Search NASA⌕ Search

SEARCH · Search NASA

Results for “6U satellite”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

3 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The DarkNESS mission: probing dark matter with a Skipper-CCD satellite observatory

The invention of Skipper-CCDs with sub-electron noise has paved the way for groundbreaking low-threshold dark matter (DM) experiments, such as SENSEI and DAMIC. Conventionally, these experiments are deployed underground to mitigate cosmogenic backgrounds; however, some DM signatures are inaccessible to underground experiments due to attenuation in the Earth’s atmosphere and crust. The DarkNESS mission will deploy an array of Skipper-CCDs on a 6U CubeSat in Low Earth Orbit (LEO) to search for electron recoils from strongly-interacting sub-GeV DM as well as X-ray line signatures from sterile neutrino decay. Using a series of observations from LEO, the DarkNESS mission will set competitive upper limits on the DM-electron scattering cross section and help resolve the experimental conundrum associated with the purported observation of a 3.5 keV X-ray line, potentially produced from sterile neutrino decay. This work will describe the DarkNESS instrument, the technical challenges in operating Skipper-CCDs in the space environment, the scientific objectives of the DarkNESS mission, and the DM parameter space that DarkNESS will probe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

MiniCarb: a passive, occultation-viewing, 6U CubeSat for observations of CO 2 , CH 4 , and H 2 O

In this report we present the final design, environmental testing, and launch history of MiniCarb, a 6U CubeSat developed through a partnership between NASA Goddard Space Flight Center and Lawrence Livermore National Laboratory. MiniCarb’s science payload, developed at Goddard, was an occultation-viewing, passive laser heterodyne radiometer for observing methane, carbon dioxide, and water vapor in Earth’s atmosphere at ~1.6 µm s -1 . MiniCarb’s satellite, developed at Livermore, implemented their CubeSat Next Generation Bus plug-and-play architecture to produce a modular platform that could be tailored to a range of science payloads. Following the launch on 5 December 2019, MiniCarb traveled to the International Space Station and was set into orbit on 1 February 2020 via Northrop Grumman’s Cygnus capsule which deployed MiniCarb with tipoff rotation of about 20° s (significantly higher than the typical rate of 3° s -1 from prior CubeSats), from which the attitude control system was unable to recover resulting in a loss of power. In spite of this early failure, MiniCarb had many successes including rigorous environmental testing, successful deployment of its solar panels, and a successful test of the radio and communication through the Iridium network. This prior work and enticing cost (approximately $\$2$ M for the satellite and $\$$250 K for the payload) makes MiniCarb an ideal candidate for a low-cost and rapid rebuild as a single orbiter or constellation to globally observe key greenhouse gases.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

MULTI-MODAL global surveillance methodology for predictive and on-demand characterization of localized processes using cube satellite platforms and deep learning techniques

This paper presents the work completed towards the development of a multi-modal global surveillance methodology using cube satellite (CubeSat) platforms and novel data analysis techniques. A CubeSat system equipped with adequate sensors and data analytics capabilities can autonomously characterize various phenomena of interest on the Earth’s surface. CubeSats are advantageous over conventional satellites in certain remote monitoring applications because of their reduced construction costs (due to the availability of commercially-off-the-shelf components) and are easier to launch. The CubeSat surveillance system developed in this paper focused on phenomena of interest surrounding the nuclear fuel cycle in support of nuclear non-proliferation and emergency response. To observe the phenomena, a constellation of 3U and 6U CubeSats deployed from the ISS with adequate components was chosen. Four different sensor configurations were identified for remote sensing: panchromatic/multispectral in the visible and near-infrared spectrum, multispectral in infrared spectrum, hyperspectral in infrared spectrum, and multispectral in ultraviolet spectrum. While a panchromatic/multispectral sensor configuration has CubeSat flight heritage at the required spatial resolutions, the other three sensor types need future 3 development to meet signature and system requirements. Once each sensor onboard the CubeSat system collects data on a target of interest, the onboard computers would then apply the deep learning-based characterization methodology developed in this paper to identify phenomena. Four surrogate datasets containing representative simplified “images” were created for each sensor type to train the characterization methodology. A convolutional neural network was applied to each dataset and produced recall rates for the phenomena between 89.7% - 99.3% and precision rates between 92.3% - 99.9%. Each phenomenon’s presence probability from each network is then combined into a final characterization solution for a target area. This paper covers multiple interdisciplinary areas to develop the foundation for a CubeSat surveillance system focused on phenomena surrounding the nuclear fuel cycle.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗