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Results for “extractants”

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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Intestinal microbiome profile of the brown rock sea cucumber ( Holothuria glaberrima ) using ITS and 16S rDNA amplicons from direct mechanical, enzymatic, and chemical metagenomic extraction

Using direct mechanical, enzymatic, and chemical extraction methods, the intestinal microbiome of the marine invertebrate Holothuria glaberrima was obtained. ITS and 16S rDNA regions were sequenced to enrich and investigate the prokaryotic and fungal diversity profiles from different anatomical regions within the sea cucumber’s intestinal biology.

16S↗
DOE OSTI2021

Mapathons versus automated feature extraction: a comparative analysis for strengthening immunization microplanning

Background: Social instability and logistical factors like the displacement of vulnerable populations, the difficulty of accessing these populations, and the lack of geographic information for hard-to-reach areas continue to serve as barriers to global essential immunizations (EI). Microplanning, a population-based, healthcare intervention planning method has begun to leverage geographic information system (GIS) technology and geospatial methods to improve the remote identification and mapping of vulnerable populations to ensure inclusion in outreach and immunization services, when feasible. We compare two methods of accomplishing a remote inventory of building locations to assess their accuracy and similarity to currently employed microplan line-lists in the study area. Methods: The outputs of a crowd-sourced digitization effort, or mapathon, were compared to those of a machine-learning algorithm for digitization, referred to as automatic feature extraction (AFE). The following accuracy assessments were employed to determine the performance of each feature generation method: (1) an agreement analysis of the two methods assessed the occurrence of matches across the two outputs, where agreements were labeled as “befriended” and disagreements as “lonely”; (2) true and false positive percentages of each method were calculated in comparison to satellite imagery; (3) counts of features generated from both the mapathon and AFE were statistically compared to the number of features listed in the microplan line-list for the study area; and (4) population estimates for both feature generation method were determined for every structure identified assuming a total of three households per compound, with each household averaging two adults and 5 children. Results: The mapathon and AFE outputs detected 92,713 and 53,150 features, respectively. A higher proportion (30%) of AFE features were befriended compared with befriended mapathon points (28%). The AFE had a higher true positive rate (90.5%) of identifying structures than the mapathon (84.5%). The difference in the average number of features identified per area between the microplan and mapathon points was larger (t = 3.56) than the microplan and AFE (t = -2.09) (alpha = 0.05). Conclusions: Our findings indicate AFE outputs had higher agreement (i.e., befriended), slightly higher likelihood of correctly identifying a structure, and were more similar to the local microplan line-lists than the mapathon outputs. These findings suggest AFE may be more accurate for identifying structures in high-resolution satellite imagery than mapathons. However, they both had their advantages and the ideal method would utilize both methods in tandem.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Life cycle greenhouse gas emissions of ethanol produced via fermentation of sugars derived from shrub willow (Salix ssp.) hot water extraction in the Northeast United States

Abstract Background The amount of carbon dioxide in the atmosphere has been on the rise for more than a century. Bioenergy crops are seen by the Intergovernmental Panel on Climate Change as an essential part of the solution to addressing climate change. To understand the potential impact of shrub willow ( Salix spp . ) crop in the northeast United States, effective and transparent life cycle assessment of these systems needs to occur. Results Here we show, ethanol produced from the fermentation of sugars from hot water extract of willow grown on cropland can sequester 0.012 ± 0.003 kg CO 2eq MJ −1 for a supply system incorporating summer harvest and storage. Despite decreases in soil organic carbon when willow is instead grown on grassland, the produced fuel still can provide significant climate benefits compared to gasoline. Conclusions Shrub willow converted to ethanol can be a carbon negative source of transportation fuel when the electricity and heat required for the conversion process are generated from renewable biomass. The sequestration of carbon in the belowground portion of the plants is essential for the negative GHG balance for cropland and low GHG emissions in grassland.

10 SYNTHETIC FUELS↗
DOE OSTI2024

Targeted Rare Earth Element Extraction from Mine Drainage Treatment Solids Informed by Advanced Characterization

In support of a clean energy transition in the U.S., National Energy Technology Laboratory (NETL) has collaborated with staff at Hedin Environmental and students at the University of Pittsburgh to characterize critical mineral content and recovery potential from acid mine drainage treatment solids (AMD solids). AMD solids in Appalachia are an unconventional feedstock of rare earth elements (REEs), with potential of suppling 1,102 tons REE/year. To inform recovery efforts, select AMD solids were examined using synchrotron microprobe analysis in conjunction with USGS-developed geochemical modeling to indicate likely phases hosting critical minerals (REE, Co, Ni, etc.) and associated metals . More than 100 AMD solids were collected from 94 passive AMD treatment systems in Pennsylvania, where limestone aggregates are used for acidity neutralization. As pH increases, dissolved metals and critical minerals in AMD are attenuated as surface coatings on limestone. The collected AMD solids contained up to 2000 mg/kg REE, up to 13,000 mg/kg transition metals (Co, Ni, Zn) and up to 440 mg/kg Li. Regardless of the diverse chemical compositions from AMD solids (Al-rich, Mn-rich, or Al,Fe,Mn-rich), REEs were mostly associated with Al and Mn (hydr)oxides, while select heavy REEs (e.g., Gd, Dy) were co-localized with Fe (hydr)oxides. Co and Ni have different distribution zones, while both co-localized with Mn (hydr)oxides. Based on this characterization, NETL developed a patent-pending innovative step-leaching protocol, “Targeted Rare Earth Extraction (TREE)” to effectively recover up to 90% REE and 60% Co in separate steps. In addition, select post-TREE solid residuals (purified Al oxides, or Mn oxides) can be further developed into functional materials (e.g., lithium and CO2 sorbents) needed for green energy transition and carbon management. This characterization-informed approach as well as TREE processing from AMD solids can be used for other legacy wastes (e.g., coal ash, oil and gas drill cutting, mine tailings), and offers an opportunity to transform waste streams into environmental and economic assets that meet U.S. Department of Energy and U.S. Environmental Protection Agency goals.

characterization and extraction of rare earth elem↗
NASA NTRS1967

A parameter extraction technique

Parameter extraction technique, based on algebraic approach, to video data displayed in histogram form and implemented for IMP flights

IMP↗
NASA NTRS2003

A computational-grid based system for continental drainage network extraction using SRTM digital elevation models

We describe a new effort for the computation of elevation derivatives using the Shuttle Radar Topography Mission (SRTM) results. Jet Propulsion Laboratory's (JPL) SRTM has produced a near global database of highly accurate elevation data. The scope of this database enables computing precise stream drainage maps and other derivatives on Continental scales. We describe a computing architecture for this computationally very complex task based on NASA's Information Power Grid (IPG), a distributed high performance computing network based on the GLOBUS infrastructure. The SRTM data characteristics and unique problems they present are discussed. A new algorithm for organizing the conventional extraction algorithms [1] into a cooperating parallel grid is presented as an essential component to adapt to the IPG computing structure. Preliminary results are presented for a Southern California test area, established for comparing SRTM and its results against those produced using the USGS National Elevation Data (NED) model.

stream extraction↗
NASA NTRS2015

Regolith and Environment Science and Oxygen and Lunar Volatile Extraction (RESOLVE): Lunar Advanced Volatile Analysis (LAVA) Capillary Fluid Dynamic Restriction Effects on Gas Chromatography

The Resource Prospector (RP) mission with the Regolith and Environment Science and Oxygen Lunar Volatile Extraction (RESOLVE) payload aims to show the presence of water in lunar regolith, and establish a proving ground for NASAs mission to Mars. One of the analysis is performed by the Lunar Advanced Volatiles Analysis (LAVA) subsystem, which consists of a fluid network that facilitates the transport of volatile samples to a gas chromatograph and mass spectrometer (GC-MS) instrument. The understanding of fluid dynamics directed from the GC to the MS is important due to the influence of flow rates and pressures that affect the accuracy of and prevent the damage to the overall GC-MS instrument. The micro-scale capillary fluid network within the GC alone has various lengths and inner-diameters; therefore, determination of pressure differentials and flow rates are difficult to model computationally, with additional complexity from the vacuum conditions in space and lack of a lunar atmosphere. A series of tests were performed on an experimental set-up of the system where the inner diameters of the GC transfer line connecting to the MS were varied. The effect on chromatography readings were also studied by applying these lines onto a GC instrument. It was found that a smaller inner diameter transfer line resulted in a lower flow rate, as well as a lower pressure differential across the thermal conductivity detector (TCD) unit of the GC and a negligible pressure drop across the mock-up capillary column. The chromatography was affected with longer retention times and broader peak integrations. It was concluded that a 0.050 mm inner diameter line still proved most suitable for the systems flow rate preferences. In addition, it was evident that this small transfer line portrayed some expense to GC signal characteristics and the wait time for steady-state operation.

RESOLVE↗
NASA NTRS2015

RESOLVE - Regolith and Environment Science and Oxygen and Lunar Volatile Extraction

The Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) payload is an exploration system designed to be placed on a rover and driven over the surface of the moon for 9 days to map the distribution of the water ice and other useful compounds seen on previous missions. RESOLVE will drill into the lunar surface and heat the material collected in order to measure the amount of water vapor and other compounds that are present, thus showing how future missions could gather and then use these valuable resources. Future missions will benefit from this analysis tool and others because it will be more cost-effective to mine water components, fuel, and other compounds at the point of destination rather than transport them from Earth. NASA is packaging the RESOLVE payload in the Resource Prospector mission targeted for launch in 2020. NASA continues to explore mission solutions by leveraging partnerships across NASA, industry, other nations and academia.

RESOLVE↗
NASA NTRS2015

FJET Database Project: Extract, Transform, and Load

The Data Mining & Knowledge Management team at Kennedy Space Center is providing data management services to the Frangible Joint Empirical Test (FJET) project at Langley Research Center (LARC). FJET is a project under the NASA Engineering and Safety Center (NESC). The purpose of FJET is to conduct an assessment of mild detonating fuse (MDF) frangible joints (FJs) for human spacecraft separation tasks in support of the NASA Commercial Crew Program. The Data Mining & Knowledge Management team has been tasked with creating and managing a database for the efficient storage and retrieval of FJET test data. This paper details the Extract, Transform, and Load (ETL) process as it is related to gathering FJET test data into a Microsoft SQL relational database, and making that data available to the data users. Lessons learned, procedures implemented, and programming code samples are discussed to help detail the learning experienced as the Data Mining & Knowledge Management team adapted to changing requirements and new technology while maintaining flexibility of design in various aspects of the data management project.

excel vba↗
NASA NTRS2015

Swamp Works: A New Approach to Develop Space Mining and Resource Extraction Technologies at the National Aeronautics Space Administration (NASA) Kennedy Space Center (KSC)

The first steps for In Situ Resource Utilization (ISRU) on target bodies such as the Moon, Mars and Near Earth Asteroids (NEA), and even comets, involve the same sequence of steps as in the terrestrial mining of resources. First exploration including prospecting must occur, and then the resource must be acquired through excavation methods if it is of value. Subsequently a load, haul and dump sequence of events occurs, followed by processing of the resource in an ISRU plant, to produce useful commodities. While these technologies and related supporting operations are mature in terrestrial applications, they will be different in space since the environment and indigenous materials are different than on Earth. In addition, the equipment must be highly automated, since for the majority of the production cycle time, there will be no humans present to assist or intervene. This space mining equipment must withstand a harsh environment which includes vacuum, radical temperature swing cycles, highly abrasive lofted dust, electrostatic effects, van der Waals forces effects, galactic cosmic radiation, solar particle events, high thermal gradients when spanning sunlight terminators, steep slopes into craters / lava tubes and cryogenic temperatures as low as 40 K in permanently shadowed regions. In addition the equipment must be tele-operated from Earth or a local base where the crew is sheltered. If the tele-operation occurs from Earth then significant communications latency effects mandate the use of autonomous control systems in the mining equipment. While this is an extremely challenging engineering design scenario, it is also an opportunity, since the technologies developed in this endeavor could be used in the next generations of terrestrial mining equipment, in order to mine deeper, safer, more economical and with a higher degree of flexibility. New space technologies could precipitate new mining solutions here on Earth. The NASA KSC Swamp Works is an innovation environment and methodology, with associated laboratories that uses lean development methods and creativity-enhancing processes to invent and develop new solutions for space exploration. This paper will discuss the Swamp Works approach to developing space mining and resource extraction systems and the vision of space development it serves. The ultimate goal of the Swamp Works is to expand human civilization into the solar system via the use of local resources utilization. By mining and using the local resources in situ, it is conceivable that one day the logistics supply train from Earth can be eliminated and Earth independence of a space-based community will be enabled.

Resource Extraction↗
NASA NTRS2019

Extraction of Dynamic Inflow Models for Coaxial and Tandem Rotors from CFD Simulations

The dynamic inflow coupling with rotor/body dynamics is crucial in the analysis of stability and control law design for helicopters. Over the past several decades, finite-state inflow models for single rotor configurations in hover, forward flight, and maneuver have developed (Ref.1-3). By capturing the interference effects between rotors, the extension of pressure potential finite state inflow model has promising result for coaxial rotor configuration (Ref.4-6). Recently, the focus of the dynamic inflow modeling has shifted to tandem rotor configurations (Ref.7, 8). The development of the dynamic inflow models for tandem rotor configuration still have some limitations due to the lack of knowledge of rotor-to-rotor interference, and rotor-wake interference. Experimental methods, and computational fluid dynamics methods are commonly used to understand the rotor performance and rotor airload variations, and measure or predict inflow velocity distributions at the rotor desk. The inflow distributions are subsequently used to improve the dynamic inflow models. Tandem rotor configurations have been studied experimentally and computationally for several decades (Ref.9-12). Sweet (Ref.10) observed that a tandem rotor with 76-percent-radius overlap required 14% more induced power at hovering condition, relative to an isolated rotor of equivalent disk area. Sweet also found that, above a shaft-to-shaft distance of 1.03 diameter, the performance of the tandem rotor was nearly the same as two isolated rotors. The objective of the present study is to apply computational fluid dynamics simulations of tandem rotors for the extraction of dynamic inflow models. The extended methodology is first validated by comparing the computed induced power against test data. Subsequently inflow distributions and wake structures are analyzed.

Extraction of Dynamic Inflow Models↗
NASA NTRS2023

Machine Learning Framework for Hazard Extraction and Analysis of Trends (HEAT) in Wildfire Response

This research proposes a natural language processing enabled risk analysis framework, named Hazard Extraction andAnalysis of Trends (HEAT), and applies the framework to the ICS-209-PLUS data set of wildfire incident responseforms. The HEAT framework produces safety- and risk- relevant analyses, consisting of: (1) a set of hazards extractedfrom text data, (2) a primary analysis using hazard-relevant metrics, such as rate and severity, to form an FMEA-styletable and risk matrix, (3) a time series analysis of metric trends, and (4) a secondary analysis examining potentialpredictors for hazards. Results from HEAT provide quantitative risk-relevant information for high-level hazards doc-umented in existing-state operations. Because of the generalizability of the steps and limited data requirements, HEATcan be applied to any dataset containing narrative text, thus providing a framework for data-driven machine learning-enabled quantitative risk analysis across a variety of domains. To demonstrate HEAT in a case study, we apply theframework to the ICS-209-PLUS dataset of wildland fire incident response forms. Hazards identified in wildfire re-sponse arise from environmental conditions, the mission, and the wildland urban interface. The resulting risk matrixidentifies evacuations as high-risk hazards, while all other identified hazards are medium or serious risk.

natural language processing↗