spacecraft Fire Safety Demonstration (Saffire) Project. As part of Saffire, the CPM instrument will measure concentrations of the target gases during low-gravity, reduced pressure oxidative pyrolysis of relevant test materials aboard a transfer vehicle returning from low Earth orbit. We will describe the CPM instrument design, absorption line selection,theoretical and experimental detection limits, and environmental testing.

Briggs, Ryan M.↗

NASA NTRS2020

Satellite Gravimetry Improves Seasonal Streamflow Forecast Initialization in Africa

West Africa is one of the poorest regions in the world and highly vulnerable to extreme hydrological events due to the lack of reliable monitoring and forecast systems. For the first time, we demonstrate that initial hydrological conditions informed by satellite-based terrestrial water storage (TWS) estimates improve seasonal streamflow forecasts. TWS variability detected by the Gravity Recovery and Climate Experiment (GRACE) satellites is assimilated into a land surface model during 2003–2016 and used to initialize 6-month hindcasts (i.e., forecasts of past events) during West Africa's wet seasons. We find that GRACE data assimilation (DA) generally increases groundwater and soil moisture storage in the region, resulting in increased evapotranspiration and reduced total runoff. Total runoff is particularly lower at the headwaters of the Niger River, positively impacting streamflow simulations and hindcast initializations. Compared to simulations without GRACE-DA, hindcasts are notably improved at locations draining from large basin areas, in particular, over the Niger River basin, which is consistent with GRACE's coarse spatial resolution. The long memory of groundwater and deep soil moisture, two main TWS components updated by GRACE-DA, is reflected in prolonged improvements in the streamflow hindcasts. Model accuracy at Niamey, Niger, the most populated city where streamflow observations are available, improved up to 33% during the flood season. These new findings directly contribute to ongoing developments in food security, flood potential forecast, and water-related disaster warning systems for Africa.

Augusto Getirana↗