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DView is a time series data visualization tool that provides several different ways to plot time series datasets. It is particularly well suited for browsing the results of energy systems simulation programs such as BEOpt, SAM, and PVWatts.
This report conducts a preliminary investigation of the available literature and summarizes some potential advanced measurement and visualization techniques for operating high-temperature heat pipe (HP) that can be implemented to support the United States (U.S.) Department of Energy (DOE) Microreactor Program (MRP). The primary objective for the extensive literature research is to investigate the possibilities and feasibility for the design and construction of an advanced experimental test facility with the aim of producing high-fidelity high-resolution heat pipe data during its operation. Based on the existing HP test facilities at Idaho National Laboratory (INL)—including the Single Primary Heat Extraction and Removal Emulator (SPHERE) and the Microreactor Agile Non-Nuclear Experimental Test Bed (MAGNET)—further efforts will be made to examine the technical feasibility to HP measurements and support the research, development, and demonstration (RD&D) process for an HP-cooled microreactor. Continuing collaborations with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, other research institutes and universities are considered to be extremely important so that the experimental facility and resultant database can satisfy the validation needs of advanced heat pipe modeling codes being developed under DOE NEAMS program.
The Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP diffusion-weighted MRI (dMRI) data. We used an open-source software library (pyAFQ; https://yeatmanlab.github.io/pyAFQ) to perform probabilistic tractography and delineate the major white matter pathways in the HCP subjects that have a complete dMRI acquisition (n = 1,041). We used diffusion kurtosis imaging (DKI) to model white matter microstructure in each voxel of the white matter, and extracted tract profiles of DKI-derived tissue properties along the length of the tracts. We explored the empirical properties of the data: first, we assessed the heritability of DKI tissue properties using the known genetic linkage of the large number of twin pairs sampled in HCP. Second, we tested the ability of tractometry to serve as the basis for predictive models of individual characteristics (e.g., age, crystallized/fluid intelligence, reading ability, etc.), compared to local connectome features. To facilitate the exploration of the dataset we created a new web-based visualization tool and use this tool to visualize the data in the HCP tractometry dataset. Finally, we used the HCP dataset as a test-bed for a new technological innovation: the TRX file-format for representation of dMRI-based streamlines. We released the processing outputs and tract profiles as a publicly available data resource through the AWS Open Data program's Open Neurodata repository. We found heritability as high as 0.9 for DKI-based metrics in some brain pathways. We also found that tractometry extracts as much useful information about individual differences as the local connectome method. We released a new web-based visualization tool for tractometry—“Tractoscope” (https://nrdg.github.io/tractoscope). We found that the TRX files require considerably less disk space-a crucial attribute for large datasets like HCP. In addition, TRX incorporates a specification for grouping streamlines, further simplifying tractometry analysis.
The mission of Employee Health Services (EHS) at Sandia National Laboratories is to positively and efficiently impact the health of Sandia through patient-centered, cost-effective, community-connected care in support of its mission and people. We strive to continuously improve the delivery of health and wellness services. For the past few years, we have modeled our health programs around findings from the 2010 World Economics Forum (WEF): there are 8 top health risks and behaviors that drive 15 chronic conditions which account for 80% of the total health-care costs for all chronic illness worldwide. The WEF goes on to state that information and innovation are the keys to prevention, and EHS has decided to take a strong stand in both categories by utilizing health scorecards and department dashboards to visualize and share metrics with Sandia Leadership to foster improvements in employee wellness and optimize wellness offerings. Finally, these 2 types of information-sharing tools allow us to track the dollars spent and saved on our wellness programs, and show leadership where there is risk, where there is progress, and where there is need by providing current data that gives monthly, quarterly, and yearly feedback.
The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore’s Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. Importantly, while present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.
Purpose: Visualization and processing of medical images and radiation treatment plan evaluation have traditionally been constrained to local workstations with limited computation power and ability of data sharing and software update. We present a web-based image processing and planning evaluation platform (WIPPEP) for radiotherapy applications with high efficiency, ubiquitous web access, and real-time data sharing. Methods: This software platform consists of three parts: web server, image server and computation server. Each independent server communicates with each other through HTTP requests. The web server is the key component that provides visualizations and user interface through front-end web browsers and relay information to the backend to process user requests. The image server serves as a PACS system. The computation server performs the actual image processing and dose calculation. The web server backend is developed using Java Servlets and the frontend is developed using HTML5, Javascript, and jQuery. The image server is based on open source DCME4CHEE PACS system. The computation server can be written in any programming language as long as it can send/receive HTTP requests. Our computation server was implemented in Delphi, Python and PHP, which can process data directly or via a C++ program DLL. Results: This software platform is running on a 32-core CPU server virtually hosting the web server, image server, and computation servers separately. Users can visit our internal website with Chrome browser, select a specific patient, visualize image and RT structures belonging to this patient and perform image segmentation running Delphi computation server and Monte Carlo dose calculation on Python or PHP computation server. Conclusion: We have developed a webbased image processing and plan evaluation platform prototype for radiotherapy. This system has clearly demonstrated the feasibility of performing image processing and plan evaluation platform through a web browser and exhibited potential for future cloud based radiotherapy.
A Surveillance Program is in place to assess how nuclear material storage containers at LANL are aging in-service. This program is guided by the LANL Surveillance Plan which is required by DOE M441.1-1. The plan is modified as necessary to ensure that any issues identified during surveillance or laboratory studies are examined in future surveillances, and that any lifetime implications are taken into account. Under the plan, overall container integrity is evaluated by a combination of visual inspections and photographs. Multiple measurements are made to assess the SAVY 4000 performance, including, helium leakage rate, O-ring hardness (durometer), O-ring compression set, filter performance and filter water resistance. The containers for surveillance are chosen annually based on the previous surveillance program results and observations. The surveillance plan targets items believed to provide the greatest challenge to the SAVY 4000 container integrity.
A Surveillance Program is in place to assess how nuclear material storage containers at LANL are aging in-service. This program is guided by the LANL Surveillance Plan which is required by DOE M441.1-1. The plan is modified as necessary to ensure that any issues identified during surveillance or laboratory studies are examined in future surveillances, and that any lifetime implications are taken into account. Under the plan, overall container integrity is evaluated by a combination of visual inspections and photographs. Multiple measurements are made to assess the SAVY 4000 performance, including, helium leakage rate, O-ring hardness (durometer), O-ring compression set, filter performance and filter water resistance. The containers for surveillance are chosen annually based on the previous surveillance program results and observations. The surveillance plan targets items believed to provide the greatest challenge to the SAVY 4000 container integrity.
Purpose: The standard TomoTherapy 2D scanning system requires manual analysis using spreadsheets or similar software. Manual analysis is time consuming and does not allow efficient use of the medical physicist or timely results that may indicate issues during the acquisition of data. The purpose of this study is to determine if an in-house solution can provide timely analysis of TomoTherapy scan data. Methods: A custom MATLAB program utilizing a streamlined graphical interface was developed to interpret the native scanning data acquired by the TomoTherapy Electrometer Measurement System (TEMS). The gold beam data provided by the manufacturer was used as a baseline for the acquired data. Two separate sets of scan data were used including longitudinal, transverse, and percent depth dose (PDD). The scan data were compared visually in an overlay and analytically for each beam width using the full width half max (FWHM) for longitudinal profiles and difference inside the field core for the transverse profiles as recommended by TG-148. A plot of the PDD percent error at each point along the curve was generated to show agreement. The time to analysis was measured on a laptop running an Intel i5 processor with 8GB of RAM. Results: The software program required on average less than 5 seconds to load and analyze the results. No conversion or reformatting of the data was required. This allowed real-time visualization of the comparison to the gold beam data as well as the parameters recommended by TG-148. The average percent difference was 0.3% for the longitudinal profiles and 0.1% for the transverse profiles. All PDD data was less than 1% different beyond dmax. Conclusion: We have developed a tool to analyze TomoTherapy scan data in real-time. This allows an efficient method to perform beam commissioning, annual QA, and adjust the beam parameters if necessary.
The annual reports of organizations are a recurring type of public disclosure that communicates what an organization has done and/or plans to do. Worldwide, organizations use annual reports as powerful instruments for communication that is rich in narrative content and visuals. From the perspective of the leadership of an organization, statutory annual reports are communication devices to stakeholders. By analogy, from the perspective of stakeholders, the annual reports are learning devices that presents stakeholders with contents to generate knowledge about an organization. We have chosen the online accessible U.S. Department of Energy (DOE) Annual Site Environmental Reports (ASERs) as a collection of resources for communicating and learning the environmental management strategies on environmental compliance and environmental sustainability. Environmental Compliance 'consists of regulatory compliance and monitoring programs that implement federal, state, and local requirements, agreements, and permits.' Environmental Sustainability 'promotes and integrates initiatives such as energy and natural resource conservation, waste minimization, green remediation, and the use of sustainable products and services.' Interactive visualizations of textual data designed with visual analytics software can allow stakeholders to interact with statements on the environmental management strategies by performing diverse actions that promote learning. These actions include annotating, comparing, filtering, navigating, selecting and sharing relevant statements. We expect that the possibility of these multiple actions in an interactive manner help stakeholders to learn more effectively about the environmental strategies at U.S. DOE sites. The current case study for the project is a collection of 1,894 annotated (value-added) statements (sentence text) from the eight chapters of the 2017 Savanah River Site (SRS) annual site environmental report. The preliminary interactive visualizations are available online. (authors)
The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program’s Bioimaging Science Program (BSP) is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. The extended goal of dynamic imaging is to functionally connect cellular components and interdependent organisms. Information about the time and place of chemical reactions in situ can identify causal relationships between biological activators and downstream effectors. BSP held its annual PI meeting virtually February 28–March 1. Contributing investigators are convened to review progress and current state-of-the-art bioimaging research. Holding the 2022 BSP meeting as part of the broader Genomic Science Program (GSP) PI meeting allowed researchers to interact with the extended GSP community. This convergence provided a platform for networking and exchange of ideas with experts in other technologies and in target BSP application areas, helping to forge new multidisciplinary collaborations among investigators from the sister programmatic areas within BER’s Biological Systems Science Division. An important highlight of the BSP meeting was the keynote presentation by Nobel Laureate Dr. Joachim Frank on Time-Resolved Macromolecular Imaging using Cryo-EM. He discussed microfluidic mixing and fast freezing to capture nonequilibrium intermediate states during molecular binding and conformational changes. The action of molecular machines can be captured at nanometer resolution and millisecond discrimination. BSP PIs made presentations describing their research focus and progress in plenary sessions on bioimaging science and on quantum-enabled bioimaging science research projects. BSP research at universities and DOE laboratories is presented in this report. A final discussion of the BSP was organized by meeting plenary session chairs, who prepared the following Executive Summary of current BSP research, research challenges, future opportunities, and potential ideas for expanding the BSP’s impact and interactions.
The central goal of this proposal was to directly visualize and quantify how electronic correlations, vibronic couplings, and local solute-solvent interactions control intramolecular electron motion on the femtosecond time scale. The proposed research program focused on solvated Ruthenium (Ru) based mixed-valence complexes, a prototypical class of transition-metal complexes, which are of significant interest for their potential applications in photochemical energy conversion. Electron movements following photochemical excitation are closely coupled with atomic/vibrational and solvent motion. To disentangle these various components requires tools designed to directly probe electron correlations and vibronic coupling (coherently coupled motions of electronic and vibrational coordinates) on the timescale of electron motion in the solution phase.
We report on the use of novel mathematical methods in hypergraph analytice over a large quantity of DNS data. Hypergraphs generalize graphs, as used in network science, to better model complex multiway relations in cyber data. Specifically, casting DNS data from Georgia Tech's ActiveDNS repository as hypergraphs allows us to fully represent the interactions between {\em collections} of domains and IP addresses. To facilitate large-scale analytics, we fielded an analytical pipeline of two capabilities. HyperNetX (HNX) is a Python package for the exploration and visualization of hypergraphs, acting as a frontend. For the backend, the Chapel HyperGraph Library (CHGL) is a library for high performance hypergraph analytics written in the exascale programming language Chapel. CHGL was used to process gigascale DNS data, performing compute-intensive calculations for data reduction and segmentation. Identified portions are then sent to HNX for both exploratory analysis and knowledge discovery targeting known tactics, techniques, and procedures.
Waste at Hanford is stored in 149 single-shell tanks and 28 double-shell tanks (DSTs). Concerns related to aging radioactive waste storage facilities throughout the US DOE complex led to Brookhaven National Laboratory (BNL) developing guidelines for structural integrity programs for tank systems (BNL-52527, Guidelines for Development of Structural Integrity Programs for DOE High-Level Waste Storage Tanks). The committee of experts who developed these guidelines is commonly known as the Tank Structural Integrity Panel (TSIP). The US DOE has subsequently adopted these guidelines, and requires site operators to have a program consistent with them (DOE M 435.1, Radioactive Waste Management Manual). The Washington River Protection Solutions, LLC (WRPS) manages the tanks for the US DOE Office of River Protection (ORP) under the Tank Operations Contract (TOC). The US DOE-ORP contractual agreement with the TOC (11-NSD-010) includes a requirement to 'maintain the tank structural integrity program as described in RPP-7574, Double-Shell tank Integrity Project Plan'. The DST integrity is maintained with a variety of activities such as ultrasonic and visual inspections, chemistry controls, corrosion monitoring and structural analyses methods. The recent loss of tank 241-AY-102 has led to the formation of the High-Level Waste Integrity Assessment Panel to evaluate the DST integrity project (DSTIP) and to recommend improvements to the DSTIP. This panel continues the DOE practice of seeking expert advice to guide the formulation and continuous assessment of tank integrity activities. The panel has concluded its work and WRPS has developed a series of tasks to implement their recommendations. (authors)
We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported programming models, including (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). We use the GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code as of April 2023 to generate a vast amount of implementations given simple + + prompt variants. To quantify and compare the results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. Results suggest that the OpenAI Codex outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general purpose Python can benefit from adding code keywords, while Julia prompts perform acceptably well for its mature programming models (e.g., Threads and CUDA.jl). We expect for these benchmarks to provide a point of reference for each programming model's community. Overall, understanding the convergence of large language models, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.
The U.S. Department of Energy Strategic Petroleum Reserve stores crude oil in caverns solution-mined in salt domes along the Gulf Coast of Louisiana and Texas. The CaveMan software program has been used since the late 1990s as one tool to analyze pressure mea- surements monitored at each cavern. The purpose of this monitoring is to catch potential cavern integrity issues as soon as possible. The CaveMan software was written in Microsoft Visual Basic, and embedded in a Microsoft Excel workbook; this method of running the CaveMan software is no longer sustainable. As such, a new version called CaveMan Enter- prise has been developed. CaveMan Enterprise version 1.0 does not have any changes to the CaveMan numerical models. CaveMan Enterprise represents, instead, a change from desktop-managed work- books to an enterprise framework, moving data management into coordinated databases and porting the numerical modeling codes into the Python programming language. This document provides a report of the code validation and verification testing.
AREVA NP developed the ATRIUM{sup TM}11 BWR fuel assembly to address the industry need for substantial improvements in fuel reliability and economic performance. The product development effort initially consisted of analytical design assessments and out-of-pile testing of prototype fuel assemblies and components. An integral component of the development project is a comprehensive in-pile demonstration program designed to fully exercise the new fuel assembly under a variety of operating conditions and to provide performance measurements of new design features. Fuel vendors, reactor operators, and regulators have successfully relied upon irradiation feedback derived from in-pile demonstration programs to safely introduce new features in reload quantities. The primary ATRIUM{sup TM} 11 in-pile demonstration program consists of 40 lead fuel assemblies (LFA) operating among five BWR reactors globally, covering the range of operational regimes and licensing environments necessary to confirm reload applications for the product. Since the initial irradiation in 2012, multiple pool-side inspection examinations have been performed. The inspection activities primarily focused on the new design features; including the spacer, fuel rod array, upper tie plate and fuel channel. These inspections have resulted in the collection of a substantial set of visual images, dimensional measurements, and performance feedback that are of general interest to the industry. Results from the inspections are compared to the database for existing products and to predetermined acceptance criteria. This paper provides details of the global in-pile demonstration program and the characteristics of the LFAs. Results of the inspection campaigns will be presented, including a summary of the technical assessment of specific new design features and the overall performance of the ATRIUM{sup TM} 11 product. (authors)
SUMMARY We introduce MTUQ, an open-source Python package for seismic source estimation and uncertainty quantification, emphasizing flexibility and operational scalability. MTUQ provides MPI-parallelized grid search and global optimization capabilities, compatibility with 1-D and 3-D Green’s function database formats, customizable data processing, C-accelerated waveform and first-motion polarity misfit functions, and utilities for plotting seismic waveforms and visualizing misfit and likelihood surfaces. Applicability to a range of full- and constrained-moment tensor, point force, and centroid inversion problems is possible via a documented application programming interface, accompanied by example scripts and integration tests. We demonstrate the software using three different types of seismic events: (1) a 2009 intraslab earthquake near Anchorage, Alaska; (2) an episode of the 2021 Barry Arm landslide in Alaska; and (3) the 2017 Democratic People’s Republic of Korea underground nuclear test. With these events, we illustrate the well-known complementary character of body waves, surface waves, and polarities for constraining source parameters. We also convey the distinct misfit patterns that arise from each individual data type, the importance of uncertainty quantification for detecting multimodal or otherwise poorly constrained solutions, and the software’s flexible, modular design.