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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Lightning-Generated NO(x) Seen By OMI during NASA's TC-4 Experiment: First Results

We present here case studies identifying upper-tropospheric NO2 produced in convective storms during NASA's Tropical Composition, Cloud and Climate Coupling Experiment (TC~i)n July and August 2007. DC8 aircraft missions, flown from the mission base in Costa Rica, recorded in situ NO2 profiles near active storms and in relatively quiet areas. We combine these data with measurements from the Ozone Monitoring Instrument (OMI) on the Aura satellite to estimate the amount of NO2 produced by lightning (LN02) above background levels in the regions influenced by storms. In our analysis, improved off-line processing techniques are employed to minimize known artifacts in the OM1 data. Information on lightning flashes (primarily CG) observed by the surface network operated by the Instituto Costarricense de Electricidad are examined upwind of regions where OM1 indicates enhanced LNO2. Comparisons of the observed flash data with measurements by the TRMM/LIS satellite instrument are used to obtain the lightning detection efficiency for total flashes. Finally, using the NO/NO2 ratio estimated from DC-8 observations, we estimate the average NO(x) production per lightning flash for each case in this study. The magnitudes of the measured NO(x) enhancements are compared with those observed by the DC-8 and with similar OM1 measurements analyzed in mid-latitude experiments.

Bucsela, Eric↗
DOE OSTI2024

Modern chemical graph theory

Abstract Graph theory has a long history in chemistry. Yet as the breadth and variety of chemical data is rapidly changing, so too do graph encoding methods and analyses that yield qualitative and quantitative insights. Using illustrative cases within a basic mathematical framework, we showcase modern chemical graph theory's utility in Chemists' analysis and model development toolkit. The encoding of both experimental and simulation data is discussed at various levels of granularity of information. This is followed by a discussion of the two major classes of graph theoretical analyses: identifying connectivity patterns and partitioning methods. Measures, metrics, descriptors, and topological indices are then introduced with an emphasis upon enhancing interpretability and incorporation into physical models. Challenging data cases are described that include strategies for studying time dependence. Throughout, we incorporate recent advancements in computer science and applied mathematics that are propelling chemical graph theory into new domains of chemical study. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Molecular Structures

Leite, Leonardo S. G.↗
NASA NTRS1993

The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data

The Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, has developed a prototype interactive software system called the Spectral Image Processing System (SIPS) using IDL (the Interactive Data Language) on UNIX-based workstations. SIPS is designed to take advantage of the combination of high spectral resolution and spatial data presentation unique to imaging spectrometers. It streamlines analysis of these data by allowing scientists to rapidly interact with entire datasets. SIPS provides visualization tools for rapid exploratory analysis and numerical tools for quantitative modeling. The user interface is X-Windows-based, user friendly, and provides 'point and click' operation. SIPS is being used for multidisciplinary research concentrating on use of physically based analysis methods to enhance scientific results from imaging spectrometer data. The objective of this continuing effort is to develop operational techniques for quantitative analysis of imaging spectrometer data and to make them available to the scientific community prior to the launch of imaging spectrometer satellite systems such as the Earth Observing System (EOS) High Resolution Imaging Spectrometer (HIRIS).

Kruse, F. A.↗
NASA NTRS2016

Multidisciplinary Model Transformation Through Simplified Intermediate Representations

There has long been a challenge of making engineering tools from multiple disciplines interoperate. This problem extends to system modeling practices. This challenge has been confronted with a wide variety of techniques. These techniques include attempting to interface tools together into combined suites, attempting to find underlying commonalities in mathematics, supporting connections through semantic encoding, various graph mappings and transformations, and code wrappers. All of these approaches have strengths and weaknesses. These are measured in multiple areas: relative freedom of action of individual domain engineers in developing their own tools, speed of execution, ease of creation, traceability, fidelity of information transfer, and degree of alignment between the concepts of different domains. This paper presents an approach to this interoperation problem currently being used in the World-Wide Web. The approach is to develop easy-to-parse formats that allow flexibility to both the file author and file interpreter. Many of the formats that are currently deployed sacrifice runtime performance for the ability of third parties to easily understand what to do with the data. XML became popular earlier as a de-facto standard format for many web applications, but is now being replaced by JSON to enhance human readability and provide a simpler data model. This is the basis for work in this paper. Our approach, which provides the key to interoperation, is a simplified “shrapnel” intermediate collection of objects and relationships that is the result of a breakdown of the system model into minimal pieces. It is then reassembled on the destination side, forming a two-step transformation. Previous efforts with single-step transformations have proven too difficult to create efficiently. In contrast, the use of this approach leads to an almost automatic procedure for transformation development. The Europa project is a large engineering project that must coordinate the efforts of many different teams with different specialties. The traditional form of exchanging engineering information has been documentation. The vision of model-based systems engineering is to make this information exchange much more digital. This paper presents the application of our simplified format to connecting two different engineering tools to the system model, with a focus on a dynamic mission simulation encoded in Modelica.

Cole, Bjorn↗
NASA NTRS1979

Empirical relationships between interplanetary conditions, magnetospheric flux transfer, and the AL index

Holzer and Slavin (1978) have found that the transfer of magnetic flux to and from the dayside magnetosphere as inferred from observed displacements of the magnetopause surface is correlated with both the magnitude of the auroral zone magnetic index AL and the incident flux of southward IMF. Empirical expressions specifying the rate at which magnetic flux is eroded in terms of interplanetary parameters and the rate of magnetic flux return as a function of AL have been developed. These relations are then used to predict magnetotail magnetic field enhancements from interplanetary and ground based data during an interval of substorm activity. The total magnetic flux in the tail is increased during intervals when the amount of flux transferred into its volume by dayside erosion exceeds the flux lost to the dayside by magnetospheric convection. Using Ogo-5 tail observations it is found for the sample events considered that these magnetic field enhancements can be described by empirical expressions for the magnetic flux transfer rates.

Slavin, J. A.↗
NASA NTRS2004

Fixed Packed Bed Reactors in Reduced Gravity

We present experimental data on flow pattern transitions, pressure drop and flow characteristics for cocurrent gas-liquid flow through packed columns in microgravity. The flow pattern transition data indicates that the pulse flow regime exists over a wider range of gas and liquid flow rates under microgravity conditions compared to 1-g and the widely used Talmor map in 1-g is not applicable for predicting the transition boundaries. A new transition criterion between bubble and pulse flow in microgravity is proposed and tested using the data. Since there is no static head in microgravity, the pressure drop measured is the true frictional pressure drop. The pressure drop data, which has much smaller scatter than most reported 1-g data clearly shows that capillary effects can enhance the pressure drop (especially in the bubble flow regime) as much as 200% compared to that predicted by the single phase Ergun equation. The pressure drop data are correlated in terms of a two-phase friction factor and its dependence on the gas and liquid Reynolds numbers and the Suratman number. The influence of gravity on the pulse amplitude and frequency is also discussed and compared to that under normal gravity conditions. Experimental work is planned to determine the gas-liquid mass transfer coefficients. Because of enhanced interfacial effects, we expect the gas-liquid transfer coefficients k(L)a and k(G)a (where a is the gas-liquid interfacial area) to be higher in microgravity than in normal gravity at the same flow conditions. This will be verified by gas absorption experiments, with and without reaction in the liquid phase, using oxygen, carbon dioxide, water and dilute aqueous amine solutions. The liquid-solid mass transfer coefficient will also be determined in the bubble as well as the pulse flow regimes using solid benzoic acid particles in the packing and measuring their rate of dissolution. The mass transfer coefficients in microgravity will be compared to those in normal gravity cocurrent flow to determine the mass transfer enhancement and propose new mass transfer correlations for two-phase gas-liquid flows through packed beds in microgravity.

Motil, Brian J.↗
DOE OSTI2026

Emerging anomaly detection techniques for electronic health records: A survey

Background Anomaly detection in electronic health records (EHRs) is a cornerstone of biomedical informatics, with direct implications for patient safety, clinical decision-making, and the prevention of healthcare fraud. Once guided primarily by simple rule-based methods, the field has advanced rapidly, driven by increased computing power, richer and more detailed health data, and the rise of machine learning and deep learning techniques. The objective of this paper is to provide a comprehensive overview of modern approaches to detecting anomalies in EHRs, outlining their strengths, limitations, and relevance to key healthcare challenges. We review traditional statistical methods alongside newer ML- and DL-based strategies and hybrid models, with particular attention to how these techniques support transparency and build clinical trust. Methods This paper presents a thorough and critical survey through systematic review (PRISMA-based) of the latest anomaly detection strategies in time-sequence data domains within electronic health record systems. Results We explore a broad spectrum of methodologies, including statistical models, supervised and unsupervised learning approaches, hybrid frameworks, and state-of-the-art ML-based techniques that collectively advance the precision and scalability of detecting anomalies in complex clinical datasets. In addition to mapping current capabilities, we address the enduring challenges that hinder widespread implementation and provide a forward-looking perspective on the future of anomaly detection in the data-rich landscape of modern healthcare. Summary The advancement in AI-based approaches is reported along with the basic principles of the individual approaches and their applicability. The increased availability of high-quality data, advancements in DL approaches, and enhanced computation power are leading to more frequent adaptation of DL-based approaches. Emerging DL-based approaches that have been adapted in other domains or recently applied in the EHR domain are also discussed in detail. Although DL-based approaches can improve model predictions by incorporating comorbidities, their application is limited in low-frequency data domains (e.g., when the total available data remains in the single digits). Therefore, the user must carefully consider the application based on data availability.

Anomaly detection↗
DOE OSTI2025

HDF5 in the exascale era: Delivering efficient and scalable parallel I/O for exascale applications

Accurately modeling real-world systems requires scientific applications at exascale to generate massive amounts of data and manage data storage efficiently. However, parallel input and output (I/O) faces challenges due to new application workflows and the state-of-the-art memory, interconnect, and storage architectures considered in exascale designs. The storage hierarchy has expanded with node-local persistent memory, solid-state storage, and traditional disk and tape-based storage, thus requiring efficiency at each layer and much more efficient data movement among these layers. This paper discusses how the ExaHDF5 project improved the I/O performance and data management for exascale architectures by enhancing HDF5, a widely used parallel I/O library. The team developed an Asynchronous I/O Virtual Object Layer (VOL) connector that allowed overlapping I/O with computation. They also created a Cache VOL to complement asynchronous I/O by incorporating fast storage layers, such as burst buffer and node-local storage, into the parallel I/O workflow through caching and staging data. Additionally, the team enabled data aggregation and I/O at the node level by using a Subfiling Virtual File Driver (VFD). To demonstrate superior I/O performance with HDF5 at exascale, the ExaHDF5 team collaborated with several exascale applications. In this paper, we show I/O performance improvements for three applications: Cabana (a particle-based simulation library), EQSIM (a regional earthquake simulation software), and E3SM (a climate system modeling library).

Asynchronous I/Ol↗
DOE OSTI2026

Knowledge-guided learning with curated prior genetic biomarkers for robust model interpretation

Abstract Motivation Knowledge-guided learning offers effective and robust model training strategies in data-scarce settings by incorporating established domain knowledge, thereby enhancing generalization, robustness, and interpretability. By contrast, conventional deep learning approaches rely purely on data-driven learning, which can limit robust model interpretability, particularly in high-dimensional settings with limited size samples. In computational biology, knowledge-guided learning has primarily leveraged network- and structural-based knowledge, leading to biologically interpretable representations and enhanced predictive performance compared to conventional approaches. However, curated biomarkers, one of the most accessible forms of biological knowledge, remain largely unexplored within knowledge-guided paradigms. Results In this study, we propose a model-agnostic training paradigm, Biomarker-driven Explainable Prior-guided Learning (BioExPL), that can be applied to any neural networks that incorporates curated prior knowledge. BioExPL enforces neural networks to reflect curated biomarker priors in their latent representations through a novel knowledge-alignment loss. BioExPL consistently demonstrated significantly improved predictive performance and enhanced model interpretability with minimized computational overhead in simulation studies and intensive experiments on multiple cancer datasets. BioExPL not only integrates prior curated knowledge into the model but also accurately identifies unknown associated signals additionally. BioExPL is model-agnostic and domain-independent, enabling its integration into diverse neural network architectures. Availability and implementation The open-source is publicly available at: https://github.com/datax-lab/BioExPL.

Baek, Beomsu [Department of Computer Science, Univ↗
NASA NTRS2018

Accessing Data Stored in Amazon S3 Using the Hyrax OPeNDAP Server

For three years we have been investigating data storage and retrieval in the Amazon Cloud, striving to optimize both storage structures and (cache-enhanced retrieval processes. These optimizations are hidden from data users, who simply employ the Data Access Protocol (DAP), a popular, Web-based Application Programmer Interface (API) developed by OPeNDAP. We present our collected findings and their realization in the Hyrax data server. Specific techniques include caching data on spinning disk; accessing sharded data in place; optimizing the organizational structures for data within the flat key-value space of Simple Storage Service (S3); and employing an API extension that permits simultaneous operations on many datasets in a single request.

Data access↗
NASA NTRS2004

Fixed Packed Bed Reactors in Reduced Gravity

We present experimental data on flow pattern transitions, pressure drop and flow characteristics for cocurrent gas-liquid flow through packed columns in microgravity. The flow pattern transition data indicates that the pulse flow regime exists over a wider range of gas and liquid flow rates under microgravity conditions compared to 1-g and the widely used Talmor map in 1-g is not applicable for predicting the transition boundaries. A new transition criterion between bubble and pulse flow in microgravity is proposed and tested using the data. Since there is no static head in microgravity, the pressure drop measured is the true frictional pressure drop. The pressure drop data, which has much smaller scatter than most reported 1-g data clearly shows that capillary effects can enhance the pressure drop (especially in the bubble flow regime) as much as 200% compared to that predicted by the single phase Ergun equation. The pressure drop data are correlated in terms of a two-phase friction factor and its dependence on the gas and liquid Reynolds numbers and the Suratman number. The influence of gravity on the pulse amplitude and frequency is also discussed and compared to that under normal gravity conditions. Experimental work is planned to determine the gas-liquid and liquid-solid mass transfer coefficients. Because of enhanced interfacial effects, we expect the gas-liquid transfer coefficients kLa and kGa (where a is the gas-liquid interfacial area) to be higher in microgravity than in normal gravity at the same flow conditions. This will be verified by gas absorption experiments, with and without reaction in the liquid phase, using oxygen, carbon dioxide, water and dilute aqueous amine solutions. The liquid-solid mass transfer coefficient will also be determined in the bubble as well as the pulse flow regimes using solid benzoic acid particles in the packing and measuring their rate of dissolution. The mass transfer coefficients in microgravity will be compared to those in normal gravity cocurrent flow to determine the mass transfer enhancement and propose new mass transfer correlations for two-phase gas-liquid flows through packed beds in microgravity.

Motil, Brian J.↗
NASA NTRS1981

The initialization of a mesoscale weather prediction model using satellite and precipitation data

An analysis and initialization procedure was developed capable of utilizing mesoscale satellite and radar data to resolve features in moisture and momentum fields on a finer scale than is discernible from radiosonde observation networks. The radiosonde moisture field is enhanced, using infrared satellite imagery and precipitation data from the surface observation network (also obtainable from the radar network) while the observed mesoscale rainfall rates are also used to define the initial divergent wind component. Results show that the predicted rainfall amounts are significantly improved when these additional data are taken into account.

Tarbell, T. C.↗
NASA NTRS1981

Texture transforms of remote sensing data

Tone and texture are fundamental interrelated visual concepts. The concepts are used for the digital analysis of remotely sensed image data. The reported investigation had the objective to develop software for the quantification of image texture and to apply the texture information to both image enhancement and thematic classification of remotely sensed data. The quantitative texture information was applied to the analysis of Landsat-2 Multispectral Scanner Subsystem (MSS) data. Attention is given to the characterization of image texture, textured transformations, the subtext program, and a description of methods and results. It is pointed out that the inability to use the texture transforms of the Landsat MSS data for the thematic mapping of the study area's land cover contrasts sharply with the reported results of the textural analysis of digitized aerial photography by Hsu (1978).

Irons, J. R.↗
NASA NTRSDate not supplied

Additional Metadata Guidelines to Improve the Structure and Usability of HDF and NetCDF Files

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global attributes or variables and are popular with the modeling community. HDF and NetCDF files are largely used with remote sensing data and have been used to support measurements from numerous campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. This metadata might be present in another file in the dataset containing the same data using the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) format. Recently, the Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a set of requirements for the HDF and NetCDF files for field studies, aiming to make the data products more interoperable and usable. Particularly, these requirements seek to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. These requirements would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. To be presented are the details of the MACIE requirements as well as examples of the implementation of these requirements for merge files and lidar observation data files.

Sean Leavor↗
DOE OSTI2020

Efficient 3-D velocity model building using joint inline and crossline plane-wave wave-equation migration velocity analyses

SUMMARY Wave-equation migration velocity analysis (WEMVA) is an image-domain inversion method for velocity model building. Automatic plane-wave WEMVA (PWEMVA) calculates the moveouts of plane-wave common-image gathers (CIGs) by searching a best-fitting parabola with semblance analysis and backprojects residual CIG moveouts into wavefield wave paths with a reflection tomographic kernel. However, 3-D PWEMVA is very computationally expensive because 3-D reflection tomographic inversion requires at least five 3-D reverse-time migrations per iteration and stores two types of source wavefields at model boundaries. We develop a joint inline and crossline PWEMVA method for efficient 3-D velocity model building. We alternatively implement the inline and crossline PWEMVAs with a constraint for each other, in which we iteratively construct the 3-D velocity model update through 1-D spline interpolation of 2-D gradients. The inline and crossline joint inversion is practical since PWEMVA only inverts for low-wavenumber velocity perturbations along wave paths, and the method can take less than 1 per cent of the computational cost of full 3-D PWEMVA. To construct unaliased plane waves for our joint inline and crossline PWEMVA, we develop a 3-D data interpolation method in the frequency–wavenumber (FK) domain to recover regularly and randomly missing traces. The method minimizes the misfit on sufficiently localized data subsets with iterative optimal step lengths and a gradient preconditioner that iteratively selects dominant dips along different azimuths. In numerical experiments, we use a 3-D synthetic seismic data set and a land 3-D field seismic data set acquired at the Farnsworth CO2-EOR (enhanced oil recovery) field to demonstrate the efficacy of our velocity model building and data interpolation methods.

Liu, Xuejian↗
DOE OSTI2025

Carbon Dioxide Removal Measurement, Reporting, and Verification Simulation toolkit (CDR MRVSim) v0.1

CDR MRVSim is a statistical software toolkit for techno-economic analysis of measurement, reporting, and verification of multiple carbon dioxide removal technologies. The current version applies Monte Carlo simulation to existing datasets estimate the cost and uncertainty of measuring the soil organic carbon (SOC) content of agricultural land, accounting for multiple sources of uncertainty, using data from field measurements. We are planning to incorporate enhanced rock weathering and other technologies into the software. The current model leverages existing data to characterize underlying variability in soil organic carbon and related parameters, including bulk density, in an agricultural field attempting to increase its SOC. We then simulate baseline and post-intervention "measurement campaigns" in which some number of SOC and bulk density measurements are conducted using a selected technology. This enables estimates of the cost and accuracy of measuring changes in SOC in the simulated field. The primary advantages over similar software are: 1) ability to quantify tradeoffs between cost and uncertainty in MRV across a range of possible MRV approaches 2) focus on guiding development of novel sensors by determining desirable sets of characteristics

Sherwin, Evan [Lawrence Berkeley National Laborato↗
NASA NTRS2000

Can Pseudobreakups be Predicted?

We statistically analyze many interplanetary shock events where there are both WIND interplanetary data and POLAR UV imaging data. We find that the shock compression events trigger pseudobreakups (PBs), substorm onsets, or enhance (pre-existing) substorm intensities. Using WIND interplanetary data and ground-based data, it is now believed that we can predict when PBs will occur and when substorm expansion phases will occur.

Zhou, X.-Y.↗
NASA NTRS2004

Derivation of Failure Rates and Probability of Failures for the International Space Station Probabilistic Risk Assessment Study

National Aeronautics and Space Administration s (NASA) International Space Station (ISS) Program uses Probabilistic Risk Assessment (PRA) as part of its Continuous Risk Management Process. It is used as a decision and management support tool to not only quantify risk for specific conditions, but more importantly comparing different operational and management options to determine the lowest risk option and provide rationale for management decisions. This paper presents the derivation of the probability distributions used to quantify the failure rates and the probability of failures of the basic events employed in the PRA model of the ISS. The paper will show how a Bayesian approach was used with different sources of data including the actual ISS on orbit failures to enhance the confidence in results of the PRA. As time progresses and more meaningful data is gathered from on orbit failures, an increasingly accurate failure rate probability distribution for the basic events of the ISS PRA model can be obtained. The ISS PRA has been developed by mapping the ISS critical systems such as propulsion, thermal control, or power generation into event sequences diagrams and fault trees. The lowest level of indenture of the fault trees was the orbital replacement units (ORU). The ORU level was chosen consistently with the level of statistically meaningful data that could be obtained from the aerospace industry and from the experts in the field. For example, data was gathered for the solenoid valves present in the propulsion system of the ISS. However valves themselves are composed of parts and the individual failure of these parts was not accounted for in the PRA model. In other words the failure of a spring within a valve was considered a failure of the valve itself.

Vitali, Roberto↗