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At least 1,027 records · Page 57

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Analyzing Mass Spectrometry Imaging Data of 13C-Labeled Phospholipids in Camelina sativa and Thlaspi arvense (Pennycress) Embryos

The combination of 13C-isotopic labeling and mass spectrometry imaging (MSI) offers an approach to analyze metabolic flux in situ. However, combining isotopic labeling and MSI presents technical challenges ranging from sample preparation, label incorporation, data collection, and analysis. Isotopic labeling and MSI individually create large, complex data sets, and this is compounded when both methods are combined. Therefore, analyzing isotopically labeled MSI data requires streamlined procedures to support biologically meaningful interpretations. Using currently available software and techniques, here we describe a workflow to analyze 13C-labeled isotopologues of the membrane lipid and storage oil lipid intermediate―phosphatidylcholine (PC). Our results with embryos of the oilseed crops, Camelina sativa and Thlaspi arvense (pennycress), demonstrated greater 13C-isotopic labeling in the cotyledons of developing embryos compared with the embryonic axis. Greater isotopic enrichment in PC molecular species with more saturated and longer chain fatty acids suggest different flux patterns related to fatty acid desaturation and elongation pathways. The ability to evaluate MSI data of isotopically labeled plant embryos will facilitate the potential to investigate spatial aspects of metabolic flux in situ.

metabolomics↗

NASA NTRS1977

Feeding the feeder

Too often the equipment used to move difficult to handle powdery material from a hopper to process creates a complex of devices whose end result falls short on good performance...simply because equipment design, in many cases, has not kept up with advanced technological concepts in fine powder handling. The Feeder, being the key to an efficient feed system, must be assured a continuous flow from the storage tank...without bridging, arching, spasmodic flow or uncontrolled flushing. The causes and effects of flow problems are discussed and also solutions are offered based on the combination of theoretical and practical experience.

Kurylchek, A. L.↗

NASA NTRS1992

Building a generalized distributed system model

The key elements in the second year (1991-92) of our project are: (1) implementation of the distributed system prototype; (2) successful passing of the candidacy examination and a PhD proposal acceptance by the funded student; (3) design of storage efficient schemes for replicated distributed systems; and (4) modeling of gracefully degrading reliable computing systems. In the third year of the project (1992-93), we propose to: (1) complete the testing of the prototype; (2) enhance the functionality of the modules by enabling the experimentation with more complex protocols; (3) use the prototype to verify the theoretically predicted performance of locking protocols, etc.; and (4) work on issues related to real-time distributed systems. This should result in efficient protocols for these systems.

Mukkamala, R.↗

NASA NTRS1999

STS-96 FD Highlights and Crew Activities Report: Flight Day 06

On this sixth day of the STS-96 Discovery mission, the flight crew, Commander Kent V. Rominger, Pilot Rick D. Husband, and Mission Specialists Ellen Ochoa, Tamara E. Jernigan, Daniel T. Barry, Julie Payette, and Valery Ivanovich Tokarev are seen performing logistics transfer activities within the Discovery/International Space Station orbiting complex. Ochoa, Jernigan, Husband and Barry devote a significant part of their day to the transfer of bags of different sizes and shapes from the SPACEHAB module in Discovery's cargo bay to resting places inside the International Space Station. Payette and Tokarev complete the maintenance on the storage batteries. Barry and Tokarev complete installation of the remaining sound mufflers over the fans in Zarya. Barry then measures the sound levels at different positions inside the module. Rominger and Tokarev conduct a news conference with Russian reporters from the Mission Control Center in Moscow.

Source record↗

NASA NTRS2015

MAST Propellant and Delivery System Design Methods

A Mars Aerospace Taxi (MAST) concept and propellant storage and delivery case study is undergoing investigation by NASA's Element Design and Architectural Impact (EDAI) design and analysis forum. The MAST lander concept envisions landing with its ascent propellant storage tanks empty and supplying these reusable Mars landers with propellant that is generated and transferred while on the Mars surface. The report provides an overview of the data derived from modeling between different methods of propellant line routing (or "lining") and differentiate the resulting design and operations complexity of fluid and gaseous paths based on a given set of fluid sources and destinations. The EDAI team desires a rough-order-magnitude algorithm for estimating the lining characteristics (i.e., the plumbing mass and complexity) associated different numbers of vehicle propellant sources and destinations. This paper explored the feasibility of preparing a mathematically sound algorithm for this purpose, and offers a method for the EDAI team to implement.

Taxi↗

NASA NTRS2017

A Pan-Tropical Cascade of Fire Driven by El Nino/Southern Oscillation

The El Nino/Southern Oscillation (ENSO) has a pronounced influence on year-to-year variations in climate. The response of fires to this forcing is complex and has not been evaluated systematically across different continents. Here we use satellite data to create a climatology of burned-area and fire emissions responses, drawing on six El Nino and six La Nina events during 1997-2016. On average, reductions in precipitation and terrestrial water storage increased fire emissions in pan-tropical forests by 133% during and following El Nino as compared with La Nina. Fires peaked in equatorial Asia early in the ENSO cycle when El Nino was strengthening (Aug-Oct), before moving to southeast Asia and northern South America (Jan-Apr), Central America (Mar-May) and the southern Amazon (Jul-Oct) during the following year. Large decreases in fire occurred across northern Australia during Sep-Oct of the second year from a reduced fuel availability. Satellite observations of aerosols and carbon monoxide provided independent confirmation of the spatiotemporal evolution of fire anomalies. The predictable cascade of fire across different tropical continents described here highlights an important time delay in the Earth system's response to precipitation redistribution. These observations help to explain why the growth rate of atmospheric CO2 increases during El Nino and may contribute to improved seasonal fire forecasts.

Chen, Yang↗

NASA NTRS2022

Optimal Estimation Framework for Ocean Color Atmospheric Correction and Pixel-level Uncertainty Quantification

Ocean color remote sensing requires compensation for atmospheric scattering and absorption (aerosol, Rayleigh, and trace gases), referred to as atmospheric correction (AC). AC allows inference of parameters such as spectrally resolved remote sensing reflectance ( R rs )(λ) ; sr 1 ) at the ocean surface from the top-of-atmosphere reflectance. Often, the uncertainty of this process is not fully explored. Bayesian inference techniques provide a simultaneous AC and uncertainty assessment via a full posterior distribution of the relevant variables, given the prior distribution of those variables and the radiative transfer (RT) likelihood function. Given uncertainties in the algorithm inputs, the Bayesian framework enables better constraints on the AC process by using the complete spectral information compared to traditional approaches that use only a subset of bands for AC. This paper investigates a Bayesian inference research method (Optimal Estimation, OE) for ocean color AC by simultaneously retrieving atmospheric and ocean properties using all visible and near-infrared spectral bands. The OE algorithm analytically approximates the posterior distribution of parameters based on normality assumptions and provides a potentially viable operational algorithm with a reduced computational expense. We developed a Neural Network (NN) RT forward model look-up-table-based emulator to increase algorithm efficiency further and thus speed up the likelihood computations. We then applied the OE algorithm to synthetic data and observations from the MODerate resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua spacecraft. We compared the R rs )(λ) retrieval and its uncertainty estimates from the OE method with in-situ validation data from the SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and Aerosol Robotic Network Ocean Color (AERONET-OC) datasets. The OE algorithm improved R rs )(λ) estimates relative to the NASA standard operational algorithm by improving all statistical metrics at 443, 555, and 667 nm. Unphysical negative R rs )(λ) , which often appear in complex water conditions, was reduced by a factor of 3. The OE-derived pixel-level R rs )(λ) uncertainty estimates were also assessed relative to in-situ data and were shown to have skill.

Atmospheric correction↗

NASA NTRSDate not supplied

Development and Testing of a New Partial Gravity Urine Processor Design and Urine Pretreatment

The Planetary Urine Processor (PUP) is a urine distillation system for lunar or planetary applications, taking advantage of local gravity for phase separation as well as the movement and storage of waste feeds and distillate. The PUP utilizes a stationary evaporator with an integrated disposable bag to process urine and capture remaining precipitates. This system aims to increase water reclamation percentage to greater than 96%, reduce resource requirements, and enhance reliability and maintainability due to lower system complexity over the existing water recovery system on the International Space Station (ISS). This paper focuses on the hardware development, testing efforts, and the associated urine pretreatment development work.

Water Recovery↗

NASA NTRSDate not supplied

Development and Testing of a New Partial Gravity Urine Processor Design and Urine Pretreatment

Water Recovery↗

NASA NTRSDate not supplied

Application of System-Theoretic Process Analysis (STPA) to a NASA Concept Electric Aircraft Battery System

System-Theoretic Process Analysis (STPA) is a systems-based hazard analysis method that identifies unsafe interactions and control deficiencies in complex systems but has been rarely used for NASA programs in favor of more well-established hazard analyses. To evaluate its applicability, a NASA Safety and Mission Assurance (SMA) team applied the STPA method to an early-stage hybrid electrified aircraft concept, focusing on the energy storage system and electric powertrain. Objectives include assessing STPA’s value relative to traditional methods and its suitability for early design phases. Activities include team training, system review, detailed STPA execution, and comparison with traditional analyses. Findings show STPA provides a structured, comprehensive hazard evaluation and can identify additional risks by expanding analysis boundaries. However, traditional methods can yield similar results when applied rigorously, though they typically require more mature designs. Overall, STPA is a valuable addition, particularly for early development, informing safety requirements and supporting preliminary hazard analyses. Further pilot applications are recommended.

Electric Aviation↗

DOE OSTI2023

Flexible Fully-Decoupled Nuclear Plants with Thermal Energy Storage - Technoeconomic Optimization

New nuclear power plants may be one of the technologies for future zero carbon electricity production. These future systems will however also need significant flexibility to cope with fluctuating demand and large share of intermittent renewable supply, rather than running in conventional baseload generation. The present work explores the use of thermal energy storage (TES) as a buffer between the reactor heat and its conversion to electricity, enabling flexible operation of nuclear plants. The focus is on maximizing flexibility, ideally as full decoupling of the nuclear and power cycle islands, as well as on system efficiency in various modes. A system design presented for a high temperature gas cooled reactor (HTGR) presents a slightly complex solution, as separate high- and low-temperature TES systems are required in order to cover the extended temperature range. Although this configuration imposes certain limitations on the discharge system configuration, it also presents the opportunity to design a more efficient system. For this case in particular, a steam reheat cycle is advantageous. Dynamic models were developed for the decoupled system in order to generate insights into aspects of off design operation and system control. A technoeconomic analysis, furthermore, provides sizing and costing of the component, followed by size and dispatch economic optimization considering energy arbitrage. This optimization shows that in all explored markets, the addition of TES system with the proposed configuration results in positive impact on project net present value. Further sensitivity analyses show impact of multiple inputs and possible technical limitations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

High‐Entropy Lithium Argyrodite Solid Electrolytes Enabling Stable All‐Solid‐State Batteries

Abstract Superionic solid electrolytes (SEs) are essential for bulk‐type solid‐state battery (SSB) applications. Multicomponent SEs are recently attracting attention for their favorable charge‐transport properties, however a thorough understanding of how configurational entropy (ΔS conf ) affects ionic conductivity is lacking. Here, we successfully synthesized a series of halogen‐rich lithium argyrodites with the general formula Li 5.5 PS 4.5 Cl x Br 1.5‐x (0≤x≤1.5). Using neutron powder diffraction and 31 P magic‐angle spinning nuclear magnetic resonance spectroscopy, the S 2− /Cl − /Br − occupancy on the anion sublattice was quantitatively analyzed. We show that disorder positively affects Li‐ion dynamics, leading to a room‐temperature ionic conductivity of 22.7 mS cm −1 (9.6 mS cm −1 in cold‐pressed state) for Li 5.5 PS 4.5 Cl 0.8 Br 0.7 (ΔS conf =1.98R). To the best of our knowledge, this is the first experimental evidence that configurational entropy of the anion sublattice correlates with ion mobility. Our results indicate the possibility of improving ionic conductivity in ceramic ion conductors by tailoring the degree of compositional complexity. Moreover, the Li 5.5 PS 4.5 Cl 0.8 Br 0.7 SE allowed for stable cycling of single‐crystal LiNi 0.9 Co 0.06 Mn 0.04 O 2 (s‐NCM90) composite cathodes in SSB cells, emphasizing that dual‐substituted lithium argyrodites hold great promise in enabling high‐performance electrochemical energy storage.

Chemistry↗

NASA NTRS1992

SNS programming environment user's guide

This document briefly describes the computing environment for the Supercomputing Network Subsystem (SNS) of the Central Scientific Computing Complex of the Langley Research Center. The major SNS computers are a CRAY-2, a CRAY Y-MP, a CONVEX C-210, and a CONVEX C-220. It describes the software that is common to all of these computers, including; the UNIX operating system, graphics, networking utilities, mass storage, and mathematical libraries. It also describes file management, validation, SNS configuration, documentation and customer services. The document is intended for all SNS users as a ready reference to frequently asked questions and to more detailed information contained within the vendor manuals. It is appropriate for both the novice and the experienced user.

Supercomputing↗

DOE OSTI2023

Machine learning and deep learning for mineralogy interpretation and CO 2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin

Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO 2 ) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO 2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO 2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO 2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO 2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. In conclusion, the study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.

58 GEOSCIENCES↗

DOE OSTI2023

Methane Partial Oxidation over Multifunctional 2-D Materials

The objective of this research is to design, synthesize, and evaluate highly selective, active, and stable multifunctional catalysts for the low temperature (< 500 Kelvin (K)) partial oxidation of methane to methanol (MTM) with molecular oxygen: CH 4 (g) + $\frac{1}{2}$O 2 (g) → CH 3 OH(g). Methane, the primary component of natural gas, is a source of energy and economic growth as well as an environmental concern. Recent developments in horizontal drilling and enhanced extraction methods have resulted in production of an estimated 62.4 trillion m 3 of ‘stranded’, or uneconomic, natural gas. Uneconomical natural gas is often flared or vented at remote oil production sites. Leaked, flared, and/or vented gas represents a "lost opportunity”, and this research project aims to maximize the value of the resource. Conventional catalysts for MTM suffer from low methanol selectivity since they exhibit ~0.55 eV higher barrier for C-H bond activation of methane compared to methanol. Without breaking these scaling relations, methanol oxidation is orders of magnitude faster than methane oxidation and it is very challenging to envision a process with economically viable single-pass yield. Here, we chose to investigate single-atom catalysts embedded and stabilized in two-dimensional materials such as graphene (GR) and "supported" on Group VIII and IB transition metals such as nickel. The electronic atomic monolayer-metal support interaction (EAMSI) present in these systems could promote methanol selectivity by breaking the scaling relations of the C-H bond activation of methane and methanol. A density functional theory (DFT) based computational study focused on predicting families of GR-based catalysts that could be active and selective for MTM. The catalyst systems predicted by the computational study were synthesized and evaluated for the gas phase MTM under relevant conditions. Unfortunately, the experimental activity and selectivity was lower than computationally predicted. The origin for the discrepancy is likely related to difficulties in synthesizing single atom catalysts in a threecomponent catalyst system at high density and with high selectivity. Future work in our groups is thus focused on reducing the system complexity to a two-component catalyst system. Finally, a techno-economic analysis (TEA) was also conducted to identify critical bottlenecks that inhibit future commercialization.

03 NATURAL GAS↗

DOE OSTI2024

Ion-specific phenomena limit energy recovery in forward-biased bipolar membranes

The ability for bipolar membranes (BPMs) to interconvert voltage and pH makes them attractive materials for use in energy conversion and storage. Reverse-biased BPMs, which use electrical voltage to dissociate water into acid and base, have become increasingly well studied. However, forward-biased BPMs (FB-BPMs), in which voltage is extracted from pH gradients through recombination, require further study. Here physics-based modeling elucidates how the complex coupling of transport and kinetics dictates the performance of FB-BPMs in electrochemical devices. Simulations reveal that the open-circuit potential of FB-BPMs is dictated by the balance of ion recombination and crossover, where recombination of buffering counter-ions attenuates the open-circuit potential. Counter-ion mass-transport limitations and uptake of ionic impurities limit achievable current densities by reducing the applied pH gradient or the available fixed-charge sites that mediate recombination. Further, the model highlights the importance of selective ion management in mitigating energy losses and provides insight into the rational material design of FB-BPMs for energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Dissociative Recombination of Cold HeH + Ions

The HeH + cation is the simplest molecular prototype of the indirect dissociative recombination (DR) process that proceeds through electron capture into Rydberg states of the corresponding neutral molecule. This Letter develops the first application of our recently developed energy-dependent frame transformation theory to the indirect DR processes. The theoretical model is based on the multichannel quantum-defect theory with the vibrational basis states computed using exterior complex scaling of the nuclear Hamiltonian. The ab initio electronic R-matrix theory is adopted to compute quantum defects as functions of the collision energy and of the internuclear distance. The resulting DR rates are convolved over the beam energy distributions relevant to a recent experiment at the Cryogenic Storage Ring, giving good agreement between the experiment and the theory.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2025

A genome-scale metabolic model for the denitrifying bacterium Thauera sp. MZ1T accurately predicts degradation of pollutants and production of polymers

The denitrifying bacterium Thauera sp . MZ1T, a common member of microbial communities in wastewater treatment facilities, can produce different compounds from a range of carbon (C) and nitrogen (N) sources under aerobic and anaerobic conditions. In these different conditions, Thauera modifies its metabolism to produce different compounds that influence the microbial community. In particular, Thauera sp . MZ1T produces different exopolysaccharides with floc-forming properties, impacting the physical disposition of wastewater consortia and the efficiency of nutrient assimilation by the microbial community. Under N-limiting conditions, Thauera sp . MZ1T decreases its growth rate and accelerates the accumulation of polyhydroxyalkanoate-related (PHA) compounds including polyhydroxybutyrate (PHB), which plays a fundamental role as C and energy storage in this β-proteobacterium. However, the metabolic mechanisms employed by Thauera sp . MZ1T to assimilate and catabolize many of the different C and N sources under aerobic and anaerobic conditions remain unknown. Systems biology approaches such as genome-scale metabolic modeling have been successfully used to unveil complex metabolic mechanisms for various microorganisms. Here, we developed a comprehensive metabolic model (M-model) for Thauera sp . MZ1T ( i Thauera861), consisting of 1,744 metabolites, 2,384 reactions, and 861 genes. We validated the model experimentally using over 70 different C and N sources under both aerobic and anaerobic conditions. i Thauera861 achieved a prediction accuracy of 95% for growth on various C and N sources and close to 85% for assimilation of aromatic compounds under denitrifying conditions. The M-model was subsequently deployed to determine the effects of substrates, oxygen presence, and the C:N ratio on the production of PHB and exopolysaccharides (EPS), showing the highest polymer yields are achieved with nucleotides and amino acids under aerobic conditions. This comprehensive M-model will help reveal the metabolic processes by which this ubiquitous species influences communities in wastewater treatment systems and natural environments.

Tec-Campos, Diego (ORCID:0000000188194150)↗