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NASA NTRS2010

NASA SPoRT GOES-R Proving Ground Activities

The NASA Short-term Prediction Research and Transition (SPoRT) program is a partner with the GOES-R Proving Ground (PG) helping prepare forecasters understand the unique products to come from the GOES-R instrument suite. SPoRT is working collaboratively with other members of the GOES-R PG team and Algorithm Working Group (AWG) scientists to develop and disseminate a suite of proxy products that address specific forecast problems for the WFOs, Regional and National Support Centers, and other NOAA users. These products draw on SPoRT s expertise with the transition and evaluation of products into operations from the MODIS instrument and the North Alabama Lightning Mapping Array (NALMA). The MODIS instrument serves as an excellent proxy for the Advanced Baseline Imager (ABI) that will be aboard GOES-R. SPoRT has transitioned and evaluated several multi-channel MODIS products. The true and false color products are being used in natural hazard detection by several SPoRT partners to provide better observation of land features, such as fires, smoke plumes, and snow cover. Additionally, many of SPoRT s partners are coastal offices and already benefit from the MODIS sea surface temperature composite. This, along with other surface feature observations will be developed into ABI proxy products for diagnostic use in the forecast process as well as assimilation into forecast models. In addition to the MODIS instrument, the NALMA has proven very valuable to WFOs with access to these total lightning data. These data provide situational awareness and enhanced warning decision making to improve lead times for severe thunderstorm and tornado warnings. One effort by SPoRT scientists includes a lightning threat product to create short-term model forecasts of lightning activity. Additionally, SPoRT is working with the AWG to create GLM proxy data from several of the ground based total lightning networks, such as the NALMA. The evaluation will focus on the vastly improved spatial coverage of the GLM, but with the trade-off of lower resolution compared to the NALMA. In addition to the above tasks, SPoRT will make these data available in the NWS next generation display software, AWIPS II. This has already been successfully completed for the two basic GLM proxies. SPoRT will use these products to train forecasters on the capabilities of GOES-R and foster feedback to develop additional products, visualizations, and requirements beneficial to end users needs. These developments and feedback will be made available to the GOES-R Proving Ground for the upcoming 2010 Spring Program in Norman, Oklahoma.

Stano, Geoffrey T.↗
NASA NTRS2002

Planetary Defense: Options for Deflection of Near Earth Objects

In FY 2002 a team of engineers and scientists at MSFC conducted a preliminary investigation of the options for deflecting a Near Earth Object (NEO) fiom a collision course with the earth. A general discussion of the current threat facing the earth from NEO s is outlined. A suite of tools were developed to model inbound and outbound trajectories, propulsive options, and assessment of threat. Propulsive options considered included; staged chemical, nuclear ablation and deflagration, mass driver and solar sail concepts. Trajectory tools plotted the outbound course to intercept the NE0 and the deflection requirements to cause the inbound NE0 to miss the earth. Threat assessment tools estimated the number of lives saved over a given time frame by deploying a system capable of deflecting an NE0 of a certain size and velocity. All of these tools were integrated into a routine to find the most effective vehicle for a given mission mass and mission time. Discussion of desired future efforts is given. This work was funded under the Revolutionary Aerospace Systems Concepts activity from NASA HQ.

Adams, Robert B.↗
NASA NTRS2004

Monte Carlo Technique Used to Model the Degradation of Internal Spacecraft Surfaces by Atomic Oxygen

Atomic oxygen is one of the predominant constituents of Earth's upper atmosphere. It is created by the photodissociation of molecular oxygen (O2) into single O atoms by ultraviolet radiation. It is chemically very reactive because a single O atom readily combines with another O atom or with other atoms or molecules that can form a stable oxide. The effects of atomic oxygen on the external surfaces of spacecraft in low Earth orbit can have dire consequences for spacecraft life, and this is a well-known and much studied problem. Much less information is known about the effects of atomic oxygen on the internal surfaces of spacecraft. This degradation can occur when openings in components of the spacecraft exterior exist that allow the entry of atomic oxygen into regions that may not have direct atomic oxygen attack but rather scattered attack. Openings can exist because of spacecraft venting, microwave cavities, and apertures for Earth viewing, Sun sensors, or star trackers. The effects of atomic oxygen erosion of polymers interior to an aperture on a spacecraft were simulated at the NASA Glenn Research Center by using Monte Carlo computational techniques. A two-dimensional model was used to provide quantitative indications of the attenuation of atomic oxygen flux as a function of the distance into a parallel-walled cavity. The model allows the atomic oxygen arrival direction, the Maxwell Boltzman temperature, and the ram energy to be varied along with the interaction parameters of the degree of recombination upon impact with polymer or nonreactive surfaces, the initial reaction probability, the reaction probability dependence upon energy and angle of attack, degree of specularity of scattering of reactive and nonreactive surfaces, and the degree of thermal accommodation upon impact with reactive and non-reactive surfaces to be varied to allow the model to produce atomic oxygen erosion geometries that replicate actual experimental results from space. The degree of erosion of various interior locations was compared with the erosion that would occur external to the spacecraft. Results of one cavity model indicate that, at depths into a two-dimensional cavity that are equal to 10 cavity widths, the erosion on the walls of the cavity is less than that on the top surface by over 2 orders of magnitude. Wall erosion near the surface of a cavity depends on which wall is receiving direct atomic oxygen attack. However, deep in the cavity little difference is present. Testing of various cavity models such as these gives spacecraft designers an indication of the level of threat to sensitive interior surfaces for different geometries. Even though the Monte Carlo model is two-dimensional, it can be used to provide qualitative information about spacecraft openings that are three-dimensional by offering reasonable insight as to the nature of the attenuation of damage that occurs within a spacecraft in low Earth orbit. As shown, there is more erosion on the side seeing direct atomic oxygen attack until a depth of approximately 5 times the width of the opening, where the erosion is the same on both sides.

Banks, Bruce A.↗
NASA NTRSDate not supplied

Flux Comparison of Master-8 and Ordem 3.1 Modelled Space Debris Population

With ESA’s Meteoroid And Space debris Terrestrial Environment Reference (MASTER-8) model and NASA’s Orbital Debris Engineering Model(ORDEM) 3.1, the two premier orbital debris engineering models have been officially released. The two models come with significant enhancements and now represent state-of-the-art orbital debris modelling for their respective agencies. Both models provide the community with estimates of the space debris environment from low Earth orbit (LEO) up to at least geostationary altitude. The MASTER population is an event-based simulation of all known events that generate debris and objects that are part of the U.S. Space Surveillance Network (SSN) catalog, which provides coverage of objects with diameters down to approximately 10cm in LEO and 1 m in geosynchronous Earth orbit (GEO). Different models are used to simulate the artificial objects and their orbit evolution over time. These models are called “sources” since they assign an origin to each individual object and consist of fragments, solid rocket motor (SRM) remainders, sodium-potassium(NaK) droplets, paintflakes, ejecta, and multi-layer insulation (MLI) fragments. The objects from each source are characterized by having individual release mechanisms, as well as orbital distributions, material composition, size, and mass distributions. Dedicated radar and telescope observation data is used to calibrate the model for objects larger than 1 cm in LEO and larger than 10 cm in GEO. For calibrating the small-sized objects, below 1 cm, impact data from returned surfaces are analyzed. Because the >1cm object population is dominated by fragments, the fragmentation event database was updated to include new events, as well as re-evaluate past events. Special attention was drawn to re-evaluating theFengyun-1C anti-satellite test from 2007 and Cosmos-Iridium collision event from 2009 since these events shape the fragment population because of their severity. After 2009, the two largest fragmentations in terms of number of tracked debris are the Briz-M explosion in 2012 and the NOAA-16explosion in 2015. In total, there are 261 confirmed fragmentations in the database up to November 2016.The baseline population for ORDEM 3.1 is based on the U.S. SSN catalog, and observational datasets from radar, in situ, and optical sources provide a foundation from which the model populations are statistically extrapolated to smaller size regions. These regions are not well-covered by the SSN catalog yet may pose the greatest threat to operational spacecraft. The NASA Standard Satellite Breakup Model is used to generate fragments greater than 1mm from collisions and explosions, and these fragment populations are scaled using ground-based radar data. Specific major debris-producing events, including the Fengyun-1C, Iridium 33, and Cosmos2251 debris clouds, and unique populations, such as NaK droplets, were re-examined, modelled, and added to the ORDEM environment separately. Optical measurement data is used to model the GEO population down to 10 cm. The debris environment is propagated using NASA’s LEO-to-GEO Environment Debris model, and future explosions of intact objects and collisions involving objects greater than 10 cm are assessed statistically. The environment from a few millimetres down to 10 𝜇m is modelled using a special degradation model where small particles are generated from intact spacecraft and rocket bodies, then the populations are scaled to fit in situ cratering data from Space Shuttle returned surfaces. Fragments smaller than 10 cm are differentiated based on material density categories, i.e., high-, medium-, and low-density, to better characterize the potential debris risk posed to upper stages and spacecraft. This paper will discuss the MASTER and ORDEM approaches for modelling populations and compare fluxes for specific orbits, including sun-synchronous, ISS-altitude, geosynchronous transfer, and GEO. In the end, a conclusion is drawn towards the importance of having multiple fundamentally different, yet validated, models to estimate the space debris population.

Andre Horstmann↗
NASA NTRS2009

Microbial Risk Assessment

Historically, microbiological spaceflight requirements have been established in a subjective manner based upon expert opinion of both environmental and clinical monitoring results and the incidence of disease. The limited amount of data, especially from long-duration missions, has created very conservative requirements based primarily on the concentration of microorganisms. Periodic reevaluations of new data from later missions have allowed some relaxation of these stringent requirements. However, the requirements remain very conservative and subjective in nature, and the risk of crew illness due to infectious microorganisms is not well defined. The use of modeling techniques for microbial risk has been applied in the food and potable water industries and has exceptional potential for spaceflight applications. From a productivity standpoint, this type of modeling can (1) decrease unnecessary costs and resource usage and (2) prevent inadequate or inappropriate data for health assessment. In addition, a quantitative model has several advantages for risk management and communication. By identifying the variable components of the model and the knowledge associated with each component, this type of modeling can: (1) Systematically identify and close knowledge gaps, (2) Systematically identify acceptable and unacceptable risks, (3) Improve communication with stakeholders as to the reasons for resource use, and (4) Facilitate external scientific approval of the NASA requirements. The modeling of microbial risk involves the evaluation of several key factors including hazard identification, crew exposure assessment, dose-response assessment, and risk characterization. Many of these factors are similar to conditions found on Earth; however, the spaceflight environment is very specialized as the inhabitants live in a small, semi-closed environment that is often dependent on regenerative life support systems. To further complicate modeling efforts, microbial dose-response characteristics may be affected by a potentially dysfunctional crew immune system during a mission. In addition, microbial virulence has been shown to change under certain conditions during spaceflight, further complicating dose-response characterization. An initial study of the applicability of microbial risk assessment techniques was performed using Crew Health Care System (CHeCS) operational data from the International Space Station potable water systems. The risk of infection from potable water was selected as the flight systems and microbial ecology are well defined. This initial study confirmed the feasibility of using microbial risk assessment modeling for spaceflight systems. While no immediate threat was detected, the study identified several medically significant microorganisms that could pose a health risk if uncontrolled. The study also identified several specific knowledge gaps in making a risk assessment and noted that filling these knowledge gaps is essential as the risk estimates may change by orders of magnitude depending on the answers. The current phase of the microbial risk assessment studies focuses on the dose-response relationship of specific infectious agents, focusing on Salmonella enterica Typhimurium, Pseudomonas spp., and Escherichia coli, as their evaluation will provide a better baseline for determining the overall hazard characterization. The organisms were chosen as they either have been isolated on spacecraft or have an identified route of infection during a mission. The characterization will utilize dose-response models selected either from the peer-reviewed literature and/or by using statistical approaches. Development of these modeling and risk assessment techniques will help to optimize flight requirements and to protect the safety, health, and performance of the crew.

Ott, C. M.↗
NASA NTRS1994

Incorporation of an evaporative cooling scheme into a dynamic model of orographic precipitation

A simple evaporative cooling scheme was incorporated into a dynamic model to estimate orographic precipitation in mountainous regions. The orographic precipitation model is based on the transport of atmospheric moisture and the quantification of preciptable water across a 3D representation of the terrain from the surface up to 250 hPa. Advective wind fields are computed independently and boundary conditions are extracted from radiosonde data. Precipitation rates are obtained through calibration of a spatially distributed precipitation efficiency parameter. The model was applied to the central Sierra Nevada. Results show a gain of the order of 20% in threat-score coefficients designed to measure the forecast ability of the model. Accuracy gains are largest at high elevations and during intense storms associated with warm air masses.

Barros, Ana Paula↗
NASA NTRS2010

Forecasting Lightning Threat Using WRF Proxy Fields

Objectives: Given that high-resolution WRF forecasts can capture the character of convective outbreaks, we seek to: 1. Create WRF forecasts of LTG threat (1-24 h), based on 2 proxy fields from explicitly simulated convection: - graupel flux near -15 C (captures LTG time variability) - vertically integrated ice (captures LTG threat area). 2. Calibrate each threat to yield accurate quantitative peak flash rate densities. 3. Also evaluate threats for areal coverage, time variability. 4. Blend threats to optimize results. 5. Examine sensitivity to model mesh, microphysics. Methods: 1. Use high-resolution 2-km WRF simulations to prognose convection for a diverse series of selected case studies. 2. Evaluate graupel fluxes; vertically integrated ice (VII). 3. Calibrate WRF LTG proxies using peak total LTG flash rate densities from NALMA; relationships look linear, with regression line passing through origin. 4. Truncate low threat values to make threat areal coverage match NALMA flash extent density obs. 5. Blend proxies to achieve optimal performance 6. Study CAPS 4-km ensembles to evaluate sensitivities.

McCaul, E. W., Jr.↗
NASA NTRS2017

Radiation Effects: Overview for Space Environment Specialists

Radiation Hardness Assurance (RHA) methodologies need to evolve to capitalize on the increased flexibility introduced by new models of space radiation environments. This presentation examines the characteristics of various radiation threats, the sources of error that RHA methodologies seek to control and the contributions of environment models to those errors. The influence of trends in microelectronic device technology is also considered.

Galactic Cosmic Ray (GCR)↗
NASA NTRS2023

Risks of Synchronized Low Yields Are Underestimated in Climate and Crop Model Projections

Simultaneous harvest failures across major crop-producing regions are a threat to global food security. Concurrent weather extremes driven by a strongly meandering jet stream could trigger such events, but so far this has not been quantified. Specifically, the ability of state-of-the art crop and climate models to adequately reproduce such high impact events is a crucial component for estimating risks to global food security. Here we find an increased likelihood of concurrent low yields during summers featuring meandering jets in observations and models. While climate models accurately simulate atmospheric patterns, associated surface weather anomalies and negative effects on crop responses are mostly underestimated in bias-adjusted simulations. Given the identified model biases, future assessments of regional and concurrent crop losses from meandering jet states remain highly uncertain. Our results suggest that model-blind spots for such high-impact but deeply-uncertain hazards have to be anticipated and accounted for in meaningful climate risk assessments.

Atmospheric dynamics↗
NASA NTRS2007

Users Guide for the Anvil Threat Corridor Forecast Tool V1.7.0 for AWIPS

The Applied Meteorology Unit (AMU) originally developed the Anvil Threat Sector Tool for the Meteorological Interactive Data Display System (MIDDS) and delivered the capability in three phases beginning with a feasibility study in 2000 and delivering the operational final product in December 2003. This tool is currently used operationally by the 45th Weather Squadron (45 WS) Launch Weather Officers (LWO) and Spaceflight Meteorology Group (SMG) forecasters. Phase I of the task established the technical feasibility of developing an objective, observations-based tool for short-range anvil forecasting. The AMU was subsequently tasked to develop short-term anvil forecasting tools to improve predictions of the threat of triggered lightning to space launch and landing vehicles. Under the Phase II effort, the AMU developed a nowcasting anvil threat sector tool, which provided the user with a threat sector based on the most current radiosonde upper wind data from a co-located or upstream station. The Phase II Anvil Threat Sector Tool computes the average wind speed and direction in the layer between 300 and 150 mb from the latest radiosonde for a user-designated station. The following threat sector properties are consistent with the propagation and lifetime characteristics of thunderstorm anvil clouds observed over Florida and its coastal waters (Short et al. 2002): a) 20 n mi standoff circle, b) 30 degree sector width, c) Orientation given by 300 to 150 mb average wind direction, d) 1-, 2-, and 3- hour arcs in upwind direction, and e) Arc distances given by 300 to 150 mb average wind speed. Figure 1 is an example of the MIDDS Anvil Threat Sector tool overlaid on a visible satellite image at 2132 UTC 13 May 2001. Space Launch Complex 39A was selected as the center point and the Anvil Threat Sector was determined from upper-level wind data at 1500 UTC in the preconvective environment. Narrow thunderstorm anvil clouds extend from central Florida to the space launch and landing facilities at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) and beyond. The anvil clouds were generated around 1930 UTC (1430 EDT) by thunderstorm activity over central Florida and transported 90 n mi east-northeastward within 2 hours, as diagnosed by the anvil forecast tool. Phase III, delivered in February 2003, built upon the results of Phase II by enhancing the Anvil Threat Sector Tool with the capability to use national model forecast winds for depiction of potential anvil lengths and orientations over the KSC/CCAFS area with lead times from 3 through 168 hours (7 days). In September 2003, AMU customers requested the capability to use data from the KSC 50 MHz Doppler Radar Wind Profiler (DRWP) in the Anvil Threat Sector Tool and this capability was delivered by the AMU in December 2003. In March 2005, the AMU was tasked to migrate the MIDDS Anvil Threat Sector Tool capabilities onto the Advanced Weather Interactive Processing System (AWIPS) as the Anvil Threat Corridor Forecast Tool.

Bauman, William H., III↗
NASA NTRS2007

Anvil Tool in the Advanced Weather Interactive Processing System

Meteorologists from the 45th Weather Squadron (45 WS) and Spaceflight Meteorology Group (SMG) have identified anvil forecasting as one of their most challenging tasks when predicting the probability of violations of the lightning Launch Commit Criteria and Space Shuttle Flight Rules. As a result, the Applied Meteorology Unit (AMU) created a graphical overlay tool for the Meteorological Interactive Data Display Systems (MIDDS) to indicate the threat of thunderstorm anvil clouds, using either observed or model forecast winds as input. In order for the Anvil Tool to remain available to the meteorologists, the AMU was tasked to transition the tool to the Advanced Weather interactive Processing System (AWIPS). This report describes the work done by the AMU to develop the Anvil Tool for AWIPS to create a graphical overlay depicting the threat from thunderstorm anvil clouds. The AWIPS Anvil Tool is based on the previously deployed AMU MIDDS Anvil Tool. SMG and 45 WS forecasters have used the MIDDS Anvil Tool during launch and landing operations. SMG's primary weather analysis and display system is now AWIPS and the 45 WS has plans to replace MIDDS with AWIPS. The Anvil Tool creates a graphic that users can overlay on satellite or radar imagery to depict the potential location of thunderstorm anvils one, two, and three hours into the future. The locations are based on an average of the upper-level observed or forecasted winds. The graphic includes 10 and 20 nm standoff circles centered at the location of interest, in addition to one-, two-, and three-hour arcs in the upwind direction. The arcs extend outward across a 30 degree sector width based on a previous AMU study which determined thunderstorm anvils move in a direction plus or minus 15 degrees of the upper-level (300- to 150-mb) wind direction. This report briefly describes the history of the MIDDS Anvil Tool and then explains how the initial development of the AWIPS Anvil Tool was carried out. After testing was performed by SMG, 45 WS, and AMU, a number of needed improvements were identified. A bug report document was created that showed the status of each bug and desired improvement. This report lists the improvements that were made to increase the accuracy and user-friendliness of the tool. Final testing was carried out and documented and then the final version of the software and Users Guide was provided to SMG and the 45 WS. Several possible future improvements to the tool are identified that would increase the flexibility of the tool. This report contains a brief history of the development of the Anvil Tool in MIDDS, and then describes the transition and development of software to AWIPS.

Barrett, Joe, III↗
NASA NTRS2011

Modeling Electrostatic Fields Generated by Internal Charging of Materials in Space Radiation Environments

Internal charging is a risk to spacecraft in energetic electron environments. DICTAT, NU MIT computational codes are the most widely used engineering tools for evaluating internal charging of insulator materials exposed to these environments. Engineering tools are designed for rapid evaluation of ESD threats, but there is a need for more physics based models for investigating the science of materials interactions with energetic electron environments. Current tools are limited by the physics included in the models and ease of user implementation .... additional development work is needed to improve models.

Minow, Joseph I.↗
NASA NTRS2015

SSI-ARC Flight Test 3 Data Review

The "Unmanned Aircraft System (UAS) Integration into the National Airspace System (NAS)" Project conducted flight test program, referred to as Flight Test 3, at Armstrong Flight Research Center from June - August 2015. Four flight test days were dedicated to the NASA Ames-developed Detect and Avoid (DAA) System referred to as Autoresolver. The encounter scenarios, which involved NASA's Ikhana UAS and a manned intruder aircraft, were designed to collect data on DAA system performance in real-world conditions and uncertainties with four different surveillance sensor systems. Resulting flight test data and analysis results will be used to evaluate the DAA system performance (e.g., trajectory prediction accuracy, threat detection) and to add fidelity to simulation models used to inform Minimum Operating Performance Standards (MOPS) for integrating UAS into routine NAS operations.

detect and avoid↗
NASA NTRS2022

Global Gridded Crop Models Underestimate Yield Responses to Droughts and Heatwaves

Extreme events can lead to crop yield declines, resulting in financial losses and threats to food security, and the frequency and intensity of such events is projected to increase. As global gridded crop models (GGCMs) are commonly used to assess climate change impacts on agricultural yields, there is a need to understand whether these models are able to reproduce the observed yield declines. We evaluated 13 GGCMs from the Inter-Sectoral Impact Model Intercomparison Project and compared observed and simulated impact of past droughts and heatwaves on yields for four crops (maize, rice, soy, wheat). We found that most models detect but underestimate the impact of droughts and heatwaves on yield. Specifically, the drought signal was detected by 12 of 13 models for maize and all models for wheat, while the heat signal was detected by eleven models for maize and six models for wheat. To investigate whether the difference between simulated and observed yield declines is due to a misrepresentation of simulated exposure to heat or water scarcity (i.e. misrepresentation of growing season), we analysed the relationship between average discrepancies between observed and simulated yield losses, and average simulated exposure to extreme weather conditions across all crop models. We found a positive correlation between simulated exposure to heat and model performance for heatwaves, but found no correlation for droughts. This suggests that there is a systematic underestimation of yield responses to heat and drought and not only a misrepresentation of exposure. Assuming that performance for the past indicates models' capacity to project future yield impacts, models likely underestimate future yield decline from climate change. High-quality temporally and spatially resolved observational data on growing seasons will be highly valuable to further improve crop models' capacity to adequately respond to extreme weather events.

extreme events↗
NASA NTRS1991

An overview of computer viruses in a research environment

The threat of attack by computer viruses is in reality a very small part of a much more general threat, specifically threats aimed at subverting computer security. Here, computer viruses are examined as a malicious logic in a research and development environment. A relation is drawn between the viruses and various models of security and integrity. Current research techniques aimed at controlling the threats posed to computer systems by threatening viruses in particular and malicious logic in general are examined. Finally, a brief examination of the vulnerabilities of research and development systems that malicious logic and computer viruses may exploit is undertaken.

Bishop, Matt↗
NASA NTRS2024

Impact of Spaceflight on Earth’s Atmosphere: Climate, Ozone, and the Upper Atmosphere

In order to eliminate potential risk from the lack of scientific understanding and resolve the current inability to assess how a rapidly growing space industry will affect Earth’s atmosphere, a well-defined research effort is recommended. As demonstrated in the white paper “Impacts of Spaceflight on the Global Atmosphere: Current Understanding, Knowledge Gaps, NASA’s Role, and Roadmap", we must improve our ability to model and observe rocket engine combustion, far field rocket plume evolution, impacts on the upper atmosphere, global launch impacts, reentry gas and aerosol production, far field reentry plume evolution, and global reentry impacts. The highly successful Atmospheric Chemistry of Combustion Emissions Near the Tropopause (ACCENT) program serves as a model for the proposed effort. ACCENT was a multiagency research program that included observation and modeling of rocket plumes and played a critical role to remove the threat of regulatory action against the Space Shuttle’s solid rocket motors. A similar effort today would be a combination of remote, in situ, and laboratory measurements that feed into model development and assessment of future launch and reentry emissions.

Ozone Layer↗