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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A methodology for decay heat characterization in molten salt reactors

Accurate decay heat prediction in molten salt reactors (MSRs) faces dual challenges: complex operational uncertainties and the need for interpretable models compatible with engineering workflows. This work presents a hybrid machine learning and segmented polynomial methodology that addresses both requirements through three key innovations. First, a modular data architecture encodes MSR-specific operational parameters (power density: 1-100 W cm -3 , humidity: 0-0.1 wt %, air ingress: 0-0.1 mol %) with uncertainty-aware temporal discretization spanning 15 orders of magnitude. Second, region-optimized machine learning models achieve 92.3 % root mean square error (RMSE) reduction over conventional polynomials while maintaining physical interpretability through automated piecewise equation generation. Third, dual front-end interfaces accelerate safety analyses — a Jupyter environment enables researchers to explore 10,000+ parameter combinations via interactive widgets, while a Streamlit web application reduces design iteration cycles through production-grade visualization tools. Operational deployment demonstrates prediction times of only a couple hundred milliseconds for 10 4 years decay profiles, enabling real-time optimization of spent fuel container designs.

42 - ENGINEERING↗
DOE OSTI2024

Updated resources for exploring experimentally-determined PDB structures and Computed Structure Models at the RCSB Protein Data Bank

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, RCSB.org), the US Worldwide Protein Data Bank (wwPDB, wwPDB.org) data center for the global PDB archive, provides access to the PDB data via its RCSB.org research-focused web portal. We report substantial additions to the tools and visualization features available at RCSB.org, which now delivers more than 227000 experimentally determined atomic-level three-dimensional (3D) biostructures stored in the global PDB archive alongside more than 1 million Computed Structure Models (CSMs) of proteins (including models for human, model organisms, select human pathogens, crop plants and organisms important for addressing climate change). In addition to providing support for 3D structure motif searches with user-provided coordinates, new features highlighted herein include query results organized by redundancy-reduced Groups and summary pages that facilitate exploration of groups of similar proteins. Newly released programmatic tools are also described, as are enhanced training opportunities.

Burley, Stephen K.↗
DOE OSTI2015

A Public-Private-Academic Partnership to Advance Solar Power Forecasting

Executive Summary NOAA is making major contributions to the solar forecasting project in three areas. First, it is improving its forecasts of solar irradiance, clouds, and aerosols in its numerical weather prediction models. Second, it is providing advanced satellite products for DOE's FOA awardees to use in their forecast systems. Third, it is using high-quality ground-based measurements from SURFRAD and ISIS stations to verify and validate forecast model output. This reports covers results from all three areas for the period May 1, 2014 - April 30, 2015. Modeling In its modeling effort, NOAA continues work to improve the skill of solar forecasts from the Earth System Research Lab (ESRL) research versions of the 13-km Rapid Refresh (RAP) and the 3-km High-Resolution Rapid Refresh (HRRR) models, which are in turn transitioned into operations at the National Centers for Environmental Prediction (NCEP). A major milestone was achieved in September 2014 with the initial operational implementation of the HRRR at NCEP. In the ESRL research versions of the models, testing and development, in both real-time runs and retrospective experiments, is guided by an extensive in-house verification system. Early in the SFIP project, we developed the capability to verify our model forecasts against the high-quality surface radiation measurements from the SURFRAD and ISIS networks. This highlighted some shortcomings with the RAP and HRRR forecasts of incoming shortwave radiation. Most of our effort during Phase 1 of SFIP was focused on addressing these problems with a variety of model system improvements. The RAP and HRRR models during the warm season of 2014 had a noticeable warm and dry bias in near-surface conditions over most of the central and eastern United States, and our new SURFRAD/ISIS verification revealed that there was also a large excess of incoming global horizontal irradiance in the models. We hypothesized that a lack of cloud cover (particularly low-level cloud cover) in the models was resulting in too much heating of the land surface. This, in turn, caused unrealistically strong surface heat fluxes and turbulent mixing in the planetary boundary layer (PBL), which further reduced the already deficient cloud cover. We addressed these issues with a combination of data assimilation system modifications and model physics improvements. Many of our data assimilation changes were made with a view towards improving the near-term representation of clouds and precipitation. One of these changes involved better accounting for regions of weak reflectivity in the RAP cloud / hydrometeor assimilation system, in order to improve the representation of light precipitation in the RAP initial conditions and provide more realistic initial cloud cover. Additional modifications more accurately accounted for radar beam blockage and data gaps (particularly in the western United States), which improves shorter lead times forecasts of clouds and precipitation. We have also tested the assimilation of new data sources within the RAP and the HRRR, including radar radial velocity data and surface mesonet observations. Within the HRRR, we have tested the cycling of the 3-km land surface fields to allow a higher-resolution treatment of land surface processes. In terms of model physics development for SFIP, we have implemented a shallow cumulus scheme within the RAP, and have made numerous improvements to the Mellor-Yamada-Nakanishi-Niino (MYNN) PBL scheme to address insufficient low-level cloud cover in the models. We have conducted tests incorporating the radiation effects of (parameterized) boundary-layer clouds within the modified MYNN PBL scheme (independent of the convective schemes). The Grell-Freitas-Olson shallow cumulus scheme has also been tested within the 3-km HRRR. Finally, we have also modified the RUC land surface model (LSM) treatment of the vegetation wilting point, reducing it to increase evapotranspiration and increase cloud cover in the boundary layer. All of these changes work in tandem to significantly improve the model forecasts of cloud cover, incoming shortwave radiation, and near-surface temperature and moisture. Satellite The role of NOAA/NESDIS in the Solar Forecasting Improvement Project is to provide Advanced Satellite Products (ASPs) for the two forecasting teams at NCAR and IBM. The ASPs are cloud, surface, and atmosphere products derived from geostationary satellite imagery at the highest possible spatial and temporal resolution - such quantities as cloud mask, cloud probability, cloud transmission, cloud top height, cloud top temperature, cloud effective particle size, etc. Ancillary data, such as elevation and numerical weather prediction fields are provided in the files at the same resolution as well. There are at this time 147 different variables in the ASP output, including quality flags and processing information. The main goals for Year 1 of the project were to implement an Advanced Satellite Products system for the use of the IBM and NCAR teams, begin validation, and make any needed changes based on feedback from the teams. ASP files are being produced every GOES Imager acquisition, which occur on a 15-30 minute schedule. Processing is done on a dedicated computer, with a turn-around time of 8-21 minutes from image acquisition to results available on ftp. Several helpful visualizations of the data are also created for users on web pages. Users have been provided with a document titled "User's Guide for 1km Cloud Products Derived from GOES Imager Data using CLAVR-x", which discusses the basics of the source imagery, the process by which it is turned into Advanced Satellite Products, and considerations users should make when using the data. Validation of selected variables from the older 4km version of the products was also included. Future work will concentrate on validation of the 1km products and improving the turn-around time, product variety, and product quality as needed. Ground Observations In the ground-based measurement effort, NOAA's main objectives are to provide high quality radiation products for validation and verification of short-term to day-ahead solar forecasts. More specifically for the three year project, our goals include (1) Maintaining and providing data from our 7 SURFRAD and 7 ISIS; (2) Update ISIS radiation measurements from 3 min to 1 min data: (3) Purchase and install new pyrheliometers for direct solar irradiance measurements at the 7 SURFRAD sites; (4) Building, testing, and deploying two mobile SURFRAD stations at two utility plants in collaboration with DOE sponsored partners, and includes ongoing maintenance and processing of the data at the mobile sites; (5) Upgrading the data acquisition and communications at 7 SURFRAD sites and 7 ISIS sites; (6) Providing radiation data at the 7 SURFRAD sites in near real-time; (7) Develop and provide aerosol optical depth and cloud images and cloud fraction at our two mobile sites; (8) Provide data recovery rates each year; (9) Provide temporally and spatially averaged radiation products for comparison to HRRR and RAP solar forecasts and advanced satellite products; (10) Provide a data-set for analysis of conversion of direct and diffuse to sloped surfaces; (11) and as time permits develop and provide spectral solar irradiance, cloud optical depth and spectral albedo from the mobile sites. Milestones this year include working with the DOE sponsored teams to find locations to deploy two mobile SURFRAD stations. One existing unit was deployed at a 30MW PV facility in the San Luis Valley in collaboration with Xcel and the NCAR team in August, 2014. The second unit was built and tested at our facilities in Boulder, CO and deployed near Green Mountain Power's Education Center in Rutland, VT in collaboration with Green Mountain Power and the IBM Team in October, 2014. Data processing was implemented and the radiation data from these two mobile sites have been made available on our ftp server in near real-time. We also are providing images and cloud fraction from the TSI cameras for these two mobile sites on our ftp site. Another milestone was upgrading our data acquisition and communication systems at 7 SURFRAD and 7 ISIS sites. We accelerated our schedule for these upgrades to provide timely radiation products. These upgrades allow more reliable and near-real time radiation data delivery to the DOE sponsored teams to meet their goals. Lastly, we changed the data rate at the ISIS sites from 3 min to 1 min.

14 SOLAR ENERGY↗
DOE OSTI2026

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗
DOE OSTI2021

PSpecteR: A User-Friendly and Interactive Application for Visualizing Top-Down and Bottom-Up Proteomics Data in R

Visual examination of mass spectrometry data is necessary to assess data quality and to facilitate data exploration. Graphics provide the means to evaluate spectral properties, test alternative peptide/protein sequence matches, prepare annotated spectra for publication, and fine-tune parameters during wet lab procedures. Visual inspection of MS data is hindered by proprietary proteomics visualization software designed for particular workflows and academic software that lack visualization tools. We built PSpecteR, an open-source and interactive R Shiny web application to address these issues, with support for several steps of proteomics data processing, including: reading various mass spectrometry files, running open-source database search tools, labelling spectra with fragmentation patterns, testing post-translational modifications, plotting where identified fragments map to reference sequences, and visualizing algorithmic output and metadata. All figures, tables, and spectra are exportable within one easy-to-use graphical user interface. Our current software provides a flexible and modern R framework to support fast implementation of additional features. The open source code is readily available (https://github.com/EMSL-Computing/PSpecteR), and a PSpecteR Docker container (https://hub.docker.com/r/emslcomputing) is available for easy local installation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Opportunities for an Integrated Web-Based Workbench for Data Access and Analysis - 20244

Management of environmental issues can require integration of multiple types of data and information, conducting data analysis and interpretation, and providing data visualization for effective communications. These data elements are important for site management to support regulator interactions and provide defensibility for remedial decisions. Databases and information repositories are core elements of managing data; however, efficient data access and analysis also enable effective site management. The U.S. Department of Energy (DOE) Hanford Site is an example of a complex site with a voluminous quantity of environmental data and a need for efficient site management. Different tiers of data and information tools have been developed and deployed to address site needs. These tools are configured for ready access via the web site interfaces and meet the rigorous quality requirements for environmental site management. Evolving efforts are focused on an integrated platform to meet site environmental management needs. In this platform, users can access site information at multiple levels of detail based on their need and permissions, so that data and associated analyses are presented within the context of the site mission and the user's management or technical needs. This concept is not only applicable at individual sites like Hanford but also applicable at other sites within the DOE complex. An integrated web-based architecture that links data visualization, data analytics, and management tools can provide holistic access to large data sets, minimize complexity, and maximize interactivity and technical communication. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

RCSB PDB Mobile : iOS and Android mobile apps to provide data access and visualization to the RCSB Protein Data Bank

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) resource provides tools for query, analysis and visualization of the 3D structures in the PDB archive. As the mobile Web is starting to surpass desktop and laptop usage, scientists and educators are beginning to integrate mobile devices into their research and teaching. In response, we have developed the RCSB PDB Mobile app for the iOS and Android mobile platforms to enable fast and convenient access to RCSB PDB data and services. Lastly, using the app, users from the general public to expert researchers can quickly search and visualize biomolecules, and add personal annotations via the RCSB PDB's integrated MyPDB service.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

The use of haptic interfaces and web services in crystallography: an application for a `screen to beam' interface

Haptic interfaces have become common in consumer electronics. They enable easy interaction and information entry without the use of a mouse or keyboard. Our work illustrates the application of a haptic interface to crystallization screening in order to provide a natural means for visualizing and selecting results. By linking this to a cloud-based database and web-based application program interface, the same application shifts the approach from `point and click' to `touch and share', where results can be selected, annotated and discussed collaboratively. Furthermore, in the crystallographic application, given a suitable crystallization plate, beamline and robotic end effector, the resulting information can be used to close the loop between screening and X-ray analysis, allowing a direct and efficient `screen to beam' approach. The application is not limited to the area of crystallization screening; `touch and share' can be used by any information-rich scientific analysis and geographically distributed collaboration.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

WHONDRS-GUI: a web application for global survey of surface water metabolites

Background The Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) is a consortium that aims to understand complex hydrologic, biogeochemical, and microbial connections within river corridors experiencing perturbations such as dam operations, floods, and droughts. For one ongoing WHONDRS sampling campaign, surface water metabolite and microbiome samples are collected through a global survey to generate knowledge across diverse river corridors. Metabolomics analysis and a suite of geochemical analyses have been performed for collected samples through the Environmental Molecular Sciences Laboratory (EMSL). The obtained knowledge and data package inform mechanistic and data-driven models to enhance predictions of outcomes of hydrologic perturbations and watershed function, one of the most critical components in model-data integration. To support efforts of the multi-domain integration and make the ever-growing data package more accessible for researchers across the world, a Shiny/R Graphical User Interface (GUI) called WHONDRS-GUI was created. Results The web application can be run on any modern web browser without any programming or operational system requirements, thus providing an open, well-structured, discoverable dataset for WHONDRS. Together with a context-aware dynamic user interface, the WHONDRS-GUI has functionality for searching, compiling, integrating, visualizing and exporting different data types that can easily be used by the community. The web application and data package are available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1484811 , which enables users to simultaneously obtain access to the data and code and to subsequently run the web app locally. The WHONDRS-GUI is also available for online use at Shiny Server ( https://xmlin.shinyapps.io/whondrs/ ).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

High‐throughput profiling and analysis of plant responses over time to abiotic stress

Abstract Sorghum ( Sorghum bicolor (L.) Moench) is a rapidly growing, high‐biomass crop prized for abiotic stress tolerance. However, measuring genotype‐by‐environment (G x E) interactions remains a progress bottleneck. We subjected a panel of 30 genetically diverse sorghum genotypes to a spectrum of nitrogen deprivation and measured responses using high‐throughput phenotyping technology followed by ionomic profiling. Responses were quantified using shape (16 measurable outputs), color (hue and intensity), and ionome (18 elements). We measured the speed at which specific genotypes respond to environmental conditions, in terms of both biomass and color changes, and identified individual genotypes that perform most favorably. With this analysis, we present a novel approach to quantifying color‐based stress indicators over time. Additionally, ionomic profiling was conducted as an independent, low‐cost, and high‐throughput option for characterizing G x E, identifying the elements most affected by either genotype or treatment and suggesting signaling that occurs in response to the environment. This entire dataset and associated scripts are made available through an open‐access, user‐friendly, web‐based interface. In summary, this work provides analysis tools for visualizing and quantifying plant abiotic stress responses over time. These methods can be deployed as a time‐efficient method of dissecting the genetic mechanisms used by sorghum to respond to the environment to accelerate crop improvement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

GRACC: GRid ACcounting Collector

The OSG has long maintained a central accounting system called Gratia. It uses small probes on each computing and storage resource in order to collect resource usage. The probes report to a central collector which stores the usage in a database. The database is then queried to generate reports. As the OSG aged, the size of the database grew very large. It became too large for the database technology to efficiently query to generate detailed reports. The design of a replacement requires data storage that could be queried efficiently to generate multi-year reports. Additionally, it requires flexibilityto add new attributes to the collected data.In this paper we will describe updates to the GRACC architecture in the last 18 months. GRACC uses modern web technologies that were designed for large data storage, query, and visualization. That includes the open source database Elasticsearch, message broker software RabbitMQ, and Grafana and Kibana as data visualization platforms. It uses multiple agents that perform operations on the data to transform it for easier querying and summarization.

Weitzel, Derek↗
DOE OSTI2018

NDDAV

Web-based Interface for the N-Dimensional Data Analysis and Visualization System.

Liu, Shusen↗
DOE OSTI2015

Improving models to predict phenological responses to global change

The term phenology describes both the seasonal rhythms of plants and animals, and the study of these rhythms. Plant phenological processes, including, for example, when leaves emerge in the spring and change color in the autumn, are highly responsive to variation in weather (e.g. a warm vs. cold spring) as well as longer-term changes in climate (e.g. warming trends and changes in the timing and amount of rainfall). We conducted a study to investigate the phenological response of northern peatland communities to global change. Field work was conducted at the SPRUCE experiment in northern Minnesota, where we installed 10 digital cameras. Imagery from the cameras is being used to track shifts in plant phenology driven by elevated carbon dioxide and elevated temperature in the different SPRUCE experimental treatments. Camera imagery and derived products (“greenness”) is being posted in near-real time on a publicly available web page (http://phenocam.sr.unh.edu/webcam/gallery/). The images will provide a permanent visual record of the progression of the experiment over the next 10 years. Integrated with other measurements collected as part of the SPRUCE program, this study is providing insight into the degree to which phenology may mediate future shifts in carbon uptake and storage by peatland ecosystems. In the future, these data will be used to develop improved models of vegetation phenology, which will be tested against ground observations collected by a local collaborator.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Real-time and Autonomous Water Quality Monitoring System Based on Remotely Operated Vehicle

Existing water quality monitoring systems near hydropower facilities are limited by the lack of mobility of the sensors’ carrier platform. Most systems use a buoy, a mounting fixture attached to a solid structure, or a human worker, which significantly limits the selection of the sampling sites and poses safety risks during data collection and equipment maintenance. To improve on this technology, we developed an autonomous water quality monitoring system that can operate in dangerous water environments near hydropower facilities for water sampling at multiple locations. The goal is to enable safe, timely, and comprehensive water-quality data collection; maximize power generation revenue with improved operational control; and reduce Federal Energy Regulatory Commission and state water quality monitoring costs for compliance. The system incorporates a remotely operated vehicle as the mobile monitoring platform, a dissolved oxygen sensor for monitoring water quality, a tether management system for automatically winding the tether, a solar mobile docking platform for suppling power to the ROV, and a web-based graphical user interface for data post-processing and visualization. In addition, preliminary field research are presented to demonstrate the system capabilities.

Salalila, Aljon L.↗
DOE OSTI2015

Deactivation and decommissioning web log analysis using big data technology - 15710

The D and D Knowledge Management Information Tool (D and D KM- IT) is a web-based knowledge management information tool built for the D and D user community. Big data is a massive volume of structured and unstructured datasets which is so large that it's difficult to process using traditional database techniques. Web logs are the repository of files which are generated automatically for any operation on the web site. Web log files generated from the D and D KM-IT will be processed using the Apache Hadoop Framework to extract meaningful data. Hadoop is an open-source software framework for storing and processing big data in a distributed environment on large clusters of commodity hardware. Hadoop framework consists of two main layers: Hadoop distributed file system (HDFS) and the Execution engine (MapReduce). Automatic parallelization and distribution; clean and simple programming abstraction. Implementation: Web log files from the D and D KM-IT server are fetched using Apache Flume and loaded into the Hadoop distributed file system. Using the Apache Hcatalog tool, the web log data is parsed and converted into a structured table format. A Pig program is developed to query the tables to retrieve and store the significant information onto the HDFS. The extracted data is fed to business visualization tools such as Microsoft Excel for analysis and reporting. Results The reports generated through the web log data processing will be analyzed to improve the usability and performance of the D and D KM-IT. Conclusion/Future Work: User keyword information can be explored to add new trending topics to the D and D KM-IT application. Statistics generated can be compared to analysis reports from existing analytical tools.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Suite of Comprehensive Rapid Analysis Tools for Estimation (SOCRATES) - 19076

Long-term monitoring and remedy implementation require ongoing assessment and analytics, much of which relies on intensive and time-consuming data integration and engineering, data manipulation, and 'big-data' analytics. Many of these analyses, such as groundwater flow direction, contaminant rate attenuation, and non-parametric statistics, are spatial-temporal in nature and involve coalescing disparate data sets from a variety of sources with measurement frequencies from milliseconds to years, as well as total data volumes often exceeding the petabyte scale. Web-based analytical tools are advantageous for ongoing real-time or near-real-time ingestion of data from various sources for general data access and visualization, and also allow for complex, data rich calculations by leveraging expansive networks and virtually unlimited compute power. A web-based framework offers a natural architecture for such endeavors, as access to compute nodes through auto-scaling and dynamic frameworks enables speedy data manipulation and unlimited access to any data set that is made available via an http request. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

A software package for plasma facing component analysis and design: the Heat flux Engineering Analysis Toolkit (HEAT)

The engineering limits of plasma facing components (PFCs) constrain the allowable operational space of tokamaks. Poorly managed heat fluxes that push the PFCs beyond their limits not only degrade core plasma performance via elevated impurities, but can also result in PFC failure due to thermal stresses or melting. Simple axisymmetric assumptions fail to capture the complex interaction between 3D PFC geometry and 2D or 3D plasmas. This results in fusion systems that must either operate with increased risk or reduce PFC loads, potentially through lower core plasma performance, to maintain a nominal safety factor. High precision 3D heat flux predictions are necessary to accurately ascertain the state of a PFC given the evolution of the magnetic equilibrium. A new code, the Heat flux Engineering Analysis Toolkit (HEAT), has been developed to provide high precision 3D predictions and analysis for PFCs. HEAT couples many otherwise disparate computational tools together into a single open source python package. Magnetic equilibrium, engineering CAD, finite volume solvers, scrape off layer plasma physics, visualization, high performace computing, and more, are connected in a single web-based user interface. Linux users may use HEAT without any software prerequisites via an appImage. This manuscript introduces HEAT, discusses the software architecture, presents first HEAT results, and outlines physics modules in development.

divertor physics↗
DOE OSTI2025

pnnl/GeoCLUSTER

GeoCLUSTER is a Python-based web application that provides a collection of interactive methods for streamlining the visualization of the technical and economic modeling of closed-loop geothermal systems.

Buchko, Alex [Pacific Northwest National Laborator↗