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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 559 records · Page 31

All sources NASA NTRS DOE OSTI

DOE OSTI2021

A hierarchical gray-box dynamic modeling methodology for direct-expansion cooling systems to support control stability analysis; Méthodologie de modélisation dynamique hiérarchique de type boîte grise pour les systèmes de refroidissement à détente directe afin de soutenir l'analyse de stabilité de la commande

In this paper, a gray-box dynamic modeling approach for direct-expansion cooling systems is presented. The overall approach incorporates a multi-stage training procedure that consists of 1) identification of component sub-models from quasi-steady-state performance data, 2) system model integration with estimation of refrigerant charge and 3) fine tuning of thermal capacitances of the evaporator and condenser to capture the system dynamic responses. Compared to traditional physics-based models, the proposed modeling approach has advantages including reduced engineering efforts in the model development phase, improved computational efficiency and enhanced prediction accuracy. The modeling method was validated using a 3-ton variable-speed heat pump and proved to be capable of accurately predicting the system transient behaviors over a wide range of operating conditions. The established dynamic model was then applied for control stability analysis, with a specific goal of determining a proper control execution time step. The case study results showed that the stable control execution time step could change significantly, from 3 sec to 19 sec, as the operating conditions and control settings vary, and a proper selection of the execution time step is critical to ensure stable and reliable operations.

42 ENGINEERING↗

DOE OSTI2025

Systematic characterization of unknown compounds via dimensionality reduction of time series

Analysis of ambient aerosols provides valuable insight into particle sources and formation chemistry. However, due to the complexity of atmospheric data and the dynamic nature of aerosol composition, a substantial fraction of data often become discarded by conventional analysis methods. Furthermore, a large fraction of chemical species within those data are unidentifiable due to a lack of matching spectral information, resulting in suboptimal characterization of chemical composition. Previous work has demonstrated techniques for cataloging analytes in a chromatographic dataset by deconvolution of mass spectra, but integration of these analytes throughout a large dataset remains time consuming. Here, we present a method to automatically identify an ion for quantitation for single-ion chromatogram based peak fitting and integration, enabling comprehensive integration of analytes with minimal user interaction. The resulting time series are clustered with a machine-learning based dimensionality reduction technique to systematically investigate the underlying characteristics of the categorized analytes and gain new insights into the chemical composition and physicochemical properties of the unidentifiable analytes. We apply these methods to existing atmospheric datasets collected in Manacapuru, Brazil during the GoAmazon2014/5 campaign to identify new analytes and interpret their variability and transformations in the atmosphere. The analysis results generate 408 time series from cataloged analytes of interest, and the clustering of those time series with spherical k-means results in 8 distinct clusters. We find the analytes form clusters based on their distinct physicochemical properties, demonstrating the method’s ability to systematically identify and selectively filter contaminants and instrumental analytes and characterize the unidentifiable analytes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Relating Land Cover Change to Runoff Distribution Using NASA Earth Observations in Riley County, Kansas

In recent years, Riley County, Kansas experienced high levels of flooding potentially due to changes in land use and impervious surface. To analyze the increase in floods and runoff patterns over time, this study contrasted two methods of curve number (CN) calculation, which estimated runoff from rainfall events, from 2006-2020. The conventional calculation method used a look-up table and tracked land use/land cover change. This method resulted in static tables from various inputs such as soil type, surface imperviousness, slope, and crop phenology to estimate runoff versus infiltration. These tables allowed for phenology specific curve numbers and accounted for various farming techniques but required many inputs and lacked flexibility to include seasonal variations in vegetation. In contrast, the dynamic method is a more modern and simple calculation employing normalized difference vegetation index (NDVI) data from Landsat 5, Landsat 7, and Landsat 8 satellites compiled over the rainy season each year to calculate curve numbers based off seasonal vegetation. This dynamic method allowed for more precise analysis of runoff variability because NDVI is a more accurate, real-time measurement for land cover and it could be calculated with greater temporal detail. The results will allow decision makers to make more informed decisions on resiliency strategies to address future flooding.

Trista Brophy↗

NASA NTRS1986

A data base and analysis program for shuttle main engine dynamic pressure measurements

A dynamic pressure data base management system is described for measurements obtained from space shuttle main engine (SSME) hot firing tests. The data were provided in terms of engine power level and rms pressure time histories, and power spectra of the dynamic pressure measurements at selected times during each test. Test measurements and engine locations are defined along with a discussion of data acquisition and reduction procedures. A description of the data base management analysis system is provided and subroutines developed for obtaining selected measurement means, variances, ranges and other statistics of interest are discussed. A summary of pressure spectra obtained at SSME rated power level is provided for reference. Application of the singular value decomposition technique to spectrum interpolation is discussed and isoplots of interpolated spectra are presented to indicate measurement trends with engine power level. Program listings of the data base management and spectrum interpolation software are given. Appendices are included to document all data base measurements.

Coffin, T.↗

NASA NTRS2006

Recent Highlights in Ring Structure, Dynamics, and Composition

While the Cassini orbiter has been in a near-equatorial orbit for most of the time since the last DPS meeting, the science teams have turned to preliminary analysis of many aspects of data taken over the first year of the mission. New understanding has been gained of several different aspects of ring structure and dynamics - especially the small-scale ring vertical structure related to marginal gravitational instabilities, and the diverse roles played by small moonlets sprinkled around and within the rings. In addition, a closer look is being taken at how ring composition varies locally and regionally and how this variation compares with models of ring compositional evolution. Cassini will re-emerge from the equator plane in late July, and new ring observations will again be available. In this talk we will review progress over the last year, highlight key outstanding issues and problems, and provide a context for the new observations reported at this meeting.

Cuzzi, Jeffrey N.↗

DOE OSTI2018

Analysis and Strategies of a Successful LDRD Collaboration

This report analyzes the workings of the “Real - time Adaptive Acceleration of Dynamic Experimental Science” LDRD team, led by James Ahrens, Cindy Bolme and Richard Sandberg, using it to outline practices of successful and innovative LDRD collaborations.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1993

Specialized data analysis for the Space Shuttle Main Engine and diagnostic evaluation of advanced propulsion system components

The Marshall Space Flight Center is responsible for the development and management of advanced launch vehicle propulsion systems, including the Space Shuttle Main Engine (SSME), which is presently operational, and the Space Transportation Main Engine (STME) under development. The SSME's provide high performance within stringent constraints on size, weight, and reliability. Based on operational experience, continuous design improvement is in progress to enhance system durability and reliability. Specialized data analysis and interpretation is required in support of SSME and advanced propulsion system diagnostic evaluations. Comprehensive evaluation of the dynamic measurements obtained from test and flight operations is necessary to provide timely assessment of the vibrational characteristics indicating the operational status of turbomachinery and other critical engine components. Efficient performance of this effort is critical due to the significant impact of dynamic evaluation results on ground test and launch schedules, and requires direct familiarity with SSME and derivative systems, test data acquisition, and diagnostic software. Detailed analysis and evaluation of dynamic measurements obtained during SSME and advanced system ground test and flight operations was performed including analytical/statistical assessment of component dynamic behavior, and the development and implementation of analytical/statistical models to efficiently define nominal component dynamic characteristics, detect anomalous behavior, and assess machinery operational condition. In addition, the SSME and J-2 data will be applied to develop vibroacoustic environments for advanced propulsion system components, as required. This study will provide timely assessment of engine component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. This contract will be performed through accomplishment of negotiated task orders.

Source record↗

DOE OSTI2019

Dynamical properties of a room temperature ionic liquid: Using molecular dynamics simulations to implement a dynamic ion cage model [plus supplemental information]

The transport behavior of ionic liquids (ILs) is pivotal for a variety of applications, especially when ILs are used as electrolytes. Many aspects of the transport dynamics of ILs remain to be understood. Here, a common ionic liquid, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (BmimNTf 2 ), was studied with molecular dynamics simulations. The results show that BmimNTf 2 displays typical structural relaxation, subdiffusive behavior, and a breakdown of the Stokes-Einstein diffusion relation as in glass-forming liquids. In addition, the simulations show that the translational dynamics, reorientation dynamics, and structural relaxation dynamics are well described by the Vogel-Fulcher-Tammann equation like fragile glass forming liquids. Building on previous work that employed ion cage models, it was found that the diffusion dynamics of the cations and anions were well described by a hopping process random walk where the step time is the ion cage lifetime obtained from the cage correlation function. Detailed analysis of the ion cage structures indicated that the electrostatic potential energy of the ion cage dominates the diffusion dynamics of the caged ion. The ion orientational relaxation dynamics showed that ion reorientation is a necessary step for ion cage restructuring. The dynamic ion cage model description of ion diffusion presented here may have implications for designing ILs to control their transport behavior.

36 MATERIALS SCIENCE↗

NASA NTRS1974

Study of time-lapse processing for dynamic hydrologic conditions

The usefulness of dynamic display techniques in exploiting the repetitive nature of ERTS imagery was investigated. A specially designed Electronic Satellite Image Analysis Console (ESIAC) was developed and employed to process data for seven ERTS principal investigators studying dynamic hydrological conditions for diverse applications. These applications include measurement of snowfield extent and sediment plumes from estuary discharge, Playa Lake inventory, and monitoring of phreatophyte and other vegetation changes. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The most unique feature of the system is the capability to time lapse the imagery and analytic displays of the imagery. Data products included quantitative measurements of distances and areas, binary thematic maps based on monospectral or multispectral decisions, radiance profiles, and movie loops. Applications of animation for uses other than creating time-lapse sequences are identified. Input to the ESIAC can be either digital or via photographic transparencies.

Serebreny, S. M.↗

DOE OSTI2020

Analysis of an all-solid state nanobattery using molecular dynamics simulations under an external electric field

Present Li-ion battery (LIB) technology requires strong improvements in performance, energy capacity, charging-time, and cost to expand their application to e-mobility and grid storage. Li-metal is one of the most promising materials to replace commercial anodes such as graphite because of its 10 times higher specific capacity. However, Li-metal has high reactivity with commercial liquid electrolytes; thus, new solid materials are proposed to replace liquid electrolytes when Li-metal anodes are used. We present a theoretical analysis of the charging process in a full nanobattery, containing a LiCoO 2 cathode, a Li 7 P2S 8 I solid-state electrolyte (SSE), a Li-metal anode as well as Al and Cu collectors for the cathode and anode, respectively. In addition, we added a Li 3 P/Li 2 S film as a solid electrolyte interphase (SEI) layer between the Li-anode and SSE. Thus, we focus this study on the SEI and SSE. We simulated the charging of the nanobattery with an external voltage by applying an electric field. We estimated temperature profiles within the nanobattery and analyzed Li-ion transport through the SSE and SEI. Here, we observed a slight temperature rise at the SEI due to reactions forming $PS_{3}^{–}$ and $P_{2}S_{7}^{4}$$^{–}$ fragments at the interfaces; however, this temperature profile changes due to the charging current under the presence of the external electric field ε = 0.75 V Å –1 . Without the external field, the calculated open-circuit voltage (OCV) was 3.86 V for the battery, which is within the range of values of commercial cobalt-based LIBs. This voltage implies a spontaneous fall of available Li-ions from the anode to the cathode (during discharge). The charge of this nanobattery requires overcoming the OCV plus an additional voltage that determines the charging current. Thus, we applied an external potential able to neutralize the OCV, plus an additional 1.6 V to induce the transport of Li + from the cathode up to the anode. Several interesting details about Li + transport paths through the SSE and SEI are discussed.

25 ENERGY STORAGE↗

DOE OSTI2021

Nanoscale chromatin imaging and analysis platform bridges 4D chromatin organization with molecular function

Extending across multiple length scales, dynamic chromatin structure is linked to transcription through the regulation of genome organization. However, no individual technique can fully elucidate this structure and its relation to molecular function at all length and time scales at both a single-cell level and a population level. Here, we present a multitechnique nanoscale chromatin imaging and analysis (nano-ChIA) platform that consolidates electron tomography of the primary chromatin fiber, optical super-resolution imaging of transcription processes, and label-free nano-sensing of chromatin packing and its dynamics in live cells. Using nano-ChIA, we observed that chromatin is localized into spatially separable packing domains, with an average diameter of around 200 nanometers, sub-megabase genomic size, and an internal fractal structure. The chromatin packing behavior of these domains exhibits a complex bidirectional relationship with active gene transcription. Furthermore, we found that properties of PDs are correlated among progenitor and progeny cells across cell division.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction

Purpose: Dynamic imaging (DI) provides additional diagnostic information in emission tomography in comparison to conventional static imaging at the cost of being computationally more challenging. Dynamic single photon emission computed tomography (SPECT) reconstruction is particularly difficult because of the limitations in the sampling geometry present in most existing scanners. We have developed an algorithm Spline Initialized Factor Analysis of Dynamic Structures (SIFADS) that is a matrix factorization method for reconstructing the dynamics of tracers in tissues and blood directly from the projections in dynamic cardiac SPECT, without first resorting to any 3D reconstruction. Methods: SIFADS is different from "pure" factor analysis in dynamic structures (FADS) in that it employs a dedicated spline-based pre-initialization. In this paper, we analyze the convergence properties of SIFADS and FADS using multiple metrics. The performances of the two approaches are evaluated for numerically simulated data and for real dynamic SPECT data from canine and human subjects. Results: For SIFADS, metrics analyzed for reconstruction algorithm convergence show better features of the metric curves vs iterations. In addition, SIAFDS provides better tissue segmentations than that from pure FADS. Measured computational times are also typically better for SIFADS implementations than those with pure FADS. Conclusion: The analysis supports the utility of the pre-initialization of a factorization algorithm for better dynamic SPECT image reconstruction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Thermally Stable Co@C3N4 Single-Atom Catalysts for CO Oxidation: Atomic-Level Insights into Structure and Activity

Single Co atoms supported on C3N4 (Co@C3N4) have demonstrated high activity and selectivity in photocatalysis. However, the investigation of structure–function relationships and reaction mechanisms under photocatalytic conditions is very challenging due to the complex conditions of light absorption, charge transfer, and catalysis. In this study, we employed thermal CO oxidation as a prototypical probe reaction to benchmark the intrinsic catalytic performance and track the active-site evolution of Co@C3N4. Single Co atoms were identified and shown to be the catalytically active sites for CO oxidation based on control experiments and isotope-labeling experiments. The Co sites remained atomically dispersed before, during, and after the reaction with temperatures up to 400 °C, as established by in situ X-ray absorption fine structure (XAFS) combined with density functional theory (DFT), FDMNES simulations, and dynamic-time-warping (DTW)-assisted X-ray absorption near edge structure (XANES) matching. Together with theoretical calculations, the integrated analysis reveals a stable coordination environment under reaction conditions, which correlates with sustained activity, establishing Co@C3N4 single-atom catalysts as thermally stable CO oxidation catalysts. Beyond these findings, the current study provides a workflow for unambiguously assigning active sites in Co@C3N4 for thermal CO oxidation. This workflow will aid the understanding of their behavior in photocatalysis in the future, where light-driven dynamics obscure direct structure–function links. Notably, this study provides fundamental insights for the rational design of robust single-atom catalysts and a foundation for the broader application of Co@C3N4 catalysts in oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Topology driven and soft phonon mode enabled Na-ion diffusion in quaternary chalcogenides, Na 3 ZnGaX 4 (X = S, and Se)

The compounds Na 3 ZnGaX 4 (X = S, Se) are potential solid electrolyte materials in sodium-based batteries, which have certain advantages over oxide materials and have shown significant ionic conductivity at ambient temperature. In this paper, we bring out atomic-level features of the diffusion process in these new materials using the microscopic techniques of inelastic neutron scattering (INS), quasielastic neutron scattering (QENS), and ab initio molecular dynamics (AIMD) simulations. The insights obtained from these techniques are unique and not available from other macroscopic experiments. Neutron scattering experiments have been performed at temperatures from 100 to 700 K. The simulations have been carried out up to 900 K. We have calculated the phonon spectra and the space–time correlation functions and found good agreement with the results of the neutron scattering experiments. The simulations enable detailed analysis of the atomic-site dependent dynamical information. We observe low-energy phonon modes of ~6 meV involving the vibrations of certain Na atoms in the lattice. This reveals that the Na at 32g Wyckoff sites (Na2) has sufficiently shallow potential among the two available crystallographic sites. This shallow potential facilitates diffusion. Furthermore, the specific structural topology of the network of interconnected zig-zag chains of the Na2 atomic sites provides the low-barrier energy pathways for diffusion. A small fraction of vacancy defects appears essential for diffusion. We further observe that the Na2 atoms undergo jump-like diffusion to the vacant next or the 2nd next neighbour sites at ~4 Å. While the QENS experiments reveal the jump-like diffusion and its time scale, detailed analysis of the AIMD simulations shows that the jumps appear mostly along zig-zag chains of the Na2 sites in the tetragonal ab-plane, as well as between the chains along the c-axis. In conclusion, the net diffusion is essentially 3-dimensional, with little anisotropy despite the anisotropy of the tetragonal crystal structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2016

Aircraft Fault Detection Using Real-Time Frequency Response Estimation

A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.

Grauer, Jared A.↗

DOE OSTI2020

Sparse and Random Sampling Techniques for High-Resolution, Full-Field, BSS-Based Structural Dynamics Identification from Video

Video-based techniques for identification of structural dynamics have the advantage that they are very inexpensive to deploy compared to conventional accelerometer or strain gauge techniques. When structural dynamics from video is accomplished using full-field, high-resolution analysis techniques utilizing algorithms on the pixel time series such as principal components analysis and solutions to blind source separation the added benefit of high-resolution, full-field modal identification is achieved. An important property of video of vibrating structures is that it is particularly sparse. Typically video of vibrating structures has a dimensionality consisting of many thousands or even millions of pixels and hundreds to thousands of frames. However the motion of the vibrating structure can be described using only a few mode shapes and their associated time series. As a result, emerging techniques for sparse and random sampling such as compressive sensing should be applicable to performing modal identification on video. This work presents how full-field, high-resolution, structural dynamics identification frameworks can be coupled with compressive sampling. The techniques described in this work are demonstrated to be able to recover mode shapes from experimental video of vibrating structures when 70% to 90% of the frames from a video captured in the conventional manner are removed.

47 OTHER INSTRUMENTATION↗

NASA NTRS1997

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Jong, Jen-Yi↗

DOE OSTI2020

Dynamic compressed sensing for real-time tomographic reconstruction

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) exploits the inherent sparse signal structure to efficiently reconstruct three-dimensional (3D) volumes at the nanoscale from undersampled measurements. However, the process bottlenecks 3D reconstruction with computation times that run from hours to days. Here we demonstrate a framework for dynamic compressed sensing that produces a 3D specimen structure that updates in real-time as new specimen projections are collected. Researchers can begin interpreting 3D specimens as data is collected to facilitate high-throughput and interactive analysis. Using scanning transmission electron microscopy (STEM), we show that dynamic compressed sensing accelerates the convergence speed by ~3-fold while also reducing its error by 27% for a Au/SrTiO 3 nanoparticle specimen. Before a tomography experiment is completed, the 3D tomogram has interpretable structure within ~33% of completion and fine details are visible as early as ~66%. Upon completion of an experiment, a high-fidelity 3D visualization is produced without further delay. Additionally, we report reconstruction parameters that tune data fidelity can be manipulated throughout the computation without re-running the entire process.

47 OTHER INSTRUMENTATION↗