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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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46 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Long-term reliability of hand-soldering M55365 Ta capacitors

This is a continuation of the report “Effects of Hand Soldering MIL-PRF-55365 Tantalum Capacitors,” which discusses the parametric effects of convection reflow soldering, JPL standard hand soldering, and optimized hand soldering on solid tantalum capacitors. The current focus is determining the long-term reliability effects of the various soldering techniques. Unfortunately, the 100-piece sample size chosen for the highly accelerated life tests was too small to reliably determine the effects of the different soldering techniques on the lifespan of the parts. In hindsight, this likely could have been predicted based on the large alphas and small betas of the Weibull failure distributions discovered during the scouting trials. Now that the effects of inadequate sample size are better understood, an opportunity exists to not only discover whether there are real differences in the reliability associated with the various soldering techniques, but also the potential to discover the voltage acceleration model and the temperature acceleration effect for these capacitors. It is recommended that the testing be repeated with a more appropriate sample size to capture this useful information.

Spence, Penelope↗
NASA NTRSDate not supplied

“Are We There Yet?” Can We Biomap the Solar System with Low-Cost Solar Sail Missions?

Abstract: So much of our effort in space exploration has been devoted to one-off missions with major investments in each. This is a great strategy for early investigations of clearly significant planetary and small body destinations, but we have an entire Solar System to interrogate and the pace has definitely been slow to date. We are in the dawning era of much smaller spacecraft, and the potential to gather data from multiple destinations over longer time spans with a heightened cadence of missions to allow us to conduct survey-style investigations of the vast number of objects that attend our particular star. If we think of solar systems as belonging to one of two classes, i.e. life-bearing or not life-bearing, then the presence of some sort of biological or prebiological phenomenon on any individual body in a system places that system in the first category. The emergence of life can then be considered as a solar system-wide property and the entire suite of ingredients and processes that go into kindling of life anywhere within that system is of interest. This ranges from bodies with prebiotic chemistry through to full-blown biospheres. Thus, all bodies in a solar system are part of the milieu within which life occurs. Can the idea of low-cost solar sail-propelled spacecraft deployed en masse be useful for something as hard to investigate as life-like phenomena and their precursors? Perhaps, the answer is yes, and we must give serious attention to the possibilities.

Penelope J Boston↗
NASA NTRS2023

Pypromice: A Python Package for Processing Automated Weather Station Data

The pypromice Python package is for processing and handling observation datasets from automated weather stations (AWS). It is primarily aimed at users of AWS data from the Geological Survey of Denmark and Greenland (GEUS), which collects and distributes in situ weather station observations to the cryospheric science research community. Functionality in pypromice is primarily handled using two key open-source Python packages, xarray (Hoyer & Hamman, 2017) and pandas (The pandas development team, 2020). A defined processing workflow is included in pypromice for transforming original AWS observations (Level 0, L0) to a usable, CF-convention-compliant dataset (Level 3, L3) (Figure 1). Intermediary processing levels (L1,L2) refer to key stages in the workflow, namely the conversion of variables to physical measurements and variable filtering (L1), cross-variable corrections and user-defined data flagging and fixing (L2), and derived variables (L3). Information regarding the station configuration is needed to perform the processing, such as instrument calibration coefficients and station type (one-boom tripod or two-boom mast station design, for example), which are held in a toml configuration file. Two example configuration files are provided with pypromice , which are also used in the package’s unit tests. More detailed documentation of the AWS design, instrumentation, and processing steps are described in Fausto et al. (2021).

pypromice↗
NASA NTRS2023

A Data Set of Monthly Freshwater Fluxes From the Greenland Ice Sheet’s Marine-Terminating Glaciers on A Glacier–Basin Scale 2010–2020

The loss of mass from the Greenland ice sheet causes an increasing influx of freshwater to the Greenlandic fjords and the oceans. Freshwater fluxes from marine-terminating glaciers are important to understand fjord circulation and ecosystem dynamics. Here, we present a data set constructed by reformulating existing products into a shared temporal and spatial framework. We combine three publicly available data sets of solid-ice discharge (iceberg), liquid-surface runoff (runoff) and basal melt to present a cohesive overview of the flow of freshwater from marine-terminating glaciers to the Greenlandic fjords. We also calculate glacier drainage basins and compare our findings to previous studies showing that drainage-basin sizes may vary considerably depending on how they were reconstructed. The data set will be a valuable asset to oceanographic, glaciological and marine biological research activities.

Ice mass loss↗
NASA NTRS2023

The Historical Greenland Climate Network (GC-Net) Curated and Augmented Level-1 Dataset

The Greenland Climate Network (GC-Net) consists of 31 automatic weather stations (AWSs) at 30 sites across the Greenland Ice Sheet. The first site was initiated in 1990, and the project has operated almost continuously since 1995 under the leadership of the late Konrad Steffen. The GC-Net AWS measured air temperature, relative humidity, wind speed, atmospheric pressure, downward and reflected shortwave irradiance, net radiation, and ice and firn temperatures. The majority of the GC-Net sites were located in the ice sheet accumulation area (17 AWSs), while 11 AWSs were located in the ablation area, and two sites (three AWSs) were located close to the equilibrium line altitude. Additionally, three AWSs of similar design to the GC-Net AWS were installed by Konrad Steffen's team on the Larsen C ice shelf, Antarctica. After more than 3 decades of operation, the GC-Net AWSs are being decommissioned and replaced by new AWSs operated by the Geological Survey of Denmark and Greenland (GEUS). Therefore, making a reassessment of the historical GC-Net AWS data is necessary. We present a full reprocessing of the historical GC-Net AWS dataset with increased attention to the filtering of erroneous measurements, data correction and derivation of additional variables: continuous surface height, instrument heights, surface albedo, turbulent heat fluxes, and 10 m ice and firn temperatures. This new augmented GC-Net level-1 (L1) AWS dataset is now available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2023) and will continue to be refined. The processing scripts, latest data and a data user forum are available at https://github.com/GEUS-Glaciology-and-Climate/GC-Net-level-1-data-processing (last access: 30 November 2023). In addition to the AWS data, a comprehensive compilation of valuable metadata is provided: maintenance reports, yearly pictures of the stations and the station positions through time. This unique dataset provides more than 320 station years of high-quality atmospheric data and is available following FAIR (findable, accessible, interoperable, reusable) data and code practices.

Greenland Climate Network↗