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At least 199 records · Page 11

Passive Fluid Transport in Microgravity Environments for the Stabilization of Rotating Spacecrafts

Rotating spacecraft offers the potential to create artificial gravity for extended space missions. However, designing a guidance and control system for such vehicles involves complex considerations. This paper examines a vehicle segmented into three parts, with the propulsion unit positioned at the vehicle’s center of mass. The vehicle must maintain stability around this central point, even under atypical conditions. Consequently, a durable and passive spin stabilization system is essential, requiring the passive transport of fluids. A combined system consisting of microcapillary bundles and hydraulic ram pumps is explored to transport fluids without any external energy added to the system. The dynamics of such a system are investigated, establishing performance and control limitations, and developing a control strategy predicated on the fluid dynamics between the segments. A model of the system is developed to validate the approach, showing that passive stabilization is possible, however, not as effective as an active stabilization system. Additionally, the model can be expanded for broader applications, including mass redistribution, a theoretical fluid ring, and three axis rotating systems.

Dynamics↗

Challenges in Remote-Sensing of Hail: Examining the Performance and Biases of Satellite Hail Retrievals Using Aqua MODIS Visible/IR and AMSR-E Passive-Microwave Observations

Hail poses threats to myriad aspects of human life and society, infrastructure, and agriculture. Scientifically, hail can often cause large errors in precipitation retrieval and estimation, posing challenges to establishing the current climatology of severe storms and their future trend in a changing Earth system. Fortunately, hailstorms exhibit distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Approaches that leverage these signatures, however, are not without their pitfalls,: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. Large horizontal areas of smaller scatterers may also meaningfully lower the brightness temperatures, especially if they are able to occupy large portions of the footprint. Radiative transfer simulations show that low frequencies such as 19- and 37-GHz can be scattered to extremely low brightness temperatures by high concentrations of smaller (graupel-sized) ice scatterers, especially in larger features that are more likely to occupy the footprint, which may cause climatologies to overestimate the frequency severe hail. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together, pairing AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis over CONUS, and then explore the performance and challenges of the algorithm when we expand outside the United States into six different geographical regimes throughout the Aqua domain.

Sarah D Bang↗

Assessing the Adhesion of Nanofibrous PVDF-HFP as Passive Thermal Control Coatings for the Extraterrestrial Storage of Cryogenic Propellants

Cryogenic propellant passive thermal management techniques in space are essential complements to active thermal management methods, helping reduce absolute dependence on the latter. Particularly, materials with superior optical properties (high solar reflectance and infrared emittance) would be beneficial for passive thermal control to reject most of the incident solar radiation and enhance thermal emission from the storage tank, leading to self-cooling. We developed a nanofibrous, porous passive thermal control material by electrospinning polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) co-polymer onto an aluminum foil substrate. The material exhibits a very high solar reflectance (>99%) and infrared emittance (~86%) when characterized in the ultraviolet-visible-near infrared and mid-infrared wavelengths. This study focuses on the adhesion of the nanofibrous PVDF-HFP to the substrate. We incorporated in-lab fabricated and commercial adhesives, under normal room conditions, between the nanofibers and the aluminum foil substrate to improve their adhesion. Some samples were also exposed to space-like conditions – vacuum and thermal cycling, to investigate their effects on the strengths of adhesives. Subsequently, adhesion peel tests were conducted on all the samples to assess the peel strengths of the bonds. Peel test strengths after space environment conditioning of the adhesives were generally higher than those observed in the pristine, unaged samples. The results are discussed in this study.

Chieloka Ibekwe↗

The Soil Moisture Active Passive (SMAP): Radar Measurements at High Latitudes and of Freeze/Thaw State

The Soil Moisture Active/Passive (SMAP) mission is scheduled for a late 2014 launch date. The mission will use both active radar and passive radiometer instruments at L-Band. In order to achieve a wide swath at sufficiently high resolution for both active and passive channels, an instrument architecture that uses a large rotating reflector is employed. In this paper, a focus will be places on the radar design and associated data products at high latitudes. The radar will employ synthetic-aperture processing to achieve a "moderate" resolution dual-pol product over a 1000 km swath. Because the radar is operating continuously, very frequent temporal coverage will be achieved at high latitudes. This data will be used, among other things, to produce a surface freeze/thaw state data product.

Earth observing↗

Electrospun Silica Nanofibers as Passive Thermal Control Materials for the Extreme Environment of Low Earth Orbit

Effective thermal management is crucial for maintaining spacecraft and onboard systems at optimal temperatures, ensuring their longevity in space missions. Passive thermal management is particularly promising due to its lower power consumption compared to active systems. This study focuses on developing materials with low solar absorptance and large thermal emittance to facilitate self-cooling under the harsh thermal conditions of space. We employ electrospinning, a nano/micro-manufacturing technique, to create a lightweight, fibrous thermal control material from silica (SiO 2 ). Using scanning electron microscopy (SEM), we examine the nanoporous structure of the electrospun material. Its optical properties, including reflectance, transmittance, and absorptance across ultraviolet, visible, and infrared wavelengths, are assessed using spectrometers interfaced with integrating spheres. To test durability in space, we conduct high temperature endurance and ultraviolet resistance tests to observe changes in optical properties of the materials and evaluate their performance in low Earth orbit (LEO). We also compare the material's solar reflectance and thermal emittance to existing spacecraft materials. The findings suggest that electrospun silica nanofibers presents a new paradigm for passive thermal control in space applications.

thermal emittance↗

Electrolyte and Electrode Passivation for Thin Film Batteries

Passivation films for thin film batteries have been prepared and the conductivity and voltage stability window have been measured. Thin films of Li2CO3 have a large voltage stability window of 4.8V, which facilitates the use of this film as a passivation at both the lithium anode-electrolyte interface at high cathodic potentials.

passivation thin film batteries↗

Reliability of Sn/Pb and Lead-Free (SnAgCu) Solders of Surface Mounted Miniaturized Passive Components for Extreme Temperature (-185 C to +125 C) Space Missions

Surface mount electronic package test boards have been assembled using tin/lead (Sn/Pb) and lead-free (Pb-free or SnAgCu or SAC305) solders. The soldered surface mount packages include ball grid arrays (BGA), flat packs, various sizes of passive chip components, etc. They have been optically inspected after assembly and subsequently subjected to extreme temperature thermal cycling to assess their reliability or future deep space, long-term, extreme temperature environmental missions. In this study, the employed temperature range (-185oC to +125oC) covers military specifications (-55oC to +100oC), extreme old Martian (-120oC to +115oC), asteroid Nereus (-180oC to +25oC) and JUNO (-150oC to +120oC) environments. The boards were inspected at room temperature and at various intervals as a function of extreme temperature thermal cycling and bake duration. Electrical resistance measurements made at room temperature are reported and the tests to date have shown some change in resistance as a function of extreme temperature thermal cycling and some showed increase in resistance. However, the change in interconnect resistance becomes more noticeable with increasing number of thermal cycles. Further research work will be carried out to understand the reliability of packages under extreme temperature applications (-185oC to +125oC) via continuously monitoring the daisy chain resistance for BGA, Flat-packs, lead less chip packages, etc. This paper will describe the experimental reliability results of miniaturized passive components (01005, 0201, 0402, 0603, 0805, and 1206) assembled using surface mounting processes with tin-lead and lead-free solder alloys under extreme temperature environments.

extreme temperatures,↗

A Long-Term and Reproducible Passive Microwave Sea Ice Concentration Data Record for Climate Studies and Monitoring

A long-term, consistent, and reproducible satellite-based passive microwave sea ice concentration climate data record (CDR) is available for climate studies, monitoring, and model validation with an initial operation capability (IOC). The daily and monthly sea ice concentration data are on the National Snow and Ice Data Center (NSIDC) polar stereographic grid with nominal 25 km × 25 km grid cells in both the Southern and Northern Hemisphere polar regions from 9 July 1987 to 31 December 2007. The data files are available in the NetCDF data format at http://nsidc.org/data/g02202.html and archived by the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA) under the satellite climate data record program (http://www.ncdc.noaa.gov/cdr/operationalcdrs.html). The description and basic characteristics of the NOAA/NSIDC passive microwave sea ice concentration CDR are presented here. The CDR provides similar spatial and temporal variability as the heritage products to the user communities with the additional documentation, traceability, and reproducibility that meet current standards and guidelines for climate data records. The data set, along with detailed data processing steps and error source information, can be found at http://dx.doi.org/10.7265/N5B56GN3.

monitoring↗

The Planned Soil Moisture Active Passive (SMAP) Mission L-Band Radar/Radiometer Instrument

The Soil Moisture Active/Passive (SMAP) mission is a NASA mission identified by the NRC 'decadal survey' to measure both soil moisture and freeze/thaw state from space. The mission will use both active radar and passive radiometer instruments at L-Band. In order to achieve a wide swath at sufficiently high resolution for both active and passive channels, an instrument architecture that uses a large rotating reflector is employed. The instrument system has completed the preliminary design review (PDR) stage, and detailed instrument design has begun. In addition to providing an overview of the instrument design, two recent design modifications are discussed: 1) The addition of active thermal control to the instrument spun side to provide a more stable, settable thermal environment for the radiometer electronics, and 2) A 'sequential transmit' strategy for the two radar polarization channels which allows a single high-power amplifier to be used.

radiometer↗

Verification of a New NOAA/NSIDC Passive Microwave Sea-Ice Concentration Climate Record

A new satellite-based passive microwave sea-ice concentration product developed for the National Oceanic and Atmospheric Administration (NOAA)Climate Data Record (CDR) programme is evaluated via comparison with other passive microwave-derived estimates. The new product leverages two well-established concentration algorithms, known as the NASA Team and Bootstrap, both developed at and produced by the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC). The sea ice estimates compare well with similar GSFC products while also fulfilling all NOAA CDR initial operation capability (IOC) requirements, including (1) self describing file format, (2) ISO 19115-2 compliant collection-level metadata,(3) Climate and Forecast (CF) compliant file-level metadata, (4) grid-cell level metadata (data quality fields), (5) fully automated and reproducible processing and (6) open online access to full documentation with version control, including source code and an algorithm theoretical basic document. The primary limitations of the GSFC products are lack of metadata and use of untracked manual corrections to the output fields. Smaller differences occur from minor variations in processing methods by the National Snow and Ice Data Center (for the CDR fields) and NASA (for the GSFC fields). The CDR concentrations do have some differences from the constituent GSFC concentrations, but trends and variability are not substantially different.

Passive Microwave↗

Development and Validation of The SMAP Enhanced Passive Soil Moisture Product

Since the beginning of its routine science operation in March 2015, the NASA SMAP observatory has been returning interference-mitigated brightness temperature observations at L-band (1.41 GHz) frequency from space. The resulting data enable frequent global mapping of soil moisture with a retrieval uncertainty below 0.040 cu m/cu m at a 36 km spatial scale. This paper describes the development and validation of an enhanced version of the current standard soil moisture product. Compared with the standard product that is posted on a 36 km grid, the new enhanced product is posted on a 9 km grid. Derived from the same time-ordered brightness temperature observations that feed the current standard passive soil moisture product, the enhanced passive soil moisture product leverages on the Backus-Gilbert optimal interpolation technique that more fully utilizes the additional information from the original radiometer observations to achieve global mapping of soil moisture with enhanced clarity. The resulting enhanced soil moisture product was assessed using long-term in situ soil moisture observations from core validation sites located in diverse biomes and was found to exhibit an average retrieval uncertainty below 0.040 cu m/cu m. As of December 2016, the enhanced soil moisture product has been made available to the public from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center.

SMAP Enhanced↗

Comparison of Passive Microwave-Derived Early Melt Onset Records on Arctic Sea Ice

Two long records of melt onset (MO) on Arctic sea ice from passive microwave brightness temperatures (Tbs) obtained by a series of satellite-borne instruments are compared. The Passive Microwave (PMW) method and Advanced Horizontal Range Algorithm (AHRA) detect the increase in emissivity that occurs when liquid water develops around snow grains at the onset of early melting on sea ice. The timing of MO on Arctic sea ice influences the amount of solar radiation absorbed by the ice-ocean system throughout the melt season by reducing surface albedos in the early spring. This work presents a thorough comparison of these two methods for the time series of MO dates from 1979through 2012. The methods are first compared using the published data as a baseline comparison of the publically available data products. A second comparison is performed on adjusted MO dates we produced to remove known differences in inter-sensor calibration of Tbs and masking techniques used to develop the original MO date products. These adjustments result in a more consistent set of input Tbs for the algorithms. Tests of significance indicate that the trends in the time series of annual mean MO dates for the PMW and AHRA are statistically different for the majority of the Arctic Ocean including the Laptev, E. Siberian, Chukchi, Beaufort, and central Arctic regions with mean differences as large as 38.3 days in the Barents Sea. Trend agreement improves for our more consistent MO dates for nearly all regions. Mean differences remain large, primarily due to differing sensitivity of in-algorithm thresholds and larger uncertainties in thin-ice regions.

sea ice↗

A Machine Learning-Based Cloud Detection and Thermodynamic Phase Classification Algorithm using Passive Spectral Observations

We trained two Random Forest (RF) machine-learning models for cloud mask and cloud thermodynamic phase detection using spectral observations from VIIRS on Suomi NPP (SNPP). Observations from CALIOP were carefully selected to provide reference labels. The two RF models were trained for all-day and daytime-only conditions using a 4-year collocated VIIRS/CALIOP dataset from 2013 to 2016. Due to the orbit difference, the collocated CALIOP and SNPP VIIRS training samples cover a broad viewing zenith angle range, which is a great benefit to overall model performance. The all-day model uses 3 VIIRS infrared (IR) bands (8.6,11, and 12 μm) and the daytime model uses 5 Near-IR (NIR) and Shortwave-IR (SWIR) bands (0.86, 1.24, 1.38, 1.64 and 2.25 μm) together with the 3 IR bands to detect clear, liquid water, and ice cloud pixels. Up to 7 surface types, namely, ocean/water, forest, cropland, grassland, snow/ice, barren/desert, and shrubland, were considered separately to enhance performance for both models. Detection of cloudy pixels and thermodynamic phase with the two RF models were compared against collocated CALIOP products from 2017. It is shown that, with a conservative screening process that excludes the most challenging cloudy pixels for passive remote sensing, the two RF models have high accuracy rates in comparison with the CALIOP reference for both cloud detection and thermodynamic phase. Other existing SNPP VIIRS and Aqua MODIS cloud mask and phase products are also evaluated, with results showing that the two RF models and the MODIS MYD06 optical property phase product are the top 3 algorithms with respect to lidar observations during the daytime. During the nighttime, the RF all-day model works best for both cloud detection and phase, in particular for pixels over snow/ice surfaces. The present RF models can be extended to other similar passive instruments if training samples can be collected from CALIOP or other lidars. However, the quality of reference labels and potential sampling issues that may impact model performance would need further attention.

cloud detection↗

Surface melting over the Greenland ice sheet from enhanced resolution passive microwave brightness temperatures (1979–2019)

Surface melting is a major component of the Greenland ice sheet (GrIS) surface mass balance, affecting sea level rise through direct runoff and the modulation on ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting in view of their long temporal coverage (1979–to date) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, being historically of the order of tens of kilometres. Here, we use a newly released passive microwave dataset (37 GHz, horizontal polarization) made available through the NASA MeASUREs program to study the spatiotemporal evolution of surface melting over the GrIS at an enhanced spatial resolution of 3.125 Km. We assess the outputs of different detection algorithms through data collected by Automatic Weather Stations (AWS) and the outputs of the MAR regional climate model. We found that surface melting is well captured using a dynamic algorithm based on the outputs of MEMLS model, capable to detect sporadic and persistent melting. Our results indicate that, during the reference period 1979–2019 (1988–2019), surface melting over the GrIS increased in terms of both duration, up to ~4.5 (2.9) days per decade, and extension, up to 6.9 % (3.6 %) of the GrIS surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season has started up to ~4 (2.5) days earlier and ended ~7 (3.9) days later per decade. We also explored the information content of the enhanced resolution dataset with respect to the one at 25 km and MAR outputs through a semi-variogram approach. We found that the enhanced product is more sensitive to local scale processes, hence confirming the potential interest of this new enhanced product for studying surface melting over Greenland at a higher spatial resolution than the historical products and monitor its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modelled melt extent at high resolution and potentially to assimilate this data in climate models.

Surface melting↗

Chapter 10: Development of a Precipitation Retrieval Scheme for Cross-track Passive Microwave Sounding Instruments

The measurement of precipitation (snowfall and rainfall) across the globe is of great importance to both science and society. Despite the importance, measurements from surface-based instruments are limited in extent and are generally absent from sparsely populated or inhospitable regions, including over the world’s oceans. Satellite-based observations have the potential to provide the necessary information to generate estimates of precipitation across the whole of the Earth’s surface. However, adequate temporal and spatial sampling is required to capture vagaries of precipitation and it is necessary to exploit all possible satellite (and, where appropriate surface) information. While much research has been carried out into the retrieval of precipitation from observations gathered by conically-scanning passive microwave imagers in previous decades, relatively little has been done to fully utilise the observations from the cross-track scanning passive microwave sounding instruments. This paper will review a number of cross-track precipitation retrieval schemes, together an evaluation of their performance, and future directions.

Precipitation retrievals↗