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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 OSTI2024

USPAS Digital Low-Level RF firmware and software suite (uspas_llrf) v1.0

The USPAS Digital Low-Level RF firmware and software suite was originally developed for the USPAS 2023 LLRF course, for demonstrating the close loop RF control on the BerkeleyLab Marble FPGA carrier and Zest digitizer platform in controlling the RF field for various accelerators. The suite features Register-transfer level (RTL) designs for the board-support layer, digital signal processing and verification test benches, system-on-chip architecture, and Experimental Physics and Industrial Control System (EPICS) support, utilizing a open-source tool chain.

Du, Qiang↗
DOE OSTI2017

Final Report Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

The primary challenge motivating this project is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who can perform analysis only on a small fraction of the data they calculate, resulting in the substantial likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, which is known as in situ processing. The idea in situ processing was not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by Department of Energy (DOE) science projects. Our objective was to produce and enable the use of production-quality in situ methods and infrastructure, at scale, on DOE high-performance computing (HPC) facilities, though we expected to have an impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve this objective, we engaged in software technology research and development (R&D), in close partnerships with DOE science code teams, to produce software technologies that were shown to run efficiently at scale on DOE HPC platforms.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Advances in Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework.

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (FCT) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two high priorities for SFWST disposal R&D are design concept development and disposal system modeling. These priorities are directly addressed in the SFWST ''Geologic Disposal Safety Assessment'' (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, ''GDSA Framework'', for evaluating disposal system performance for nuclear waste in geologic media. ''GDSA Framework'' is supported by SFWST Campaign and its predecessor the Used Fuel Disposition (UFD) campaign. This report fulfills the GDSA Uncertainty and Sensitivity Analysis Methods work package (SF-20SN01030403) level 3 milestone — ''Advances in Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework'' (M3SF-20SN010304032). It presents high level objectives and strategy for development of uncertainty and sensitivity analysis tools, demonstrates uncertainty quantification (UQ) and sensitivity analysis (SA) tools in GDSA Framework in FY20, and describes additional UQ/SA tools whose future implementation would enhance the UQ/SA capability of ''GDSA Framework''. This work was closely coordinated with the other Sandia National Laboratory GDSA work packages: the GDSA Framework Development work package (SF- 2051\101030404), the GDSA Repository Systems Analysis work package (SF-2051\101030405), and the GDSA PFLOTRAN Development work package (SF-20SN01030406). This report builds on developments reported in previous ''GDSA Framework'' milestones, particularly M2SF- 19SNO1030403.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Exploring MDSplus data-acquisition software and custom devices

MDSplus is a software tool designed for data acquisition, storage, and analysis of complex scientific experiments. Over the years, MDSplus has primarily been used for data management for fusion experiments. This paper demonstrates that MDSplus can be used for a much wider variety of systems and experiments. We present a step-by-step tutorial describing how to create a simple experiment, manage the data, and analyze it using MDSplus and Python. To this end, a custom example device was developed to be used as the data source. This device was built on an opensource electronic hardware platform, and it consists of a microcontroller and two sensors. We read data from these sensors, store it in MDSplus, and use JupyterLab to visualize and process it. This project and code demo are available on the GitHub site at this URL: https://github.com/santorofer/MDSplusAndCustomeDevices

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Recovering Topology of Nested Volumes Represented by Single Closed Surfaces

As scientific computing abilities continue to advance, so too have the efforts to model and simulate highly complex geometries in radiation environments. Modeling has advanced from primitive constructive solid geometry (CSG) to voxelized models, and now to high fidelity polygon mesh models. While polygon mesh surface models are very accurate, most Monte Carlo codes do not allow for their direct use. Often they are converted to voxel or tetrahedral mesh models and then used with the physics codes. The Direct Accelerated Geometry Monte Carlo (DAGMC) software package has the ability to efficiently run transport calculations directly on tessellated surface models. Typically the surface meshes used for DAGMC calculations come from CAD-based geometry models generated by solid modeling software. In some cases geometries of interest, like human phantoms, are generated by other means and may not contain all of the necessary information for particle transport. For example, mesh geometries in the OBJ file format contain vertex and connectivity data for each surface, but do not have any information about surface topology. These types of file formats necessitate a tool that can build a hierarchy of surfaces and reconstruct the topological information. The generate hierarchy tool was developed for this purpose. The following summary will explain the algorithm behind the tool, describe a test case, and finally demonstrate a real-world application of the tool with an MCNP5 calculation that directly uses a polygon mesh human phantom.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

FENIX: An Open-Source Multiphysics Integrated Framework Enabling Collaborative Development of Plasma Facing Component Modeling Capabilities

Advanced modeling and simulation tools have a crucial role to play in accelerating fusion energy deployment as a sustainable power source. Multiphysics, high-fidelity computational tools can help understand, model, and quantify the complex interactions between materials performance, plasma and neutron exposure, and engineering processes. As a result, they accelerate the design, safety analysis, and performance evaluation of fusion systems. This webinar introduces the Fusion ENergy Integrated multiphys-X (FENIX) framework, an open-source multiphysics tool for plasma facing component modeling. FENIX leverages the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has been developed by the United States Department of Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. FENIX couples various MOOSE capabilities such as heat transfer, thermomechanics, thermal hydraulics, electromagnetics, and plasma kinetics with the MOOSE-based applications Cardinal (neutronics) and TMAP8 (tritium transport). During the webinar, we will present FENIX and discuss how its modularity, openness, software quality assurance processes, and licensing approach supports effective collaborations, including public-private partnerships.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Enabling Exascale Hardware and Software Design through Scalable System Virtualization (Final Report)

The purpose of this project has been to extend the state of the art of systems software for high-end computing (HEC) platforms, and to use systems software to better enable the evaluation of potential future HEC platforms, for example exascale platforms. Such platforms, and their systems software, have the goal of providing scientific computation at new scales, thus enabling new research in the physical sciences and engineering. Over time, the innovations in systems software for such platforms also become applicable to more widely used computing clusters, data centers, and clouds. This was a five-institution project, centered on the Palacios virtual machine monitor (VMM) systems software, a project begun at Northwestern, and originally developed in a previous collaboration between Northwestern University and the University of New Mexico. In this project, Northwestern (including via our subcontract to the University of Pittsburgh) contributed to the continued development of Palacios, along with other team members. We took the leadership role in (1) continued extension of support for emerging Intel and AMD hardware, (2) integration and performance enhancement of overlay networking, (3) connectivity with architectural simulation, (4) binary translation, and (5) support for modern Non-Uniform Memory Access (NUMA) hosts and guests. We also took a supporting role in support for specialized hardware for I/O virtualization, profiling, configurability, and integration with configuration tools. The efforts we led (1-5) were largely successful and executed as expected, with code and papers resulting from them. The project demonstrated the feasibility of a virtualization layer for HEC computing, similar to such layers for cloud or datacenter computing. For effort (3), although a prototype connecting Palacios with the GEM5 architectural simulator was demonstrated, our conclusion was that such a platform was less useful for design space exploration than anticipated due to inherent complexity of the connection between the instruction set architecture level and the microarchitectural level. For effort (4), we found that a code injection approach proved to be more fruitful. The results of our efforts are publicly available in the open source Palacios codebase and published papers, all of which are available from the project web site, v3vee.org. Palacios is currently one of the two codebases (the other being Sandia’s Kitten lightweight kernel) that underlies the node operating system for the DOE Hobbes Project, one of two projects tasked with building a systems software prototype for the national exascale computing effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-T-468: Efficient Scanning Data Analysis for TomoTherapy

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.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Paraview-MCP

This project provides a streamlined way for users to interact with and control powerful scientific visualization software (ParaView) through a conversational interface. By developing an automated "Model Context Protocol" (MCP) server with a Python-based ParaView manager, the system allows users to seamlessly load and visualize complex datasets, explore visualization options with AI assistance, and optimize visualization output in a close loop. This is achieved by issuing intuitive, natural-language commands. The result is a user-friendly interface that integrates high-level conversation and scriptable data visualization, making scientific visualization tools more accessible to a broad audience.

Liu, Shusen [Lawrence Livermore National Laborator↗
DOE OSTI2013

Building Energy Monitoring and Analysis

This project aimed to develop a standard methodology for building energy data definition, collection, presentation, and analysis; apply the developed methods to a standardized energy monitoring platform, including hardware and software, to collect and analyze building energy use data; and compile offline statistical data and online real-time data in both countries for fully understanding the current status of building energy use. This helps decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Building Energy Monitoring and Analysis

U.S. and China are the world’s top two economics. Together they consumed one-third of the world’s primary energy. It is an unprecedented opportunity and challenge for governments, researchers and industries in both countries to join together to address energy issues and global climate change. Such joint collaboration has huge potential in creating new jobs in energy technologies and services. Buildings in the US and China consumed about 40% and 25% of the primary energy in both countries in 2010 respectively. Worldwide, the building sector is the largest contributor to the greenhouse gas emission. Better understanding and improving the energy performance of buildings is a critical step towards sustainable development and mitigation of global climate change. This project aimed to develop a standard methodology for building energy data definition, collection, presentation, and analysis; apply the developed methods to a standardized energy monitoring platform, including hardware and software, to collect and analyze building energy use data; and compile offline statistical data and online real-time data in both countries for fully understanding the current status of building energy use. This helps decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Research and Development of Multiphysics Models in Support of the Conversion of the High Flux Isotope Reactor to Low Enriched Uranium Fuel

The findings presented in this report are results of a five year effort led by the RRD Division of the ORNL, which is focused on research and development toward the conversion of the High Flux Isotope Reactor (HFIR) fuel from high-enriched uranium (HEU) to low-enriched uranium (LEU). This report focuses on the tasks accomplished by the University of Tennessee Knoxville (UTK) team from the Department of Mechanical, Aerospace, and Biomedical Engineering (MABE) that provided expert support in multiphysics modeling of complex problems associated with the LEU conversion of the HFIR reactor. The COMSOL software was used as the main computational modeling tool, whereas Solidworks was also used in support of computer-aided-design (CAD) modeling of the proposed LEU fuel design. The UTK research has been governed by a statement of work (SOW), which was updated annually to clearly define the specific tasks reported herein. Ph.D. student Isaac T. Bodey has focused on heat transfer and fluid flow modeling issues and has been aided by his major professor Dr. Rao V. Arimilli. Ph.D. student Franklin G. Curtis has been focusing on modeling the fluid-structure interaction (FSI) phenomena caused by the mechanical forces acting on the fuel plates, which in turn affect the fluid flow in between the fuel plates, and ultimately the heat transfer, is also affected by the FSI changes. Franklin Curtis has been aided by his major professor Dr. Kivanc Ekici. M.Sc. student Adam R. Travis has focused two major areas of research: (1) on accurate CAD modeling of the proposed LEU plate design, and (2) reduction of the model complexity and dimensionality through interdimensional coupling of the fluid flow and heat transfer for the HFIR plate geometry. Adam Travis is also aided by his major professor, Dr. Kivanc Ekici. We must note that the UTK team, and particularly the graduate students, have been in very close collaboration with Dr. James D. Freels (ORNL technical monitor and mentor) and have benefited greatly from his leadership and expertise in COMSOL modeling of complex physical phenomena. Both UTK and ORNL teams have used COMSOL releases 3.4 through 5.0 inclusive (with particular emphasis on 3.5a, 4.3a, 4.3b, and 4.4) for most of the work described in this report, except where stated otherwise. Just as in the performance of the research, each of the respective sections has been originally authored by respective authors. Therefore, the reader will observe a contrast in writing style throughout this document.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Near Term Reliability and Resilience: Revisiting Resilience Metrics for the Electric Grid

This report presents the metrics employed in the Near-Term Reliability and Resilience (NTRR) project to study the inter-dependencies between electric and natural gas infrastructures, particularly under challenging conditions. These metrics were developed and applied to evaluate the reliability and resilience of the electric grid and natural gas systems in near-term scenarios (within the next 10 years) involving extreme weather events and major supply disruptions. The report defines the metrics, explains how they are calculated, and describes the process by which they are used to evaluate reliability and resilience across simulated scenarios. It also demonstrates how the resilience metrics integrate with other project activities and summarizes the software tools deployed to calculate and visualize the results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Is Every kWh the Same? How Do Energy Efficiency Measures Stack Up Across Regions?

The U.S. residential building sector is responsible for thirty-eight percent of electricity use, as well as for 49%, 8%, 19% and 2% of U.S. SO2, NOx, CO2 and PM2.5 emissions, respectively. The residential building sector is also a key target of customer funded energy efficiency programs, which have typically been designed to reduce energy consumption (kWh). Today, energy efficiency is also being used to meet air emissions goals. However, not every kWh saved has the same mitigation potential. The goal of this work is to evaluate energy efficiency potential in the U.S. residential building sector and determine how energy conservation measures (ECMs) that reduce electricity consumption correlate to air emissions reductions. To assess energy efficiency potential, this analysis uses Scout, a software program developed by the U.S. Department of Energy that estimates the energy and CO2 impact potential of various ECMs on the U.S. residential and commercial building sectors. Here, Scout is first used to assess the total long term national energy (electricity, gas, and oil), CO2, and cost savings of deploying residential ECM portfolios. Then, electricity savings results from Scout in 2021 are used to assess the regional differences in emissions reductions with the Avoided Emissions and geneRation Tool (AVERT) model from different end uses. Better understanding the relationship between ECMs and cost-effective emission reductions will enable states, municipalities and other interested parties to meet multiple policy objectives through energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

SU-F-T-101: Insight into Dosimetry Workload and Planning Timelines: A 6 Year Review at One Institution

Purpose: To elucidate realistic clinical treatment planning workload and timelines to improve understanding for patients, payers, and other institutions involved in radiotherapy processes. Methods: A web based tool was developed using Oracle Express (Oracle Corp, Redwood City, CA) which allowed communication between the physicians and staff about the current state of the patient plan. For 6 years, all patient courses were logged and time-stamped in 22 discreet steps which detailed start and stop times for simulation, contouring, and treatment planning tasks. This data was combined with the treatment planning database (TPDB) using the Eclipse Scripting API (Varian Medical Systems, Palo Alto, CA) to cross-identify plans between the two systems. This time data was analyzed across our dosimetry staff and treatment modality. Results: In 6 years, 110,477 patient statuses were time-logged for 9683 courses of treatment using our internal software. The courses contained 8305 unique patients who were binned into one of 11 diagnosis site categories. 8253 courses could be reconciled against the TPDB using timestamp data from patient statuses. The average planning volume per dosimetrist was 375.8 ± 142.4 plans per year with the average number of planning revisions per dosimetrist of 71.0 ± 27.1 plans per year. The median treatment planning times by modality ranged from to 48.3 hours for IMRT plans 5 fields or less to 119.6 hours for IMRT with 8 or more fields. Two arc VMAT, three arc VMAT, and 3D plans median times were 89.1 hours, 113.8 hours, and 50.9 hours respectively. Conclusion: Using our web based tool, we have demonstrated the ability to quantify treatment planning timelines and workloads which could help in setting appropriate expectations for patients, payers, and hospital administration. COI: Author received monies from Varian Medical Systems for research and teaching honorarium.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

INTEGRATE - Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design technology can capture complex non-linear aerodynamic effects while being 100 times faster than design approaches based on computational fluid dynamics. This project enables innovation in wind turbine design by accelerating time to market through higher-accuracy early design iterations to reduce the levelized cost of energy. INVERTIBLE NEURAL NETWORKS Researchers are leveraging a specialized invertible neural network (INN) architecture along with the novel dimension-reduction methods and airfoil/blade shape representations developed by collaborators at the National Institute of Standards and Technology (NIST) learns complex relationships between airfoil or blade shapes and their associated aerodynamic and structural properties. This INN architecture will accelerate designs by providing a cost-effective alternative to current industrial aerodynamic design processes, including: - Blade element momentum (BEM) theory models: limited effectiveness for design of offshore rotors with large, flexible blades where nonlinear aerodynamic effects dominate - Direct design using computational fluid dynamics (CFD): cost-prohibitive - Inverse-design models based on deep neural networks (DNNs): attractive alternative to CFD for 2D design problems, but quickly overwhelmed by the increased number of design variables in 3D problems AUTOMATED COMPUTATIONAL FLUID DYNAMICS FOR TRAINING DATA GENERATION - MERCURY FRAMEWORK The INN is trained on data obtained using the University of Marylands (UMD) Mercury Framework, which has with robust automated mesh generation capabilities and advanced turbulence and transition models validated for wind energy applications. Mercury is a multi-mesh paradigm, heterogeneous CPU-GPU framework. The framework incorporates three flow solvers at UMD, 1) OverTURNS, a structured solver on CPUs, 2) HAMSTR, a line based unstructured solver on CPUs, and 3) GARFIELD, a structured solver on GPUs. The framework is based on Python, that is often used to wrap C or Fortran codes for interoperability with other solvers. Communication between multiple solvers is accomplished with a Topology Independent Overset Grid Assembler (TIOGA). NOVEL AIRFOIL SHAPE REPRESENTATIONS USING GRASSMAN SPACES We developed a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation as an analytic generative model, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data , (ii) improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes. TECHNOLOGY TRANSFER DEMONSTRATION - COUPLING WITH NREL WISDEM Researchers have integrated the inverse-design tool for 2D airfoils (INN-Airfoil) into WISDEM (Wind Plant Integrated Systems Design and Engineering Model), a multidisciplinary design and optimization framework for assessing the cost of energy, as part of tech-transfer demonstration. The integration of INN-Airfoil into WISDEM allows for the design of airfoils along with the blades that meet the dynamic design constraints on cost of energy, annual energy production, and the capital costs. Through preliminary studies, researchers have shown that the coupled INN-Airfoil + WISDEM approach reduces the cost of energy by around 1% compared to the conventional design approach. This page will serve as a place to easily access all the publications from this work and the repositories for the software developed and released through this pr...

aerodynamics↗
DOE OSTI2019

A Design Document: Custom Analytical Tools and Automation for the Industrial Hygienist

This report outlines an approach for developing a modular and scalable web-based application suite, Internal Data Access and Visualization (I-DAV), that would be developed to meet the specific analytic requirements for Industrial Hygienist (IH) analysts and tank vapors Subject Matter Expert’s (SME) at the Hanford site. Through interviews and requirements elicitation with IH analyst, and on-site in depth review of workflow patterns and expected outcomes, PNNL has developed a framework for proposed collection of interdependent goal oriented software applications. Commercial off the shelf applications, which require only minimal custom code, were deployed this year as a mechanism of rapid prototyping and providing proof of concept. This report describes these efforts and accomplishments to date, as well as concepts for future applications and general enhancement of the DAV and core concepts for the I-DAV. Additional content was integrated into this report as of March 2019. Updated content was added to reflect the inclusion of I-DAV concepts and ideas, and refined versions of original concepts set forth as the work commenced and continued through the first half of FY19. New and refined concepts have been the product of ongoing weekly meetings, outreach, and elicitation with WRPS.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗