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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Replication of Segments of STS-94 as a Lunar Surface Mission

The Artemis program established the goal to land the first woman and first person of color on the Moon, but that is only the beginning of the program. Artemis plans to move towards a sustainable phase, with four crew living on the lunar surface for roughly 30-day annual missions, operating from a Pressurized Rover (PR) and a Surface Habitat (SH). The crew will split up – two living and operating from the PR and the others in the SH, perhaps swapping places halfway through the surface mission. There is a significant degree of maturity surrounding PR operations due to the NASA Desert Research and Technology Studies field tests from 2007-2011. However, there is a degree of uncertainty surrounding activity in the SH, with anecdotal speculation among some Artemis lunar surface engineers that the SH crew might not be fully utilized. Contrary to this belief, there is evidence in US human spaceflight history that the SH crew may instead be extremely busy. In particular, portions of the STS-94 Microgravity Science Lab mission demonstrate a science-based use case for crew activity in the SH. Fifteen Spacelab missions (not including STS-83, which was terminated early due to a fuel cell problem and reflown as STS-94) and eight Spacehab missions used the previously mentioned modules as science labs to expand the science capability of shuttle orbital missions, most flown prior to the assembly of the International Space Station. STS-94 is selected as an example of these flights. STS-94 was a 15.7-day mission with a 7-person crew. The crew operated in split 12-hour shifts, enabling 24-hour science operations. STS-94 used the space shuttle Columbia with the Spacelab module and Extended Duration Orbiter pallet in the cargo bay. The STS-94 physical science investigations were intended to explore various physical aspects of microgravity. These same investigations can be conducted on the Moon to explore 1/6 gravity. The Spacelab module was outfitted with several key facilities to enable this research: Large Isothermal Furnace, Combustion Module-1, Droplet Combustion Experiment, EXPRESS Rack, TEMPUS, Gravity Measurement Devices, and Middeck Glovebox. The current reference concept for the SH is a hybrid inflatable in a vertical orientation. Fairly typical of hybrid inflatables, the SH has an aluminum core pressurized section and a larger inflatable volume, in this case attaching to the top of the core. Two crew will live in the SH at a time, though four can briefly occupy the habitat, such as for contingency or handover activities. This paper will discuss use of the STS-94 physical science equipment in the SH and options for the architectural layout of a resulting physics laboratory. It will also discuss how this laboratory may accompany other science facilities such as biology, human research, and geology. The person hours used by the STS-94 crew to conduct physical science research will be estimated and then mapped to a two-person SH crew, making it possible to determine how many days are required in the SH to complete the lunar gravity physical science investigations at varying levels of crew availability.

STS-94↗
NASA NTRSDate not supplied

Magnetic Measurements of Arc Instabilities in Segmented Arc Heater Column

The Aerodynamic Heating Facility (AHF) at NASA Ames Research Center (ARC) generates high enthalpy, supersonic flow environments for ground testing of NASAheat shield materials. This arc jet heater operates by passing a DC arc (<3200A,<2500V) through a gas column (~10cm diameter, 2m length) and ejecting the heatedgas through a supersonic nozzle into a test chamber. The arc plasma is a partially ionized air mixture at low temperature (< 2eV) but needs to be stable for long test times (up to 30min) at high power (< 20MW). Currently, the operational envelope of the facility is limited by arc instabilities including the kink instability. Consequently, it is of interest to characterize these instabilities to better understand facility limits and inform methods to extend stable operational ranges. Due to the high enthalpy and long timescales (i.e., minutes) diagnostics must be non-invasive. This work will cover the development of two sets of magnetic sensors: differential B-dot sensors and tri-axial magnetic hall sensors and will describe initial measurements of arc motion usingthese sensors.

Kink instability↗
NASA NTRSDate not supplied

Replication of Segments of STS-94 as a Lunar Surface Mission

The Artemis exploration plan will progress from initial Commercial Lunar Payloads Services (CLPS) landers to human landings to an established surface infrastructure supporting four crew for surface missions of a month or greater. NASA teams are currently working with partners to define the surface assets that will comprise this infrastructure, including habitation and laboratory facilities. However, design engineers often have limited insight into the laboratory capabilities needed inside a pressurized habitat or the demands such a facility will place upon crew availability. The Space Shuttle STS-94 Microgravity Science Laboratory (MSL-1) mission is used as an intravehicular activity science analog for the Surface Habitat. The STS-94 primary physical science instruments and crew activity in support of physical science investigations will be examined. Based on recent reference concepts for the Surface Habitat, options for incorporating the instruments and options for dividing physical science tasks among the Surface Habitat crew are discussed, based on STS94 crew tasks and assumptions for Surface Habitat operations. Crew size considerations are raised along with recommendations to reassess some of the current assumptions. Having shown that STS-94’s physical science investigations can be applied to a lunar surface mission, recommendations are made for increased attention to pressurized laboratory objectives, capabilities, and crew size.

Surface Habitat↗
NASA NTRSDate not supplied

Magnetic Measurements of Arc Instabilities in Segmented Arc Heater Column

The Aerodynamic Heating Facility (AHF) at NASA Ames Research Center (ARC) generates high enthalpy, supersonic flow environments for ground testing of NASAheat shield materials. This arc jet heater operates by passing a DC arc (<3200 A,<2500 V) through a gas column (~6 cm diameter, 2 m length) and ejecting the heated gas through a supersonic nozzle into a test chamber. The arc plasma is a partially ionized air mixture at low temperature (< 2 eV) but needs to be stable for long test times (up to 30 min) at high power (< 20 MW). Currently, the operational envelope of the facility is limited by arc instabilities including the kink instability. Consequently, it is of interest to characterize these instabilities to better understand facility limits and inform methods to extend stable operational ranges. Due to the high enthalpy and long timescales (i.e., minutes) diagnostics must be non-invasive. This work will cover the development of two sets of magnetic sensors: differential B-dot sensors and tri-axial magnetic hall sensors and will describe initial measurements of arc motion using these sensors.

Kink instability↗
NASA NTRSDate not supplied

The Electric Propulsion Segment of Prometheus 1

This presentation describes the electric propulsion element for the Jupiter Icy Moons Orbiter. It focusses on technology selection, early testing, technology and development plans, and mission challenges. It was presented at the 2005 JPC

Nuclear Electric Propulsion↗
NASA NTRSDate not supplied

Image-to-Image Wildfire Detection via Quantum-Compatible Variational Segmentation from Remotely-sensed Data

Over the last decade, the incidence of wildfires has surged, causing widespread destruction globally. To better comprehend and manage these incidents, remote sensing and aerial missions have been implemented in recent efforts. However, this has resulted in an exponential rise in the amount of remote sensing data utilization, leading to a need for intelligent automation of data extraction in wildfire studies. Machine learning provides an accurate automated approach for detecting these natural anomalies and facilitates decision-makers to take prompt actions. To make insightful decisions in wildfire management, it is imperative to move beyond simple detection and explore the potential of probabilistic generative machine learning for creating "what-if" scenarios for various wildfire conditions. Such models offer improved representation of the stochastic nature of wildfire events. However, the optimization of these models can be computationally expensive, especially when using classical computers. Quantum computers have recently emerged as a promising solution to reduce the computational cost of training such models and improve their performance. In this study, we aim to utilize quantum-compatible machine learning techniques to implement our probabilistic generative approach. To that end, we propose a supervised probabilistic variational model consisting of a U-NET-based image-to-image component along with encoder and decoder networks which work as a variational autoencoder (VAE) component. Additionally, we explore the type of latent distribution type in the VAE component and implement different means for modeling the prior distribution. We further investigate the quantum-compatible versions of the model compared to the classical counterpart and benchmark potential benefits of quantum compatibility over the classical model.

quantum machine learning↗