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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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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Reconstruction of Orion Engineering Development Unit (EDU) Parachute Inflation Loads

The process of reconstructing inflation loads of Capsule Parachute Assembly System (CPAS) has been updated as the program transitioned to testing Engineering Development Unit (EDU) hardware. The equations used to reduce the test data have been re-derived based on the same physical assumptions made by simulations. Due to instrumentation challenges, individual parachute loads are determined from complementary accelerometer and load cell measurements. Cluster inflations are now simulated by modeling each parachute individually to better represent different inflation times and non-synchronous disreefing. The reconstruction procedure is tailored to either infinite mass or finite mass events based on measurable characteristics from the test data. Inflation parameters are determined from an automated optimization routine to reduce subjectivity. Infinite mass inflation parameters have been re-defined to avoid unrealistic interactions in Monte Carlo simulations. Sample cases demonstrate how best-fit inflation parameters are used to generate simulated drag areas and loads which favorably agree with test data.

Ray, Eric S.↗
NASA NTRS2013

Oxygen Isotope Measurements of a Rare Murchison Type A CAI and Its Rim

Ca-, Al-rich inclusions (CAIs) from CV chondrites commonly show oxygen isotope heterogeneity among different mineral phases within individual inclusions reflecting the complex history of CAIs in both the solar nebula and/or parent bodies. The degree of isotopic exchange is typically mineral-specific, yielding O-16-rich spinel, hibonite and pyroxene and O-16-depleted melilite and anorthite. Recent work demonstrated large and systematic variations in oxygen isotope composition within the margin and Wark-Lovering rim of an Allende Type A CAI. These variations suggest that some CV CAIs formed from several oxygen reservoirs and may reflect transport between distinct regions of the solar nebula or varying gas composition near the proto-Sun. Oxygen isotope compositions of CAIs from other, less-altered chondrites show less intra-CAI variability and 16O-rich compositions. The record of intra-CAI oxygen isotope variability in CM chondrites, which commonly show evidence for low-temperature aqueous alteration, is less clear, in part because the most common CAIs found in CM chondrites are mineralogically simple (hibonite +/- spinel or spinel +/- pyroxene) and are composed of minerals less susceptible to O-isotopic exchange. No measurements of the oxygen isotope compositions of rims on CAIs in CM chondrites have been reported. Here, we present oxygen isotope data from a rare, Type A CAI from the Murchison meteorite, MUM-1. The data were collected from melilite, hibonite, perovskite and spinel in a traverse into the interior of the CAI and from pyroxene, melilite, anorthite, and spinel in the Wark-Lovering rim. Our objectives were to (1) document any evidence for intra-CAI oxygen isotope variability; (2) determine the isotopic composition of the rim minerals and compare their composition(s) to the CAI interior; and (3) compare the MUM-1 data to oxygen isotope zoning profiles measured from CAIs in other chondrites.

Matzel, J. E. P.↗
NASA NTRS2014

The TSO Logic and G2 Software Product

This internship assignment for spring 2014 was at John F. Kennedy Space Center (KSC), in NASAs Engineering and Technology (NE) group in support of the Control and Data Systems Division (NE-C) within the Systems Hardware Engineering Branch. (NEC-4) The primary focus was in system integration and benchmarking utilizing two separate computer software products. The first half of this 2014 internship is spent in assisting NE-C4s Electronics and Embedded Systems Engineer, Kelvin Ruiz and fellow intern Scott Ditto with the evaluation of a newly piece of software, called G2. Its developed by the Gensym Corporation and introduced to the group as a tool used in monitoring launch environments. All fellow interns and employees of the G2 group have been working together in order to better understand the significance of the G2 application and how KSC can benefit from its capabilities. The second stage of this Spring project is to assist with an ongoing integration of a benchmarking tool, developed by a group of engineers from a Canadian based organization known as TSO Logic. Guided by NE-C4s Computer Engineer, Allen Villorin, NASA 2014 interns put forth great effort in helping to integrate TSOs software into the Spaceport Processing Systems Development Laboratory (SPSDL) for further testing and evaluating. The TSO Logic group claims that their software is designed for, monitoring and reducing energy consumption at in-house server farms and large data centers, allows data centers to control the power state of servers, without impacting availability or performance and without changes to infrastructure and the focus of the assignment is to test this theory. TSOs Aaron Rallo Founder and CEO, and Chris Tivel CTO, both came to KSC to assist with the installation of their software in the SPSDL laboratory. TSOs software is installed onto 24 individual workstations running three different operating systems. The workstations were divided into three groups of 8 with each group having its own operating system. The first group is comprised of Ubuntus Debian -based Linux the second group is windows 7 Professional and the third group ran Red Hat Linux. The highlight of this portion of the assignment is to compose documentation expressing the overall impression of the software and its capabilities.

TSO Logic↗
NASA NTRS2016

Nitrous Oxides Ozone Destructiveness Under Different Climate Scenarios

Nitrous oxide (N2O) is an important greenhouse gas and ozone depleting substance as well as a key component of the nitrogen cascade. While emissions scenarios indicating the range of N2O's potential future contributions to radiative forcing are widely available, the impact of these emissions scenarios on future stratospheric ozone depletion is less clear. This is because N2O's ozone destructiveness is partially dependent on tropospheric warming, which affects ozone depletion rates in the stratosphere. Consequently, in order to understand the possible range of stratospheric ozone depletion that N2O could cause over the 21st century, it is important to decouple the greenhouse gas emissions scenarios and compare different emissions trajectories for individual substances (e.g. business-as-usual carbon dioxide (CO2) emissions versus low emissions of N2O). This study is the first to follow such an approach, running a series of experiments using the NASA Goddard Institute for Space Sciences ModelE2 atmospheric sub-model. We anticipate our results to show that stratospheric ozone depletion will be highest in a scenario where CO2 emissions reductions are prioritized over N2O reductions, as this would constrain ozone recovery while doing little to limit stratospheric NOx levels (the breakdown product of N2O that destroys stratospheric ozone). This could not only delay the recovery of the stratospheric ozone layer, but might also prevent a return to pre-1980 global average ozone concentrations, a key goal of the international ozone regime. Accordingly, we think this will highlight the importance of reducing emissions of all major greenhouse gas emissions, including N2O, and not just a singular policy focus on CO2.

stratospheric ozone depletion↗
NASA NTRS2016

Instrumentation for Examining Microbial Response to Changes In Environmental Pressures

The Automated Adaptive Directed Evolution Chamber (AADEC) is a device that allows operators to generate a micro-scale analog of real world systems that can be used to model the local-scale effects of climate change on microbial ecosystems. The AADEC uses an artificial environment to expose cultures of micro-organisms to environmental pressures, such as UV-C radiation, chemical toxins, and temperature. The AADEC autonomously exposes micro-organisms to selection pressures. This improves upon standard manual laboratory techniques: the process can take place over a longer period of time, involve more stressors, implement real-time adjustments based on the state of the population, and minimize the risk of contamination. We currently use UV-C radiation as the main selection pressure, UV-C is well studied both for its cell and DNA damaging effects as a type of selection pressure and for its related effectiveness as a mutagen; having these functions united makes it a good choice for a proof of concept. The AADEC roadmap includes expansion to different selection pressures, including heavy metal toxicity, temperature, and other forms of radiation.The AADEC uses closed-loop control to feedback the current state of the culture to the AADEC controller that modifies selection pressure intensity during experimentation, in this case culture density and growth rate. Culture density and growth rate are determined by measuring the optical density of the culture using 600 nm light. An array of 600 nm LEDs illuminate the culture and photodiodes are used to measure the shadow on the opposite side of the chamber.Previous experiments showed that we can produce a million fold increase to UV-C radiation over seven iterations. The most recent implements a microfluidic system that can expose cultures to multiple different selection pressures, perform non-survival based selection, and autonomously perform hundreds of exposure cycles. A scalable pump system gives the ability to pump in various different growth media to individual cultures and introduce chemical toxins during experimentation; AADEC can perform freeze and thaw cycles. We improved our baseline characterization by building a custom UV-C exposure hood, a shutter operates on a preset timer allowing the user to set exposure intensity consistently for multiple iterations.

Environment↗
NASA NTRS2017

Quantifying TOLNet Ozone Lidar Accuracy During the 2014 DISCOVER-AQ and FRAPPE Campaigns

The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure high-resolution atmospheric profiles of ozone. The accurate characterization of these lidars is necessary to determine the uniformity of the network calibration. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission and the Front Range Air Pollution and Photochemistry Experiment (FRAPPA) to measure ozone variations from the boundary layer to the top of the troposphere. This study presents the analysis of the intercomparison between the TROPOZ, TOPAZ, and LMOL lidars, along with comparisons between the lidars and other in situ ozone instruments including ozonesondes and a P-3B airborne chemiluminescence sensor. The TOLNet lidars measured vertical ozone structures with an accuracy generally better than +/-15 % within the troposphere. Larger differences occur at some individual altitudes in both the near-field and far-field range of the lidar systems, largely as expected. In terms of column average, the TOLNet lidars measured ozone with an accuracy better than +/-5 % for both the intercomparison between the lidars and between the lidars and other instruments. These results indicate that these three TOLNet lidars are suitable for use in air quality, satellite validation, and ozone modeling efforts.

TOLNet↗
NASA NTRS2018

Almahata Sitta MS-MU-011 and MS-MU-012: Formation Conditions of Two Unusual Rocks From the Ureilite Parent Body

Almahata Sitta meteorites are unique polymict breccia, comprising of many different meteorite groups as individual fragments dominated by ureilite lithologies and are considered to be recovered fragments of the asteroid 2008TC3. Recently, two unusual Almahata Sitta samples (MS-MU-011 and MS-MU-012) have been reported that show close petrogenetic relationships to ureilites. MS-MU-011 is a trachyandesite mainly composed of feldspar (plagioclase and anorthoclase) and pyroxene (pigeonite and augite) having ureilitic oxygen isotopic ratios. MS-MU-012 is the first ureilite example (unbrecciated) containing primary plagioclase crystals. The findings of these two rock types are important to better understand formation conditions of ureilites and the evolution of their parent body(s). In this abstract we discuss formation conditions of these ureilite-related rocks using redox state estimate by Fe valence states of plagioclase and olivine cooling rate calculations.

Mikouchi, T.↗
NASA NTRS2018

Computer Controlled Solid State Lighting Assembly to Emulate Diurnal Cycle and Improve Circadian Rhythm Control

A light system can simultaneously emulate more than one different diurnal cycle to individually improve circadian rhythm control for more than one observer by having each light fixture autonomously self-controlled. Each light fixture is mountable in respective locations to individually treat respective observers. Each light fixture includes one or more light elements mounted to a housing and are controllable to emit a selected light intensity at a selected light temperature. A micro controller is contained in the housing and includes memory containing instructions for one or more automatic diurnal cycle protocols. The micro controller is in communication with the memory and the one or more light elements to execute the instructions to configure the light fixture to vary the light intensity and the light temperature of the emitted light.

Holbert, Eirik↗
NASA NTRS2017

High-Power Performance of a 100-kW Class Nested Hall Thruster

Operations of a three-channel 100-kW class nested Hall thruster at total power levels from 5 to 102 kW and discharge currents from 16 to 247 A were successful. The thruster was operated in all seven available channel combinations at discharge voltages of 300, 400, and 500 V and at current densities that were 0.60 and 0.95 of the nominal value. Additional test points were also collected at 1.20 the nominal current density. The thruster was throttled through a total of forty-six unique operating conditions. At each condition, thruster performance was measured using a high-power thrust stand designed to measure up to 8 N of thrust. From these thrust measurements, specific impulse and efficiency were calculated. All seven channel combinations showed similar performance at a given discharge voltage and current density. The largest thrust recorded was 5.42 N at 99 kW, 400 V discharge voltage. Total efficiency values 0.54 to 0.67, and total specific impulse ranged from 1800 seconds to 2650 seconds. Discharge current oscillations were also measured. Generally these oscillations increased on the inner and middle channels during multi-channel mode but stayed roughly a constant fraction of the channel discharge current for the outer channel in both single- and multi-channel operation. We also found that the thrust of the three channels firing together was not significantly higher than the sum of each channel _ring individually, a result that differs from what was found previously for nested Hall thrusters.

Hall, Scott J.↗
NASA NTRSDate not supplied

Novel insights enabled by combining mouse muscle datasets from the Rodent Research-1 mission

Biological space experiments are often expensive and difficult to conduct. As such, it is critical to maximize the value of the data that is collected during these experiments. One way to do this is to combine multiple–previously separate–datasets. This can increase the number of replicates for the conditions of interest (and hence statistical power), allow new multi-factor questions to be asked, and potentially highlight new patterns that otherwise would not have been identified from single-dataset studies. However, the process of combining datasets introduces noise due to inherent technical variations between experiments. To better understand the insights that can be gained from multi-dataset analyses and the problems that may arise from joining multiple datasets, several mouse muscle RNA-Seq datasets from the Rodent Research-1 mission were first selected. Then, using the R package DESeq2, principal component analysis (PCA) plots and differentially expressed gene (DEG) lists between ground and flight muscle samples were generated for individual datasets and for different pairwise combinations of datasets. Several new DEGs were identified in the combined datasets, and patterns in the PCA plots were affected depending on which datasets were joined. Understanding the results of this work will be critical for future studies that seek to perform multi-dataset analyses.

spaceflight↗
NASA NTRSDate not supplied

Behavioral Health Factors in Long Duration Space Flight: Lessons Learned From Apollo And Their Implications For Artemis

Behavioral health will be a critical factor in future Long Duration Spaceflights (LDSF). As humans venture further from Earth, astronauts will face greater isolation and need to be more autonomous than ever before. Astronauts will face a plethora of stressors, both internally and externally, and it will be mission critical to optimize their mind and bodies to endure and overcome these challenges. Personalities, environmental and physical factors will affect each individual and crew in different ways and it will be important to look at these factors independently and as a whole to maximize the chances of a successful mission. By analyzing environments analogous to space and building upon the lessons learned from the Apollo missions and over 50 years of Low Earth Orbit spaceflight, we hypothesize that a general framework can be developed to optimize crew mental wellbeing.

Nicolas Heft↗
NASA NTRSDate not supplied

A Study of Precipitation Mean Particle Size with the GPM Combined Radar-Radiometer Algorithm

The Global Precipitation Measurement (GPM) mission provides quantitative estimates of the mass-weighted mean diameter, Dm, a characteristic parameter of the precipitation particle size distribution (PSD). This study investigates the three-dimensional distribution of Dm retrieved by the GPM Combined Radar-Radiometer Algorithm (CORRA) using observations from GPM’s dual-frequency precipitation radar and microwave imager. We examine Dm in individual precipitation systems in different climate regimes and investigate a six-year global climatology. The vertical structure of Dm is demonstrated with cases of deep convection, frontal rain and snow, and stratocumulus light rain. The Dm values, detectable by GPM, range from appx 0.7 mm in stratocumulus precipitation to >3.5 mm in the ice layers of intense convection. Within the constraint of the 12-dBZ detectability threshold, the smallest climatological mean Dm (~ 0.8 mm) are found in the eastern oceans, and the largest values (~ 2 mm) occur above the melting levels in convection over land in summer. The standard deviation is generally < 0.45 mm below 6 km. Climate regimes are characterized with Dm annual/seasonal variations, its convective/stratiform components, and vertical variabilities (2-10 km). The US Central Plains and Argentina are associated with the largest Dm in a deep layer. Tropical Africa has larger Dm and standard deviation than Amazon. Large convective Dm occurs at high latitudes of Eurasia and North America in summer; the southern hemisphere high latitudes have shallower systems with smaller Dm. Oceanic storm tracks in both hemispheres have relatively large Dm, particularly for convective Dm in winter.

Mei Han↗
NASA NTRS2021

Understanding the Global Three-Dimensional Distribution of Precipitation Mean Particle Size with the Global Precipitation Measurement Mission

This study addresses the global distribution of precipitation mean particle size using data from the Global Precipitation Measurement (GPM) mission. The mass-weighted mean diameter Dm is a characteristic parameter of the precipitation particle size distribution (PSD), estimated from the GPM Combined Radar–Radiometer Algorithm (CORRA) using data from GPM’s dual-frequency precipitation radar and microwave imager. We examine Dm in individual precipitation systems in different climate regimes and investigate a 6-yr (2014–20) global climatology within 70°N–70°S. The vertical structure of Dm is demonstrated with cases of deep convection, frontal rain and snow, and stratocumulus light rain. The Dm values, detectable by GPM, range from ~0.7 mm in stratocumulus precipitation to >3.5 mm in the ice layers of intense convection. Within the constraint of the 12-dBZ detectability threshold, the smallest annual mean Dm (~0.8 mm) are found in the eastern oceans, and the largest values (~2 mm) occur above the melting levels in convection over land in summer. The standard deviation of the annual mean is generally <0.45 mm below 6 km. Climate regimes are characterized with Dm annual/seasonal variations, its convective/stratiform components, and vertical variabilities (2–10 km). The U.S. Central Plains and Argentina are associated with the largest Dm in a deep layer. Tropical Africa has larger Dm and standard deviation than Amazon. Large convective Dm occurs at high latitudes of Eurasia and North America in summer; the Southern Hemisphere high latitudes have shallower systems with smaller Dm. Oceanic storm tracks in both hemispheres have relatively large Dm, particularly for convective Dm in winter. Relatively small Dm occurs over tropical oceans, including ITCZ, requiring further investigation.

Mei Han↗
NASA NTRS2023

Orbital Collector Concept

This is a concept for a system that can perform most aspects of recycling/manufacturing in zero-g & low-g space environments. The system consists primarily of a rotating arm that provides artificial gravity, power, data, and mechanical connections to different modules designed for individual aspects of recycling/manufacturing. The modules are designed to contain the materials being processed, thereby preventing the system from generating external debris during recycling/manufacturing. This system is designed to complement the abilities of the Orbital Workshop (see NTR 1662994822).

manufacturing↗
DOE OSTI2021

Personal Resiliency Index

A plethora of information exists in literature focusing on different aspects of personal resilience. There are a number of questionnaires available to measure resilience in different aspects of an individual’s life, such as mental health. However, there is a lack of comprehensive information on the subject of personal resilience to natural and man-made disasters. A Personal Resiliency Index identifying four key areas of resilience related to natural and man-made disasters will help fill this gap by providing individuals an idea of where the stand comparatively to their peers on this topics. As an increasing amount of man-made disasters, natural disasters and pandemics occur, we realize that preparation is key.?“Crisis can be experienced at individual, group and mass levels and at local, regional, national or supra-national levels.” 1? Dr. Ron Fisher, the principal investigator has over 20 years’ critical infrastructure protection including developing vulnerability assessment methodology, risk and resiliency analyses and infrastructure interdependencies. Dr. Fisher and his team will research and develop a voluntary survey which evaluates the user’s personal resilience level to natural and man-made disasters. The research team is focusing on 4 main categories:? financial resilience, cyber security, physical and mental health, and emergency preparedness.?The web based application will?provide a resilience score for each of the categories and also a comprehensive personal resiliency score based on the voluntary survey. The application will also provide feedback to the user on actions to take to become more resilient to natural and man-made disasters. Through this effort, we will also be able to identify the areas where participants are excelling as well as opportunities for improvement in terms of resilience. This information will provide insight into areas of further investigation and identify potential areas of support needed for the general public to adopt strategies to become more resilient. 1 Lynott, William. “Surviving a Natural (or Man-Made) Disaster: How to Prepare for and Bounce Back? from a Crisis in Your Business | 2018-02-01 | NOLN.” Home Page, NOLN, 1 Feb. 2018, https://www.noln.net/articles/2683-surviving-a-natural-or-man-made-disaster-how-to-prepare-for-and-bounce-back-from-a-crisis-in-your-business.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Magnetic properties of CrFeCoNi based high entropy alloys

Monte Carlo simulations are performed on three high entropy alloys: Cr0.25Fe0.25Co0.25Ni0.25, Cr0.2Fe0.2Co0.2Ni0.2Pd0.2, and Cr0.2Mn0.2Fe0.2Co0.2Ni0.2, with exchange interactions extracted from The ab initio Korringa-Kohn-Rostoker method combined with the coherent potential approximation calculations. Using finite size scaling analyses, we estimate the magnetic phase transition temperature for the four component alloy to be 108(2) K, and although the individual critical exponents are different from 3D Heisenberg universality class, the reduced exponent follows Suzuki weak universality. With the additional Palladium component, the transition temperature elevates to about 200 K. In contrast, we find no magnetic order for the five component alloy with Manganese at any finite temperatures.

Yin, Junqi↗
DOE OSTI2021

Accelerate Nuclear Research and Development by Reducing Time and Cost Spend in the Pre-conceptual Design Phase of Advanced Reactor Experiments

The design process of every new concept, such as advanced nuclear reactors or associated experiments, starts with the pre-conceptual design phase. In this phase, the viability of a wide range of design options needs to be assessed quickly, to understand the operating envelope and its feasibility. A variety of physics models (thermal-hydraulics, neutronics, mechanical design, etc.) has to be considered at this very first design stage and optimum component sizes and materials (e.g. heat exchangers, piping, turbomachinery, coolant type, etc.) have to be chosen for a given set of boundary conditions (e.g. heat source, heat sink, flow rate, etc.). Detailed solutions such as provided by high fidelity methods like computational fluid dynamics (CFD), Monte Carlo methods, etc. and even lower fidelity tools such as system or subchannel codes, etc. are usually not used during the pre-conceptual design due to the relatively long time needed to create input models, the computational time to obtain a solution and the lack of flexibility to quickly investigate different combinations of components, individual component sizes and material properties. High fidelity tools are usually only employed in the conceptual design and later phases once a base concept has been identified during the pre-conceptual design stage. The current practice during the pre-conceptual design stage is that analysts collect the needed equations, material properties, closure laws, etc. and create ad-hoc solutions form scratch for every new problem. There clearly is a lack of a flexible scoping tool that can be used during pre-conceptional design before higher fidelity tools (as described above) come into play. To reduce user errors in ad-hoc solutions and increase fidelity and efficiency, this project aims to investigate and develop a user-friendly scoping tool to address the thermal-hydraulic designing needs during preconceptual experiment design, i.e. Thermal-hydraulic Research Universal Scoping Tool (TRUST). The success of TRUST will provide the nuclear engineers with an easy-to-use and affordable calculator for early reactor system design and optimization.

42 ENGINEERING↗
DOE OSTI2022

Devices and methods for increasing the speed and efficiency at which a computer is capable of modeling a plurality of random walkers using a particle method

A method for increasing a speed or energy efficiency at which a computer is capable of modeling a plurality of random walkers. The method includes defining a virtual space in which a plurality of virtual random walkers will move among different locations in the virtual space. The method also includes either assigning a corresponding set of ringed neurons in a spiking neural network to a corresponding virtual random walker, or assigning a corresponding set of ringed neurons to a point in the virtual space. Movement of a given virtual random walker is tracked by decoding differences between states of individual neurons in a corresponding given set of ringed neurons. A virtual random walk of the plurality of virtual random walkers is executed using the spiking neural network.

Aimone, James Bradley↗