Neutron self-shielding factors for multiple- body concentric cylindrical configurations
Neutron self-shielding factors for multiple-body concentric cylinder configurations
CONCENTRIC CYLINDER↗
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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.
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Space adaptation syndrome: multiple etiological factors and individual differences
Space motion sickness is a significant operational concern in the American and Soviet space programs. Nearly 70% of all astronauts and cosmonauts are affected to some degree during their first several days of flight. It is now beginning to appear that space motion sickness like terrestrial motion sickness is the consequence of multiple etiological factors. As we come to understand basic mechanisms of spatial orientation and sensory-motor adaptation we can begin to predict etiological factors in different motion environments. Individuals vary greatly in the extent to which they are susceptible to these different factors. However, individuals seem to be relatively self-consistent in terms of their rates of adaptation to provocative stimulation and their retention of adaptation. Attempts to relate susceptibility to motion sickness during the microgravity phases of parabolic flight maneuvers to vestibular function under 1G and 0G test conditions are described.
short duration↗
An Assessment of Turbulence Models for MSR Sample Retrieval Lander Aerothermal Design
Several cases from past entries in the T9 and T5 hypersonic test facilities are examined using various turbulence models and shock-layer thermochemistries with the objectives of verifying/validating turbulence models and determining appropriate multiplicative factors on predicted turbulent heating for use in aerothermal design of the heatshield of the Sample Retrieval Lander (SRL) of the Mars Sample Return (MSR) Flagship mission. The zero-equation turbulence models of Baldwin-Lomax and Cebeci-Smith are shown to replicate measurements to within experimental uncertainty for the T9 cases. For T5 cases, the zero-equation model of Baldwin-Lomax can also replicate measurements provided the shock-layer thermochemistry is modified. The modified thermochemistry resolves a dichotomy from past CFD that required different wall catalycity assumptions in the laminar and turbulent flow regimes. The present work shows that such assumptions are not necessary. Finally, an initial estimate for a multiplicative factor on turbulent heating is estimated for the SST turbulence model – the chosen model for SRL aerothermal design simulations.
Mars entry↗
Ice Clouds Lidar Ratio and Multiple Scattering Factor in Version 4 CALIOP Level 2 Algorithm
Explore the source record for details and available documents.
A Garnier↗
WFIRST Coronagraph Flight Performance Modeling
As it has for the past few years, numerical modeling is being used to predict the on-orbit, high-contrast imaging performance of the WFIRST coronagraph, which was recently defined to be solely a technology demonstrator. A consequence has been a realignment of modeling priorities and revised applications of modeling uncertainty factors and margins, which apply to multiple factors such as pointing and wavefront jitter, thermally-induced deformations, polarization, and aberration sensitivities. At the same time, the models have increased in fidelity as additional parameters have been added, such as time-dependent pupil shear and mid-spatial-frequency deformations of the primary and secondary mirrors, detector effects, and reaction-wheel-speed-dependent pointing and wavefront jitter.
Trauger, John↗
A field measure of the shade fraction
'Shade' has a technical definition peculiar to linear spectral mixture analysis of imaging spectrometer data: it is the reduction in radiance from a surface due to lighting conditions and geometry, and includes topographic shading described by photometric functions as well as shadowing at all scales. 'Shade' is an important constituent of nearly all remotely sensed images, and is one endmember resolved in spectral mixture analysis, where it is represented as a fraction of the measured radiance and a characteristic spectrum. This spectrum is typically the null vector, provided the data have been corrected for atmospheric and instrument effects: i.e., 'shade' is the radiance from an ideal black surface. In topographic shading, irradiance is reduced - typically in proportion to cos(i), where i (incidence angle) is the angle between the sun and the local surface normal vectors. Therefore, the radiance is lowered by a multiplicative factor. Shadowing occurs when i is greater than 90 deg, or when sunlight is blocked by adjacent high terrain; the only irradiance is down-welling skylight and bounce light from adjacent terrain. In spectral mixture analysis, 'shade' is regarded as an additive term. In this regard, it is an accurate description of the proportion of a scene that consists of ideal shadows ('checkerboard mixing'); however, 'shade' represents the multiplicative cos(i) factor as well, as here it should be interpreted as the proportion of shadow that would darken the scene an equivalent amount. In either case, the 'shade' fraction is lessened by adjacency effects, because the scene has a non-zero reflectivity instead of the ideal black surface generally assumed.
Gillespie, Alan R.↗
Systems identification and application systems development for monitoring the physiological and health status of crewmen in space
The use of automated, analytical techniques to aid medical support teams is suggested. Recommendations are presented for characterizing crew health in terms of: (1) wholebody function including physiological, psychological and performance factors; (2) a combination of critical performance indexes which consist of multiple factors of measurable parameters; (3) specific responses to low noise level stress tests; and (4) probabilities of future performance based on present and periodic examination of past performance. A concept is proposed for a computerized real time biomedical monitoring and health care system that would have the capability to integrate monitored data, detect off-nominal conditions based on current knowledge of spaceflight responses, predict future health status, and assist in diagnosis and alternative therapies. Mathematical models could play an important role in this approach, especially when operating in a real time mode. Recommendations are presented to update the present health monitoring systems in terms of recent advances in computer technology and biomedical monitoring systems.
Leonard, J. I.↗
Modal decomposition of Hamiltonian variational equations
Over any finite arc of trajectory, the variational equations of a Hamiltonian system can be separated into 'normal' modes. This transformation is canonical, and the Lyapunov exponents over the trajectory arc occur as positive/negative pairs for conjugate modes, while the modal vectors remain unit vectors. This decomposition effectively solves the variational equations for any canonical, linear-dependent system. As an example, we study the Voyager I trajectory. In an interplanetary flyby, some of the modal variables increase by very large multiplicative factors, but this means that their conjugate modal variables decrease by those same very large multiplicative vectors. Maneuver strategies for this case are explored, and the minimum delta upsilon maneuver is found.
Wiesel, William E.↗
Probabilistic Multi-Factor Interaction Model for Complex Material Behavior
Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required to represent the ejected foam. The exponents were evaluated by least squares method from experimental data. The equation is used and it can represent multiple factors in other problems as well; for example, evaluation of fatigue life, creep life, fracture toughness, and structural fracture, as well as optimization functions. The software is rather simplistic. Required inputs are initial value, final value, and an exponent for each factor. The number of factors is open-ended. The value is updated as each factor is evaluated. If a factor goes to zero, the previous value is used in the evaluation.
Abumeri, Galib H.↗
Increased Intracranial Pressure and Visual Impairment Associated with Long-Duration Spaceflight
Although humans have been flying in space since the 1960s, more recent missions have revealed a new suite of physiological adaptations and consequences of space flight. Notably, 60% of long-duration crewmembers (ISS/MIR) and >25% of short-duration (Shuttle) crewmembers have reported subjective degradation in vision (based on debrief comments) (Gibson 2011). Decreased near-visual acuity was demonstrated in 46% of ISS/Mir and 21% of Shuttle crewmembers, resulting in a shift of up to 1-2 diopters in their refractive correction. It is likely that the recently revealed ophthalmic changes have been present since the first days of human space flight, but have been overlooked or attributed to other causations. The reported changes in vision have occurred at various time points throughout missions, with ranging degrees of visual degradation. Although some cases resolved upon return to Earth, several astronauts have not regained preflight visual acuity, indicating that the damage may be permanent. While observing these changes over the years, without other overt symptomology and with the given age range of the flying population, this has largely been attributed to an expected hyperopic shift due to aging. However, the availability of onboard analysis techniques, including visual acuity assessments, retinal imagery, and ultrasounds of the eye and optic nerve tracts, along with more detailed post-flight techniques, has led to the recent recognition of a wider syndrome. Along with vision changes, findings include flattening of the globe, swelling of the optic disc (papilledema), choroidal folds in the retina, swelling of the optic nerve sheath, and visual field defects. It is widely hypothesized that this constellation of findings may be explained by an elevation of intracranial pressure (ICP). Out of the 60% of long-duration astronauts that have reported a subjective degradation in vision, a subset (currently 10 astronauts) have developed this syndrome. The National Aeronautics and Space Administration (NASA) has made it a high priority to understand this syndrome and provide mitigation techniques to protect crewmembers from visual impairment. While there are many possible factors that could contribute to intracranial hypertension associated with spaceflight, the relative contribution of these, as well as the processes by which eye damage occurs as a result of intracranial hypertension, are not fully understood. The observed pathophysiological phenomena are extremely complex and it is likely that multiple factors contribute to their incidence, rather than one simple mechanism. This paper will define and examine the findings in detail, and expound upon the potential contributing factors and their relative contribution to this syndrome.
Marshall-Bowman, Karina↗
A Markov Decision Process Framework for Optimal Airport Reconfiguration
The airport runway configuration is defined as a combination set of runways for arrivals and departures used at a point during operation of the airport. An optimal configuration of these runways depends on a number of factors, including traffic demand, wind magnitude and direction, other adverse weather conditions, and noise restrictions, among others. Based on the current state of these factors and predictions of traffic demand and weather conditions, runway configuration changes are made and coordinated between tower controller, other air traffic control facilities, pilots, and ground personnel. Reconfigurations can be quite disruptive to airport operations; minimizing their frequency and scheduling them well in advance is essential for mitigating some of the added workload for controllers and pilots. Unfortunately, deciding on an appropriate time to change is challenging for human decision makers. Not only do multiple factors need to be evaluated, but the uncertainty in their forecasts must also be considered. Previous optimization methods, such as mixed linear integer programming, have been proposed. Although these methods can reason over a large set of variables, they do not systematically handle the uncertainty associated with weather movement, traffic demands, and other variables. In this work, we introduce a Markov Decision Process (MDP)-based decision making framework which can reason effectively over the inherent uncertainties and make optimal decisions on if/when to change the airport configuration. In a prototype implementation, we present a single runway with three aircraft and utilize knowledge of the forecasted wind speed and direction to determine whether to keep or change the current runway configuration. Our aim through this work is to present a framework for airport reconfiguration which can be scalable to additional aircraft, multiple runways, and various input parameters. This technique will optimize the airport reconfiguration procedure by providing a proactive approach, optimizing not just at the next optimal opportunity for a reconfiguration based on varying atmospheric and traffic conditions in the terminal airspace, but also anticipating future necessary reconfigurations. This will eliminate the inefficiencies of frequent changes currently associated with runway reconfiguration procedures.
runway reconfiguration↗
Influence of the atmosphere on remotely sensed data
Factors which influence the effects of the atmosphere on the data of remote sensing are examined. A radiative-transfer model is considered and effects of varied optical thickness of the atmosphere are investigated. Effects of varied surface albedo are discussed along with the effects of the sun angle, the effects of the scan angle, and questions regarding the atmospheric effects on the recognition performance. It is found that a multiplicative factor involving the sun angle alone is not sufficient for the correction of space data.
Turner, R. E.↗
Climate change reshapes the drivers of false spring risk across European trees
Temperate and boreal forests are shaped by late spring freezing events after budburst, which are also known as false springs. Research has generated conflicting results on whether or not these events will change with climate change, potentially because---to date---no study has compared the myriad climatic and geographic factors that contribute to a plant's risk of a false spring. We assessed and compared the strength of the effects of mean spring temperature, distance from the coast, elevation and the North Atlantic Oscillation (NAO) using PEP725 leafout data for six temperate, decidious tree species across 11,648 sites in Central Europe and how these predictors shifted with climate change. Across species before recent warming, mean spring temperature and distance from the coast were the strongest predictors, with higher mean spring temperatures associated with decreased risk in false springs (–7.64% per 2°C increase) and sites further from the coast experiencing an increased risk (5.32% per 150km from the coast). Elevation (2.23% per 200m increase in elevation) and NAO index (1.91% per 0.3 increase) also increased false spring risk. With climate change, elevation and distance from coast---i.e., the geographic factors---remain relatively stable, while climatic factors shifted in magnitude for mean spring temperature (down to -2.84% in risk per 2°C), and in direction, with positive NAO phases leading to lower risk (-9.15% per 0.3). The residual effects of climate change---unexplained by the climatic and geographic factors already included in the model---magnified the species-level variation in risk, with risk increasing among early-leafout species (i.e., Aesculus hippocastanum, Alnus glutinosa and Betula pendula) but a decline or no change in risk among late-leafout species (i.e., Fagus sylvatica, Fraxinus excelsior and Quercus robur). Our results show that climate change has reshaped the major drivers of false spring risk and highlight how considering multiple factors can yield a better understanding of the complexities of climate change.
Climate change↗
Understanding Model-Observation Discrepancies in Satellite Retrievals of Atmospheric Temperature Using GISS ModelE
We examine multiple factors in the representation of satellite-retrieved atmospheric temperature diagnostics in historical simulations of climate change during the satellite era (specifically 1979–2021) using GISS ModelE contributions to the Coupled Model Intercomparison Project (Phase 6) (CMIP6). The tropospheric and stratospheric trends in these diagnostics are affected by greenhouse gases (notably carbon dioxide and ozone), coupling with the ocean, volcanic aerosols, solar activity and compositional and dynamic feedbacks. We explore the impacts of internal variability, changing forcing specifications, composition interactivity, the quality of the stratospheric circulation, vertical resolution, and possible impacts of the mis-specification of volcanic aerosol optical depths. Overall temperature trends throughout the satellite period are well captured, but discrepancies at all levels exist and have multiple distinct causes. We find that stratospheric comparisons (using Stratospheric Sounding Unit (SSU) retrievals and successor instruments) are most affected by variations in the representation of ozone depletion and feedbacks, followed by the volcanic signals. Tropospheric skill (using the Microwave Sounding Unit (MSU) retrievals) is affected by the trends in ocean heat uptake and tropospheric aerosols, but also by the representation of stratospheric processes through the impact of the Brewer-Dobson circulation on the height of the tropical tropopause. We demonstrate that no single factor is the dominant cause of the discrepancies and that almost all observations lie within the broad envelope of structural uncertainty.
satellite retrievals of atmospheric temperature↗
An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data
This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, satellite, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. MODIS-based change products were applied to view and assess insect-induced swamp forest defoliation. MODIS, Landsat, and ASTER satellite data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.
Spruce, Joseph P.↗
Model Performance in Simulating the Mid-Holocene Green Sahara
The Green Sahara Period, spanning about 11,500 to 5,000 years ago, offers an opportunity to test the ability of climate models to simulate large-scale changes in northern African climate through the strengthening of the West African Monsoon. In this study, we evaluate the performance of four models in simulating the mid-Holocene (6,000 BP), namely – EC-Earth, iCESM, CCSM4-Toronto, and the GISS ModelE2.1-G. Two scenarios are considered for each model – a standard PMIP scenario simulated with the mid-Holocene orbital parameters and greenhouse gas concentrations with vegetation prescribed to pre-industrial conditions, as well as a Green-Sahara scenario which additionally considers factors such as enhanced vegetation, reduced dust, presence of lakes, and land and soil feedbacks. All mid-Holocene scenarios capture an increase in monsoonal precipitation in northern Africa. However, a comparison of the two mid-Holocene scenarios reveals significantly higher precipitation in northern Africa for all the Green-Sahara scenarios relative to the PMIP scenarios – an observation consistent across all models. Accompanied by a strengthened Saharan Heat Low, these changes in the West African Monsoon are also linked to polar amplification, a stronger Indian Summer Monsoon and alterations to the Walker circulation. Model results are in agreement with pollen-based SAT records, multi-proxy SST records and African lake level records. This comparison indicates that a realistic simulation of the mid-Holocene Green Sahara requires consideration of multiple factors in addition to orbital and greenhouse gas forcings.
Green Sahara Period↗
Chromatin Folding, Fragile Sites, and Chromosome Aberrations Induced by Low- and High- LET Radiation
We previously demonstrated non-random distributions of breaks involved in chromosome aberrations induced by low- and high-LET radiation. To investigate the factors contributing to the break point distribution in radiation-induced chromosome aberrations, human epithelial cells were fixed in G1 phase. Interphase chromosomes were hybridized with a multicolor banding in situ hybridization (mBAND) probe for chromosome 3 which distinguishes six regions of the chromosome in separate colors. After the images were captured with a laser scanning confocal microscope, the 3-dimensional structure of interphase chromosome 3 was reconstructed at multimega base pair scale. Specific locations of the chromosome, in interphase, were also analyzed with bacterial artificial chromosome (BAC) probes. Both mBAND and BAC studies revealed non-random folding of chromatin in interphase, and suggested association of interphase chromatin folding to the radiation-induced chromosome aberration hotspots. We further investigated the distribution of genes, as well as the distribution of breaks found in tumor cells. Comparisons of these distributions to the radiation hotspots showed that some of the radiation hotspots coincide with the frequent breaks found in solid tumors and with the fragile sites for other environmental toxins. Our results suggest that multiple factors, including the chromatin structure and the gene distribution, can contribute to radiation-induced chromosome aberrations.
Zhang, Ye↗
A Multi-Scale Sampling Strategy for Detecting Physiologically Significant Signals in AVIRIS Imagery
Models of photosynthetic production at ecosystem and global scales require multiple input parameters specifying physical and physiological surface features. While certain physical parameters (e.g., absorbed photosynthetically active radiation) can be derived from current satellite sensors, other physiologically relevant measures (e.g., vegetation type, water status, carboxylation capacity, or photosynthetic light-use efficiency), are not generally directly available from current satellite sensors at the appropriate geographic scale. Consequently, many model parameters must be assumed or derived from independent sources, often at an inappropriate scale. An abundance of ecophysiological studies at the leaf and canopy scales suggests strong physiological control of vegetation-atmosphere CO2 and water vapor fluxes, particularly in evergreen vegetation subjected to diurnal or seasonal stresses. For example hot, dry conditions can lead to stomatal closure, and associated "downregulation" of photosynthetic biochemical processes, a phenomenon often manifested as a "midday photosynthetic depression". A recent study with the revised simple biosphere (SiB2) model demonstrated that photosynthetic downregulation can significantly impact global climate. However, at the global scale, the exact significance of downregulation remains unclear, largely because appropriate physiological measures are generally unavailable at this scale. Clearly, there is a need to develop reliable ways of extracting physiologically relevant information from remote sensing. Narrow-band spectrometers offer many opportunities for deriving physiological parameters needed for ecosystem and global scale photosynthetic models. Experimental studies on the ground at the leaf- to stand-scale have indicated that several narrow-band features can be used to detect plant physiological status. One physiological signal is caused by xanthophyll cycle pigment activity, and is often expressed as the Photochemical Reflectance Index (PRI). Because the xanthophyll cycle pigments are photoregulatory pigments closely linked to photosynthetic function, this index can be used to derive relative photosynthetic rates. An additional signal with physiological significance is the 970 nm water absorption band, which provides a measure of liquid water content. This feature has been quantified both using a simple 2-band ratio (900/970 nm, here referred to as the "Water Band Index" or WBI;), and using the "continuum removal" method. Current atmospheric correction methods for AVIRIS imagery also obtain quantitative expressions of surface liquid water absorption based on the 970 nm water band and may be comparable to ground-based estimates of water content using this feature. However, physiological interpretations of both the PRI and the WBI are best understood at the leaf and canopy scales, where complications of atmospheric interference and complex stand and landscape features can be minimized, and where experimental manipulations can be readily applied. Currently it is not known whether these physiological indices can be used to derive meaningful physiological information from AVIRIS imagery. In addition to the problem of atmospheric interference, another challenge is that any simple physiological index can be confounded by multiple factors unrelated to physiology, and this problem can become more severe at progressively larger spatial scales. For example, previous work has suggested that both the PRI and the WBI, are strongly correlated with other optical measures of canopy structure (e.g., the Normalized Difference Vegetation Index or green vegetation fraction), indicating a confounding effect of structure on physiological signals at the larger, landscape scale. Furthermore, the normal operating mode of most imaging spectrometers does not allow simultaneous, ground truthing at a level of detail needed for physiological sampling. Additionally, manipulative experiments of physiology are difficult to apply at a geographic scale suitable for comparison with remote imagery, which often works at spatial scales that are several orders of magnitude larger than those typically used for physiological studies. These limitations require the consideration of alternative approaches to validating physiological information derived from AVIRIS data. In this report, we present a multi-scale sampling approach to detecting physiologically significant signals in narrow-band spectra. This approach explores the multi-dimensional data space provided by narrow-band spectrometry, and combines AVIRIS imagery at a large scale, with ground spectral sampling at an intermediate scale, and detailed ecophysiological measurements at a fine scale, to examine seasonally and spatially changing relationships between multiple structural and physiological variables. Examples of this approach are provided by simultaneous sampling of the Normalized Difference Vegetation Index (NDVI), an index of fractional PAR interception and green vegetation cover, the Water Band Index (WBI, an index of liquid water absorption, and the Photochemical Reflectance Index (PRI, an index of xanthophyll cycle pigment activity and photosynthetic light-use efficiency. By directly linking changing optical properties sampled on the ground with measurable physiological states, we hope to develop a basis for interpreting similar signals in AVIRIS imagery.
Gamon, John A.↗