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Framework for Analysis and Visualization of Simulation Data (VizAly)
As supercomputing resources increase, cosmological scientists are able to run more detailed and larger simulations generating massive amounts of data. Analyzing these simulations with an available open-source toolkit is important for collaborative Department of Energy scientific discovery across labs, universities, and other partners. Developed software as a part of this collection include: comparing data with other existing simulations, verifying and validating results with observation databases, new halo finder algorithms, and using analytical tools to get insights into the physics of the cosmological universe. The goal of this software project is to provide a set of open-source libraries, tools, and packages for large-scale cosmology that allows scientists to visualize, analyze, and compare large-scale simulation and observational data sets. Developed software will provide a variety of methods for processing, visualization, and analysis of astronomical observation and cosmological simulation data. These tools are intended for deployment on multiple scientific computing platforms, including but not limited to personal computers, cloud computing, experimental sites (telescopes) and high performance supercomputers.
Commercial Building Energy Saver, Web App v2.0
The CBES App is a web-based toolkit for use by small businesses and building owners and operators of small and medium size commercial buildings to perform energy benchmarking and retrofit analysis for buildings. The CBES App analyzes the energy performance of user's building for pre- and post-retrofit, in conjunction with user's input data, to identify recommended retrofit measures, energy savings and economic analysis for the selected measures.
Tafel Fitter v1.5
This program a new physical insight regarding efforts to evaluate electrochemical catalysts being developed for electrochemical energy conversion and storage. In particular, we ask: The methodology described here offers a solution to the problem of how to conduct Tafel analysis, which is used in determining electrocatalyst performance, in a quantitative manner, rather than through the qualitative guesswork it currently requires. This enables the measurement of electrocatalyst Tafel slopes and their associated parameters in a way that avoids the introduction of researcher bias, a problem to which current methods of Tafel fitting are prone. This procedure should significantly improve the ability of researchers working in the field of electrochemical energy conversion to rate and compare the catalyst materials being developed, advancing the characterization toolkit available to experimental electrochemists. This work is born out of our general hypothesis that it should be possible to determine the proper regions for unambiguously fitting Tafel data by applying some set of physical constraints that link aspects of a Tafel plot to its corresponding J-V polarization curve. This algorithm applies such constraints and achieves the extraction of Tafel slopes in a wholly quantifiable and reliable fashion. Verification of this approach is achieved by pairing the theory with experiment, as the algorithm was tested using experimentally acquired data of three distinct, electrochemical reactions: platinum hydrogen evolution, iridium-catalyzed oxygen evolution, and platinum-catalyzed dioxygen reduction. For each of these cases, the algorithm predicts the same Tafel slope as those reported in long-established bodies of electrochemical literature, results suggesting the general applicability of this method for determining electrocatalyst Tafel slopes.
HyRAM (Hydrogen Risk Assessment Models) v. 2.0
HyRAM is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM contains validated, simplified hydrogen behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM 1.0 was developed by Sandia National Laboratories for the U. S. Department of Energy. SAND2019-5270 M
LLNL/Rescal-snow
When wind blows over snow, it self-organizes. This forms surface features, such as ripples and dunes, that alter the reflectivity and thermal conductivity of the snow. These features have just begun to be studied by the snow and climate science communities (see 1, 2, 3 for recent work). We created rescal-snow to provide a highly capable snow dune modelling toolkit, to enable snow scientists to study snow features in controlled numerical experiments, and produce high-quality quantitative output. We hope that this model will be useful to researchers in snow science, geomorphology, and polar climate.
Efficent XAI Information Saliency Tool
This software is an implementation which is described in: "Efficient Saliency Maps for Explainable AI" (https://openreview.net/forum?id=ryxf9CEKDr). The toolkit is located in: https://mybitbucket.llnl.gov/projects/SAL/repos/smoe_lovi/browse. It is a set of of PyTorch related python scripts for extracting the what parts of an image are most salient to a deep neural network in an efficient manner. This source will allow one to replicate the results in the paper referenced above. Is there
TripleGraph
RDF triplestores are great tools for online graph analytic processing (i.e., graph pattern query processing), but they do not provide graph mining capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.). The software title “TripleGraph” is a graph analysis toolkit, which uses an RDF triplestore as its backend for creating, manipulating, mining, and programming with large scale property graphs. It allows users to run various graph mining algorithms easily. User can import edgelist-formatted (homogeneous graph) or JSON-formatted graph (property graph) into the RDF triplestore using the provided tool and perform various analysis such as (1) Node/edge retrieval and manipulation, (2) Pathfinding between two given nodes, (3) Running graph mining algorithms (PageRank/Personalized PageRank, Single Source Shortest Path/Multi-Source Shortest Path, Connected Component, Node Eccentricity, Peer Pressure Clustering). It supports standard graph data format and works with a standard SPARQL endpoint like Jena Fuseki. It allows users to perform online graph analytic processing and graph mining on the same platform (a triplestore).
hfem3d_parfrac
A toolkit of FORTRAN90 and PYTHON routines to automate calculation of electrostatic response of fracture networks in geomaterials, specifically designed for distributed memory compute clusters. Software integrates pre-processing of Cubit-generated meshes with calculations from HFEM3D and post-processing for aggregate data analysis.SAND2019-11083 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Aerial 3D Building Reconstruction from Drone Imagery (A3DBR) v1
This toolkit is composed of several modules for extracting buildings geometrical and thermal characteristics from RGB and thermal imagery captured using a drone. - Building 3D reconstruction module: leverage a photogrammetry software to construct a 3D point cloud from RGB drone imagery, which is then used in conjunction with image processing and geometric methods to extract building footprint and building height (i.e., 3D model of the building). - Windows to wall ratio estimation module: leverage deep learning semantic segmentation modeling to detect windows on 2D drone RGB images. The detected windows are then projected onto the extracted building 3D model (using building 3D reconstruction module) and their area is computed to obtain window to wall ratio estimation. - Thermal anomalies detection module: leverage image processing and machine learning algorithm to detect on 2D drone thermal images potential thermal anomalies within building's facades and roofs.
Zoltan2
Zoltan2 is a refactoring of the open-source Zoltan library that enables Zoltan users to take better advantage of current and emerging high performance computing architectures and software tools. Like Zoltan, Zoltan2 is a toolkit of combinatorial scientific computing algorithms that enable better performance of scientific codes via improved data locality and parallel scalability. Specifically Zoltan2 partitions data, colors graphs, and orders matrices. Zoltan2 is a software library written in template C++; it supports a wider range of data types and problem sizes than Zoltan. It will be available as part of Sandia's Trilinos framework of scientific computing packages.
Ensemble Data Analysis ENvironment (EDEN)
The EDEN toolkit facilitates exploratory data analysis and visualization of global climate model simulation datasets. EDEN provides an interactive graphical user interface (GUI) that helps the user visually construct dynamic queries of the characteristically large climate datasets using temporal ranges, variable selections, and geographic areas of interest. EDEN reads the selected data into a multivariate visualization panel which features an extended implementation of parallel coordinates plots as well as interactive scatterplots. The user can query data in the visualization panel using mouse gestures to analyze different ranges of data. The visualization panel provides coordinated multiple views whereby selections made in one plot are propagated to the other plots.
Warewulf 3.0
Warewulf is a scalable systems management suite originally developed to manage large high-performance Linux clusters. Focused on general scalable systems management, it includes a framework for system configuration, management, provisioning/installation, monitoring, event notification, and more via a modular plugin architecture. Install the components and features you need or leverage the existing system configuration stored within Warewulf to create custom solutions to meet your performance needs. One of the goals of the project is to grow the project by allowing other organizations and developers to contribute back to the project under an open source BSD license. We have been successful with gaining support within the open source community already and have contributors and support in not only the government and academic space but also the commercial sector (e.g. Intel). Being both open source and vendor neutral puts Warewulf in a unique position to be supported and utilized as an open standard in High Performance Computing (HPC). Warewulf is an active member of various HPC initiatives and groups and is considered one of the most utilized, extensible and scalable clustering toolkits available.
LibIsopach
LibIsopach is a toolkit for high performance distributed immersive visualization, leveraging modern OpenGL. It features a multi-process scenegraph, explicit instance rendering, mesh generation, and three-dimensional user interaction event processing.
JAva GUi for Applied Research (JAGUAR) v 3.0
JAGUAR is a Java software tool for automatically rendering a graphical user interface (GUI) from a structured input specification. It is designed as a plug-in to the Eclipse workbench to enable users to create, edit, and externally execute analysis application input decks and then view the results. JAGUAR serves as a GUI for Sandia's DAKOTA software toolkit for optimization and uncertainty quantification. It will include problem (input deck)set-up, option specification, analysis execution, and results visualization. Through the use of wizards, templates, and views, JAGUAR helps uses navigate the complexity of DAKOTA's complete input specification. JAGUAR is implemented in Java, leveraging Eclipse extension points and Eclipse user interface. JAGUAR parses a DAKOTA NIDR input specification and presents the user with linked graphical and plain text representations of problem set-up and option specification for DAKOTA studies. After the data has been input by the user, JAGUAR generates one or more input files for DAKOTA, executes DAKOTA, and captures and interprets the results
Vertical-Axis Wind Turbine Mesh Generator
VAWTGen is a mesh generator for creating a finite element beam mesh of arbitrary vertical-axis wind turbines (VAWT). The software accepts input files specifying tower and blade structural and aerodynamic descriptions and constructs a VAWT using a minimal set of inputs. VAWTs with an arbitrary number of blades can be constructed with or without a central tower. Strut connections between the tower and blades can be specified in an arbitrary manner. The software also facilitates specifying arbitrary joints between structural components and concentrated structural tenns (mass and stiffness). The output files which describe the VAWT configuration are intended to be used with the Offshore Wind ENergy Simulation (OWENS) Toolkit software for structural dynamics analysis of VAWTs. Furthermore, VAWTGen is useful for visualizing output from the OWENS analysis software.
IHT: Tools for Computing Insolation Absorption by Particle Laden Flows
INT is a toolkit for computing radiative heat exchange between particles. The algorithm is based on the the 'Photon Monte Carlo" approach described by Wang and Modest and implemented as a library that can be interfaced with a variety of CFD codes to analyze radiative heat transfer in particle laden flows.
Geant4 based positron beam source (GPos) v1.0
GPos is a software that was created to determine the properties of positron beams resulting from the interaction of the LBNL BELLA center PetaWatt laser-driven plasma-capillary accelerated electron beam and the atoms of a thin solid target. GPos is written in C++, easily compiled with cmake and the spack package manager, which allows for multi-thread and MPI parallel computing. Its functions expand on the Geant4 toolkit library and allow for propagation of the modelled particles through vacuum drift distances with a focusing element (thin lens approximation). Users can change beam-foil-drift-lens parameters - to adapt GPos to other particle sources and infrastructures - in a simple input file. The code particle data output format, openPMD, which is compatible, for example, with the input of the ECP WarpX project code used to explore the physics of particle acceleration in plasmas. Using GPos in conjunction to WarpX allowed us to test various configurations for designing a high-quality and high-energy positron source at BELLA -required for us to address positron acceleration challenges in the development of future linear colliders. GPos can also be advantageous when tackling the physics of muon sources for future muon colliders as well as for the investigation of positron sources in lower energy regimes for applications like annihilation spectroscopy and astrophysical gamma-ray-bursts.