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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

GIS Visualization of Transportation Energy Consumption

Transportation is witnessing unprecedented transformation, where emerging technologies are disrupting the way we travel. Be it sharing economy, or micro-mobility, the landscape of urban transportation is undergoing a much-needed paradigm shift. In order to capture and model these shifts, researchers need to be agile in their studies of the current and future transportation landscape. The need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration. " need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

BioenergyKDF: Enabling Spatiotemporal Data Synthesis and Research Collaboration

The Bioenergy Knowledge Discovery Framework (BioenergyKDF) is a scalable, web-based collaborative environment for scientists working on bioenergy related research in which the connections between data, literature, and models can be explored and more clearly understood. The fully-operational and deployed system, built on multiple open source libraries and architectures, stores contributions from the community of practice and makes them easy to find, but that is just its base functionality. The BioenergyKDF provides a national spatiotemporal decision support capability that enables data sharing, analysis, modeling, and visualization as well as fosters the development and management of the U.S. bioenergy infrastructure, which is an essential component of the national energy infrastructure. The BioenergyKDF is built on a flexible, customizable platform that can be extended to support the requirements of any user community especially those that work with spatiotemporal data. While there are several community data-sharing software platforms available, some developed and distributed by national governments, none of them have the full suite of capabilities available in BioenergyKDF. For example, this component-based platform and database independent architecture allows it to be quickly deployed to existing infrastructure and to connect to existing data repositories (spatial or otherwise). As new data, analysis, and features are added; the BioenergyKDF will help lead research and support decisions concerning bioenergy into the future, but will also enable the development and growth of additional communities of practice both inside and outside of the Department of Energy. These communities will be able to leverage the substantial investment the agency has made in the KDF platform to quickly stand up systems that are customized to their data and research needs.

Bioenergy.↗
DOE OSTI2015

GRDC. A Collaborative Framework for Radiological Background and Contextual Data Analysis

The Radiation Mobile Analysis Platform (RadMAP) is unique in its capability to collect both high quality radiological data from both gamma-ray detectors and fast neutron detectors and a broad array of contextual data that includes positioning and stance data, high-resolution 3D radiological data from weather sensors, LiDAR, and visual and hyperspectral cameras. The datasets obtained from RadMAP are both voluminous and complex and require analyses from highly diverse communities within both the national laboratory and academic communities. Maintaining a high level of transparency will enable analysis products to further enrich the RadMAP dataset. It is in this spirit of open and collaborative data that the RadMAP team proposed to collect, calibrate, and make available online data from the RadMAP system. The Berkeley Data Cloud (BDC) is a cloud-based data management framework that enables web-based data browsing visualization, and connects curated datasets to custom workflows such that analysis products can be managed and disseminated while maintaining user access rights. BDC enables cloud-based analyses of large datasets in a manner that simulates real-time data collection, such that BDC can be used to test algorithm performance on real and source-injected datasets. Using the BDC framework, a subset of the RadMAP datasets have been disseminated via the Gamma Ray Data Cloud (GRDC) that is hosted through the National Energy Research Science Computing (NERSC) Center, enabling data access to over 40 users at 10 institutions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS2014

Analyzing a 35-Year Hourly Data Record: Why So Difficult?

At the Goddard Distributed Active Archive Center, we have recently added a 35-Year record of output data from the North American Land Assimilation System (NLDAS) to the Giovanni web-based analysis and visualization tool. Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) offers a variety of data summarization and visualization to users that operate at the data center, obviating the need for users to download and read the data themselves for exploratory data analysis. However, the NLDAS data has proven surprisingly resistant to application of the summarization algorithms. Algorithms that were perfectly happy analyzing 15 years of daily satellite data encountered limitations both at the algorithm and system level for 35 years of hourly data. Failures arose, sometimes unexpectedly, from command line overflows, memory overflows, internal buffer overflows, and time-outs, among others. These serve as an early warning sign for the problems likely to be encountered by the general user community as they try to scale up to Big Data analytics. Indeed, it is likely that more users will seek to perform remote web-based analysis precisely to avoid the issues, or the need to reprogram around them. We will discuss approaches to mitigating the limitations and the implications for data systems serving the user communities that try to scale up their current techniques to analyze Big Data.

computational performance↗
DOE OSTI2025

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science↗
DOE OSTI2021

Visualizing Vehicle Acceleration and Braking Energy at Intersections along a Major Traffic Corridor

Automobiles approaching a controlled intersection need to brake and come to a full stop when the signal transitions from green to red, and the vehicle must later accelerate to normal speeds after the signal changes back to green. These stops and starts associated with normal signal changes lead to unnecessary energy consumption and vehicle emissions. Previous studies have revealed that the optimization of traffic intersections' signal controls and coordination facilitates smoother traffic flows with reduced stop-and-go driving, which can significantly reduce traffic congestion and unnecessary fuel waste. This paper presents an interactive visual analytics dashboard that allows transportation planners to explore and analyze energy consumption patterns resulting from temporally varying traffic signal phases at multiple intersections along a major transportation corridor using traffic simulation outputs. The visual dashboard is implemented as an accessible and responsive web application and employs a combination of visualization techniques to cover multiple aspects of vehicle acceleration and braking at multiple adjacent intersections along a corridor. The paper presents a case study of a simulated traffic scenario on the Shallowford Road traffic corridor located in Chattanooga, Tennessee to demonstrate the capability of the visual dashboard.

Xu, Haowen↗
NASA NTRS2019

Visualization and Analysis of Data from Small-Body Missions with NASA's Solar System Treks Portals

The portals of NASA's Solar System Trek Project (SSTP) provide web-based suites of interactive visualization and analysis tools enabling mission planners, planetary scientists, students, and the general public to explore planetary surfaces as seen through the eyes of many different instruments aboard a wide range of spacecraft. The portals present a vast collection of mapped data products from past and current missions for a growing number of planetary bodies. As web-based toolsets, the portals do not require users to purchase or install any software beyond current web browsers. They feature a common user interface and are available through a single integrated website at https://trek.nasa.gov. This presentation will highlight 4 portals focusing on small bodies. We will provide an overview of established portals for (1) Ceres and (4) Vesta, and present the early capabilities for new portals being introduced for (162173) Ryugu and (101955) Bennu.

Day, Brian↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Biologically Relevant Space Radiation Data

RadLab, a new component of the NASA Open Science Data Repository (OSDR), comprises a database of radiation measurements relevant to space biology, and visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. modules of the ISS), associated celestial bodies, trajectories, and spacecraft coordinates. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations, such as spacecraft schematics, time series plots, geospatial visualizations, and provides easy means to iteratively refine search parameters, inspect the data on the fly, and download target subsets. The release of RadLab currently available to the public contains datasets provided by US and international collaborators and focuses on data recorded on the ISS. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit; RadLab will also soon expand to include past (e.g. Shuttle and Mir) and future (e.g. Artemis) data. RadLab will provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. The RadLab Working Group has been formed to foster collaborations among data contributors and users, to identify data sources, to put in place standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the space radiation environment in human habitats.

database↗
NASA NTRS2015

Open Source Mission Control for Chrome

New technology presents the possibility to evolve mission control. WARP (Web Applications for Resource Prospector) a new open source toolset for mission visualization, brings mission control to the Chrome Web Browser. WARP integrates multiple data sources into a coherent visualization toolset from which users may assemble their own software, thus giving mission controllers more flexibility. This frees us to operate based on mission needs, rather than constraints enforced by software application boundaries.

software engineering↗
DOE OSTI2023

Status of genome function annotation in model organisms and crops

Abstract Since the entry into genome‐enabled biology several decades ago, much progress has been made in determining, describing, and disseminating the functions of genes and their products. Yet, this information is still difficult to access for many scientists and for most genomes. To provide easy access and a graphical summary of the status of genome function annotation for model organisms and bioenergy and food crop species, we created a web application ( https://genomeannotation.rheelab.org ) to visualize, search, and download genome annotation data for 28 species. The summary graphics and data tables will be updated semi‐annually, and snapshots will be archived to provide a historical record of the progress of genome function annotation efforts. Clear and simple visualization of up‐to‐date genome function annotation status, including the extent of what is unknown, will help address the grand challenge of elucidating the functions of all genes in organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Mapping the kinematical regimes of semi-inclusive deep inelastic scattering

We construct a language for identifying kinematical regions of transversely differential semi-inclusive deep inelastic scattering (SIDIS) cross sections with particular underlying partonic pictures, especially in the regions of moderate to low Q where sensitivity to kinematical effects becomes non-trivial. These partonic pictures map to power law expansions whose leading contributions ultimately lead to well-known QCD factorization theorems. In order to establish the consistency of a particular observable in SIDIS process with an estimate of the appropriate underlying partonic picture, we introduce new quantitative criteria expressed in terms of various ratios of partonic and hadronic momentum degrees of freedom. We propose how to use these criteria in phenomenology and provide a web tool which allows visualization of these ratios for any chosen kinematic configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

OpenMSI: A High-Performance Web-Based Platform for Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) enables researchers to directly probe endogenous molecules directly within the architecture of the biological matrix. Unfortunately, efficient access, management, and analysis of the data generated by MSI approaches remain major challenges to this rapidly developing field. Despite the availability of numerous dedicated file formats and software packages, it is a widely held viewpoint that the biggest challenge is simply opening, sharing, and analyzing a file without loss of information. Here we present OpenMSI, a software framework and platform that addresses these challenges via an advanced, high-performance, extensible file format and Web API for remote data access (http://openmsi.nersc.gov). The OpenMSI file format supports storage of raw MSI data, metadata, and derived analyses in a single, self-describing format based on HDF5 and is supported by a large range of analysis software (e.g., Matlab and R) and programming languages (e.g., C++, Fortran, and Python). Careful optimization of the storage layout of MSI data sets using chunking, compression, and data replication accelerates common, selective data access operations while minimizing data storage requirements and are critical enablers of rapid data I/O. The OpenMSI file format has shown to provide >2000-fold improvement for image access operations, enabling spectrum and image retrieval in less than 0.3 s across the Internet even for 50 GB MSI data sets. To make remote high-performance compute resources accessible for analysis and to facilitate data sharing and collaboration, we describe an easy-to-use yet powerful Web API, enabling fast and convenient access to MSI data, metadata, and derived analysis results stored remotely to facilitate high-performance data analysis and enable implementation of Web based data sharing, visualization, and analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

yStreX: yeast stress expression database

Over the past decade genome-wide expression analyses have been often used to study how expression of genes changes in response to various environmental stresses. Many of these studies (such as effects of oxygen concentration, temperature stress, low pH stress, osmotic stress, depletion or limitation of nutrients, addition of different chemical compounds, etc.) have been conducted in the unicellular Eukaryal model, yeast Saccharomyces cerevisiae. However, the lack of a unifying or integrated, bioinformatics platform that would permit efficient and rapid use of all these existing data remain an important issue. To facilitate research by exploiting existing transcription data in the field of yeast physiology, we have developed the yStreX database. It is an online repository of analyzed gene expression data from curated data sets from different studies that capture genome-wide transcriptional changes in response to diverse environmental transitions. The first aim of this online database is to facilitate comparison of cross-platform and cross-laboratory gene expression data. Additionally, we performed different expression analyses, meta-analyses and gene set enrichment analyses; and the results are also deposited in this database. Lastly, we constructed a user-friendly Web interface with interactive visualization to provide intuitive access and to display the queried data for users with no background in bioinformatics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

GRid Analysis and Visualization Interface (GRAVI) [SWR-24-16]

GRAVI (GRid Analysis and Visualization Interface) is a web application for viewing and analyzing nodal Production Cost Model (PCM) and Capacity Expansion Model (CEM) simulations. The web application provides the ability to animate geospatially coupled timeseries data in an agnostic way regardless of the underlying simulation tool used to generate the data. GRAVI also provides capabilities to animate non-geospatial data relevant to a PCM or CEM model. Furthermore, this web application can be tailored as an real-time operational tool to better understand a live grid.

Webb, Micah↗
DOE OSTI2014

The Integrated Basin-Scale Opportunity Assessment Initiative: Pilot Assessment for the Deschutes River Basin

In 2010, the U.S. Department of Energy’s (DOE’s) Wind and Water Power Technologies Office provided funding to Pacific Northwest National Laboratory, Oak Ridge National Laboratory (ORNL), and Argonne National Laboratory to develop an approach for assessing a river basin as an integrated system within the context of existing uses and environmental conditions to identify opportunities for sustainable hydropower development and environmental improvements. Called the Integrated Basin-Scale Opportunity Assessment Initiative (BSOA Initiative), the project is one of seven action items of the March 24, 2010 Memorandum of Understanding (MOU) for Sustainable Hydropower. Early efforts of the BSOA Initiative focused on forming a National Steering Committee, identifying potential basins for opportunity assessments, methodologies for stakeholder engagement, existing and needed analytical tools, barriers to the opportunity assessment process, and significant data gaps. One of the key outcomes was identifying a need for better collaborative decision-making tools that can be used by stakeholders. In response to this need, the Basin-Scale Project Team chose a scenario-based modeling approach for assessing hydropower, environmental, and other water-use opportunities. The approach involved the development of a daily hydrologic model for the Upper Deschutes River and Lower Crooked River subbasins to simulate alternative water management scenarios. Two example scenarios were constructed to demonstrate the use of the hydrologic model to explore three management goals in the Deschutes Basin: 1) increasing hydropower assets by adding new generation at existing dams or diversions and in existing irrigation canals or conduits, 2) increasing instream flows to benefit fish and aquatic ecosystems, and 3) maintaining existing water uses (primarily irrigation). Actions to achieve these goals were simulated by incrementally increasing minimum flow requirements during the storage season and reducing water demands during the irrigation season, while simulating hydropower generation at non-powered dams and in irrigation canals. As part of the effort to demonstrate scenario-based modeling, the project team also developed a web-based data-visualization interface for synthesizing modeling results. The interface allows users to view model results in raw form (daily flow) or in the form of value-based metrics that are based on specific information needs expressed by stakeholders (e.g., how often flow exceeds a conservation flow target at a certain location). In addition to the modeling efforts, 29 potential hydropower sites (14 non-powered dams, 15 canal/conduit sites) were evaluated for their technical and economic feasibility using ORNL’s Hydropower Energy and Economic Assessment tool. Results of the feasibility assessment indicated that eight of the sites (four non-powered dams, four canals/conduits) may be feasible and could add approximately 19 megawatts (MW) of hydroelectric capacity in the basin and generate over 78 gigawatt-hours (GWh) of energy per year. The approach presented here is intended to encourage consideration of methods that emphasize exploration of a range of potential management actions that may achieve a better balance among multiple, and often conflicting, management goals. It is important to consider the approach as an iterative and collaborative process focused on moving debates beyond agreement about an exact target that is acceptable to all parties to a discussion of how stakeholders can better understand how achieving their goals interacts with the achievement of goals by other stakeholder groups. By exploring the results of the model in this way, stakeholders are more likely to narrow the bounds of interest so that more in-depth analysis can be completed.

13 HYDRO ENERGY↗
DOE OSTI2015

Discovery of Protein–lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets

Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein–lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP–lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP–lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1997

A Web-Based System for Monitoring and Controlling Multidisciplinary Design Projects

In today's competitive environment, both industry and government agencies are under enormous pressure to reduce the time and cost of multidisciplinary design projects. A number of frameworks have been introduced to assist in this process by facilitating the integration of and communication among diverse disciplinary codes. An examination of current frameworks reveals weaknesses in various areas such as sequencing, displaying, monitoring, and controlling the design process. The objective of this research is to explore how Web technology, in conjunction with an existing framework, can improve these areas of weakness. This paper describes a system that executes a sequence of programs, monitors and controls the design process through a Web-based interface, and visualizes intermediate and final results through the use of Java(Tm) applets. A small sample problem, which includes nine processes with two analysis programs that are coupled to an optimizer, is used to demonstrate the feasibility of this approach.

Salas, Andrea O.↗