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At least 595 records · Page 33

Solar Activity Across the Scales: From Small-Scale Quiet-Sun Dynamics to Magnetic Activity Cycles

Observations as well as numerical and theoretical models show that solar dynamics is characterized by complicated interactions and energy exchanges among different temporal and spatial scales. It reveals magnetic self-organization processes from the smallest scale magnetized vortex tubes to the global activity variation known as the solar cycle. To understand these multiscale processes and their relationships, we use a two-fold approach: 1) realistic 3D radiative MHD simulations of local dynamics together with high resolution observations by IRIS, Hinode, and SDO; and 2) modeling of solar activity cycles by using simplified MHD dynamo models and mathematical data assimilation techniques. We present recent results of this approach, including the interpretation of observational results from NASA heliophysics missions and predictive capabilities. In particular, we discuss the links between small-scale dynamo processes in the convection zone and atmospheric dynamics, as well as an early prediction of Solar Cycle 25.

Solar↗

Lightning Strike Distance Distribution Beyond a Preexisting Lightning Area

The 45th Weather Squadron (45 WS) asked the Applied Meteorology Unit (AMU) to review the 30-year-old, lightning stand-off distances of 5 nautical miles (nmi) for applicability to today's operations. This was based on the realization that previous lightning strike distance studies did not match how 45 WS issues lightning warnings (Roeder, 2008). The previous lightning distance studies were from the point of origin of the lightning or the average starting location that would tend to be in the core of the thunderstorm. However, the 45 WS issues lightning warnings based on the edge of a preexisting lightning area. Before beginning the AMU project, it took several years to develop a method to calculate a distance distribution beyond a preexisting area (Roeder, 2015). The AMU pulled Lightning Detection and Ranging (LDAR) sensor data from 1/1/2013 to 12/31/2013. This dataset consisted of 37 million individual source data points from the LDAR sensors. Only sources within 50 km north, south, east or west of the LDAR grid center were included in the dataset. This limited the use of LDAR data to that with the greatest accuracy of source detection and increased data processing. Points were grouped into flashes based on spatial and temporal criteria. Based on the sensitivity analysis the AMU performed on the flash clustering algorithm, a time value of 0.3 seconds was found to model flashes adequately. Distance parameters were tested from 1,500 to 7,500 meters (m) in 500 m increments. Distance parameters of both 3,000 m and 4,000 m produced results in the plotting tool that were most representative of the physical behavior of lightning. Thus statistics were gathered for the most representative of these spatial and temporal criteria on the flash size and the polygon expansion distance in order to find the correct data distributions. The best fit curves for the LDAR polygon expansion frequency vs. distances for both the 3 kilometer (km) and 4 km distance threshold values were exponential decay functions and had R2 values of > 0.998, indicating good model fits. The equations of the best fit curves were then used to calculate a desired safety radius of 4 nmi for either 3 km or 4 km distance threshold criteria. The AMU analysis concludes the safe reduction of the 5 nmi lightning warning circles to 4 nmi should improve the operational impact by 36% if based on distance from the center of the property area being protected. If based on the edge of the property being protected, then the reduction is 4.5 nmi to 4 nmi and the operational impact is decreased by 21%. For the 6 nmi lightning warning circles, the recommended 4 nmi stand-off distance will result in a safe reduction of operational impact of 31% if based on the center of the area being protected, or 16% if based on the edge of the property.

Flash clustering algorithm↗

Object-Based Comparison of Data-Driven and Physics-Driven Satellite Estimates of Extreme Rainfall

The Global Precipitation Measurement (GPM) constellation of spaceborne sensors provides a variety of direct and indirect measurements of precipitation processes. Such observations can be employed to derive spatially and temporally consistent gridded precipitation estimates either via data-driven retrieval algorithms or by assimilation into physically based numerical weather models. We compare the data-driven Integrated Multisatellite Retrievals for GPM (IMERG) and the assimilation-enabled NASA-Unified Weather Research and Forecasting (NU-WRF) model against Stage IV reference precipitation for four major extreme rainfall events in the southeastern United States using an object-based analysis framework that decomposes gridded precipitation fields into storm objects. As an alternative to conventional ‘‘grid-by-grid analysis,’’ the object-based approach provides a promising way to diagnose spatial properties of storms, trace them through space and time, and connect their accuracy to storm types and input data sources. The evolution of two tropical cyclones are generally captured by IMERG and NU-WRF, while the less organized spatial patterns of two mesoscale convective systems pose challenges for both. NU-WRF rain rates are generally more accurate, while IMERG better captures storm location and shape. Both show higher skill in detecting large, intense storms compared to smaller, weaker storms. IMERG’s accuracy depends on the input microwave and infrared data sources; NU-WRF does not appear to exhibit this dependence. Findings highlight that an object-oriented view can provide deeper insights into satellite precipitation performance and that the satellite precipitation community should further explore the potential for ‘‘hybrid’’ data-driven and physics-driven estimates in order to make optimal usage of satellite observations.

extreme events↗

Laser Patterning Assisted Devitrification and Domain Engineering of Amorphous and Nanocrystalline Alloys

We have investigated laser-patterning and devitrification as a novel method to realize emergent properties in modified regions at the ribbon surface consisting of periodic localized laser spots thermally treated under rapid heating and cooling conditions. Fe-based amorphous ribbons were annealed for systematically varied laser power. Extremely high heating and cooling rates on the order of 10(exp 8)-10(exp 10)K/s have been estimated by finite element analysis simulations. Observations suggest surface melting followed by rapid solidification fast enough to quench and form an amorphous structure upon cooling. Diffusion of heat occurs from the laser irradiated surface region so that a finite volume of material surrounding this region rises in temperature above the crystallization temperature relevant for conventional isothermal annealing experiments. The underlying mechanism of laser annealing and consequences of heat transients involved are discussed in terms of impacts upon micro/nanostructure, residual stresses, and magnetic domain structure surrounding the laser irradiated region. The study illustrates the potential to exploit spatially optimized phase transformations in a scalable manufacturing process of amorphous and nanocrystalline alloys to locally access otherwise inaccessible extreme heating and cooling rates.

Amorphous ribbons↗

Oxygen Isotopic Composition of Refractory Inclusions from the Miller Range (MIL) 090019 Carbonaceous Chondrite

Introduction: Primitive meteorites contain Calcium-Aluminum-rich Inclusions (CAIs)that preserve the records of the earliest times in the Solar System. CAIs record O isotopic variations with time and/or location from solar (16O-rich) to planetary (16O-poor) compositions [e.g., 1, 2].However, CAIs were also affected by parent body processing to varying degrees. The goal of this work was to identify the processes that resulted in the fine-scale spatial variations in oxygen isotopic compositions within the most ancient Solar System solids. We report oxygen isotopic composition of CAIs from MIL 090019 CO3.1 carbonaceous chondrite. MIL 090019 contains a high abundance of CAIs showing mineralogical as well as textural variations [3]. Methods: We analyzed 10 CAIs with different mineralogical assemblages, classified as corundum-bearing, grossite-bearing, hibonite-bearing, melilite-bearing, anorthite-bearing inclusions and amoeboid olivine aggregates(AOA’s). The mineralogical and petrological characterization of CAIs was performed using the JOEL Hyperprobe 8530 electron microprobe at NASA JSC. Oxygen isotopic imaging of the CAIs was done using the Cameca NanoSIMS 50L ion microprobe at NASA JSC. We followed the analytical protocol described in [4]. O-isotopic maps of the CAI were acquired by rastering a ~3 pA primary Cs+beam at 16 keVover an area of 20 ×20μm2over a period of ~7 hours. Negative secondary ions of 16O−, 17O−, 18O−, 28Si−, 24Mg16O−, 27Al16O−, and 40Ca16O−were simultaneously acquired using electron multiplier detectors at a mass resolving power sufficient to resolve the 16OH−interference from the 17O−peak, where the contribution of 16OH−was <0.1%.An electron flood gun was used to mitigate sample charging during the analyses. We used San Carlos olivine and Madagascar hibonite as isotopic standards to correct for the instrumental mass fractionation. The O-isotopic ratios were corrected for the quasi simultaneous arrival (QSA) effect and the detector dead time. All reported errors are 1 sigma. Results: The MIL 090019 carbonaceous chondrite hosts refractory inclusions varying in their mineralogies and textures[2, 3]. We found the oxygen isotopic compositions of mineral phases in MIL 090019 CAIs show large variations with Δ17O values varying from -27 to 0‰. A corundum-bearing inclusion records isotopic variations with corundum, melilite, perovskite, and anorthite showing Δ17Ovalues of -20 ±2.5, -10.2 ± 6.5, -10.7 ± 1.3,and -1.2 ± 3.2‰ respectively. A grossite-hibonite-bearing inclusion also records O-isotopic heterogeneity, where grossite, hibonite, Mg-rich spinel, and melilite show -3.7 ± 2.7, -22.9 ± 2.5, -21.4 ± 2.6, and -17.3 ± 2.8‰ respectively, whereas perovskite grains record a heterogenous isotopic composition ranging from -22.6 to -13.9‰. A hibonite-bearing inclusion shows average Δ17Ο values of -17.6 ± 5.3 ‰ and -15.1 ± 4.8 ‰ for hibonite and spinel respectively. The two perovskite grains also show relatively 16O-poor composition (Δ17Ο = -11.8 ± 6.4 ‰ and -8.6 ± 5.2 ‰). Anorthite has ~0.1 wt% Na2O and ~0.52 wt% FeO and a Δ17Ο value of -7.2 ± 5.0 ‰, whereas diopside records a Δ17Ο value of -3.5 ± 5.0 ‰. A hibonite-spinel-rich inclusion contains spinel and hibonite that are16O-rich (Δ17Οvalues -21.3 ± 2.8‰ and -19.4 ± 3.0‰, respectively). Melilite shows heterogenous oxygen isotopic composition, with an inner 16O-rich region and an outer 16O-poor region separated by a sharp boundary, with a bulk Δ17Ο= -16.2 ± 2.1‰, whereas two perovskite grains are relatively 16O-poor (Δ17Ο= -13.2 ± 3.7‰ and -7.1 ± 3.4‰).A spinel-rich inclusion contains perovskite grains with Δ17Οranging from -27.0 to -22.8 ‰and spinel with average Δ17Οvalue of -21.4 ± 2.8 ‰. In a melilite and spinel-rich CAI, perovskite, spinel, diopside, melilite, and Al-Ti-rich pyroxene record Δ17Ο values of-26.9 ± 4.6‰, -22.4 ± 4.3‰,-23.4 ± 4.9, -19.3 ± 3.4, and -19.0 ± 4.3 ‰ respectively. Olivine and spinel components of 2 AOA’s record a 16O-rich composition with Δ17O~-23‰. Discussion: The coexistence of 16O-rich and 16O-poor minerals within CAIs has been attributed to differing degrees of O isotopic exchange, reflecting a wide range of O diffusion rates[5]. However, the O isotopic heterogeneity observed in these CAIs cannot be explained by oxygen diffusion in nebular or parent body settings alone. The isotopic imaging of CAIs from the MIL 090019 meteorite shows variations in the O isotopic composition recorded in their mineral components, suggesting that these CAIs record the oxygen isotopic heterogeneity in the nebular gas from which they condensed. The coexistence of 16O-rich and 16O-poor mineral components in the CAI-forming region suggests that the gas in this region was not well-mixed and consisted of distinct 16O-rich and 16O-poor gaseous reservoirs.

P Mane↗

Investigation of Microphysics and Precipitation for Atlantic Coast Threatening Snowstorms (IMPACTS): the 2022 Deployment

The Investigation of Microphysics and Precipitation for Atlantic Coast Threatening Snowstorms (IMPACTS) is a NASA-supported field campaign to study snowstorms particularly over the northeastern United States. Snowfall within these winter storms is often organized in banded structures that can vary on multiple scales. The goals of IMPACTS are to characterize the spatial and temporal scale of snowbands, understand the processes controlling the structure and evolution of the bands and apply this knowledge to improving remote sensing and numerical modeling. IMPACTS takes place over three winter seasons, 2020, 2022 and 2023. IMPACTS flies two aircraft: the ER-2 equipped with satellite-simulating remote sensing instruments; and the P-3 equipped with in situ microphysics probes and environmental instrumentation. Stationary and mobile radar facilities and mobile sounding teams round out the observational assets. The preliminary results from the 2022 deployment are highlighted here.

Lynn A McMurdie↗

Characterizing the Risk: Review of Sensorimotor Evidence and Research Roadmap

BACKGROUND: NASA’s Artemis program will take astronauts back to the lunar surface for the first time in almost 50 years. Despite the successes of the previous Apollo program, the Artemis missions will differ in duration, vehicle characteristics, and landing tasks that may exacerbate the risks to crew health/safety and mission objectives. NASA’s Human Research Program identifies the risk of altered sensorimotor/vestibular function impacting critical mission tasks as one of the top priority risks to lunar exploration missions. This session will review the existing evidence and remaining gaps in knowledge for the sensorimotor risk. DESCRIPTION: Alterations in sensorimotor processing during spaceflight can lead to motion sickness, spatial disorientation, and decrements in postural control, locomotion, and fine motor control during and following gravity-transitions. The risk of impairment is greatest during and soon after gravity-transitions, when performance decrements may have high operational impacts (e.g., manual landings, immediate egress following landing, and early extravehicular activities (EVAs)). Recent studies have specifically improved the risk characterization of changes in perception, motion sickness, postural and locomotor control, manual control, and fine-motor coordination. However, given the difficulty in obtaining measurements during and soon after gravity-transitions, evidence for initial decrements immediately following gravity-transitions remains limited. The most significant gaps in the risk include manual control ability around gravity-transitions, the incidence and severity of motion sickness during landings, and the ability to perform egress/EVAs soon after gravity-transition. To address these gaps, current research roadmaps leverage both spaceflight studies and ground-based analogs for risk characterization and countermeasure development/validation. DISCUSSION: This panel will further describe the current sensorimotor research strategies with an emphasis on the operational scenarios of manual control, crew egress, and EVA. The goal of this research is to accommodate the needs of the crew and facilitate human capabilities to ensure lunar mission success. This work will prepare NASA for successful Artemis missions and enable the next giant leap, the exploration of Mars.

Timothy Ryan Macaulay↗

Geometric Assessment of PlanetScope Imagery

Commercial companies such as Maxar, Planet Labs, and BlackSky have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. The high spatial resolution allows scientists to push studies to a fine scale such as monitoring agricultural growth experiments or detecting vehicles for traffic management. Scientists using these data need to know geolocation accuracy, band-to-band registration (BBR), and pixel footprint size to best determine appropriate applications as well as what extra steps they will need to take to use the data. Here, we find those key geometric properties for images from Planet Labs’ SuperDove constellation. Geolocation accuracy is assessed relative to WorldView images at globally distributed cities, band-to-band registration (BBR) is examined for every image we acquired (200+ images), and pixel footprint sizes are calculated from edge responses of the images over Cal/Val sites in China, India, or USA both near launch time and 1+ years after launch. We find that SuperDove geolocation is highly self-consistent with average global offsets among SuperDove images of 3.80 m (1.27 pixels). Despite this self-consistency, relative geolocation accuracy (with WorldView images as reference) varies by location from 3.20 m – 28.09 m mean offset. SuperDove BBR is sub-pixel and varies by band, with a mean radial offset relative to red band varying from 0.39 - 1.13 m. SuperDove image footprint size improves after 1+ years in orbit, with an average footprint size of 3.41 pixels (10.24 m) soon after launch and 3.23 pixels (9.7 m) 1+ years after launch. The BBR and self-consistency offsets are relatively small, given the large footprint sizes. A similarly extensive investigation is in progress for Planet Labs’ Dove-R series.

Alana G. Semple↗

Calculating Soil Wetness, Evapotranspiration and Carbon Cycle Processes Over Large Grid Areas Using a New Scaling Technique

Soil wetness typically shows great spatial variability over the length scales of general circulation model (GCM) grid areas (approx 100 km ), and the functions relating evapotranspiration and photosynthetic rate to local-scale (approx 1 m) soil wetness are highly non-linear. Soil respiration is also highly dependent on very small-scale variations in soil wetness. We therefore expect significant inaccuracies whenever we insert a single grid area-average soil wetness value into a function to calculate any of these rates for the grid area. For the particular case of evapotranspiration., this method - use of a grid-averaged soil wetness value - can also provoke severe oscillations in the evapotranspiration rate and soil wetness under some conditions. A method is presented whereby the probability distribution timction(pdf) for soil wetness within a grid area is represented by binning. and numerical integration of the binned pdf is performed to provide a spatially-integrated wetness stress term for the whole grid area, which then permits calculation of grid area fluxes in a single operation. The method is very accurate when 10 or more bins are used, can deal realistically with spatially variable precipitation, conserves moisture exactly and allows for precise modification of the soil wetness pdf after every time step. The method could also be applied to other ecological problems where small-scale processes must be area-integrated, or upscaled, to estimate fluxes over large areas, for example in treatments of the terrestrial carbon budget or trace gas generation.

Sellers, Piers↗

Probing the Sun with Imaging Spectrographs

EUV and X-ray images of the Sun have revolutionized our understanding of our closest star. With them, we can probe the morphology and temperature structure of the solar atmosphere and see how they evolve as a function of space and time. However, image data cannot be used to determine line-of-sight velocities, abundances, or densities. This information is required to calculate the energy budget of eruptive events, provide boundary conditions for global solar models, and explore fundamental processes occurring in the solar atmosphere. For those diagnostics, we require spectroscopy. Because the structures on the Sun are extended sources, most modern-day spectrometers observe the Sun through long narrow slits. Two-dimensional, spectrally pure solar images with velocity, abundance, and density information are built up by stepping the slit over regions of interest. This method implies that two-dimensional information is highly limited by cadence and the temporal evolution and spatial structure of these parameters can never be truly separated. Both spatial and spectral information can be obtained in a single snapshot with slitless spectrometers, which were often used in the 1950-1970s, but were abandoned due to the difficulty of unfolding the overlapping spatial and spectral information. Thanks to advances in computer processing speeds and machine learning algorithms, there have been several techniques developed to complete the spatial/spectral unfolding, unlocking the full capability of slitless spectrometers for solar observations. The goal of this talk is to give an overview of the capability of such instruments, including recent results from a sounding rocket flight, and demonstrate their usefulness in the next decade of solar observatories and beyond.

Amy Winebarger↗

Probing the Sun with Imaging Spectrographs

EUV and X-ray images of the Sun have revolutionized our understanding of our closest star. With them, we can probe the morphology and temperature structure of the solar atmosphere and see how they evolve as a function of space and time. However, image data cannot be used to determine line-of-sight velocities, abundances, or densities. This information is required to calculate the energy budget of eruptive events, provide boundary conditions for global solar models, and explore fundamental processes occurring in the solar atmosphere. For those diagnostics, we require spectroscopy. Because the structures on the Sun are extended sources, most modern-day spectrometers observe the Sun through long narrow slits. Two-dimensional, spectrally pure solar images with velocity, abundance, and density information are built up by stepping the slit over regions of interest. This method implies that two-dimensional information is highly limited by cadence and the temporal evolution and spatial structure of these parameters can never be truly separated. Both spatial and spectral information can be obtained in a single snapshot with slitless spectrometers, which were often used in the 1950-1970s, but were abandoned due to the difficulty of unfolding the overlapping spatial and spectral information. Thanks to advances in computer processing speeds and machine learning algorithms, there have been several techniques developed to complete the spatial/spectral unfolding, unlocking the full capability of slitless spectrometers for solar observations. The goal of this talk is to give an overview of the capability of such instruments, including recent results from a sounding rocket flight, and demonstrate their usefulness in the next decade of solar observatories and beyond.

Amy Winebarger↗

Probing the Sun with Imaging Spectrographs

EUV and X-ray images of the Sun have revolutionized our understanding of our closest star. With them, we can probe the structure of the solar atmosphere and see how they evolve as a function of space and time. However, image data cannot be used to determine line-of-sight velocities, abundances, or densities. This information is required to calculate the energy budget of eruptive events, provide boundary conditions for global solar models, and explore fundamental processes occurring in the solar atmosphere. For those diagnostics, we require spectroscopy. Because the structures on the Sun are extended sources, most modern-day spectrometers observe the Sun through long narrow slits. Two-dimensional, spectrally pure solar images with velocity, abundance, and density information are built up by stepping the slit over regions of interest. This method implies that two-dimensional information is highly limited by cadence and the temporal evolution and spatial structure of these parameters can never be truly separated. Both spatial and spectral information can be obtained in a single snapshot with slitless spectrometers, which were often used in the 1950-1970s, but were abandoned due to the difficulty of unfolding the overlapping spatial and spectral information. Thanks to advances in computer processing speeds and machine learning algorithms, there have been several techniques developed to complete the spatial/spectral unfolding, unlocking the full capability of slitless spectrometers for solar observations. The goal of this talk is to give an overview of the capability of such instruments and demonstrate their usefulness in the next decade of solar observatories and beyond.

Amy Winebarger↗

Spatially Characterizing Effective Timber Supply

The structure of a computer-oriented cartographic model for assessing roundwood supply for generation of base load electricity is discussed. The model provides an analytical procedure for coupling spatial information of harvesting economics and owner willingness to sell stumpages. Supply is characterized in terms of standing timber; of accessibility considering various harvesting and hauling factors; and of availability as affected by ownership and residential patterns. Factors governing accessibility to timber include effective harvesting distance to haulic roads as modified by barriers and slopes. Haul distance is expressed in units that take into account the relative ease of travel along various road types to a central processing facility. Areas of accessible timber are grouped into spatial units, termed 'timbersheds', of common access to particular haul road segments that belong to unique 'transport zones'. Timber availability considerations include size of ownership parcels, housing density and excluded areas. The analysis techniques are demonstrated for a cartographic data base in western Massachusetts.

Berry, J. K.↗

Probing the Sun with Imaging Spectrographs

EUV and X-ray images of the Sun have revolutionized our understanding of our closest star. With them, we can probe the morphology and temperature structure of the solar atmosphere and see how they evolve as a function of space and time. However, image data cannot be used to determine line-of-sight velocities, abundances, or densities. This information is required to calculate the energy budget of eruptive events, provide boundary conditions for global solar models, and explore fundamental processes occurring in the solar atmosphere. For those diagnostics, we require spectroscopy. Because the structures on the Sun are extended sources, most modern-day spectrographs observe the Sun through long narrow slits. Two-dimensional, spectrally pure solar images with velocity, abundance, and density information are built up by stepping the slit over regions of interest. This mode of operation implies that two-dimensional information is highly limited by cadence and the temporal evolution and spatial structure of these parameters can never be truly separated. Both spatial and spectral information can be obtained in a single snapshot with slitless spectrographs, which were often used in the 1950-1970s, but were abandoned due to the difficulty of unfolding the overlapping spatial and spectral information. Thanks to advances in computer processing speeds and machine learning algorithms, there have been several techniques developed to complete the spatial/spectral unfolding, unlocking the full capability of slitless spectrographs for solar observations. The goal of this talk is to give a broad overview of the capability of such instruments and demonstrate their usefulness in the next decade of solar observatories and beyond.

Amy Winebarger↗

Single beam synthesis from thinned arrays

Radio astronomers have investigated spatial frequencies and their relationship to apertures with the objective to improve the resolution in radio observations. Welch (1965) has related Fourier transform theory developed for linear communications to aperture design problems, while Fakley (1959) has conducted a comparison between the performances of a time-averaged product array and an intraclass correlator. The present investigation is concerned with an approach which resembles very closely the intraclass correlator system considered by Fakley. A description is presented of a process whereby a thinned array of elements samples selected spatial frequencies from a uniform signal wave front incident on the array. The spatial frequencies are used to generate a set of synthetic spatial frequencies which behave as though they had been sampled by a fully filled array. Beam formation is obtained by summing the set of synthetic spatial frequencies.

Kaiser, J. A., Jr.↗

Spiral waves are stable in discrete element models of two-dimensional homogeneous excitable media

The spontaneous breakup of a single spiral wave of excitation into a turbulent wave pattern has been observed in both discrete element models and continuous reaction-diffusion models of spatially homogeneous 2D excitable media. These results have attracted considerable interest, since spiral breakup is thought to be an important mechanism of transition from the heart rhythm disturbance ventricular tachycardia to the fatal arrhythmia ventricular fibrillation. It is not known whether this process can occur in the absence of disease-induced spatial heterogeneity of the electrical properties of the ventricular tissue. Candidate mechanisms for spiral breakup in uniform 2D media have emerged, but the physical validity of the mechanisms and their applicability to myocardium require further scrutiny. In this letter, we examine the computer simulation results obtained in two discrete element models and show that the instability of each spiral is an artifact resulting from an unphysical dependence of wave speed on wave front curvature in the medium. We conclude that spiral breakup does not occur in these two models at the specified parameter values and that great care must be exercised in the representation of a continuous excitable medium via discrete elements.

NASA Discipline Cardiopulmonary↗

Computer program for analysis of split-Stirling-cycle cryogenic coolers

A computer program for predicting the detailed thermodynamic performance of split-Stirling-cycle refrigerators has been developed. The mathematical model includes the refrigerator cold head, free-displacer/regenerator, gas transfer line, and provision for modeling a mechanical or thermal compressor. To allow for dynamic processes (such as aerodynamic friction and heat transfer) temperature, pressure, and mass flow rate are varied by sub-dividing the refrigerator into an appropriate number of fluid and structural control volumes. Of special importance to modeling of cryogenic coolers is the inclusion of real gas properties, and allowance for variation of thermo-physical properties such as thermal conductivities, specific heats and viscosities, with temperature and/or pressure. The resulting model, therefore, comprehensively simulates the split-cycle cooler both spatially and temporally by reflecting the effects of dynamic processes and real material properties.

Brown, M. T.↗

Otolith-Canal Convergence in Vestibular Nuclei Neurons

During manned spaceflight, acute vestibular disturbances often occur, leading to physical duress and a loss of performance. Vestibular adaptation to the weightless environment follows within two to three days yet the mechanisms responsible for the disturbance and subsequent adaptation are still unknown In order to understand vestibular system function in space and normal earth conditions the basic physiological mechanisms of vestibular information co coding must be determined. Information processing regarding head movement and head position with respect to gravity takes place in the vestibular nuclei neurons that receive signals From the semicircular canals and otolith organs in the vestibular labyrinth. These neurons must synthesize the information into a coded output signal that provides for the head and eye movement reflexes as well as the conscious perception of the body in three-dimensional space The current investigation will for the first time. determine how the vestibular nuclei neurons quantitatively synthesize afferent information from the different linear and angular acceleration receptors in the vestibular labyrinths into an integrated output signal. During the second year of funding, progress on the current project has been focused on the anatomical orientation of semicircular canals and the spatial orientation of the innervating afferent responses. This information is necessary in order to understand how vestibular nuclei neurons process the incoming afferent spatial signals particularly with the convergent otolith afferent signals that are also spatially distributed Since information from the vestibular nuclei is presented to different brain regions associated with differing reflexive and sensory functions it is important to understand the computational mechanisms used by vestibular neurons to produce the appropriate output signal.

Dickman, J. David↗