Results for “difference scaling” — Page 23

NASA NTRS2021

Spatio-Temporal Patterns of Optimal Landsat Data for Burn Severity Index Calculations: Implications for High Northern Latitudes Wildfire Research

Satellite remote sensing has been widely used for the evaluation of wildfire burn severity in various ecosystems. While a variety of remote sensing-based burn severity indices have been developed, the Landsat-based differ-enced Normalized Burn Ratio (dNBR) presents the most widely-used approach to burn severity assessment for fire research and management. Although dNBR-based approaches have been continuously updated, including the development of the relative dNBR (RdNBR) and the Relativized Burn Ratio (RBR), one key obstacle for the reliable applications of the burn severity indices in the high northern latitudes has not been adequately addressed. Specifically, optimal Landsat image pairs are very rarely available for the calculation of the burn severity indices in certain regions of the high northern latitudes (HNL), resulting in the burn severity index outputs calculated for a large number of wildfires being considerably affected by non-fire-related factors. The suboptimal selection of image pairs may have partially contributed to the lack of consistency in the performance of the burn severity indices in the HNL regions. In this paper, we systematically evaluated the impacts of sub-optimal image pairs on signal stability through two sets of analyses conducted at different spatial scales. First, at the regional scale, we examined the burn severity indices calculated for a selection of wildfires in Alaska. Here, we demonstrate the inconsistent performance of the same index calculated based on Landsat data that are typically considered as “optimal”. In addition, we show that the calculated indices may be more prone to the negative impacts of these inconsistencies, thus leading to reduced reliability, when there is limited Landsat data availability. Second, at the continental scale, we show that certain areas in the HNL, especially Alaska during the pre-2000 era, are subject to the potentially strong negative impact associated with the limited data availability. Through systematically analyzing this issue, we hope to not only divert more attention to it but also to provide potential solutions, based on which further improvements that may be of particular importance for research on Arctic wildfires could be made.

Dong Chen↗

NASA NTRSDate not supplied

Test Results for the SEA Ice Crystal Detector (ICD) under SLD Conditions at the NASA IRT

The Science Engineering Associates hot-wire Ice Crystal Detector was tested under Appendix C and Supercooled Large Drop Conditions at the NASA Icing Research Tunnel, with the purpose of comparing the measurements to the tunnel LWC calibration, and to test the performance of the mixed-phase retrievals of the probe. The liquid water content measured by the total water content sensor of the probe agreed well with the tunnel calibration over a wide range of MVDs, not unexpectedly since the tunnel was calibrated with a similar Multiwire hot-wire probe. A scale factor difference of about 7% was attributed to the lack of an efficiency correction for the Ice Crystal Detector at smaller median volume diameters, and typical sample area uncertainties of liquid water content devices. In addition, the simultaneous equations that are used to retrieve liquid and ice water contents were tested under liquid and glaciated conditions. Using constant ice and water efficiencies for each wire, the equations were found to produce a large and false ice water content retrieval in large median volume diameter liquid cases. By applying a liquid efficiency to the liquid water content sensor that varied with median volume diameter, retrievals were improved such that false ice water content was less than ±10% of the total water content out to the 460 μm median volume diameter limit of the testing. The probe was also tested in glaciated conditions by freezing out a small median volume diameter spray. Using constant ice efficiencies for the two sensors provided from aircraft measurements, the retrieved ice water content was about 40% higher than expected for the case presented, likely due to the ice efficiencies that were used from aircraft measurements of natural clouds being too low for the tunnel’s glaciated sprays. Application of ice efficiencies that vary with particle size and potentially other parameters will be explored for future improvement of retrievals.

Air Craft Icing↗

NASA NTRS2021

Test Results for the SEA Ice Crystal Detector (ICD) under SLD Conditions at the NASA IRT

The Science Engineering Associates hot-wire Ice Crystal Detector was tested under Appendix C and Supercooled Large Drop Conditions at the NASA Icing Research Tunnel, with the purpose of comparing the measurements to the tunnel LWC calibration, and to test the performance of the mixed-phase retrievals of the probe. The liquid water content measured by the total water content sensor of the probe agreed well with the tunnel calibration over a wide range of MVDs, not unexpectedly since the tunnel was calibrated with a similar Multiwire hot-wire probe. A scale factor difference of about 7% was attributed to the lack of an efficiency correction for the Ice Crystal Detector at smaller median volume diameters, and typical sample area uncertainties of liquid water content devices. In addition, the simultaneous equations that are used to retrieve liquid and ice water contents were tested under liquid and glaciated conditions. Using constant ice and water efficiencies for each wire, the equations were found to produce a large and false ice water content retrieval in large median volume diameter liquid cases. By applying a liquid efficiency to the liquid water content sensor that varied with median volume diameter, retrievals were improved such that false ice water content was less than ±10% of the total water content out to the 460 μm median volume diameter limit of the testing. The probe was also tested in glaciated conditions by freezing out a small median volume diameter spray. Using constant ice efficiencies for the two sensors provided from aircraft measurements, the retrieved ice water content was about 40% higher than expected for the case presented, likely due to the ice efficiencies that were used from aircraft measurements of natural clouds being too low for the tunnel’s glaciated sprays. Application of ice efficiencies that vary with particle size and potentially other parameters will be explored for future improvement of retrievals.

o Aircraft Icing↗

NASA NTRSDate not supplied

Using Secondary Craters to Assess Strength Differences Between Neighboring Surface Units

An issue with Martian remote sensing studies is the difficulty inferring surface and crustal material properties. For direct information we rely on the instruments of landed missions, like InSight, and extrapolate to other locations. To apply that extrapolation, we would like to use a methodology that can benefit from remote sensing data. We are exploring using secondary craters, which are often thought of as nuisances when determining accurate ages, to calculate crustal properties. The upside of secondary craters is that they are from ejecta blocks moving at relatively lower speeds, this lets them reside in a different crater scaling regime [1], one that is more sensitive to the crust’s effective strength (Yeff) and porosity/internal friction (through the μ and KD terms [A]).

Mars↗

NASA NTRS2022

Solar Irradiance Variability Monitor for the Galileo Solar Space Telescope Mission: Concept and Challenges

Long and reliable total solar irradiance (TSI) time series is one of the essential parameters for understanding solar contributions to climate change. The minor fluctuations of TSI in long timescales could impact the energy balance. Despite the improvement of accurate measurements provided by the instruments, at the time, long-term TSI variability and its effects had not been established. The space-borne radiometer era provided observations in short timescales from minutes to years. Therefore, this study presents an overview of irradiance observations, highlighting the importance of following its variability in different time scales. In this context, the Galileo Solar Space Telescope that has been developed by the Institute for Space Research (INPE), Brazil, includes the Irradiance Monitor Module with a radiometer cavity like the classical design and a next-generation compact radiometer.

total solar irradiance (TSI)↗

NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗

NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗

NASA NTRS2022

Characterizing Aerosol From Space With the MODerate Resolution Imaging Spectroradiometer (Modis) on the Terra and Aqua Satellites

Aerosols, the small, suspended liquid and solid particles in the atmosphere, have myriad effects on climate, weather, and air quality. When the NASA Earth-Observing System’s (EOS) Terra and Aqua satellites launched in 1999 and 2002, they each included many advanced sensors that have been used for aerosol research. In particular, the MODerate-resolution Imaging Spectroradiometer (MODIS) deployed on both satellites, has provided key data relating to aerosol loading and relative aerosol type on the global scale. Three different algorithms, known as “Dark Target”, “Deep Blue” and “MAIAC”, use different subsets of MODIS measurements and different assumptions to create various products such as Aerosol Optical Depth (AOD), fine mode fraction (FMF) and single scattering albedo (SSA). Although all three derive AOD in cloud-free conditions, each algorithm has different strengths and weaknesses in different areas of the globe and under different conditions. Here, we provide a short summary of each algorithm, description of products, and basic information about downloading and using the products. We also provide some examples of how MODIS aerosol products are used. Finally, we add a quick discussion about how these algorithms and products will continue after MODIS leaves orbit.

MODIS↗

NASA NTRS2023

Understanding Sun-as-a-Star Variability of Solar Balmer Lines

Precise, high-cadence, long-term records of stellar spectral variability at different temporal scales lead to better understanding of a wide variety of phenomena including stellar atmospheres and dynamos, convective motions, and rotational periods.

solar activity, solar cycle↗

NASA NTRSDate not supplied

Performance Risk Model (PRisM) Proof-of-Concept: An Operational Decision Support Tool to Predict Crew Performance in Space from Available Performance Tests

The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center has developed a range of tools to evaluate astronaut health during spaceflight and to optimize the medical set required for missions. Among these, the Performance Risk Model (PRisM) represents a novel advancement, extending CHP-PRA’s focus beyond medical systems into the domain of human performance. Such tool could be pivotal in optimizing astronaut capabilities during space travel, thereby enhancing overall mission success. PRisM leverages data from well-established performance assessments conducted during previous crewed space missions and Earth analogs to strategically predict outcomes for planned tasks, even when direct performance testing has not been conducted for those specific tasks. To evaluate performance, PRisM references the various metrics outlined in NASA-STD-3001 and employs a methodology to integrate different performance scales. This framework analyzes the contribution of various human system task categories (HSTCs) to task execution and compares these contributions to the HSTCs’ involvement in other known tests. The model further employs a Monte Carlo simulation to sample performance scores from their distribution in operationally relevant tests such as those in Mulavara et al. (2018) and, by leveraging similarities in HSTC involvement, transfers this knowledge to actual mission tasks, such as those outlined in the "Human Exploration of Mars: Preliminary List of Crew Tasks”. The current PRisM proof-of-concept includes analyses of the impact of exercise and specific medications on astronauts’ performance, with provisions to incorporate additional countermeasures as data becomes available. Furthermore, the tool is customizable to include any system necessary to fully encompass the domain of human systems and can be adapted to evaluate performance for any spaceflight activities as requested by operational stakeholders. PRisM has the potential to assist the Human Research Program in exploring the capabilities trade space for optimized crew performance.

performance modeling↗

NASA NTRS2026

High Temperature Dielectric Properties and Differential Scanning Calorimetry of Lunar Simulants

To guide development of microwave process technology that could be used during in situ construction on the Moon, we measured the high-temperature basic dielectric properties (εʹ and εʺ) of 17 lunar simulants and related materials. In order to confidently use these data one needs to understand the data’s strengths and weaknesses. Therefore, a goal of this publication is to provide insights into the comparative effects of sample composition, pre-treatments, experimental variables, high temperatures, and other factors on the measured response. The dielectric measurements were performed using the cavity perturbation method over a temperature range between room temperature to 1000 °C, or higher, and provided the real and imaginary components of permittivity at six frequencies. The utility of the original values was limited by the varying density of the pellets used in the measurement. Therefore, all of the εʹ and εʺ measurements at the frequency of 2466 MHz have been scaled to a constant density, 1.75 g/cm 3 . Here the data are presented as graphs chosen to aid analysis within and across simulant groups. To gain additional insight into the processes happening at the elevated temperatures in the dielectric measurements, heat capacity data was obtained using differential scanning calorimetry (DSC) on several of the simulant materials. Our data show that over the frequency range 397 MHz – 2985 MHz a material’s behavior does not greatly change, as compared to the scale of differences observed between lunar mare and highland simulants at high temperatures. For example at 1000 °C, the mare simulant JSC-1A absorbs 10 times more power than the highland simulant NUW-LHT-5M. We observe that as melting temperatures are reached both permittivity and dielectric loss rise non-linearly, helping to explain thermal runaway during microware heating. Our data show that even less than a few weight % of many non-lunar minerals, and the use of mixtures in simulants can affect the dielectric behavior at higher temperatures. A comparison of our results with published dielectric data for Apollo samples and with remote sensing of the Moon supports the conclusion the simulants and lunar material at room temperature have very similar dielectric values.

Differential Scanning Calorimetry↗

NASA NTRS2018

Differing Properties of Two Ion‐Scale Magnetopause Flux Ropes

Explore the source record for details and available documents.

L. Alm↗

NASA NTRS1981

On the development and global oscillations of cometary ionospheres

Representing the cometary ionosphere by a single fluid model characterized by an average ionization time scale, both the ionosphere's development as a comet approaches the sun and its response to sudden changes in solar wind conditions are investigated. Three different nuclear sizes (small, average, very large) and three different modes of energy addition to the atmosphere (adiabatic, isothermal, suprathermal) are considered. It is found that the crucial parameter determining both the nature and the size of the ionosphere is the average ionization time scale within the ionosphere. Two different scales are identified. It is noted that the ionosphere can also be characterized by the relative sizes of three different scale lengths: the neutral standoff distance from the nucleus, the ion standoff distance from the nucleus, and the nuclear distance at which the ions and the neutrals decouple collisionally.

Houpis, H. L. F.↗

NASA NTRS1990

Erosive Augmentation of Solid Propellant Burning Rate: Motor Size Scaling Effect

Two different independent variable forms, a difference form and a ratio form, were investigated for correlating the normalized magnitude of the measured erosive burning rate augmentation above the threshold in terms of the amount that the driving parameter (mass flux or Reynolds number) exceeds the threshold value for erosive augmentation at the test condition. The latter was calculated from the previously determined threshold correlation. Either variable form provided a correlation for each of the two motor size data bases individually. However, the data showed a motor size effect, supporting the general observation that the magnitude of erosive burning rate augmentation is reduced for larger rocket motors. For both independent variable forms, the required motor size scaling was attained by including the motor port radius raised to a power in the independent parameter. A boundary layer theory analysis confirmed the experimental finding, but showed that the magnitude of the scale effect is itself dependent upon scale, tending to diminish with increasing motor size.

Strand, L. D.↗

NASA NTRS1989

Comparison of AVHRR and SMMR data for monitoring vegetation phenology on a continental scale

AVHRR normalized difference vegetation index (NDVI) data for a one-year period were compared with Scanning Multichannel Microwave Radiometer microwave polarization difference temperature (MPDT) data for the study of vegetation phenology. It is shown that the MPDT response differs considerably from the seasonal NDVI pattern. The results do not support the hypothetical relationship between MPDT and leaf water content. It is found that only vegetation types with a substantial seasonal variation in the areal extent of vegetated cover show strong seasonality in MPDT data.

Justice, C. O.↗

NASA NTRS1990

Differential memory in the trilinear model magnetotail

The previously proposed concept of 'differential memory' is quantitatively demonstrated using an idealized analytical model of particle dynamics in the magnetotail geometry. In this model (the 'trilinear' tail model) the magnetotail is divided into three regions. The particle orbits are solved exactly in each region, thus reducing the orbit integration to an analytical mapping. It is shown that the trilinear model reproduces the essential phase space features of the earlier model (Chen and Palmadesso, 1986), possessing well-defined entry and exit regions, and stochastic, integrable (regular), and transient orbits, occupying disjoint phase space regions. Different regions have widely separated characteristic time scales corresponding to different types of particle motion. Using the analytical model, the evolution of single-particle distribution functions is calculated.

Chen, James↗

NASA NTRS1931

Full-Scale Wind-Tunnel Tests on Several Metal Propellers Having Different Blade Forms

This report gives the full-scale aerodynamic characteristics of five different aluminum alloy propellers having four different blade forms. They were tested on an open cockpit fuselage with a radial air-cooled engine having conventional cowling. The results show that (1) the differences in propulsive efficiency due to the differences in blade form were small; (2) the form with the thinnest airfoil sections had the highest efficiency; (3) it is advantageous as regards propulsive efficiency for a propeller operating in front of a body, such as a radial engine, to have its pitch reduced toward the hub.

Weick, Fred E↗

NASA NTRS1988

Relationships between persistent large-scale flow anomalies and variation in synoptic-scale eddy activity and cyclogenesis

Observational analyses to study the relationships between large-scale flow anomalies and variations in synoptic-scale eddy activity and cyclogenesis are presented. The way in which changes in the large-scale flow influence the behavior of synoptic-scale eddies and the way in which changes in eddies may feedback to influence the large-scale flow anomalies are examined. Situations characterized by differing large-scale flows are compared, showing well-defined diferences in synoptic-scale eddy activity. The net forcings of anomalous mean flows by eddies as deduced from tendency methods and E-vector analyses suggest that synoptic-scale eddies may play an important role in maintaining certain anomalous flow patterns such as blocking.

Dole, Randall M.↗