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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrative Multi-PTM Proteomics Reveals Dynamic Global, Redox, Phosphorylation, and Acetylation Regulation in Cytokine-treated Pancreatic Beta Cells

Studying regulation of protein function at a systems level necessitates an understanding of the interplay among diverse post-translational modifications (PTMs). A variety of proteomics sample processing workflows are currently used to study specific PTMs but rarely characterize multiple types of PTMs from the same sample inputs. Method incompatibilities and laborious sample preparation steps complicate large-scale physiological investigations and can lead to variations in results. The single-pot, solid-phase-enhanced sample preparation (SP3) method for sample cleanup is compatible with different lysis buffers and amenable to automation, making it attractive for high-throughput multi-PTM profiling. Herein, we describe an integrative SP3 workflow for multiplexed quantification of protein abundance, cysteine thiol oxidation, phosphorylation, and acetylation. The broad applicability of this approach is demonstrated using cell and tissue samples, and its utility for studying interacting regulatory networks is highlighted in a time-course experiment of cytokine-treated ß-cells. We observed a swift response in global regulation of protein abundances consistent with rapid activation of JAK-STAT and NF-?B signaling pathways. Regulators of these pathways as well as proteins involved in their target processes displayed multi-PTM dynamics indicative of a complex cellular response stages: acute, adaptation, and chronic (prolonged stress). PARP14, a negative regulator of JAK-STAT, had multiple co-localized PTMs that may be involved in intraprotein regulatory crosstalk. Our workflow provides a high-throughput platform that can profile multi-PTMomes from the same sample set, which is valuable in unraveling the functional roles of PTMs and their co-regulation.

proteomics, PTM, automation, SP3, cysteine thiol o↗
NASA NTRS1991

Counterflow diffusion flames of hydrogen, and hydrogen plus methane, ethylene, propane, and silane vs. air - Strain rates at extinction

Five coaxial tubular opposed jet burners (OJBs) with tube diameter D(T) of 1.8-10 mm and 5 mm conical nozzles were used to form dish-shaped counterflow diffusion flames centered by opposing laminar jets of nitrogen and hydrocarbon-diluted H2 versus air in an argon-purged chamber at 1 atm. Area-averaged air jet velocities at blowoff of the central flame, U(air), characterized extinction of the airside flame as functions of input H2 concentration on the fuelside. A master plot of extensive U(air) data at blowoff versus D(T) shows that U(air) varies linearly with D(T). This and other data sets are used to find that nozzle OJB results for U(air)/diameter average 4.24 + or - 0.28 times larger than tubular OJB results for the same fuel compositions. Critical radial velocity gradients consistent with one-dimensional stagnation point boundary theory and with plug flow inputs are estimated. The results compare favorably with published numerical results based only on potential flow.

Pellett, G. L.↗
NASA NTRS1993

Computational Fluid Dynamic (CFD) analysis of axisymmetric plume and base flow of film/dump cooled rocket nozzle

Film/dump cooling a rocket nozzle with fuel rich gas, as in the National Launch System (NLS) Space Transportation Main Engine (STME), adds potential complexities for integrating the engine with the vehicle. The chief concern is that once the film coolant is exhausted from the nozzle, conditions may exist during flight for the fuel-rich film gases to be recirculated to the vehicle base region. The result could be significantly higher base temperatures than would be expected from a regeneratively cooled nozzle. CFD analyses were conduced to augment classical scaling techniques for vehicle base environments. The FDNS code with finite rate chemistry was used to simulate a single, axisymmetric STME plume and the NLS base area. Parallel calculations were made of the Saturn V S-1 C/F1 plume base area flows. The objective was to characterize the plume/freestream shear layer for both vehicles as inputs for scaling the S-C/F1 flight data to NLS/STME conditions. The code was validated on high speed flows with relevant physics. This paper contains the calculations for the NLS/STME plume for the baseline nozzle and a modified nozzle. The modified nozzle was intended to reduce the fuel available for recirculation to the vehicle base region. Plumes for both nozzles were calculated at 10kFT and 50kFT.

Tucker, P. K.↗
NASA NTRS2010

Testing to Characterize the Advanced Stirling Radioisotope Generator Engineering Unit

The Advanced Stirling Radioisotope Generator (ASRG), a high efficiency generator, is being considered for space missions. Lockheed Martin designed and fabricated an engineering unit (EU), the ASRG EU, under contract to the Department of Energy. This unit is currently undergoing extended operation testing at the NASA Glenn Research Center to generate performance data and validate life and reliability predictions for the generator and the Stirling convertors. It has also undergone performance tests to characterize generator operation while varying control parameters and system inputs. This paper summarizes and explains test results in the context of designing operating strategies for the generator during a space mission and notes expected differences between the EU performance and future generators.

Lewandowski, Edward↗
NASA NTRS2013

Testing of the Advanced Stirling Radioisotope Generator Engineering Unit at NASA Glenn Research Center

The Advanced Stirling Radioisotope Generator (ASRG) is a high-efficiency generator being developed for potential use on a Discovery 12 space mission. Lockheed Martin designed and fabricated the ASRG Engineering Unit (EU) under contract to the Department of Energy. This unit was delivered to NASA Glenn Research Center in 2008 and has been undergoing extended operation testing to generate long-term performance data for an integrated system. It has also been used for tests to characterize generator operation while varying control parameters and system inputs, both when controlled with an alternating current (AC) bus and with a digital controller. The ASRG EU currently has over 27,000 hours of operation. This paper summarizes all of the tests that have been conducted on the ASRG EU over the past 3 years and provides an overview of the test results and what was learned.

Lewandowski, Edward J.↗
NASA NTRS2014

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Current Insights and Trends

NASA or NOAA Earth-observing satellites are not the only space-based TIR platforms. The European Space Agency (ESA), the Chinese, and other countries have in orbit or plan to launch TIR remote sensing systems. Satellite remote sensing provides an excellent opportunity to study land-atmosphere energy exchanges at the regional scale. A predominant application of TIR data has been in inferring evaporation, evapotranspiration (ET), and soil moisture. In addition to using TIR data for ET and soil moisture analysis over vegetated surfaces, there is also a need for using these data for assessment of drought conditions. The concept of ecological thermodynamics provides a quantification of surface energy fluxes for landscape characterization in relation to the overall amount of energy input and output from specific land cover types.

Quattrochi, Dale A.↗
NASA NTRS2022

Advancing Solar Energetic Particle Forecasting

With growing interest from the aviation and satellite industries, and for NASA’s upcoming Artemis lunar missions, the need for improved scientific understanding and accurate forecasting of solar energetic particle events has never been stronger. In this paper we discuss the observational, validation and model transition support required to achieve these goals. Well-calibrated, high-quality energetic electron, proton, and ion measurements are essential. Expansions to the fields of view offered by current X-ray, extreme ultraviolet and coronagraph instruments, to obtain increased coverage of the solar corona and heliosphere, from vantage points off the Sun-Earth line, are desired for model input. New observations of suprathermal particles are needed to characterize seed particle distributions and low latency space-based observations of solar radio emissions are also desired. Together, this observational suite should offer high cadence, low latency, reliable and accurate space weather data streams. Consistent, extensive and quantitative model validation is required to assess scientific advancements and pave the way for models transitioning to real-time forecast operations. Model performance and skill should be compared to observations and to current operational forecasting baselines. Finally, resources are required to support the significant effort of transitioning mature models into forecast operations.

solar energetic particles↗
NASA NTRS1996

Automation of Data Analysis Programs Used in the Cryogenic Characterization of Superconducting Microwave Resonators

Knowledge of the microwave properties at cryogenic temperatures of components fabricated using High-Temperature-Superconductors (HTS) is useful in the design of HTS-based microwave circuits. Therefore, fast and reliable characterization techniques have been developed to study the aforementioned properties. In this paper, we discuss computer analysis techniques employed in the cryogenic characterization of HTS-based resonators. The revised data analysis process requires minimal user input. and organizes the data in a form that is easily accessible by the user for further examination. These programs retrieve data generated during the cryogenic characterization at microwave frequencies of HTS based resonators and use it to calculate parameters such as the loaded and unloaded quality factors (Q and Q(sub o), respectively), the resonant frequency (f(sub o)), and the coupling coefficient (k), which are important quantities in the evaluation of HTS resonators. While the data are also stored for further use, the programs allow the user to obtain a graphical representation of any of the measured parameters as a function of temperature soon after the completion of the cryogenic measurement cycle. Although these programs were developed to study planar HTS-based resonators operating in the reflection mode, they could also be used in the cryogenic characterization of two ports (i.e., reflection/transmission) resonators.

Creason, A. S.↗
NASA NTRS2012

A Statistics-Based Material Property Analysis to Support TPS Characterization

Accurate characterization of entry capsule heat shield material properties is a critical component in modeling and simulating Thermal Protection System (TPS) response in a prescribed aerothermal environment. The thermal decomposition of the TPS material during the pyrolysis and charring processes is poorly characterized and typically results in large uncertainties in material properties as inputs for ablation models. These material property uncertainties contribute to large design margins on flight systems and cloud re- construction efforts for data collected during flight and ground testing, making revision to existing models for entry systems more challenging. The analysis presented in this work quantifies how material property uncertainties propagate through an ablation model and guides an experimental test regimen aimed at reducing these uncertainties and characterizing the dependencies between properties in the virgin and charred states for a Phenolic Impregnated Carbon Ablator (PICA) based TPS. A sensitivity analysis identifies how the high-fidelity model behaves in the expected flight environment, while a Monte Carlo based uncertainty propagation strategy is used to quantify the expected spread in the in-depth temperature response of the TPS. An examination of how perturbations to the input probability density functions affect output temperature statistics is accomplished using a Kriging response surface of the high-fidelity model. Simulations are based on capsule configuration and aerothermal environments expected during the Mars Science Laboratory (MSL) entry sequence. We identify and rank primary sources of uncertainty from material properties in a flight-relevant environment, show the dependence on spatial orientation and in-depth location on those uncertainty contributors, and quantify how sensitive the expected results are.

Copeland, Sean R.↗
NASA NTRS2010

Flexible Material Systems Testing

An experimental program has been undertaken to better characterize the stress-strain characteristics of flexible material systems to support a NASA ground test program for inflatable decelerator material technology. A goal of the current study is to investigate experimental methods for the characterization of coated woven material stiffness. This type of experimental mechanics data would eventually be used to define the material inputs of fluid-structure interaction simulation models. The test methodologies chosen for this stress-strain characterization are presented along with the experimental results.

Lin, John K.↗
DOE OSTI2025

Deep Learning Super-Resolution X-Ray Computed Tomography Algorithms for Additive Manufacturing

Industrial X-ray computed tomography (XCT) is a nondestructive method for inspection and characterization of additively manufactured (AM) materials and parts. In practice, the resolution of XCT can be limited by factors such as detector binning, restricted field of view for large-scale objects, system blur, motion during scanning, and acquisition settings. These limitations can reduce the detectability of critical flaws such as pores, cracks, and lack of fusion. Super-resolution (SR) techniques offer a promising solution for improving the effective resolution and image quality of XCT reconstructions without the need for expensive hardware upgrades or laborious, time-consuming scans. In particular, deep learning-based SR methods have garnered attention in recent years as powerful tools for reconstructing high-resolution volumes from low-resolution inputs. In this work, a novel deep learning-based SR method is proposed for XCT scans of AM parts, and compared against several existing state-of-the-art (SOTA) methods. The proposed method, Simurgh-SR, is built on the pre-existing Simurgh framework and consists of a 2.5D U-Net trained to map low-quality inputs containing noise and artifacts to high-quality reconstructions characterized by higher flaw contrast, better noise texture, and reduced artifacts. The experimental results demonstrate superior performance of Simurgh-SR in performing 4× SR on real industrial XCT scans of thick 316L components, enhancing the structural similarity score and peak signal-to-noise ratio (>7dB) compared to the LR counterpart while improving the F1-score for flaw detection by more than 2.3× when compared to alternative SOTA SR methods. This improvement enables more accurate and significantly faster characterization of metal AM components. Additionally, Simurgh-SR was trained for both 2X and 4X SR and performs effectively at both levels, enabling the use of a single model for various SR factors.

Rahman, Obaid [ORNL] (ORCID:0000000277810840)↗
NASA NTRS2006

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation.

Brenner, Martin J.↗
NASA NTRS2005

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This paper investigates the utility of the Hilbert-Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert-Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert-Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this paper is to demonstrate the potential applications of the Hilbert-Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized/online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F/A-18 Active Aeroelastic Wing aircraft, an Aerostructures Test Wing, and pitch-plunge simulation.

Brenner, Marty↗
NASA NTRS1999

Characterization of ionic currents of cells of the subfornical organ that project to the supraoptic nuclei

The subfornical organ (SFO) is a forebrain structure that converts peripheral blood-borne signals reflecting the hydrational state of the body to neural signals and then through efferent fibers conveys this information to several central nervous system structures. One of the forebrain areas receiving input from the SFO is the supraoptic nucleus (SON), a source of vasopressin synthesis and control of release from the posterior pituitary. Little is known of the transduction and transmission processes by which this conversion of systemic information to brain input occurs. As a step in elucidating these mechanisms, the present study characterized the ionic currents of dissociated cells of the SFO that were identified as neurons that send efferents to the SON. A retrograde tracer was injected into the SON area in eleven-day-old rats. After three days for retrograde transport of the label, the SFOs of these animals were dissociated and plated for tissue culture. The retrograde tracer was used to identify the soma of SFO cells projecting to the SON so that voltage-dependent ionic currents using whole-cell voltage clamp methods could be studied. The three types of currents in labeled SFO neurons were characterized as a 1) rapid, transient inward current that can be blocked by tetrodotoxin (TTX) characteristic of a sodium current; 2) slow-onset sustained outward current that can be blocked by tetraethylammonium (TEA) characteristic of a delayed rectifier potassium current; and 3) remaining outward current that has a rapid-onset and transient characteristic of a potassium A-type current. Copyright 1999 Elsevier Science B.V.

Non-NASA Center↗
NASA NTRS2009

Hybrid NN/SVM Computational System for Optimizing Designs

A computational method and system based on a hybrid of an artificial neural network (NN) and a support vector machine (SVM) (see figure) has been conceived as a means of maximizing or minimizing an objective function, optionally subject to one or more constraints. Such maximization or minimization could be performed, for example, to optimize solve a data-regression or data-classification problem or to optimize a design associated with a response function. A response function can be considered as a subset of a response surface, which is a surface in a vector space of design and performance parameters. A typical example of a design problem that the method and system can be used to solve is that of an airfoil, for which a response function could be the spatial distribution of pressure over the airfoil. In this example, the response surface would describe the pressure distribution as a function of the operating conditions and the geometric parameters of the airfoil. The use of NNs to analyze physical objects in order to optimize their responses under specified physical conditions is well known. NN analysis is suitable for multidimensional interpolation of data that lack structure and enables the representation and optimization of a succession of numerical solutions of increasing complexity or increasing fidelity to the real world. NN analysis is especially useful in helping to satisfy multiple design objectives. Feedforward NNs can be used to make estimates based on nonlinear mathematical models. One difficulty associated with use of a feedforward NN arises from the need for nonlinear optimization to determine connection weights among input, intermediate, and output variables. It can be very expensive to train an NN in cases in which it is necessary to model large amounts of information. Less widely known (in comparison with NNs) are support vector machines (SVMs), which were originally applied in statistical learning theory. In terms that are necessarily oversimplified to fit the scope of this article, an SVM can be characterized as an algorithm that (1) effects a nonlinear mapping of input vectors into a higher-dimensional feature space and (2) involves a dual formulation of governing equations and constraints. One advantageous feature of the SVM approach is that an objective function (which one seeks to minimize to obtain coefficients that define an SVM mathematical model) is convex, so that unlike in the cases of many NN models, any local minimum of an SVM model is also a global minimum.

Rai, Man Mohan↗
DOE OSTI2024

Test and characterization of finely segmented pixel CZT detectors for future hard x-ray missions

The NuSTAR (Nuclear Spectroscopic Telescope Array) mission was launched in 2012, and it has successfully deployed the first orbiting telescopes to focus high energy X-ray (3 - 79 keV) light, providing a wealth of new information on high-energy X-rays sources. Follow-up missions, such as the proposed HEX-P, BEST, and FORCE, could perform a deeper black hole census providing a more refined measurement of black hole spins, allowing for greater knowledge about supermassive black holes. Here, these missions are motivated by the recent breakthroughs in the hard X-ray mirror technologies, where mirrors, either made of monolithic silicon segments, or made directly or via replication of shells, demonstrate the feasibility of making hard X-ray mirrors with angular resolutions of 5-10 arc-seconds Half Power Diameter (HPD) compared to the NuSTAR’s 1 arc-minute HPD. Such a high angular resolution requires matched detectors with higher degree of segmentation to fully benefit from the achievable improved spatial resolution. In the above framework, the HEXID ASIC, a novel pixelated front-end suitable for reading out a finely segmented CZT sensor with 150 μm pixel pitch in a hexagonal arrangement has been developed. This readout pixelated chip is capable of processing photon-generated charge packets over a large dynamic range (from 2 keV up to 180 keV), while keeping a low input noise (ENC <20 e - ). In this work, the initial characterization of the ASIC prototype will be presented.

47 OTHER INSTRUMENTATION↗
NASA NTRS2003

Discharge Characterization of 40 cm-Microwave ECR Ion Source and Neutralizer

Discharge characteristics of a 40 cm, 2.45 GHz Electron Cyclotron Resonance (ECR) ion thruster discharge chamber and neutralizer were acquired. Thruster bulk discharge plasma characteristics were assessed using a single Langmuir probe. Total extractable ion current was measured as a function of input microwave power and flow rate. Additionally, radial ion current density profiles at the thruster.s exit plane were characterized using five equally spaced Faraday probes. Distinct low and high density operating modes were observed as discharge input power was varied from 0 to 200 W. In the high mode, extractable ion currents as high as 0.82 A were measured. Neutralizer emission current was characterized as a function of flow rate and microwave power. Neutralizer extraction currents as high as 0.6 A were measured.

Foster, John E.↗
NASA NTRS2017

Contamination Knowledge Strategy for the Mars 2020 Sample-Collecting Rover

The Mars 2020 rover will collect carefully selected samples of rock and regolith as it explores a potentially habitable ancient environment on Mars. Using the drill, rock cores and regolith will be collected directly into ultraclean sample tubes that are hermetically sealed and, later, deposited on the surface of Mars for potential return to Earth by a subsequent mission. Thorough characterization of any contamination of the samples at the time of their analysis will be essential for achieving the objectives of Mars returned sample science (RSS). We refer to this characterization as contamination knowledge (CK), which is distinct from contamination control (CC). CC is the set of activities that limits the input of contaminating species into a sample, and is specified by requirement thresholds. CK consists of identifying and characterizing both potential and realized contamination to better inform scientific investigations of the returned samples. Based on lessons learned by other sample return missions with contamination-sensitive scientific objectives, CC needs to be "owned" by engineering, but CK needs to be "owned" by science. Contamination present at the time of sample analysis will reflect the sum of contributions from all contamination vectors up to that point in time. For this reason, understanding the integrated history of contamination may be crucial for deciphering potentially confusing contaminant-sensitive observations. Thus, CK collected during the Mars sample return (MSR) campaign must cover the time period from the initiation of hardware construction through analysis of returned samples in labs on Earth. Because of the disciplinary breadth of the scientific objectives of MSR, CK must include a broad spectrum of contaminants covering inorganic (i.e., major, minor, and trace elements), organic, and biological molecules and materials.

Farley, K. A.↗