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At least 379 records · Page 21

Cosmic dust in the atmosphere and in the interplanetary space at 1 AU today and in the early solar system

A description of techniques used in recent experiments to detect and analyze cosmic dust and micrometeorites is given and the results both from the study of lunar crater statistics and from in situ measurements are reviewed. The results from lunar crater statistics show an agreement with the results obtained from in situ measurements in interplanetary space and derived from zodiacal light measurements. The near earth results show an enhancement in the flux numbers. This can be caused either by secondary lunar debris or by disintegration of low density fireballs in the outer atmosphere.

Fechtig, H.↗

Engineering evaluation of SSME dynamic data from engine tests and SSV flights

An engineering evaluation of dynamic data from SSME hot firing tests and SSV flights is summarized. The basic objective of the study is to provide analyses of vibration, strain and dynamic pressure measurements in support of MSFC performance and reliability improvement programs. A brief description of the SSME test program is given and a typical test evaluation cycle reviewed. Data banks generated to characterize SSME component dynamic characteristics are described and statistical analyses performed on these data base measurements are discussed. Analytical models applied to define the dynamic behavior of SSME components (such as turbopump bearing elements and the flight accelerometer safety cut-off system) are also summarized. Appendices are included to illustrate some typical tasks performed under this study.

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Processing Aleatory and Epistemic Uncertainties in Experimental Data From Sparse Replicate Tests of Stochastic Systems for Real-Space Model Validation

This paper presents a practical methodology for propagating and processing uncertainties associated with random measurement and estimation errors (that vary from test-to-test) and systematic measurement and estimation errors (uncertain but similar from test-to-test) in inputs and outputs of replicate tests to characterize response variability of stochastically varying test units. Also treated are test condition control variability from test-to-test and sampling uncertainty due to limited numbers of replicate tests. These aleatory variabilities and epistemic uncertainties result in uncertainty on computed statistics of output response quantities. The methodology was developed in the context of processing experimental data for “real-space” (RS) model validation comparisons against model-predicted statistics and uncertainty thereof. The methodology is flexible and sufficient for many types of experimental and data uncertainty, offering the most extensive data uncertainty quantification (UQ) treatment of any model validation method the authors are aware of. It handles both interval and probabilistic uncertainty descriptions and can be performed with relatively little computational cost through use of simple and effective dimension- and order-adaptive polynomial response surfaces in a Monte Carlo (MC) uncertainty propagation approach. A key feature of the progressively upgraded response surfaces is that they enable estimation of propagation error contributed by the surrogate model. Sensitivity analysis of the relative contributions of the various uncertainty sources to the total uncertainty of statistical estimates is also presented. Finally, the methodologies are demonstrated on real experimental validation data involving all the mentioned sources and types of error and uncertainty in five replicate tests of pressure vessels heated and pressurized to failure. Simple spreadsheet procedures are used for all processing operations.

97 MATHEMATICS AND COMPUTING↗

ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model

Wildfires have shown increasing trends in both frequency and severity across the contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth system models (ESMs). Alternatively, fire models based on machine learning (ML), which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ELM2.1-XGBFire1.0) that integrates an eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran–C–Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001–2019, the ELM2.1-XGBFire1.0 outperforms process-based fire models in terms of spatial distribution and seasonal variations. The ELM2.1-XGBFire1.0 has proven to be a new tool for studying vegetation–fire interactions and, more importantly, enables seamless exploration of climate–fire feedback, working as an active component of E3SM.

54 ENVIRONMENTAL SCIENCES↗

A system overview of the Aerospace Safety Research and Data Institute data management programs

The NASA Aerospace Safety Information System, is an interactive, generalized data base management system. The on-line retrieval aspects provide for operating from a variety of terminals (or in batch mode). NASIS retrieval enables the user to expand and display (review) the terms of index (cross reference) files, select desired index terms, combine sets of documents corresponding to selected terms and display the resulting records. It also allows the user to print (record) this information on a high speed printer if desired. NASIS also provides the ability to store the strategy of any given session the user has executed. It has a searching and publication ability through generalized linear search and report generating modules which may be performed interactively or in a batch mode. The user may specify formats for the terminal from which he is operating. The system features an interactive user's guide which explains the various commands available and how to use them as well as explanations for all system messages. This explain capability may be extended, without program changes, to include descriptions of the various files in use. Coupled with the ability of NASIS to run in an MTT (multi-terminal task) mode is its automatic accumulation of statistics on each user of the system as well as each file.

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Magnetospheric plasma modeling (0-100 keV)

Spacecraft surface charging, which is primarily a current balance phenomenon, is in general a function of the dominant currents to and from the vehicle's surface. Within the near-earth magnetosphere the dominant currents to the surface are the ambient space plasma fluxes between approximately 0 and 100 keV. A major effort to understand the near-earth environment was initiated when spacecraft charging became a major issue. The present paper has the objective to summarize the basic features of the models which have resulted from this effort. A description is given of four categories of models, based primarily on the degree of empirical and theoretical input. Types of quantitative models are discussed, taking into account definitions, statistical models, analytic models, static models, and time-dependent models. Engineering models are also considered, giving attention to baseline models and 'worst-case' models.

Garrett, H. B.↗

Knowledge-based machine indexing from natural language text: Knowledge base design, development, and maintenance

One strategy for machine-aided indexing (MAI) is to provide a concept-level analysis of the textual elements of documents or document abstracts. In such systems, natural-language phrases are analyzed in order to identify and classify concepts related to a particular subject domain. The overall performance of these MAI systems is largely dependent on the quality and comprehensiveness of their knowledge bases. These knowledge bases function to (1) define the relations between a controlled indexing vocabulary and natural language expressions; (2) provide a simple mechanism for disambiguation and the determination of relevancy; and (3) allow the extension of concept-hierarchical structure to all elements of the knowledge file. After a brief description of the NASA Machine-Aided Indexing system, concerns related to the development and maintenance of MAI knowledge bases are discussed. Particular emphasis is given to statistically-based text analysis tools designed to aid the knowledge base developer. One such tool, the Knowledge Base Building (KBB) program, presents the domain expert with a well-filtered list of synonyms and conceptually-related phrases for each thesaurus concept. Another tool, the Knowledge Base Maintenance (KBM) program, functions to identify areas of the knowledge base affected by changes in the conceptual domain (for example, the addition of a new thesaurus term). An alternate use of the KBM as an aid in thesaurus construction is also discussed.

Genuardi, Michael T.↗

Data-driven learning of Mori–Zwanzig operators for isotropic turbulence

Developing reduced-order models for turbulent flows, which contain dynamics over a wide range of scales, is an extremely challenging problem. In statistical mechanics, the Mori–Zwanzig (MZ) formalism provides a mathematically exact procedure for constructing reduced-order representations of high-dimensional dynamical systems, where the effects due to the unresolved dynamics are captured in the memory kernel and orthogonal dynamics. Turbulence models based on MZ formalism have been scarce due to the limited knowledge of the MZ operators, which originates from the difficulty in deriving MZ kernels for complex nonlinear dynamical systems. In this work, we apply a recently developed data-driven learning algorithm, which is based on Koopman's description of dynamical systems and Mori's linear projection operator, on a set of fully resolved isotropic turbulence datasets to extract the Mori–Zwanzig operators. With data augmentation using known turbulence symmetries, the extracted Markov term, memory kernel, and orthogonal dynamics are statistically converged and the generalized fluctuation–dissipation relation can be verified. The properties of the memory kernel and orthogonal dynamics, and their dependence on the choices of observables are investigated to address the modeling assumptions that are commonly used in MZ-based models. A series of numerical experiments are then constructed using the extracted kernels to evaluate the memory effects on prediction. The results show that the prediction errors are strongly affected by the choice of observables and can be further reduced by including the past history of the observables in the memory kernel.

97 MATHEMATICS AND COMPUTING↗

The Delplot kinetic method applied to systems with adsorbates: Hydrodeoxygenation of benzofuran on a bimetallic CoPd phosphide catalyst supported on KUSY

The Delplot method provides a means of analyzing conversion and selectivity data to derive a reaction sequence and has been applied so far to gas-phase or liquid-phase species. This study analyses the applicability of the method for catalytic reactions and considers for the first time adsorbed intermediates. The method is applied to a contact time study of the hydrodeoxygenation (HDO) of benzofuran at 0.5 MPa and 350 °C over a catalyst consisting of bimetallic CoPd phosphide supported on a potassium ion-exchanged ultra-stable Y (KUSY) zeolite. Both simple and detailed reaction networks were derived. The simple networks considered only gas-phase species and were modeled by a first-order sequence of steps, whereas the detailed network took into account adsorbed intermediates and was simulated using a rake mechanism. The networks were compared using F-statistics, which accounted for the differences in the number of fitting parameters. The detailed network gave a better fit to the experimental data because it represented a more realistic description of the transformation. A suggested sequence from the Delplot method was consistent with the simple network but not with the detailed network. The lack of applicability of the Delplot analysis to the network with adsorbates was linked to overly large equilibrium constants, a determination supported by Delplot fitting for a model sequence. Further, this study indicated the inapplicability of the Delplot method in determining reaction sequences that involve adsorbed species with large equilibrium constants for formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

OSSE spectral analysis techniques

Analysis of the spectra from the Oriented Scintillation Spectrometer Experiment (OSSE) is complicated because of the typically low signal to noise (approx. 0.1 percent) and the large background variability. The OSSE instrument was designed to address these difficulties by periodically offset-pointing the detectors from the source to perform background measurements. These background measurements are used to estimate the background during each of the source observations. The resulting background-subtracted spectra can then be accumulated and fitted for spectral lines and/or continua. Data selection based on various environmental parameters can be performed at various stages during the analysis procedure. In order to achieve the instrument's statistical sensitivity, however, it will be necessary for investigators to develop a detailed understanding of the instrument operation, data collection, and the background spectrum and its variability. A brief description of the major steps in the OSSE spectral analysis process is described, including a discussion of the OSSE background spectrum and examples of several observational strategies.

Purcell, W. R.↗

The Development and Evaluation of an Operational Aerobraking Strategy for the Mars 2001 Odyssey Orbiter

The Mars 2001 Odyssey Orbiter successfully completed the aerobraking phase of its mission on January 11, 2002. This paper discusses the support provided by NASA's Langley Research Center to the navigation team at the Jet Propulsion Laboratory in the planning and operational support of Mars Odyssey Aerobraking. Specifically, the development of a three-degree-of-freedom aerobraking trajectory simulation and its application to pre-flight planning activities as well as operations is described. The importance of running the simulation in a Monte Carlo fashion to capture the effects of mission and atmospheric uncertainties is demonstrated, and the utility of including predictive logic within the simulation that could mimic operational maneuver decision-making is shown. A description is also provided of how the simulation was adapted to support flight operations as both a validation and risk reduction tool and as a means of obtaining a statistical basis for maneuver strategy decisions. This latter application was the first use of Monte Carlo trajectory analysis in an aerobraking mission.

Tartabini, Paul V.↗

CO2 Washout Testing of the REI and EM-ACES Space Suits

Requirements for using a space suit during ground testing include providing adequate carbon dioxide (CO2) washout for the suited subject. Acute CO2 exposure can lead to symptoms including headache, dyspnea, lethargy and eventually unconsciousness or even death. Symptoms depend on several factors including partial pressure of CO2 (ppCO2), duration of exposure, metabolic rate of the subject and physiological differences between subjects. The objective of this test was to characterize inspired oronasal ppCO2 in the Rear Entry I-Suit (REI) and the Enhanced Mobility Advanced Crew Escape Suit (EM-ACES) across a range of workloads and flow rates for which ground testing is nominally performed. Three subjects were tested in each suit. In all but one case, each subject performed the test twice to allow for comparison between tests. Suit pressure was maintained at 4.3 psid. Subjects wore the suit while resting, performing arm ergometry, and walking on a treadmill to generate metabolic workloads of approximately 500 to 3000 BTU/hr. Supply airflow was varied at 6, 5 and 4 actual cubic feet per minute (ACFM) at each workload. Subjects wore an oronasal mask with an open port in front of the mouth and were allowed to breathe freely. Oronasal ppCO2 was monitored real-time via gas analyzers with sampling tubes connected to the oronasal mask. Metabolic rate was calculated from the total CO2 production measured by an additional gas analyzer at the air outlet from the suit. Real-time metabolic rate was used to adjust the arm ergometer or treadmill workload to meet target metabolic rates. In both suits, inspired CO2 was primarily affected by the metabolic rate of the subject, with increased metabolic rate resulting in increased inspired ppCO2. Suit flow rate also affected inspired ppCO2, with decreased flow causing small increases in inspired ppCO2. The effect of flow was more evident at metabolic rates greater than or equal to 2000 BTU/hr. Results were consistent between suits, with the EM-ACES demonstrating slightly better CO2 washout than the REI suit, but not statistically significant. Regression equations were developed for each suit to predict the mean inspired ppCO2 as a function of metabolic rate and suit flow rate. This paper provides detailed descriptions of the test hardware, methodology and results, as well as implications for future ground testing in the REI and EM-ACES.

Mitchell, Kate↗

Physiological time-series analysis: what does regularity quantify?

Approximate entropy (ApEn) is a recently developed statistic quantifying regularity and complexity that appears to have potential application to a wide variety of physiological and clinical time-series data. The focus here is to provide a better understanding of ApEn to facilitate its proper utilization, application, and interpretation. After giving the formal mathematical description of ApEn, we provide a multistep description of the algorithm as applied to two contrasting clinical heart rate data sets. We discuss algorithm implementation and interpretation and introduce a general mathematical hypothesis of the dynamics of a wide class of diseases, indicating the utility of ApEn to test this hypothesis. We indicate the relationship of ApEn to variability measures, the Fourier spectrum, and algorithms motivated by study of chaotic dynamics. We discuss further mathematical properties of ApEn, including the choice of input parameters, statistical issues, and modeling considerations, and we conclude with a section on caveats to ensure correct ApEn utilization.

NASA Discipline Cardiopulmonary↗

Nonequilibrium statistical thermodynamics of multicomponent interfaces

Nonequilibrium interfacial thermodynamics has important implications for crucial biological, physical, and industrial-scale transport processes. Here, we discuss a theory of local equilibrium for multiphase multicomponent interfaces that builds upon the “sharp” interface concept first introduced by Gibbs, allowing for a description of nonequilibrium interfacial processes such as those arising in evaporation, condensation, adsorption, etc. By requiring that the thermodynamics be insensitive to the precise location of the dividing surface, one can identify conditions for local equilibrium and develop methods for measuring the values of intensive variables at the interface. We then use extensive, high-precision nonequilibrium molecular dynamics (NEMD) simulations to verify the theory and establish the validity of the local equilibrium hypothesis. In particular, we demonstrate that equilibrium equations of state are also valid out of equilibrium, and can be used to determine interfacial temperature and chemical potential(s) that are consistent with nonequilibrium generalizations of the Clapeyron and Gibbs adsorption equations. We also show, for example, that, far from equilibrium, temperature or chemical potential differences need not be uniform across an interface and may instead exhibit pronounced discontinuities. However, even in these circumstances, we demonstrate that the local equilibrium hypothesis and its implications remain valid. These results provide a thermodynamic foundation and computational tools for studying or revisiting a wide variety of interfacial transport phenomena.

36 MATERIALS SCIENCE↗

Two transitions in complex eigenvalue statistics: Hermiticity and integrability breaking

Open quantum systems have complex energy eigenvalues which are expected to follow non-Hermitian random matrix statistics, when chaotic, or two-dimensional (2d) Poisson statistics, when integrable. We investigate the spectral properties of a many-body quantum spin chain, i.e., the Hermitian Heisenberg model with imaginary disorder. Its rich complex eigenvalue statistics is found to separately break both Hermiticity and integrability at different scales of the disorder strength. With no disorder, the system is integrable and Hermitian, with spectral statistics corresponding to the 1d Poisson point process. At very small disorder, we find a transition from 1d Poisson statistics to an effective D -dimensional Poisson point process, showing Hermiticity breaking. At intermediate disorder, we find integrability breaking, as inferred from the statistics matching that of non-Hermitian complex symmetric random matrices in class AI † . For large disorder, as the spins align, we recover the expected integrability (now in the non-Hermitian setup), indicated by 2d Poisson statistics. These conclusions are based on fitting the spin-chain data of numerically generated nearest- and next-to-nearest-neighbor spacing distributions to an effective 2d Coulomb gas description at inverse temperature β . We confirm that such an effective description of random matrices also applies in classes AI † and AII † up to next-to-nearest-neighbor spacings. Published by the American Physical Society 2025

Akemann, Gernot (ORCID:0000000217104258)↗

The attractor dimension of solar decimetric radio pulsations

The temporal characteristics of decimetric pulsations and related radio emissions during solar flares are analyzed using statistical methods recently developed for nonlinear dynamic systems. The results of the analysis is consistent with earlier reports on low-dimensional attractors of such events and yield a quantitative description of their temporal characteristics and hidden order. The estimated dimensions of typical decimetric pulsations are generally in the range of 3.0 + or - 0.5. Quasi-periodic oscillations and sudden reductions may have dimensions as low as 2. Pulsations of decimetric type IV continua have typically a dimension of about 4.

Kurths, J.↗

Statistical analysis of correlations in the x-ray induced Coulomb explosion of iodopyridine

Coulomb explosion imaging is a promising experimental tool to study individual molecules. Here, in this work simulation data for the x-ray induced Coulomb explosion of 2-iodopyridine is analyzed and the involved fragmentation dynamics are described. It is found that particular final ion momenta show correlations that reflect a collision of two atoms during the explosion. Variations of the proton kinetic energies can be associated with variations in the charge build-up time. Covariances of the forces during the explosion can be utilized to simplify the description of the dynamics in reduced dimensionality using only four collective coordinates.

74 ATOMIC AND MOLECULAR PHYSICS↗

The variation of solar proton energy spectra and size distribution with heliolongitude

A statistical study of the initial phases of a large number of solar particle events provides an approach for an investigation of the variability in the production process and coronal diffusion. A description is given of the procedures which are suitable for identifying the parent flare of an event, taking into account the heliocentric distribution of the flare-associated events. The determination of the proton energy spectrum at the sun is discussed along with the variation of the spectral index with the associated flare heliocentric longitude, questions concerning the source spectra and the acceleration process, and the size distribution of flare associated particle events.

Van Hollebeke, M. A. I.↗