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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 91 records · Page 5

Omics-Lethal Human Viruses, West Nile Experiment WCT001

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus (WNV-NY99 382) and mutant WNV-E218A (WNV-NY99 382 E218A 2 nt) virus infection. Sample data was obtained from mouse cortex tissue for mRNA, miRNA, proteomics, lipidomics, and metabolomics expression analysis. Tissues from this experiment were matched to tissues from GSE77192 (WCB001), using 1/4 of the cortex and 1/2 of cerebellum from the same mice. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, West Nile Experiment WDC010

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus (WNVMT) and mutant (WNVE218A) virus infection. Sample data was obtained from primary mouse myeloid dendritic cells for mRNA and proteomics expression analysis. See Experiment WDC011 (GSE75222) for corresponding independent biological replicate study. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics and transcriptomics, each dataset download has a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, West Nile Experiment WDC011

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus (WNVMT) and mutant (WNVE218A) virus infection. Sample data was obtained from primary mouse myeloid dendritic cells for mRNA expression analysis. See Experiment WDC010 (GSE74628) for corresponding independent biological replicate study. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, West Nile Experiment WGCN002

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus infectious clone (WNV-NY99 clone 382) and mutant (WNVE218A) virus infection. Sample data was obtained from mouse granule cell neurons for mRNA and miRNA expression analysis. See Experiment WGCN003 for corresponding independent biological replicate study. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, West Nile Experiment WGCN003

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus infectious clone (WNV-NY99 clone 382) and mutant (WNVE218A) virus infection. Sample data was obtained from mouse granule cell neurons for mRNA and miRNA expression analysis. See Experiment WGCN002 for corresponding independent biological replicate study. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, West Nile Experiment WLN002

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus infectious clone (WNV-NY99 clone 382) and mutant WNV-E218A (WNV-NY99 382 E218A 2 nt) virus infection. Sample data was obtained from mouse popliteal draining lymph nodes for mRNA and miRNA expression analysis. See Experiment WLN003 for corresponding omics analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, West Nile Experiment WLN003

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus infectious clone (WNV-NY99 clone 382) and mutant WNV-E218A (WNV-NY99 382 E218A 2 nt) virus infection. Sample data was obtained from mouse popliteal draining lymph nodes for proteomics, metabolomics, and lipidomics expression analysis. See Experiment WLN002 for corresponding transcriptome analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, and lipidomics dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Giovanni in the Cloud: Earth Science Data Exploration in Amazon Web Services

Giovanni is an exploration tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), providing 22 analysis and visualization services for over 1600 Earth Science data variables. Owing to its popularity, Giovanni has experienced a consistent growth in overall demand, with periodic usage spikes attributed to trainings by education organizations, extensive data analysis in response to natural disasters, preparations for science meetings, etc. Furthermore, the new generation of spaceborne sensors and high resolution models have resulted in an exponential growth in data volume with data distributed across the traditional boundaries of data centers. Seamless exploration of data (without users having to worry about data center boundaries) has been a key recommendation of the GES DISC User Working Group. These factors have required new strategies for delivering acceptable performance. The cloud-based Giovanni, built on Amazon Web Services (AWS), evaluates (1) AWS native solutions to provide a scalable, serverless architecture; (2) open standards for data storage in the Cloud; (3) a cost model for operations; and (4) end-user performance. Our preliminary findings indicate that the use of serverless architecture has a potential to significantly reduce development and operational cost of Giovanni. The combination of using AWS managed services, storage of data in open standards, and schema-on-read data access strategy simplifies data access and analytics, in addition to making data more accessible to the end users of Giovanni through popular programming languages.

Giovanni↗

Enhancing occupant behavior representation for interoperability between building information modeling and building energy modeling

Building Performance Simulation (BPS) has been adopted as an essential tool for designing, operating, and retrofitting buildings to optimize energy efficiency throughout the building life cycle. The Green Building XML (gbXML) schema facilitates seamless data exchange between Building Information Modeling (BIM) and Building Energy Modeling (BEM) software tools. However, limited occupant behavior (OB) representation in BIM often leads to inconsistent and inaccurate energy simulation in BEM software. This paper presents 154 systematic enhancements to the existing occupant behavior XML (obXML) schema v1.3.4, initially developed for standardizing OB representation for BEM, to address existing limitations and improve interoperability with BIM models. The enhancements encompass improved integration with BIM models through extended building representations and system operations, expanded support for advanced OB models with additional environmental parameters and mathematical capabilities, and implementation of a standardized model documentation framework. To facilitate seamless data transformation between gbXML and obXML schemas, we developed a publicly available gb-obXML Schema Converter. Three case studies demonstrate the enhanced schema’s capabilities: representation of building information using a two-story office building model, documentation of a window operation behavior model, and validation of the schema converter’s functionality. The enhanced obXML schema v1.4 enables sophisticated modeling of occupant-building interactions while maintaining consistency with industry-standard BIM schemas. The standardized documentation framework facilitates reproducibility and knowledge sharing in the OB research community, while the schema converter automates the integration of building information into OB simulation workflows. These enhancements establish a foundation for more accurate building performance simulation by supporting sophisticated representation of occupant behavior within the BIM-to-BEM simulation workflows.

Chung, Jihoon↗

dGen (Distributed Generation Market Demand) Model Data: Alpha Release

Open sourced data needed to run the basic alpha release version of the dGen model. Includes a pre-generated agent file of 100,000 agents in pickle file format along with the base schema and table data in parquet format that are needed to create a postgreSQL database for the model to interact with.

14 SOLAR ENERGY↗

A Robust Schema for Storing and Managing Machine Learning Data and Models

- Machine Learning (ML) has enabled models that can improve efficiency and decrease computational cost - ML models are crucial in enabling Integrated Computational Materials Engineering (ICME) - Large data sets require robust means of storing ML data and models

Brandon L. Hearley↗

Sandia National Laboratories Ecosystem for Open Science: Metadata Schema v0.2 Description.

The Ecosystem for Open Science (eOS) initiative was established in 2019. Its objective is improving openness and sharing of data and information across Defense Nuclear Nonproliferation (DNN) Research and Development (R&D) activities. To support this initiative, the eOS team at Sandia National Laboratories (SNL) developed metadata and data standards and proposed a machine-readable metadata schema. The nuclear explosion monitoring field was selected as a focus area due to its the wide range of pertinent phenomenologies.We developed the DCAT-eOS-AP metadata schema extending the Data Catalog Vocabulary version 2 (DCATv2) standard using an application profile (AP), to fit the needs of multi-disciplinary NA-22 projects. The DCAT-eOS-AP metadata schema describes data at different levels of granularity ranging from general descriptions to more domain-specific granular metadata. Its implementation and serialization is flexible with the ability to include new file or data types. Thus, it will scale with the ever-increasing data management needs of government research. Due to the multitude of phenomenologies represented in the DCAT-eOS-AP schema, we anticipate that it will be easily extensible to various projects across many DOE mission areas. This document describes data management challenges faced within the DNN R&D portfolio and provides insight on how metadata and data standards/guidelines combined with a comprehensive metadata schema can add value to programs throughout the Department of Energy (DOE). It reviews the importance of metadata standards, FAIR (Findability, Accessibility, Interoperability, and Reusability) data principles, and metadata schemas. Additionally, it summarizes input from subject matter experts (SME) at SNL and other National Laboratories that resulted in metadata and data standards/guidelines encompassing domains relevant to NA-22 projects. Finally, we discuss the DCAT-eOS-AP metadata development. Implementation recommendations and future development directions are included for those keen on adopting the DCAT-eOS-AP metadata schema.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A Design of Activity-Based Mobility Intervention

Human mobility influences our society and vice versa. During the COVID-19 pandemic, non-pharmaceutical intervention that alters activity-based mobility such as work-from-home greatly impacted human mobility patterns. Many studies on developing mitigation strategies have employed or implemented their own mobility intervention within their model assumption. For fair evaluation between intervention strategies across models, it is significant to set up compatible experimental environments. However, it is difficult to apply the identical intervention to different kinds of models and compare their effectiveness because each model might have different assumptions, capabilities, and implementations. Even if one can apply intervention to heterogeneous models, it may produce undesirable artifacts due to difference of models and integration with intervention. Therefore, minimizing undesirable artifacts and facilitating intervention experiments across heterogeneous models are substantial. Taking this into account, this paper investigates a design of activity-based mobility intervention (ABMI). We define ABMI together with related concepts and develop an extensible data model and schema of ABMI based on the 5W1H method that can be used in different models. As a case study, we apply the ABMI model to a micro-simulation to demonstrate the usability of the proposed model. We expect that standardized ABMI and interfaces may help to streamline development and experiments of intervention strategies across heterogeneous models.

Kim, Joon-Seok↗

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗

CO2-Locate: A Dynamic Database and Tool for Accessing National Oil and Gas Well Data to Inform Carbon Storage Projects

The CO2-Locate Database is a growing compilation of publicly available wellbore resources that have been merged based on common attributes across data sources with an attribute schema developed to be consistent across disparate resources, reduce data gaps, and eliminate record redundancy. The first version of CO2-Locate has been published to Energy Data eXchange (EDX) and includes the integrated public wells dataset as well as additional geospatial summary layers of key wellbore characteristics to protect proprietary resources. Additionally, the CO2-Locate database has been deployed into a web application, enabling easy access, data filtering capabilities, and visualization of U.S. wellbore infrastructure by stakeholders to inform injection site selection and risk assessments.

Dyer, Alec S. [NETL Site Support Contractor, Natio↗

Bay Area Regional Energy: Network Integrated Commercial Retrofits (BRICR) Project. Final Report

The BRICR project applied large-scale building energy modeling concepts with the aim of reducing the cost of energy efficiency targeting, design, and project development, and measurement of energy savings for energy efficiency programs implemented by local governments that serve small and medium commercial buildings (SMB). The project leveraged the services and resources of existing local government energy programs serving disadvantaged and hard-to-reach SMB customers. In contrast to programs run by utilities, local government programs generally do not have direct access to energy billing records for an entire class of customers in a geographic area, which prior research demonstrated useful for large-scale building energy model baseline development and calibration. , However, local governments are rich in public records that offer important clues about physical attributes and uses that, along with behavior, determine energy use. Relying only on public records, BRICR demonstrated development of credible baseline energy models for 3,792 office, retail, and hotel buildings. Publicly disclosed annual energy use data from a local energy benchmarking program and anonymized data from the Building Performance Database, the nation’s largest dataset about energy-related characteristics of buildings, were utilized to validate and calibrate energy models via an innovative method comparing distributions of energy intensity by fuel type for portfolios of buildings of similar size, vintage, and use. Portfolio calibration does not provide certainty that an energy model fits an individual building; the method is useful when billing data is not accessible – a common situation for researchers, energy service providers and ESCOs, local governments, and any party other than a utility. A software component was developed, the BRICR gem, which automates simulation when relevant data is added or edited by the user to a file saved in the standardized BuildingSync XML schema for energy audit data. The component was demonstrated as a simplified means to generate a mass of energy models corresponding to public records containing basic attributes such as building scale, location, use, year built, and aspect ratio in combination with building energy code prototype data corresponding to use and vintage. The component was also demonstrated as a simplified means to automate energy simulation when attributes are revised; the intention was to enable iterative improvement of the baseline model and energy savings estimates for common energy conservation measures as users revise relevant attributes based on their observations. In the context of institutional change and uncertainty for the participating local government energy programs, 13 whole building retrofits were completed. Impacts were measured by applying the CalTRACK2.0 methods to standardize measurement of normalized metered energy consumption. The GRIDMeter methods of stratified sampling and individual load shape analysis were applied to adjust for impacts of the effect of COVID-19 on retrofitted buildings in the context of all local buildings of similar size and use. Excluding impacts of the pandemic, retrofitted buildings demonstrated between 1.6% and 25.1% reduction in energy use. The project contributed use cases and feedback that helped inform evolution of the software tools and data formats that were combined for the first time in the BRICR project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A wind tunnel database using RIM

Engineering data base development which has become increasingly widespread to industry with the availability of data management systems is examined. A large data base was developed for wind tunnel data and related model test information, using RIM as the data base manager. The arrangement of the wind tunnel data into the proper schema for the most efficient database utilization is discussed. The FORTRAN interface program of RIM is used extensively in the loading phases of the data base and by the users. Several examples to illustrate how the Wind Tunnel Data base might be searched for specific data items and test information using RIM are presented.

Wray, W. O., Jr.↗

Landsat Data Continuity Mission (LDCM) - Optimizing X-Band Usage

The NASA version of the low-density parity check (LDPC) 7/8-rate code, shortened to the dimensions of (8160, 7136), has been implemented as the forward error correction (FEC) schema for the Landsat Data Continuity Mission (LDCM). This is the first flight application of this code. In order to place a 440 Msps link within the 375 MHz wide X band we found it necessary to heavily bandpass filter the satellite transmitter output . Despite the significant amplitude and phase distortions that accompanied the spectral truncation, the mission required BER is maintained at < 10(exp -12) with less than 2 dB of implementation loss. We utilized a band-pass filter designed ostensibly to replicate the link distortions to demonstrate link design viability. The same filter was then used to optimize the adaptive equalizer in the receiver employed at the terminus of the downlink. The excellent results we obtained could be directly attributed to the implementation of the LDPC code and the amplitude and phase compensation provided in the receiver. Similar results were obtained with receivers from several vendors.

Garon, H. M.↗