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At least 505 records · Page 28

Assessing Drought and Fire Conditions, Trends, and Susceptibility to Inform State Mitigation Efforts and Bolster Monitoring Protocol in North Central Idaho

Escalating severity and frequency of drought and wildfire call for effective and cost-efficient mitigation planning and monitoring protocols. The Palouse ecoregion, an agricultural epicenter in North-central Idaho, is of particular concern as both drought and wildfire present substantial economic threats. The DEVELOP team implemented Earth observation data to assist the Idaho Office of Emergency Management, Idaho Department of Water Resources, and Idaho Department of Lands in updating the state’s Hazard Mitigation Plan by enhancing their drought and fire monitoring capabilities. The team utilized Landsat 8 Operational Land Imager (OLI), and Aqua and Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS), along with ancillary datasets, to assess drought indicators and map hazard susceptibility. The team upgraded the state’s current fire hazard model by updating existing data layers and adding drought indicator data to support partners’ continued assessment of fire hazard conditions. The team observed Evaporative Demand Drought Index (EDDI) spikes during the highest fire occurrence and burned area years in the study period: 2015 and 2021. Models from dry, high fire occurrence and burned area year 2015 outperformed models from mesic, low fire occurrence and burned area year 2016. The increased understanding of drought conditions and fire susceptibility in this ecosystem will assist partners in improving land management practices.

Ford Freyberg↗

Radiation Tolerance and Mitigation for Neuromorphic Processors

Neuromorphic processors are designed to execute Deep Neural Networks (DNNs) at very high speed using only a fraction of the electrical power needed to run a DNN on a traditional CPU or GPU. This unique capability makes Neuromorphic processors a prime candidate for space systems, where advanced computational tasks like image analysis, depth map reconstruction, or rover control need to be executed in a power-starved environment. In contrast to the growing number of applications of Neuromorphic processors in smart phones, the automotive and robotics domain, the space environment is unforgiving because of extreme temperatures and high levels of radiation. Any space system, operating beyond LEO requires computing hardware that is resilient against radiation effects. However, Neuromorphic processors have not yet been designed or tested for their radiation tolerance. In this report, we consider traditional methods of detection of radiation events and mitigation via redundancy and gauge their effectiveness on DNNs. In contrast to traditional flight software, however, neural networks represent a statistical algorithm, which might affect its resilience against radiation events. We will focus on the analysis of the tolerance of DNNs with respect to radiation events and discuss techniques to detect radiation hits using on-chip triple modular redundancy (TMR) on an Intel Loihi neuromorphic processor and to mitigate radiation damage. We describe an architecture for on-chip TMR for the Intel Loihi and present results of initial experiments.

Neural Networks↗

Lunar Dust Mitigation: A Guide and Reference: First Edition (2021)

On the surface of the Moon, lunar dust specifically presents unique challenges to operations long-term due to regolith particles’ ubiquitous presence in the lunar environment, potential to electrostatically charge and possible chemical reactivity. Whether to avoid exposure, try to remove or simply to tolerate lunar dust infiltrating a system becomes a complex question involving length of required service life, dust effects and critical risks, mass and complexity trades for the entire system. This publication provides a snapshot of advice from topical experts for specific areas of concern to systems targeted for deployment on the lunar surface. Following introductory overview commentary, dust mitigation approaches appropriate to the lunar surface are first addressed for typically static structures such as optical surfaces, radiators, and other thermal control surfaces, followed by regolith exposure concerns for communications equipment and non-optical sensors. The broad topic of mechanisms and mechanical assemblies is broken down to address relevant component level concerns, such as for bearings and for seals. “Soft goods” components of space suits (fabric) specific concerns are discussed, followed finally by brief coverage of human health issues and concerns, though the emphasis of this publication remains with components directly exposed to the harsh lunar surface environment. A description of some lunar surface hazard details, in particular characteristics of lunar surface dust, follows in Appendix A, and more detailed explanations of quantification issues for particulates are in Appendix B. The simple inertial removal of particles from a surface is discussed in Appendix C, followed by a summary of terrestrial best practices for dust mitigation recommended within select industries in Appendix D. The aggregated bibliography of references, while extensive and very useful, should not be construed to be exhaustive and can serve as a constructive start.

dust↗

Revisiting the Effectiveness of Debris Mitigation by Back-Dating Fragmentation Event

Since 1961, more than 250 satellites have fragmented while in orbit about the Earth, from very low Earth orbit out to the geostationary belt. The problem of orbital debris has been recognized since at least the late 1970s, with the institution of the NASA Orbital Debris Program Office (ODPO) in 1979 at the Johnson Space Center. Efforts to mitigate the growth of the orbital debris environment have mainly focused in two areas: the reduction and elimination of accidental explosions of spacecraft and rocket upper stages and the timely removal of spacecraft and rocket upper stages from orbit after completion of their missions. The ODPO continues to analyze the orbital population in orbit based on object type, mass, and other parameters of interest for characterizing the overall growth of objects in Earth’s orbit. Of the 268 known fragmentation events, 46 have occurred more than ten years after the affected satellites’ launch. These long-delayed breakups increase the population of orbital debris on the date of fragmentation, but we can also consider that the debris generated during that event could be attributed to the launch date of that satellite. We will present here an analysis of the historical growth of the low-Earth orbit debris environment, removing intentional fragmentation events, and examine the effectiveness of mitigation measures (such as passivation and reducing post-mission orbital lifetime).

Chris Ostrom↗

InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API

Urban flooding poses as one of the biggest issues for cities today, as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017 in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating the rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.

Son Do↗

Los Angeles Urban Development: Utilizing NASA Earth Observations to Evaluate the Impact of Tree Coverage on Urban Heat Mitigation

Over the last several decades the city of Los Angeles, California, has been experiencing increased temperatures resulting from the urban heat island effect. This is largely due to the expansion of developed areas which allow for the trapping of heat, posing dangerous health risks. As a solution, many organizations have turned to urban greening and tree planting initiatives to help cool vulnerable communities. NASA DEVELOP has partnered with City Plants and the City of Los Angeles, Office of Forest Management to study the role of trees in urban environments and their relation to the mitigation of local urban heat islands. This team used NASA Earth observation data spanning from 2016 to 2022, including land surface temperature and Normalized Difference Vegetation Index (NDVI) data collected from Landsat 8 Thermal Infrared Sensor (TIRS) and International Space Station (ISS) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), respectively. Data from the National Agriculture Imagery Program (NAIP) were also used to obtain a supervised classification of tree canopy cover. Our analysis reveals a spatial and temporal connection between temperature and vegetation, suggesting that areas with more vegetation are less likely to suffer high summertime temperatures. Results also highlight the impacts of tree planting programs, such as the Vermont Corridor planting project, which increased tree canopy cover by up to 5% in the community between 2016 and 2022. These findings support the implementation of urban greening practices and inform residents and officials about how investing in trees will help mitigate increasing heat within Los Angeles.

Urban heat island↗

InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API

Urban flooding poses as one of the biggest issues for cities today as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While the InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model’s accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017, in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.

Urban flooding↗

Revisiting the Effectiveness of Debris Mitigation by Back-Dating Fragmentation Events

Since 1961, more than 250 satellites have fragmented while in orbit about the Earth, from very low Earth orbit out to the geostationary belt. The problem of orbital debris has been recognized since at least the late 1970s, with the institution of the NASA Orbital Debris Program Office (ODPO) in 1979 at the Johnson Space Center. Efforts to mitigate the growth of the orbital debris environment have mainly focused in two areas: the reduction and elimination of accidental explosions of spacecraft and rocket upper stages and the timely removal of spacecraft and rocket upper stages from orbit after completion of their missions. The ODPO continues to analyze the orbital population in orbit based on object type, mass, and other parameters of interest for characterizing the overall growth of objects in Earth’s orbit. Of the 268 known fragmentation events, 46 have occurred more than ten years after the affected satellites’ launch. These long-delayed breakups increase the population of orbital debris on the date of fragmentation, but we can also consider that the debris generated during that event could be attributed to the launch date of that satellite. We will present here an analysis of the historical growth of the low-Earth orbit debris environment, removing intentional fragmentation events, and examine the effectiveness of mitigation measures (such as passivation and reducing post-mission orbital lifetime).

Chris Ostrom↗

Sarasota Climate: Monitoring Heat and Assessing Heat Vulnerability to Identify Locations for Heat Mitigation Efforts in Sarasota, Florida

The coastal county of Sarasota, Florida, is located within the humid subtropical climate region and experiences an average of 250 days of sunshine every year. The county has large, urbanized communities which are vulnerable to urban heat island (UHI) effects. These rapidly growing communities contribute to the increasing surface temperatures and placing more residents at risk of heat-related illness. In partnership with Sarasota County Sustainability, the Sarasota Climate team utilized Earth observation data from NASA Landsat 8 and Landsat 9’s Thermal Infrared Sensors (TIRS), and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to model UHI effects within the county during the Summer for the last five years, 2019 to 2023. Data analysis with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Urban Heat Exposure Assessment Tempe 1.0 (UHEAT 1.0) models and within ModelBuilder produced maps that identified the land surface temperature (LST) variance within the county, the regions that are most susceptible to extreme heat, and areas least capable of mitigating the effects of UHI. The results revealed that heat intensity varies significantly across Sarasota County with the highest temperatures in the more developed western part of the county. Additionally, the team identified that there are at least three vulnerable communities that exist in high-heat regions, including North Sarasota, Venice, and North Port. These regions have an overlap between socioeconomic sensitivity and environmental hazard that indicate a high priority in future heat mitigation efforts.

Remote sensing↗

Transfer of NASA Technology to the DoD: Mitigating Motion Sickness with Autogenic Feedback Training Exercise

Motion sickness poses a significant safety risk, particularly in the context of aviation. Given its prevalence among aviators and its detrimental impact on performance, researchers have attempted to identify effective mitigation strategies for motion sickness. Currently, many of the existing interventions are pharmacological, and while effective, they present a problem due to their associated adverse side effects. The primary goals of the current research were 1) demonstrate the value of the application of Autogenic-Feedback Training Exercise (AFTE), a physiological training program developed by NASA to mitigate the impact of operational stressors such as motion sickness and spatial disorientation on human physiology and performance and 2) evaluate a new enhanced version of AFTE training software and demonstrate the ability to apply it remotely and train other personnel to administer it. AFTE combines principles of autogenic therapy, and biofeedback in training individuals to control their physiological reactions through a series of relaxation and arousal exercises. This study included twenty-six participants, 17 men and 9 women. On day 1 participants were tested in a rotating chair (pre-test) to determine their motion sickness tolerance (measured as minutes of rotation); days 2-5 consisted of four AFTE training sessions, each 30-min. in duration for a total of 2 hours; and on day 6 the participants were re-tested in the rotating chair. Results revealed a significant increase in motion sickness tolerance with AFTE on the post-test when compared to pre-test, participants had significantly lower symptom diagnostic scores post-test, and there was no significant gender effect. In addressing the first goal it was concluded that the modified 2-hour version of AFTE significantly improved motion sickness tolerance with participants experiencing fewer symptoms. A second goal of this research was to refine and transfer a NASA technology, software and methods for applications within DOD by training other personnel to administer AFTE. A comparison of NASA and NAMRU-D trainers on AFTE outcome for improving participants’ motion sickness tolerance revealed no significant difference indicating the successful transfer of methods to DOD. In addition, remote AFTE training of military aviators at distant sites was feasible. A third goal was to identify individual patterns of interoceptive abilities and related autonomic metrics able to predict stress response and training outcome. These data included measures of personality traits obtained from questionnaires and specific autonomic measures (e.g., heart rate variability) collected by NAMRU-D investigators. These results will be reported in a separate paper.

autonomic nervous system↗

Mitigation of High Lateral Asymmetry Rates Due to Loss of a Cruise Motor on the X-57 Mod III Aircraft

The X-57 Mod III aircraft utilizes wingtip electric motors to generate thrust. The potential benefit of wingtip propulsion is a reduction in induced drag because wingtip vortices are interrupted. Wingtip propulsors, however, pose the risk of dangerous thrust asymmetry if one of the motors abruptly stops producing full thrust. This paper examines the effects of a full-power, single-motor failure at various phases of flight for the X-57 Mod III aircraft design by way of piloted-in-the-loop simulations conducted by two National Aeronautics and Space Administration test pilots. After determining that a failure during takeoff potentially poses the highest risk of catastrophic consequences, possible mitigations to the failure were explored and evaluated through pilot simulation data, Cooper-Harper ratings, and pilot comments. The preferred mitigation was found to be an automated power reduction system that allowed for a lower pilot workload and quick reduction of the asymmetric thrust.

Ryan Wallace↗

Mitigating Worst-Case Exozodiacal Dust Structure in High-Contrast Images of Earth-Like Exoplanets

Detecting Earth-like exoplanets in direct images of nearby Sun-like systems brings a unique set of challenges that must be addressed in the early phases of designing a space-based direct imaging mission. In particular, these systems may contain exozodiacal dust, which is expected to be the dominant source of astrophysical noise. Previous work has shown that it may be feasible to subtract smooth, symmetric dust from observations; however, we do not expect exozodiacal dust to be perfectly smooth. Exozodiacal dust can be trapped into mean-motion resonances with planetary bodies, producing large-scale structures that orbit in lock with the planet. This dust can obscure the planet, complicate noise estimation, or be mistaken for a planetary body. Our ability to subtract these structures from high-contrast images of Earth-like exoplanets is not well understood. In this work, we investigate exozodi mitigation for Earth–Sun-like systems with significant mean-motion resonant disk structures. We find that applying a simple high-pass filter allows us to remove structured exozodi to the Poisson noise limit for systems with inclinations <60° and up to 100 zodis. However, subtracting exozodiacal disk structures from edge-on systems may be challenging, except for cases with densities <5 zodis. For systems with three times the dust of the solar system, which is the median of the best fit to survey data in the habitable zones of nearby Sun-like stars, this method shows promising results for mitigating exozodiacal dust in future Habitable Worlds Observatory observations, even if the dust exhibits significant mean-motion resonance structure.

Miles H. Currie↗

Monitoring and Assessing Heat Vulnerability to Identify Locations for Heat Mitigation Efforts in Sarasota, Florida

Located in the coastal subtropical region, Florida’s Sarasota County receives plenty of sunlight for more than half of the year. However, the ongoing rise in summer temperatures attributed to climate change poses an increasing vulnerability to extreme heat for the residents. Moreover, the area's high relative humidity exacerbates the discomfort of high temperatures, thereby intensifying the severity of heat events and elevating the risks of heat-related illnesses. Our collaborations with Sarasota County Sustainability underscore shared concerns about the impact of urban heat island (UHI) on the community. We utilized Earth observation data from NASA Landsat 8 and Landsat 9’s Thermal Infrared Sensors (TIRS) and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to model UHI effects within the county during the summer from 2019 to 2023. By implementing the open-source Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling software model, ArcGIS ModelBuilder, and principal component analysis, we identified the land surface temperature variance within the county and areas that are least capable of mitigating the effects of UHI. In addition, we use socioeconomic and demographic data as indicators to quantify vulnerability at the census tract level. The results revealed that heat intensity varies significantly across Sarasota County, with the highest temperatures being in the more developed western part of the region. We pinpointed that at least three vulnerable communities reside in high-heat regions: North Sarasota, Venice, and North Port. These areas demonstrate a confluence between socioeconomic sensitivity and environmental hazard, indicating a high priority in future heat mitigation efforts.

Theresia Phoa↗

On the Characterization and Mitigation of Noise in Space-borne Microwave Sounding Instruments

Space-borne microwave sounding instruments have become vital data sources for weather prediction and climate change studies. Among the various radiometer configurations, the total power microwave radiometer is particularly appealing for current and future operational satellites due to its superior sensitivity and simple design. However, its performance is vulnerable to degradation caused by receiver gain fluctuations, electronic 1/f noise, and other time varying receiver characteristics. For Numerical Weather Prediction (NWP) users, 1/f noise introduces inter-channel correlations, complicating the assimilation of affected observations and reducing their accuracy. Addressing this noise issue in ground data processing system is essential to enhance the utility of microwave sounding data. This paper focuses on the characterization and mitigation of noise in current and future microwave sounding instruments, with particular emphasis on the impact of 1/f noise. Various methods are applied to quantitatively characterize noise features in both frequency and time domains. Additionally, the influence of calibration parameters on 1/f noise are analyzed. Based on these findings, we propose a mitigation algorithm for reducing noise during the on-orbit calibration of microwave sounding instruments, aiming to improve the quality of retrieved data for operational use.

calibration↗

Soft error-mitigating semiconductor design system and associated methods

A soft error-mitigating semiconductor design system and associated methods that tailor circuit design steps to mitigate corruption of data in storage elements (e.g., flip flops) due to Single Events Effects (SEEs). Required storage elements are automatically mapped to triplicated redundant nodes controlled by a voting element that enforces majority-voting logic for fault-free output (i.e., Triple Modular Redundancy (TMR)). Storage elements are also optimally positioned for placement in keeping with SEE-tolerant spacing constraints. Additionally, clock delay insertion (employing either a single global clock or clock triplication) in the TMR specification may introduce useful skew that protects against glitch propagation through the designed device. The resultant layout generated from the TMR configuration may relax constraints imposed on register transfer level (RTL) engineers to make rad-hard designs, as automation introduces TMR storage registers, memory element spacing, and clock delay/triplication with minimal designer input.

Miryala, Sandeep↗

Anomaly Detection and Mitigation for Dynamic Frequency Regulation in Hydropower-Battery Systems: Preprint

Hydropower operators and energy storage providers are increasingly interested in participating in frequency regulation services, driven by the incentives offered by independent system operators, such as the Pennsylvania-New Jersey-Maryland Interconnection (PJM), in a competitive electricity market. This transition, however, unfolds against the backdrop of a modernizing and rapidly digitizing power grid, exposing the integrated legacy infrastructure and vulnerable communication networks to a multitude of cybersecurity threats. These evolving threats not only endanger grid operations but also have the potential to trigger cascading disruptions across the broader grid network and influence regulation markets. This work presents an approach for developing an anomaly detection and mitigation system to address cybersecurity challenges during the participation of a hydropower-integrated battery energy storage system (BESS) in a frequency regulation market. The applied anomaly detector utilizes machine learning algorithms to provide detailed classification of cyber-physical events and provide a comprehensive situation awareness to grid operators. Later, the applied mitigation system triggers predefined corrective actions to minimize the impact of data integrity attacks on the regulation market and system stability. We evaluated the proposed approach on a fully active BESS topology using the slow regulation signal (Reg A) coming from the PJM market. Our simulation results reveal that the proposed approach performs well in detecting data integrity attacks within the allocated time frame and also minimizes the system's instability and economic loss during the participation of hydropower and BESS in the regulation market.

battery energy storage system↗

Mitigation Methods for Piperazine Oxidation in Post-Combustion Carbon Capture

Piperazine is a promising second-generation solvent for amine scrubbing in post-combustion CO2 capture. However, the oxidative degradation of PZ can cause environmental problems and economic loss. This work presents the effects of two mitigation methods: carbon treating and N2 sparging, on the PZ oxidation in long-term operations. The species and their respective quantities adsorbed by the activated carbon were tested in a bench-scale device. The carbon was then tested in the High Temperature Oxidation Reactor (HTOR), where the solvent oxidizes at a reasonably fast rate. Pilot plant campaigns were also performed at the UT Austin SRP and the National Carbon Capture Center (NCCC) and the effects were verified. When dissolved Fe is removed by carbon treating or other methods, available soluble Fe in the system dissolves and replaces the dissolved Fe. Therefore, all available Fe and ligands need to be removed for the mitigation to be effective. The sources of soluble Fe include fly ash and the corrosion of stainless steel, and the ligands are degradation products. 8 All PZ degraded solvents have two absorbance peaks at 320 nm and 538 nm. The 320 nm peak is caused by dissolved metals, especially Fe, complexed by degradation products. The 320 nm peak is related to the amine degradation level and can be used as a simple and efficient method to estimate the amine degradation rate. The pilot plant data suggest that NO2 can oxidize PZ significantly, possibly through radical reactions. 0.01 mmol/kg-hr absorption of NO2 increased the PZ oxidation rate from 1.2 mmol/kg-hr to 2.5 mmol/kg-hr.

Yuying, Wu↗

Soft error-mitigating semiconductor design system and associated methods

A soft error-mitigating semiconductor design system and associated methods that tailor circuit design steps to mitigate corruption of data in storage elements (e.g., flip flops) due to Single Events Effects (SEEs). Required storage elements are automatically mapped to triplicated redundant nodes controlled by a voting element that enforces majority-voting logic for fault-free output (i.e., Triple Modular Redundancy (TMR)). Storage elements are also optimally positioned for placement in keeping with SEE-tolerant spacing constraints. Additionally, clock delay insertion (employing either a single global clock or clock triplication) in the TMR specification may introduce useful skew that protects against glitch propagation through the designed device. The resultant layout generated from the TMR configuration may relax constraints imposed on register transfer level (RTL) engineers to make rad-hard designs, as automation introduces TMR storage registers, memory element spacing, and clock delay/triplication with minimal designer input.

Miryala, Sandeep↗