Potential Applications of Active Antenna Technologies for Emerging NASA Space Communications Scenarios
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Tests have been conducted concerning the active control of the potentials of the geosynchronous satellites ATS-5 and ATS-6. The ATS-5 tests show that a simple electron emitter can be used to reduce the magnitude of the potential of a spacecraft which has been charged negatively by the environment. The ATS-6 ion thruster had also a pronounced effect on the potential barrier. In this case, the flux of high-energy primary ions and of low-charge exchange ions produces a space-charge neutralization effect which the electron gun alone cannot achieve.
Most fast coronal mass ejections (CMEs) originate from solar active regions (ARs). Non-potentiality of ARs plausibly determines the speed of CMEs in the outer corona. Several other unexplored parameters might be important as well. To find out the relation between the intial speed of CMEs and the non-potentiality of source ARs, we identified over a hundred of CMEs with source ARs via their co-produced flares. The speed of the CMEs are collected from the SOHO LASCO CME catalog. We have used vector magnetograms obtained with HMI/SDO, to evaluate various magnetic non-potentiality parameters, e.g. magnetic free-energy proxies, twist, shear angle, signed shear angle, net current etc. We have also included several other parameters e.g. total unsigned flux, magnetic area of ARs, area of sunspots, to investigate their correlation, if any, with the initial speeds of CMEs. Our preliminary results show that the ARs with larger non-potentiality and area produce faster CMEs but they can also produce slow ones. The ARs with lesser non-potentiality and area generally produce only slower CMEs.
The potential applications of active controls are examined for improving the characteristics of transport type aircraft used in short-haul service ( 1,000-kilometer range capability). The types of aircraft to meet future needs (quiet operation, congestion alleviation, fuel conservation, operating economy, and traveler acceptance) are identified as helicopters for shorter stage lengths and fixed wing aircraft of reduced field-length capability for longer stage lengths. Likely uses for active controls for these aircraft are examined regarding payoffs which can be expected and problems and constraints which must be dealt with. Uses showing significant benefits include augmented stability and control, gust-load alleviation, and ride smoothing. Gust-load alleviation is particularly effective for low-wing-loading aircraft employing conventional lift. Ride-smoothing systems are indicated to be the furthest advanced and ready for production commitment for those applications where they can be shown to have payoff.
Active noise control technology offers the potential for weight-efficient aircraft interior noise reduction, particularly for propeller aircraft. However, there is little information on how passengers respond to this type of interior noise control. This paper presents results of two experiments that use sound quality engineering practices to determine the subjective effectiveness of hypothetical active noise control (ANC) systems in a range of propeller aircraft. The two experiments differed by the type of judgments made by the subjects: pair comparisons based on preference in the first and numerical category scaling of noisiness in the second. Although the results of the two experiments were in general agreement that the hypothetical active control measures improved the interior noise environments, the pair comparison method appears to be more sensitive to subtle changes in the characteristics of the sounds which are related to passenger preference. The reductions in subjective response due to the ANC conditions were predicted with reasonable accuracy by reductions in measured loudness level. Inclusion of corrections for the sound quality characteristics of tonality and fluctuation strength in multiple regression models improved the prediction of the ANC effects.
Space-Weather MDI Active Region Patches (SMARPs) and Space-Weather HMI Active Region Patches (SHARPs) are two recently developed data products, which have been used for solar flare prediction studies. The present work is an effort to expand the application of SMARP and SHARP summary heliomagnetic parameters to the forecasting of solar flares. A new data product was derived by filtering, rescaling, and merging the SMARP and SHARP summary parameter data series, which were further converted into two-dimensional arrays by selecting time slices corresponding to R-value maxima, where R-value is a measure of the unsigned magnetic flux near polarity inversion lines. The resulting combined MDI-HMI time series currently span the period between April 4, 1996 and December 13, 2022, and can be extended to a more recent date, providing an opportunity to correlate and compare them with other solar activity parameters, such as the daily solar flare index, which is computed as a sum of the product of GOES X-ray flare magnitude and flare duration, for all M- and X-class flares during a day. Preliminary results demonstrate a significant overall correlation, with Pearson coefficients between 0.339 and 0.627. In addition, an oscillating pattern is seen in the daily-averaged sliding-window correlation coefficient. Time-lagged cross-correlation indicates that a leader-follower dynamic exists in some parameters, especially R-value, where they lead the flare index by at least several days, which may have potential for further application in space weather forecasting.
The concept of activated recombination of atomic species on surfaces can explain the production of vibrationally and translationally excited desorbed molecular species. Equilibrium statistical mechanics predicts that the molecular quantum state distributions of desorbing molecules is a function of surface temperature only when the adsorption probability is unity and independent of initial collision conditions. In most cases, the adsorption probability is dependent upon initial conditions such as collision energy or internal quantum state distribution of impinging molecules. From detailed balance, such dynamical behavior is reflected in the internal quantum state distribution of the desorbing molecule. This concept, activated recombinative desorption, may offer a common thread in proposed mechanisms of spacecraft glow. Using molecular beam techniques and equipment available at Los Alamos, which includes a high translational energy 0-atom beam source, mass spectrometric detection of desorbed species, chemiluminescence/laser induced fluorescence detection of electronic and vibrationally excited reaction products, and Auger detection of surface adsorbed reaction products, a fundamental study of the gas surface chemistry underlying the glow process is proposed.
Developing an automated active learning framework for Neural Network Potentials, focusing on accurately simulating bond-breaking in hexane chains through steered molecular dynamics sampling and assessing model transferability.
Evoked potential and microelectrical analysis of sensory activity within cerebellum
Nitrogenous fertilizers provide a short-lived benefit to crops in agroecosystems, but stimulate nitrification and denitrification, processes that result in nitrate pollution, N2O production, and reduced soil fertility. Recent advances in plant microbiome science suggest that genetic variation in plants can modulate the composition and activity of rhizosphere N-cycling microorganisms. Here we attempted to determine whether genetic variation exists in Zea mays for the ability to influence the rhizosphere nitrifier and denitrifier microbiome under “real-world” conventional agricultural conditions. To capture an extensive amount of genetic diversity within maize we grew and sampled the rhizosphere microbiome of a diversity panel of germplasm that included ex-PVP inbreds ( Z. mays ssp. mays ), ex-PVP hybrids ( Z. mays ssp. may s), and teosinte ( Z. mays ssp. mexicana and Z. mays ssp. parviglumis ). From these samples, we characterized the microbiome, a suite of microbial genes involved in nitrification and denitrification and carried out N-cycling potential assays. Here we are showing that populations/genotypes of a single species can vary in their ecological interaction with denitrifers and nitrifers. Some hybrid and teosinte genotypes supported microbial communities with lower potential nitrification and potential denitrification activity in the rhizosphere, while inbred genotypes stimulated/did not inhibit these N-cycling activities. These potential differences translated to functional differences in N2O fluxes, with teosinte plots producing less GHG than maize plots. Taken together, these results suggest that Zea genetic variation can lead to changes in N-cycling processes that result in N leaching and N2O production, and thereby are selectable targets for crop improvement. Understanding the underlying genetic variation contributing to belowground microbiome N-cycling into our conventional agricultural system could be useful for sustainability.
A remote sensing-based system has been developed to characterize the potential for rainfall-triggered landslides across the globe in near real-time. The Landslide Hazard Assessment for Situational Awareness (LHASA) model uses a decision tree framework to combine a static susceptibility map derived from information on slope, rock characteristics, forest loss, distance to fault zones and distance to road networks with satellite precipitation estimates from the Global Precipitation Measurement (GPM) mission. Since 2016, the LHASA model has been providing near real-time and retrospective estimates of potential landslide activity. Results of this work are available at https://landslides.nasa.gov. In order to advance LHASA’s capabilities to characterize landslide hazards and impacts dynamically, we have implemented a new approach that leverages machine learning, new parameters, and new inventories. LHASA 2.0 uses the XGBoost machine learning model to bring in dynamic variables as well as additional static variables to better represent landslide hazard globally. Global rainfall forecasts are also being evaluated to provide a 1-3 day forecast of potential landslide activity. Additional factors such as recent seismicity and burned areas are also being considered to represent the preconditioning or changing interactions with subsequent rainfall over affected areas. A series of parameters are being tested within this structure using NASA’s Global Landslide Catalog as well as many other event-based and multi-temporal inventories mapped by the project team or provided by project partners. In addition to estimates of landslide hazard, LHASA Version 2 will incorporate dynamic estimates of exposure including population, roads and infrastructure to highlight the potential impacts that rainfall-triggered landslides. The ultimate goal of LHASA Version 2.0 is to approximate the relative probabilities of landslide hazard and exposure across different space and time scales to inform hazard assessment retrospectively over the past 20 years, in near real-time, and in the future. In addition to the hazard. This presentation will outline the new activities for LHASA Version 2.0 and present some next steps for this system.
The potential benefits of an IPACS system compared to NiCd and/or Regen Fuel Cell systems are summarized. The benefits are: (1) significant life cycle cost savings; (2) total weight to orbit savings (30 yrs) as much as 10 times; (3) end to end efficiency increase results in approximately 10 kW reduction in array size(6%); (4) motor/generator controller regulation during discharge simplifies distribution system; and (5) momentum stored for attitude control increased by 4 times.
Potential sources for the central power in AGN are examined. The continuum, emission line profiles, and time variability and broad emission line region for AGN are analyzed. The supermassive black hole hypothesis, the supermassive magnetized core model of Kundt (1978), and the model of Stoner and Ptak (1984) in which the supermassive stars maintain a kind of long-term quasi-stability, but accretion is balanced by mass loss and spherical bursts rather than in jets are considered. It is argued that the hypothesis that the supermassive blackholes are the central engines for AGN is based on theoretical principles; however, AGN emission line profiles and variability suggest a spherical geometry for the observed components of these engines. Also the supermassive black hole models do not account for all the AGN observations.
Background and aims: Peat-accumulating wetlands have undulating surfaces of raised areas (hummocks) and depressions (hollows). Hummock-hollow microtopography in relation to the water table influences the distribution of plant species, root density, and microbial community composition, which could in turn alter carbon (C) and nitrogen (N) cycling within peatlands. We used paired hummock and hollow cores from a boreal, forested peatland to assess how microtopography influences peatland microbial function and, in turn, ecosystem C and N cycling. Methods: The peat was analyzed for microbial biomass and potential enzyme activity in 10 cm depth increments relative to the water table, resulting in two increments for hollows and three for hummocks, which has a raised increment above the water table. Results: Across hummocks and hollows, microbial C and N and fungal biomass generally decreased with depth from the peat surface. In contrast, potential enzyme activity often increased with depth, but this varied within enzyme functional groups according to topography, depth, or both. The potential enzyme activity of C-N degrading peptidases, for example, differed across the five topography × depth increments with the lowest rate in the aerated hummocks. Hummocks compose approximately 66% of the land area at our study site and would therefore underestimate C turnover by an average of 25% if solely used to extrapolate patterns across a forested bog. Conclusion: In conclusion, our results suggest that asynchrony in C and N cycling across the undulating surface of forested peatlands impacts our ability to accurately predict biogeochemical cycling across this important ecosystem.
Abstract Machine learning surrogate models for quantum mechanical simulations have enabled the field to efficiently and accurately study material and molecular systems. Developed models typically rely on a substantial amount of data to make reliable predictions of the potential energy landscape or careful active learning (AL) and uncertainty estimates. When starting with small datasets, convergence of AL approaches is a major outstanding challenge which has limited most demonstrations to online AL. In this work we demonstrate a Δ-machine learning (ML) approach that enables stable convergence in offline AL strategies by avoiding unphysical configurations with initial datasets as little as a single data point. We demonstrate our framework’s capabilities on a structural relaxation, transition state calculation, and molecular dynamics simulation, with the number of first principle calculations being cut down anywhere from 70%–90%. The approach is incorporated and developed alongside AMP torch , an open-source ML potential package, along with interactive Google Colab notebook examples.
Arabia Terra is a unique area on Mars in that it is the only major, equatorial region characterized by high abundances of near-surface water (as measured by gamma ray and neutron spectroscopy). Vernal Crater is a 55 km-diameter structure in southwest Arabia Terra, centered at 6 N, 355.5 E. The crater includes layered sediments, potential remnants of fluvio-lacustrine activity, and indications of aeolian processes. Regional considerations, along with new THEMIS and MOC data, are being assessed to gain insight into the significance of the geomorphic units within Vernal Crater and the geologic history of SW Arabia Terra.
Changes in precipitation represent a major effect of climate change on tropical forests, which contain some of the earth’s largest terrestrial carbon (C) stocks. Such changes are expected to influence microbes, nutrients, and the fate of C in tropical forest soils. To explore this, we assessed soil microbial biomass, potential extracellular enzyme activities, and nutrient availability in a partial throughfall exclusion experiment in four seasonal lowland tropical humid forests in Panama with wide variation in precipitation and soil fertility. We hypothesized that throughfall exclusion would reduce microbial biomass and activity and accentuate dry season soil nutrient accumulation, with larger effects in wetter, less droughtresistant forests. We observed a baseline seasonal pattern of decreased microbial biomass and increased extractable dissolved organic C (DOC), total dissolved nitrogen (TDN), nitrate (NO 3 – ), and resinextractable phosphorus (P) in the dry season, with the strongest patterns for nitrogen (N). However, potential enzyme activities showed no consistent seasonality. In line with seasonal drying, throughfall exclusion decreased soil microbial biomass in the wet season and increased TDN and NO 3 – , especially in the dry season. In contrast to seasonal drying, throughfall exclusion decreased DOC and did not affect resinextractable P, but slightly decreased potential phosphatase activities. Potential enzyme activities varied among sites and sampling times, but did not explain much variation in microbial biomass or substrate availability. We conclude that reduced rainfall in tropical forests might accentuate some dry season patterns, like reductions in microbial biomass and accumulation of extractable nutrients. However, our data also suggest new patterns, like reduced inputs of DOC to soils with drying, which could have cascading effects on soil ecological function and C storage.