Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Comprehension”

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.

At least 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Comprehensive eVTOL Performance Evaluation Framework in Urban Air Mobility

In this paper, we developed an open-source simulation framework for the evaluation of electric vertical takeoff and landing vehicles (eVTOLs) in the context of Unmanned Traffic Management (UTM) and under the concept of Urban Air Mobility (UAM). Unlike most existing studies, the proposed framework combines the utilization of UTM and eVTOLs to develop a realistic UAM testing platform. For this purpose, we first develop an UTM simulator to simulate the real-world UAM environment. Then, instead of using a simplified eVOTL model, a high-fidelity eVTOL design tool, namely SUAVE, is employed and an dilation sub-module is introduced to bridge the gap between the UTM simulator and SUAVE eVTOL performance evaluation tool to elaborate the complete mission profile. Based on the developed simulation framework, experiments are conducted and the results are presented to analyze the performance of eVTOLs in the UAM environment.

Mrinmoy Sarkar↗
NASA NTRSDate not supplied

The Project “Analogs for Venus’ Geologically Recent Surfaces” (AVENGERS): A Comprehensive Database of Terrestrial Active Volcanoes for the Analysis of Ongoing Volcanism on Venus

The recently selected missions to Venus have opened a new era for the exploration of the Earth’s twin planet. As the Venus decade approaches, it is crucial to set the science goals for the future orbiting and in-situ investigations. One of the key science targets on Venus is certainly represented by the young topographic rises, which can be defined as the surface expression of underlying mantle plumes. These areas can be considered as the geologically youngest regions of Venus, being characterized by recent volcanic and tectonic activity. Studying areas of active volcanism and tectonism on Venus is crucial because it can reveal clues on the geologic past of the planet, as well as provide information about the volatile content of its interior and about the formation of its dense atmosphere. To this regard, the Project “Analogs for VENus’ GEologically Recent Surfaces” (AVENGERS) aims to build a database of Terrestrial analog sites for the analysis and identification of recent and possibly ongoing volcanic as well as tectonic activity on Venus to be investigated by the future missions. The Project AVENGERS will be a powerful tool for allowing a more efficient exploitation of the wealth of data to be provided by the future investigations of Venus during the upcoming decade.

P D Incecco↗
NASA NTRS2022

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗
NASA NTRS2024

Low-Speed Space Launch System Computational Fluid Dynamics: A Comprehensive Overview

In this review paper, low-speed computational work from NASA Langley in support of the Space Launch System (SLS) is discussed. This information includes both historic and present efforts with the Kestrel CFD solver. The low-speed aerodynamics of SLS is highly complex and analysis of the unsteady flowfield requires significant computational efforts. The SLS mission profile varies from the vehicle static on the launch pad through high-speed ascent, and this paper focuses on the prelaunch as well as liftoff and transition portions of the flight both in proximity to the launch tower and in isolation. High-alpha conditions, as large as 90 deg, result in a flowfield dominated by massive, large-scale flow separation and asymmetric vortices. High-fidelity solutions require an unsteady computational formulation to accurately capture the aerodynamics of the vehicle. A detailed discussion of the computational approach is presented, followed by key efforts to support the program, both historic and present, including information which has been either previously published or that has never before published external to NASA.

Brent Pomeroy↗
NASA NTRS2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consists of eighty-channel detector plane histograms that accumulate photon counts over time periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey dataset between 14 and 195 keV. Survey data comprises >90% of all BAT data by volume and allows for the tracking of long term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey dataset has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis python package , a wrapper for HEASoftpy, which provides a modern, open-source pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the python code and exemplify its usefulness and accuracy by analyzing survey data from the Crab Pulsar, NGC 2992, and a previously uncataloged MAXI Transient. The BatAnalysis package allows for ∼ 18 years of BAT survey to be used in a systematic way to study a large variety of astrophysical sources.

Tyler Parsotan↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Analysis Toolkit for Space Radiation Measurements Relevant to Space Radiation Biology

RadLab, a new addition to the NASA Open Science Data Repository (OSDR), is a public platform for space radiation data relevant to human space exploration. RadLab consists of a database, a submission portal, and user-friendly visualization and data analysis tools, including a graphical user interface (GUI) and an application programming interface (API). Investigators from ISS partners including Germany, Italy, Canada, Hungary, the Czech Republic, Russia, Japan have committed to providing data from their instruments. RadLab will also include data from other spacecraft in LEO: the Space Shuttle, the Mir space station, biosatellites; and beyond LEO: the lunar and the Martian surface, the heliocentric orbit at 1 AU, Mars orbit, and Earth-Mars space. Once fully operational, RadLab will provide open, centralized access to space radiation physics data relevant to human space exploration; a platform for submission of data by agencies and research institutions responsible for radiation detectors deployed in space; analysis tools to facilitate detector and dataset intercomparison to better understand space habitat radiation environments; capabilities for space biology investigators to determine the radiation environment to which samples were exposed. A RadLab Working Group (RLWG) has been formed, modeled on the GeneLab Analysis Working Groups and comprised of data contributors and users. RLWG tasks include identifying data sources, normalizing data from diverse detectors, expanding the analysis toolkit and, perhaps most importantly, sharing ideas for research exploiting capabilities of RadLab. We will provide an overview of RadLab data and capabilities and discuss examples of its potential as a resource for open science.

radiation↗
NASA NTRSDate not supplied

Trade-Offs of Simplified Versus Comprehensive Representation of Mineralogy When Studying Dust Impacts on Earth’s Climate Systems

The intensity and direction of dust impacts on Earth’s climate systems depend on mineral composition. For example, the presence or absence of a few percent of iron oxides in dust will determine if dust is warming or cooling the atmosphere. Similarly, feldspar will enhance ice cloud formation, while acid gases in the atmosphere will react on the surface of dust calcite limiting acid rain. Still, most climate models use a simplified representation of dust mineralogy. They assume a fixed composition at emission which stays invariant during transport and removal. Such simplification assumes spatially and temporally constant physical and chemical properties of dust, and appears to provide satisfactory results when comparing some properties with observations. The trade-off is their lack of spatial gradients, which will fail to induce circulation, cloud and precipitation changes. The two reasons to omit mineral variations are the uncertainty of current atlases of soil mineral composition in arid regions, and, more practically, an improved runtime efficiency. The former reason is losing ground with the recent launch (July 2022) of a dedicated mission (NASA/JPL EMIT) to retrieve global soil mineralogy of dust sources at high spatial resolution. While the EMIT science team is finalizing a satisfactory global map of mineral composition of dust sources, we analyzed the interaction of dust mineralogy on radiation and its impact on the fast temperature response using different representations of mineral composition from detailed and spatially varying to simplified and globally uniform, assuming different hematite contents and methods to calculate optical properties. Our results show that resolving dust mineralogy reduces dust absorption, and results in improved agreement with observation-based single scattering albedo (SSA), radiative fluxes from CERES (the Clouds and the Earth’s Radiant Energy System), and land surface temperature from CRU (Climatic Research Unit), compared to the baseline bulk dust model version. It also results in distinct radiative impacts on Earth’s climate over North Africa. From our 19-year simulation, we will show that it leads to a reduction of over 50% in net downward radiation at top of atmosphere (TOA) across the Sahara and an approximately 20% reduction over the Sahel. We will explain how the surface temperature response affects the monsoon flow from the Gulf of Guinea. Interestingly, we find similar results by simply fixing the hematite content of dust to a globally uniform value of 0.9% by volume. We will discuss the underlying reasons for such results and show that they may be unrelated to the distribution of soil mineralogy. Still, an accurate representation of soil mineralogy is necessary to better understand dust impacts on the Earth’s climate systems.

dust impacts↗
NASA NTRS2024

Comprehensive Observations and Geostatistics of Slope Streaks within the Olympus Mons Aureole

Slope streaks (SS) are enigmatic linear features characterized by relatively low-albedo features that appear and fade on high-albedo slopes on Mars. Despite numerous hypotheses proposed to explain their formation, the primary mechanism behind SS remains elusive. Here, we examine 702 SS features using 32 multitemporal Context Imager (CTX) images and mesoscale modeling data obtained from a site (centered at 31.230°N, 216.281°E) in the Olympus Mons Aureole region. Our investigation revealed several key findings that shed light on the dynamics of SS formation and fading. We discovered a significant preference for SS formation on south-facing (equator-facing) slopes compared to north-facing slopes, with SS being over seven times more likely to occur on the former. Furthermore, SS formation was found to be seasonal with significantly enhanced by a factor of ∼6 near the equinoxes (from solar longitude Ls 337°-42° and 136°-227°) compared to other times of the year. Our analysis also revealed a correlation between the rates of SS formation and fading, with scree slopes exhibited the fastest-fading SS also experiencing the highest rates of newly-formed SS. Additionally, we measured the median starting and stopping slopes of SS to be 23.4° and 14.9°, respectively, significantly below the angle of repose of sand. These low slopes suggest the necessity for an energetic trigger mechanism to initiate SS formation. Infrared spectroscopy revealed that the principal distinction between the material inside and outside of a SS lies in the reduced abundance of dust within the streak. Notably, this site demonstrates the highest rates of SS formation (a 29.6% increase in new SS per Mars year) and fading (a 12% fading of SS per Mars year) ever quantified. These elevated rates may be attributed to the site's topography, which facilitates calm surficial nighttime winds throughout the year, leading to widespread dust deposition. Daytime downhill winds near the ridgelines of S-facing slopes may then trigger movement of newly deposited dust aggregates or alternatively, a Knudsen pump phenomenon could serve as a potential trigger for SS. We propose that SS is inhibited during the northern summer solstice season due to the relatively clear aphelion atmosphere, which limits dust deposition. Similarly, the lack of triggering activity during the winter solstice is likely due to more moderate daytime winds. Overall, our findings are consistent with the wind-triggered dry avalanche hypothesis as a plausible explanation for SS formation.

D E Stillman↗
NASA NTRSDate not supplied

NASA’s Comprehensive Databases for Materials Selection (MAPTIS) and Low-Gravity Experiments (PSI)

In the realm of advancing technological change the convergence of materials science and scientific inquiry stands as a testament to humanity’s insatiable curiosity. To assist in this endeavor the National Aeronautics and Space Administration (NASA) provides curated access to two unique databases. Physical Sciences Informatics (PSI) is an online database that houses completed physical science reduced-gravity experiments. Whereas Materials and Processes Technical Information System (MAPTIS) contains several other databases that relate to aerospace materials and processes. Equipped with curated access to these databased provided by the NASA scientists and engineers are furnished with invaluable resources needed to propel technological change.

PSI↗
NASA NTRSDate not supplied

Comprehensive Evaluation of Electrochemical Hydrogen Separator as Hydrogen Recovery Solution for Plasma Pyrolysis Assembly

The previously tested State-of-the-Art (SOA) air revitalization architecture onboard the International Space Station recovers approximately 50% of the oxygen (O 2 ) from metabolic carbon dioxide (CO 2 ) via the Sabatier process. Maximum O 2 recovery is required to reduce resupply mass for long-duration manned missions. O 2 recovery is constrained by the limited availability of reactant hydrogen (H 2 ) from water (H 2 O) electrolysis, and Sabatier-produced methane (CH 4 ) is vented as a waste product resulting in a continuous loss of reactant H 2 . The Plasma Pyrolysis Assembly (PPA) has the potential to substantially increase O 2 recovery by post-processing the Sabatier-produced methane to recover H 2 . The PPA decomposes CH 4 into predominately H 2 and acetylene (C 2 H 2 ). A separation system is needed to purify the H 2 from the PPA stream before it is recycled back to the Sabatier reactor. Two sub-scale electrochemical H 2 separation systems, developed by Skyre, Incorporated, were delivered to NASA for evaluation. Complimentary of the previous submittal, ICES-2023-260, this paper reports a summation of Phase I and Phase II testing and evaluation of the C 2 H 2 removal systems as well as lessons learned.

Plasma Pyrolysis Assembly↗
NASA NTRSDate not supplied

NASA’s Space Launch System: Comprehensive Test Program Leads to Mission Success during Artemis I Flight Test

NASA’s SLS (Space Launch System) rocket had a successful first launch on Nov. 16, 2022, sending an uncrewed Orion spacecraft to the Moon on the agency’s Artemis I mission. Ten 6U CubeSats were also deployed from SLS during the mission. Orbital insertion parameters, including insertion velocity and altitude, were within hundredths and tenths of a percent from predicted values, corroborating data collected from the individual elements that showed similar performance accuracy. While launch remains the main test – and Artemis I was a true test flight – to collect data, confirm and refine computer models, and validate hardware test data, multiple test programs led up to the first flight and enabled the historic launch. Additionally, SLS was designed from the beginning to be a crew-rated launch vehicle, and teams put the astronauts who will fly on it at the forefront of the development process. This paper and presentation will cover the SLS design and development programs that led to the successful Artemis I mission, and which have set the stage to send the first astronauts back to cislunar space since the Apollo 17 crew in 1972.

John Honeycutt↗