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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Measurement of lunar and planetary magnetic fields by reflection of low energy electrons

The paper describes the technique of planetary electron reflection magnetometry (PERM), a method for measuring the magnitude, direction, and scale size of magnetic fields near the surface of the moon and other planetary bodies with weak and small-scale-size surface fields. It is noted that the PERM technique is based on the ability of magnetic fields to reflect charged particles. A qualitative account of the implementation of the technique is presented along with some results obtained by the Apollo 15 and 16 Particles and Fields subsatellites. The quantitative aspects of PERM are treated by examining solutions to the equation of motion of a charged particle in a magnetic field, computing reflection coefficients on the basis of trajectory calculations, and determining the direction of the lunar surface magnetic field. The sensitivity of the PERM technique is calculated, and effects of lunar electric fields and spacecraft potentials on the measurements are described. Extension of the technique to Mars and Venus is discussed.

Anderson, K. A.↗
NASA NTRS1977

Mathematical and computational studies of equilibrium capillary free surfaces

The results of several independent studies are presented. The general question is considered of whether a wetting liquid always rises higher in a small capillary tube than in a larger one, when both are dipped vertically into an infinite reservoir. An analytical investigation is initiated to determine the qualitative behavior of the family of solutions of the equilibrium capillary free-surface equation that correspond to rotationally symmetric pendent liquid drops and the relationship of these solutions to the singular solution, which corresponds to an infinite spike of liquid extending downward to infinity. The block successive overrelaxation-Newton method and the generalized conjugate gradient method are investigated for solving the capillary equation on a uniform square mesh in a square domain, including the case for which the solution is unbounded at the corners. Capillary surfaces are calculated on the ellipse, on a circle with reentrant notches, and on other irregularly shaped domains using JASON, a general purpose program for solving nonlinear elliptic equations on a nonuniform quadrilaterial mesh. Analytical estimates for the nonexistence of solutions of the equilibrium capillary free-surface equation on the ellipse in zero gravity are evaluated.

Albright, N.↗
NASA NTRS1981

Ground-truth measurement systems

Ground-truth measurements of precipitation and related weather events are an essential component of any satellite system designed for monitoring rainfall from space. Such measurements are required for testing, evaluation, and operations; they provide detailed information on the actual weather events, which can then be compared with satellite observations intended to provide both quantitative and qualitative information about them. Also, very comprehensive ground-truth observations should lead to a better understanding of precipitation fields and their relationships to satellite data. This process serves two very important functions: (a) aiding in the development and interpretation of schemes of analyzing satellite data, and (b) providing a continuing method for verifying satellite measurements.

Serafin, R.↗
NASA NTRS2011

Downhole Elemental Analysis with LIBS

In this paper we discuss a novel instrument, currently under development at Honeybee Robotics with SBIR funding from NASA. The device is designed to characterize elemental composition as a function of depth in non-terrestrial geological formations. The instrument consists of a miniaturized laser-induced breakdown spectrometer (LIBS) analyzer integrated in a 2" diameter drill string. While the drill provides subsurface access, the LIBS analyzer provides information on the elemental composition of the borehole wall. This instrument has a variety of space applications ranging from exploration of the Moon for which it was originally designed, to Mars, as well as a variety of terrestrial applications. Subsurface analysis is usually performed by sample acquisition through a drill or excavator, followed by sample preparation and subsequent sample presentation to an instrument or suite of instruments. An alternative approach consisting in bringing a miniaturized version of the instrument to the sample has many advantages over the traditional methodology, as it allows faster response, reduced probability of cross-contamination and a simplification in the sampling mechanisms. LIBS functions by focusing a high energy laser on a material inducing a plasma consisting of a small fraction of the material under analysis. Optical emission from the plasma, analyzed by a spectrometer, can be used to determine elemental composition. A triangulation sensor located in the sensor head determines the distance of the sensor from the borehole wall. An actuator modifies the position of the sensor accordingly, in order to compensate for changes due to the profile of the borehole walls. This is necessary because LIBS measurements are negatively affected by changes in the relative position of the focus of the laser with respect to the position of the sample (commonly referred to as the "lens to sample distance"). Profiling the borehole is done by adjusting the position of the sensor with a vertical stage; a second actuator at the top of the downhole probe allows radial scanning of the borehole. Analysis of iron and titanium in lunar simulant with LIBS was performed in air using the method of standard addition. The results for lunar simulant NU-LHT-2M show a value for the concentration of iron ranging between 2.29% and 3.05% depending on the atomic line selected. The accepted value for the sample analyzed is 2.83%, showing the capability for the system in development to provide qualitative and semi-quantitative analysis in real-time.

Moreschini, Paolo↗
NASA NTRS2014

Hydrogen-Bonding Surfaces for Ice Mitigation

Ice formation on aircraft, either on the ground or in-flight, is a major safety issue. While ground icing events occur predominantly during the winter months, in-flight icing can happen anytime during the year. The latter is more problematic since it could result in increased drag and loss of lift. Under a Phase I ARMD NARI Seedling Activity, coated aluminum surfaces possessing hydrogen-bonding groups were under investigation for mitigating ice formation. Hydroxyl and methyl terminated dimethylethoxysilanes were prepared via known chemistries and characterized by spectroscopic methods. These materials were subsequently used to coat aluminum surfaces. Surface compositions were based on pure hydroxyl and methyl terminated species as well as mixtures of the two. Coated surfaces were characterized by contact angle goniometry. Receding water contact angle data suggested several potential surfaces that may exhibit reduced ice adhesion. Qualitative icing experiments performed under representative environmental temperatures using supercooled distilled water delivered via spray coating were inconclusive. Molecular modeling studies suggested that chain mobility affected the interface between ice and the surface more than terminal group chemical composition. Chain mobility resulted from the creation of "pockets" of increased free volume for longer chains to occupy.

Smith, Joseph G., Jr.↗
NASA NTRS2023

Requirements Engineering Scorecard and the Next-Generation Space Suit

The objective for a NASA contractor, the performing organization in this case study, is to provide engineering services to develop and deliver the next generation space suit to NASA, the customer in this case study. A case study with qualitative and quantitative analyses regarding a new process and approach to requirements engineering is described, with the intent that if utilized, these tools may have contributed to improvements across the project in terms of meeting cost, scope, budget and quality while appropriately accounting for risk management. The procedure entails a research method in which the current state of the project, current state of the art, and the identified systems engineering challenges are evaluated. Iterative models are tempered through development by continual improvements by engineering evaluation of engineers on the project. The current results have produced a prototype of a requirements engineering scorecard with implementations of FMEA and quantitative analysis to (i) identify root cause of underdeveloped requirements and (ii) project management impacts with regards to project risk. Forward work includes customer, performing organization, acceptance against applicable INCOSE community accepted practices.

INCOSE↗
NASA NTRS1990

Numerical methods for TVD transport and coupled relaxing processes in gases and plasmas

The construction of second-order upwind schemes for nonequilibrium plasmas, for both one- and two-fluid formulations is demonstrated. Coupled relaxation processes, including ionization kinetics and radiative processes and their algorithms for nonequilibrium, multiple temperature conditions are described as well. The paper applies the numerical techniques on some simple test cases, points out critical problems and their solutions, and makes qualitative comparisons with known results, whenever possible.

Cambier, Jean-Luc↗
DOE OSTI2021

Computational scanning tunneling microscope image database

We introduce the systematic database of scanning tunneling microscope (STM) images obtained using density functional theory (DFT) for two-dimensional (2D) materials, calculated using the Tersoff-Hamann method. It currently contains data for 716 exfoliable 2D materials. Examples of the five possible Bravais lattice types for 2D materials and their Fourier-transforms are discussed. All the computational STM images generated in this work are made available on the JARVIS-STM website ( https://jarvis.nist.gov/jarvisstm ). We find excellent qualitative agreement between the computational and experimental STM images for selected materials. As a first example application of this database, we train a convolution neural network model to identify the Bravais lattice from the STM images. We believe the model can aid high-throughput experimental data analysis. These computational STM images can directly aid the identification of phases, analyzing defects and lattice-distortions in experimental STM images, as well as be incorporated in the autonomous experiment workflows.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

A review on recent machine learning applications for imaging mass spectrometry studies

Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology, chemistry, and materials science fields that continue to expand. IMS provides a qualitative compositional analysis and spatial mapping with high chemical specificity. The spatial mapping information can be 2D or 3D depending on the analysis technique employed. Due to the combination of complex mass spectra coupled with spatial information, large high-dimensional datasets (hyperspectral) are often produced. Therefore, the use of automated computational methods for an exploratory analysis is highly beneficial. The fast-paced development of artificial intelligence (AI) and machine learning (ML) tools has received significant attention in recent years. These tools, in principle, can enable the unification of data collection and analysis into a single pipeline to make sampling and analysis decisions on the go. There are various ML approaches that have been applied to IMS data over the last decade. Here, in this review, we discuss recent examples of the common unsupervised (principal component analysis, non-negative matrix factorization, k-means clustering, uniform manifold approximation and projection), supervised (random forest, logistic regression, XGboost, support vector machine), and other methods applied to various IMS datasets in the past five years. The information from this review will be useful for specialists from both IMS and ML fields since it summarizes current and representative studies of computational ML-based exploratory methods for IMS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Entanglement features of random neural network quantum states

Restricted Boltzmann machines (RBMs) are a class of neural networks that have been successfully employed as a variational ansatz for quantum many-body wave functions. Here, we develop an analytic method to study quantum many-body spin states encoded by random RBMs with independent and identically distributed complex Gaussian weights. By mapping the computation of ensemble-averaged quantities to statistical mechanics models, we are able to investigate the parameter space of the RBM ensemble in the thermodynamic limit. We discover qualitatively distinct wave functions by varying RBM parameters, which correspond to distinct phases in the equivalent statistical mechanics model. Notably, there is a regime in which the typical RBM states have near-maximal entanglement entropy in the thermodynamic limit, similar to that of Haar-random states. However, these states generically exhibit nonergodic behavior in the Ising basis, and do not form quantum state designs, making them distinguishable from Haar-random states.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Quantifying the Complexity of Flaring Active Regions

While solar physicists have a better understanding of the importance magnetic fields play in the solar heating mechanism, it is still not possible to predict whether or when an active region will flare. In recent decades, qualitative studies of the changes in active region morphology have shown that there is generally an increase in the complexity of the spatial configuration of a solar active region leading up to a flare event. In this study, we quantify the spatial structure of the region using the differential Box-Counting Method (DBC) of fractal analysis. We analyze data from NASA/Marshall Space Flight Centr's vector magnetograph from two flaring active regions: AR 6089 from June 10, 1990, which produced one M1.7 flare, and AR 6659 from June 8, 9 and 10, 1991, this data set including one C5.7 and two M(6.4 and 3.2) flare. (AR 6659 produced several other flares). Several magnetic parameters are studied, including the transverse and longitudinal magnetic field components (Bt and B1), the total field (Bmag), and the magnetic shear, which describes the non-potentiality of the field. Results are presented for the time series of magnetograms in relation to the timing of flare events.

Stark, B.↗
NASA NTRS2011

NEEMO 14: Evaluation of Human Performance for Rover, Cargo Lander, Crew Lander, and Exploration Tasks in Simulated Partial Gravity

The ultimate success of future human space exploration missions is dependent on the ability to perform extravehicular activity (EVA) tasks effectively, efficiently, and safely, whether those tasks represent a nominal mode of operation or a contingency capability. To optimize EVA systems for the best human performance, it is critical to study the effects of varying key factors such as suit center of gravity (CG), suit mass, and gravity level. During the 2-week NASA Extreme Environment Mission Operations (NEEMO) 14 mission, four crewmembers performed a series of EVA tasks under different simulated EVA suit configurations and used full-scale mockups of a Space Exploration Vehicle (SEV) rover and lander. NEEMO is an underwater spaceflight analog that allows a true mission-like operational environment and uses buoyancy effects and added weight to simulate different gravity levels. Quantitative and qualitative data collected during NEEMO 14, as well as from spacesuit tests in parabolic flight and with overhead suspension, are being used to directly inform ongoing hardware and operations concept development of the SEV, exploration EVA systems, and future EVA suits. OBJECTIVE: To compare human performance across different weight and CG configurations. METHODS: Four subjects were weighed out to simulate reduced gravity and wore either a specially designed rig to allow adjustment of CG or a PLSS mockup. Subjects completed tasks including level ambulation, incline/decline ambulation, standing from the kneeling and prone position, picking up objects, shoveling, ladder climbing, incapacitated crewmember handling, and small and large payload transfer. Subjective compensation, exertion, task acceptability, and duration data as well as photo and video were collected. RESULTS: There appear to be interactions between CG, weight, and task. CGs nearest the subject s natural CG are the most predictable in terms of acceptable performance across tasks. Future research should focus on understanding the interactions between CG, mass, and subject differences.

Chappell, Steven P.↗
NASA NTRS2010

Proposed Objective Odor Control Test Methodology for Waste Containment

The Orion Cockpit Working Group has requested that an odor control testing methodology be proposed to evaluate the odor containment effectiveness of waste disposal bags to be flown on the Orion Crew Exploration Vehicle. As a standardized "odor containment" test does not appear to be a matter of record for the project, a new test method is being proposed. This method is based on existing test methods used in industrial hygiene for the evaluation of respirator fit in occupational settings, and takes into consideration peer reviewed documentation of human odor thresholds for standardized contaminates, industry stardnard atmostpheric testing methodologies, and established criteria for laboratory analysis. The proposed methodology is quantitative, though it can readily be complimented with a qualitative subjective assessment. Isoamyl acetate (IAA - also known at isopentyl acetate) is commonly used in respirator fit testing, and there are documented methodologies for both measuring its quantitative airborne concentrations. IAA is a clear, colorless liquid with a banana-like odor, documented detectable smell threshold for humans of 0.025 PPM, and a 15 PPB level of quantation limit.

Vos, Gordon↗
DOE OSTI2022

Impacts of Solvent Washing on the Electrochemical Remediation of Commercial End-of-Life Cathodes

Changes to surface structure and chemistry occurring throughout the functional lifetime of lithium-ion batteries (LIBs) may impact the effectiveness of end-of-life rejuvenation methods. Solvent washing prior to electrochemical relithiation is shown to both increase relithiation efficacy and beneficially alter the interfacial chemistry of heavily degraded industrial cathode material. Four common solvents (acetone, diethyl carbonate, isopropyl alcohol, propylene carbonate) are employed to investigate the role of varying physicochemical solvent properties on the mechanism of capacity recovery. Electrochemical (dQ/dV, EIS), structural (XRD), and chemical (SPME-GC-MS) analysis techniques are employed to comprehensively analyze solvent-cathode interactions. Highly nucleophilic solvents (acetone, DEC) are found to reduce cathode charge-transfer impedance and enable stable impedance growth throughout subsequent cycling. The use of nucleophilic solvents under mechanically aggressive washing conditions may also enable the reintroduction of bulk lattice oxygen, thereby restoring anionic redox capacity. Further, the four solvents are found to selectively remove a subset of surface species from the aged cathode material, including residual electrolyte, additives, and electrolyte-additive reaction products, which are qualitatively analyzed. Surface species removal by each solvent is correlated with the electrochemical performance of the correspondingly washed cathode, highlighting the importance of an optimized washing protocol to effective remediation in the context of direct LIB recycling. For the material under study, the use of a simple acetone washing protocol prior to electrochemical relithiation enables up to 174% capacity recovery relative to unwashed/relithiated black mass.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Bayesian SegNet for Semantic Segmentation with Improved Interpretation of Microstructural Evolution During Irradiation of Materials

Understanding the relationship between the evolution of microstructures of irradiated LiAlO2pellets and tritium diffusion, retention and release could improve predictions of tritium performance. Given expert-labeled segmented images of irradiated and unirradiated pellets, we trained Deep Convolutional Neural Networks to segment images into defect, grain, and boundary classes. Qualitative microstructural information was calculated from these segmented images to facilitate the comparison of unirradiated and irradiated pellets. We tested modifications to improve the sensitivity of the model, including incorporating meta-data into the model and utilizing uncertainty quantification. The predicted segmentation was similar to the expert-labeled segmentation for most methods of microstructural qualification, including pixel proportion, defect area, and defect density. Overall, the high performance metrics for the best models for both irradiated and unirradiated images shows that utilizing neural network models is a viable alternative to expert-labeled images.

Oostrom, Marjolein T.↗
DOE OSTI2021

Initial Fermi orbital descriptors for FLOSIC calculations: The quick-FOD method

Fermi orbital descriptors (FODs) play a key role in Fermi-Löwdin orbital self-interaction correction (FLOSIC) calculations used to remove self-interaction from approximate density functionals. Optimal FODs are obtained by minimizing the self-interaction-corrected total energy, and, in this process, identifying initial sets of FODs becomes crucial. Here we propose, implement and test a novel method for automatically initializing FODs, quick-FOD, based on the minimization of an empirical energy expression that involves a Coulomb-like FOD-electron density attraction, an FOD-FOD short-range repulsion, and an exchange-like FOD-density repulsion. Quick-FOD successfully reproduces FOD arrangements in qualitatively good agreement with Lewis theory and with full-fledged FLOSIC calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multi-modal Free-moving Data Fusion (MFDF) v1.0

Multi-modal Free-moving Data Fusion (MFDF) is a python package that implements low and high-level functionality for performing qualitative and quantitative gamma-ray imaging analyses. Such analyses enable the use of gamma-ray spectrometers and/or imagers to estimate the distribution and quantity of radiological materials in an environment. Free-moving 3D imaging requires additional information about the 3D trajectory and orientation of the system, however all of these methods can be applied to 2D static gamma-ray imaging as well. The package includes methods (MLEM and MAP) for distributed source reconstruction, methods (PSL) for point source reconstruction, the ability to ingest and utilize quantitative detector response functions (for absolute analyses), and the ability to perform 3D estimation of dose-rates from quantitative reconstructions.

Joshi, Tenzing↗
NASA NTRS1973

Mixing-controlled supersonic combustion.

The technology of supersonic combustion and its practical significance for hypersonic flight are reviewed. It is shown that this technology makes possible a good qualitative and quantitative understanding of the physical phenomena related to the process of supersonic combustion. Some of the more important, summarized aspects of this technology include the physical description of the supersonic combustion flame, the chemical reaction rates and the diffusion process involved, the interaction between combustion and fluid dynamics, and the mathematical methods of supersonic combustion analysis.

Ferri, A.↗