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DOE OSTI2024

Exploring the synergy of kinematics and dynamics for collider physics

In collider experiments, an event is characterized by two distinct yet mutually complementary features: the “global features” and the “local features.” Kinematic information such as the event topology of a hard process, masses, and spins of particles comprises global features spanning the entire phase space. This global feature can be inferred from reconstructed objects. In contrast, representations of particles in gauge groups, such as quantum chromodynamics (QCD), offer localized features revealing the dynamics of an underlying theory. These local features, particularly observed in the patterns of radiation as raw data in various detector components, complement the global kinematic features. We propose a simple but effective neural network architecture that seamlessly integrates information from both kinematics and QCD to enhance the signal sensitivity at colliders. Published by the American Physical Society 2024

Ban, Kayoung (ORCID:000000019691877X)↗

DOE OSTI2026

Atomic Layer Deposition (ALD) of Metal and Metal Oxide Films: A Surface Science Study (Final Report)

This is the final report for this project. The long-term objective of our project is to develop a general molecular-level picture of the surface chemistry associated with ALD processes. Our central hypothesis is that the chemistry of ALD precursors can differ significantly from that seen in solution. Awareness of such differences should provide general guidelines on what to watch for when synthesizing new ALD precursors and designing and optimizing new ALD processes, especially in terms of minimizing the incorporation of impurities in the growing films and of carrying out depositions under mild pressure and temperature conditions. The main objective of our research project has been to advance the fundamental knowledge of the surface chemistry of ALD precursors needed for the design and optimization of film deposition processes. A modern surface-science approach has been implemented to both elucidate the mechanism of the reactions of the precursors on the surface and characterize the composition and morphology of the growing films. In general, emphasis is being placed on: • Identifying the primary reactions that may lead to the deposition of clean films; •Identifying the secondary reactions that may help the ALD process, by, for instance, helping with the reduction (or oxidation) of the metal atom; • Identifying the secondary reactions that may lead to the deposition of undesirable impurities in the growing films; • Determining the kinetic parameters of the relevant surface reactions in order to define the optimum conditions for film deposition and to minimize impurity deposition. • Characterizing the nature of the resulting films, with focus on their stoichiometry and on the final oxidation states of the constituent elements; and • Using the information obtained to propose better precursors for given ALD processes.

36 MATERIALS SCIENCE↗

DOE OSTI2026

NEWTS Integrated Dataset (version 2.0)

The National Energy Water Treatment and Speciation (NEWTS) Integrated Dataset v2.0 provides water researchers, community leaders, regulators, and industry stakeholders with a unified and standardized energy-process wastewater chemistry database. This resource is derived from 39 state and federal entities, and scientific publications, and contains more than 700,000 sample records, many of which also provide geospatial information. The dataset includes chemistry data for several different energy-process wastewater types including produced water, other oil and gas wastewaters, mine drainage, coal ash leachate, power plant wastewater, and geothermal fluids. The NEWTS Integrated Dataset was built to support prudent decision-making, characterization of potential critical mineral sources, and modeling of treatment and valorization options. A subset of this novel resource is also featured on the NEWTS State-Level Database Dashboard. Additional data can be found in the NEWTS EDX Group and the NEWTS Federal Database Dashboard.

AMD↗

DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Atmospheric Carbon and Transport – America (ACT-America) Data Sets: Description, Management, and Delivery

The ACT-America project is a NASA Earth Venture Suborbital-2 mission designed to study the transport and fluxes of greenhouse gases. The open and freely available ACT-America data sets provide airborne in situ measurements of atmospheric carbon dioxide, methane, trace gases, aerosols, clouds, and meteorological properties, airborne remote sensing measurements of aerosol backscatter, atmospheric boundary layer height and columnar content of atmospheric carbon dioxide, tower-based measurements, and modeled atmospheric mole fractions and regional carbon fluxes of greenhouse gases over the Central and Eastern United States. In this study, we conducted 121 research flights during five campaigns in four seasons during 2016–2019 over three regions of the US (Mid-Atlantic, Midwest and South) using two NASA research aircraft (B-200 and C-130). We performed three flight patterns (fair weather, frontal crossings, and OCO-2 underflights) and collected more than 1,140 h of airborne measurements via level-leg flights in the atmospheric boundary layer, lower, and upper free troposphere and vertical profiles spanning these altitudes. We also merged various airborne in situ measurements onto a common standard sampling interval, which brings coherence to the data, creates geolocated data products, and makes it much easier for the users to perform holistic analysis of the ACT-America data products. Here, we report on detailed information of data sets collected, the workflow for data sets including storage and processing of the quality controlled and quality assured harmonized observations, and their archival and formatting for users. Finally, we provide some important information on the dissemination of data products including metadata and highlights of applications of ACT-America data sets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Principles for Equitable Transmission Planning

Energy justice is gaining traction in the planning processes that govern the generation and supply of electric power in the U.S., with a growing number of federal and state authorities applying it as a framework to ensure that the benefits of a clean energy future extend to all levels of society. However, the principles of energy justice have not yet been integrated into electric transmission planning processes, which are designed to meet established reliability criteria and have not historically considered externalities like social inequities. This paper presents a review of transmission planning requirements in the U.S. and existing literature on energy justice, then synthesizes them to propose a framework for incorporating energy justice principles into transmission planning processes to yield more equitable outcomes. By applying procedural and recognition justice principles to create more extensive, inclusive, and diverse public participation in the planning process, planners can gain insight into—and begin to correct—the inequities created by previous planning decisions. Equipped with this understanding and informed by affected communities, planners can improve the distributional outcomes of the planning process and identify opportunities for energy system investments that will restore communities and place them on more equitable footing.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Autonomous direct freeform fabrication strategy for multi-axis additive manufacturing

Multi-axis additive manufacturing (M-AM) enables precise material deposition along both planar and curved layers, eliminating the need for support structures through a continuous material deposition approach. In contrast to conventional 2-dimensional planar layers constrained to a fixed building orientation, the deposition on freeform layers demands the specification of guided curves to determine material deposition directions which are no longer to be fixed to a build direction. There are challenges that arise when fabricating components with multiple “build” directions, necessitating the decomposition of geometries and the specification of guided curves for the resulting volumes. Furthermore, multi-axis systems introduce heightened challenges due to an increased degree of freedom in motion. Consequently, the potential risks of collision between the deposited geometry and the motion platform become a notable concern. This research proposes a freeform layering algorithm to address the challenge of seamless transitions between planar and curved layers in the process planning of M-AM. The algorithm computes 3D “printable” layers by leveraging topological information derived from the geometry to be built and integrates collision-free manufacturability considerations into the computational process. These accumulated volumes serve as a “substrate” and support volumes for subsequent deposition, allowing later layers to be built without the need for additional support material. In conclusion, the proposed method successfully devises a freeform layering approach suitable for intricate models that demand substantial support, thus enabling the fabrication of diverse geometries in a manner previously unachievable.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Advanced spectrometric methods for characterizing bio-oils to enable refineries to reduce fuel carbon intensity during co-processing

A promising approach for supplementing petroleum-derived fuels to support reductions in green-house gas emissions is to convert abundant biomass feedstocks into renewable carbon-rich oils using pyrolysis. However, the resultant bio-oils contain various oxygenated compounds that can impart acidity, chemical and thermal instability, and immiscibility with petroleum derived fuels, necessitating further upgrading to derive fuel blendstocks. Co-processing bio-oils and petroleum-derived liquids in existing refineries is a potentially near-term, cost-effective approach for upgrading bio-oils while reducing refinery carbon intensities. However, one cause for hesitation in co-processing bio-oils is limited comprehensive characterization and speciation of the bio-oil components. Advanced analytical techniques are currently under investigation to enable identification of elusive species in bio-oils, enabling researchers to develop strategies to mitigate catalyst deactivation agents and contaminants. This review provides a brief overview of several analytical methods commonly used to analyze bio-oils and their limitations. In addition, advanced techniques currently under development are discussed to further elucidate bio-oil components that may limit its end use. This will help inform the technical and economic feasibility of co-processing bio-oils with petroleum-derived liquids, therefore, improving the overall downstream processes for biofuels blendstock production.

09 BIOMASS FUELS↗

DOE OSTI2020

"Russians in the Grid" Enrichment Process

Threat intelligence sources are numerous, and the quality of their intelligence is equally variable. The need for quality, actionable, and shareable intelligence is becoming increasingly important as cyber-threats continue to increase. In this paper, we describe the process we used to enrich U.S. CERT’s Technical Alert entitled “Russian Government Cyber-Activity Targeting Energy and Other Critical Infrastructure Sectors,” affectionately referred to as “Russians In the Grid,” from a series of separate but related reports to a final, actionable, unified Structured Threat Information Expression (STIX) v2 representation of the report. In the process, we detail the tools and procedures we used, some of which are automated and others highly manual. We identify some of the limitations of current STIX enrichment tools and techniques, and propose enhancements to allow for more effective enrichment and better overall threat intelligence to be used for more effective threat data-sharing, as well as machine learning-based predictive threat work being conducted at Idaho National Laboratory.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2023

Data and scripts associated with a manuscript investigating impacts of solid phase extraction on freshwater organic matter optical signatures and mass spectrometry pairing

This data package is associated with the publication “Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high-resolution mass spectrometry data in a freshwater system” submitted to “Limnology and Oceanography: Methods.” This data is an extension of the River Corridor and Watershed Biogeochemistry SFA’s Spatial Study 2021 (https://doi.org/10.15485/1898914). Other associated data and field metadata can be found at the link provided. The goal of this manuscript is to assess the impact of solid phase extraction (SPE) on the ability to pair ultra-high resolution mass spectrometry data collected from SPE extracts with optical properties collected on ambient stream samples. Forty-seven samples collected from within the Yakima River Basin, Washington were analyzed dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), absorbance, and fluorescence. Samples were subsequently concentrated with SPE and reanalyzed for each measurement. The extraction efficiency for the DOC and common optical indices were calculated. In addition, SPE samples were subject to ultra-high resolution mass spectrometry and compared with the ambient and SPE generated optical data. Finally, in addition to this cross-platform inter-comparison, we further performed and intra-comparison among the high-resolution mass spectrometry data to determine the impact of sample preparation on the interpretability of results. Here, the SPE samples were prepared at 40 milligrams per liter (mg/L) based on the known DOC extraction efficiency of the samples (ranging from ~30 to ~75%) compared to the common practice of assuming the DOC extraction efficiency of freshwater samples at 60%. This data package folder consists of one main data folder with one subfolder (Data_Input). The main data folder contains (1) readme; (2) data dictionary (dd); (3) file-level metadata (flmd); (4) final data summary output from processing script; and (5) the processing script. The R-markdown processing script (SPE_Manuscript_Rmarkdown_Data_Package.rmd) contains all code needed to reproduce manuscript statistics and figures (with the exception of that stated below). The Data_Input folder has two subfolders: (1) FTICR and (2) Optics. Additionally, the Data_Input folder contains dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (SPS_NPOC_Summary.csv) and relevant supporting Solid Phase Extraction Volume information (SPS_SPE_Volumes.csv). Methods information for the optical and FTICR data is embedded in the header rows of SPS_EEMs_Methods.csv and SPS_FTICR_Methods.csv, respectively. In addition, the data dictionary (SPS_SPE_dd.csv), file level metadata (SPS_SPE_flmd.csv), and methods codes (SPS_SPE_Methods_codes.csv) are provided. The FTICR subfolder contains all raw FTICR data as well as instructions for processing. In addition, post processed FTICR molecular information (Processed_FTICRMS_Mol.csv) and sample data (Processed_FTICRMS_Data.csv) is provided that can be directly read into R with the associated R-markdown file. The Optics subfolder contains all Absorbance and Fluorescence Spectra. Fluorescence spectra have been blank corrected, inner filter corrected, and undergone scatter removal. In addition, this folder contains Matlab code used to make a portion of Figure 1 within the manuscript, derive various spectral parameters used within the manuscript, and used for parallel factor analysis (PARAFAC) modeling. Spectral indices (SPS_SpectralIndices.csv) and PARAFAC outputs (SPS_PARAFAC_Model_Loadings.csv and SPS_PARAFAC_Sample_Scores.csv) are directly read into the associated R-markdown file. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Simulating Buildings While the Design is Still in the Architect's Imagination

Very early in the design process, prior to drawing a single line, architects get information from their client or prospective client trying to understand the nature and requirements of the building that needs to be designed. The design of the building is completely fluid, as the architect considers many options in their imagination. The overall massing of the building, the general shape and form, are being considered during this early step. Even for a simple box-shaped building, the aspect ratio between the east-west and the north-south dimensions of the building can greatly impact energy consumption due to daylighting availability. The prevailing winds and building orientation can impact natural ventilation. The locations of high and low population density spaces can also impact energy use. Deciding the floor area per office workstation or the size of the auditorium will impact energy use. Does making a building two stories instead of one reduce energy impacts by reducing roof area or does the additional volume for stairs and elevators result in more energy use. Since certain types of spaces require more windows for occupants than others, the locations of those spaces will determine how much glazing each building orientation has impacting daylighting as well as heating and cooling energy. The project was an attempted first step toward creating a system tailored toward architects for this very early stage in the design process to help them understand the energy impacts of design options. The approach was not to be based on drawing the building, and instead, the main inputs would have been the size of each type of space in the building. This report describes information gathered during the development that might be of use to others developing similar software as well as some of the software that was developed during the project. Phase II funding to continue this work was not pursued due to intellectual property issues discovered during the development of the commercialization plan.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Templates of expected measurement uncertainties

The covariance committee of CSEWG (Cross Section Evaluation Working Group) established templates of expected measurement uncertainties for neutron-induced total, (n,γ), neutron-induced charged-particle, and (n,xn) reaction cross sections as well as prompt fission neutron spectra, average prompt and total fission neutron multiplicities, and fission yields. Templates provide a list of what uncertainty sources are expected for each measurement type and observable, and suggest typical ranges of these uncertainties and correlations based on a survey of experimental data, associated literature, and feedback from experimenters. Information needed to faithfully include the experimental data in the nuclear-data evaluation process is also provided. These templates could assist (a) experimenters and EXFOR compilers in delivering more complete uncertainties and measurement information relevant for evaluations of new experimental data, and (b) evaluators in achieving a more comprehensive uncertainty quantification for evaluation purposes. This effort might ultimately lead to more realistic evaluated covariances for nuclear-data applications. In this topical issue, we cover the templates coming out of this CSEWG effort–typically, one observable per paper. This paper here prefaces this topical issue by introducing the concept and mathematical framework of templates, discussing potential use cases, and giving an example of how they can be applied (estimating missing experimental uncertainties of 235 U(n,f) average prompt fission neutron multiplicities), and their impact on nuclear-data evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Non‐Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models

Abstract Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resulting in reduced trustworthiness in these methods. Here, we use Variational Encoder Decoder structures (VED), a non‐linear dimensionality reduction technique, to learn and understand convective processes in an aquaplanet superparameterized climate model simulation, where deep convective processes are simulated explicitly. We show that similar to previous deep learning studies based on feed‐forward neural nets, the VED is capable of learning and accurately reproducing convective processes. In contrast to past work, we show this can be achieved by compressing the original information into only five latent nodes. As a result, the VED can be used to understand convective processes and delineate modes of convection through the exploration of its latent dimensions. A close investigation of the latent space enables the identification of different convective regimes: (a) stable conditions are clearly distinguished from deep convection with low outgoing longwave radiation and strong precipitation; (b) high optically thin cirrus‐like clouds are separated from low optically thick cumulus clouds; and (c) shallow convective processes are associated with large‐scale moisture content and surface diabatic heating. Our results demonstrate that VEDs can accurately represent convective processes in climate models, while enabling interpretability and better understanding of sub‐grid‐scale physical processes, paving the way to increasingly interpretable machine learning parameterizations with promising generative properties.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Compound-Nucleus and Doorway-State Decays of β -Delayed Neutron Emitters K 51 , 52 , 53

We investigated decays of K 51 , 52 , 53 at the ISOLDE Decay Station at CERN in order to understand the mechanism of the β -delayed neutron-emission ( β n ) process. The experiment quantified neutron and γ -ray emission paths for each precursor. We used this information to test the hypothesis, first formulated by Bohr in 1939, that neutrons in the β n process originate from the structureless “compound nucleus.” The data are consistent with this postulate for most of the observed decay paths. The agreement, however, is surprising because the compound-nucleus stage should not be achieved in the studied β decay due to insufficient excitation energy and level densities in the neutron emitter. In the K 53 β n decay, we found a preferential population of the first excited state in Ca 52 that contradicted Bohr’s hypothesis. The latter was interpreted as evidence for direct neutron emission sensitive to the structure of the neutron-unbound state. We propose that the observed nonstatistical neutron emission proceeds through the coupling with nearby doorway states that have large neutron-emission probabilities. The appearance of “compound-nucleus” decay is caused by the aggregated small contributions of multiple doorway states at higher excitation energy. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Techno-Economic Analysis for Co-Processing Fast Pyrolysis Liquid in Fossil Refineries

Recent work at the National Renewable Energy Laboratory (NREL) and throughout the bioenergy community has highlighted incentives associated with co-processing bio-intermediates in existing refineries to reduce capital costs associated with renewable fuels and chemicals production and reduce overall risk for emerging biomass conversion technologies. This presentation summarizes the techno-economic analysis results from the NREL-Petrobras collaboration that focused on refinery integration of fast pyrolysis oil through co-processing in the fluid catalytic cracking (FCC) process. The NREL-Petrobras work highlights the economic opportunity for refiners to engage in co-processing for low-carbon products and introduces the risks for refiners based on variability in crude and fossil-product markets. The NREL-Petrobras results also serve as a basis to inform policy design that reduces economic risk for refinery co-processing and repurposing opportunities. The final topics in the presentation highlight experimental capabilities and emerging analysis approaches at NREL and partner laboratories that support the development and commercial deployment of refinery utilization strategies.

bio-fuels↗

DOE OSTI2023

NEWTS Coal Mine Drainage Dataset from Cravotta Brady (2015)

Data from Cravotta, Brady, "Priority pollutants and associated constituents in untreated and treated discharges from coal mining or processing facilities in Pennsylvania, USA". Applied Geochemistry, 2015. https://doi.org/10.1016/j.apgeochem.2015.03.001 Dataset includes information on water quality composition including inorganic compounds from untreated and treated streams of coal-mine discharge from coal mining and coal processing locations. Data is provided in the original version as well as in a summarized version for easy input into aqueous chemistry modeling software.

Aqueous Chemistry↗

DOE OSTI2020

Distributed Macroscopic Traffic Simulation with Open Traffic Models

This paper presents OTM-MPI, an extension of the Open Traffic Models platform (OTM) for running macroscopic traffic simulations in high-performance computing environments. OTM-MPI represents the first open-source, distributed-memory, macroscopic simulation model developed for modern high performance parallel machines and large networks. Macroscopic simulations are appropriate for studying regional traffic scenarios when aggregate trends are of interest, rather than individual vehicle traces. They are also appropriate for studying the routing behavior of classes of vehicles, such as app-informed vehicles. The network partitioning was performed with METIS. Inter-process communication was done with MPI (message-passing interface). Results are provided for two networks: one realistic network which was obtained from Open Street Maps for Chattanooga, TN, and another larger synthetic grid network. The software recorded a speedups of 198x using 256 cores for Chattanooga, and 475x with 1,024 cores for the synthetic network.

macro-scopic traffic simulation↗

DOE OSTI2020

When Every Drum is a Win - Tackling a Thirty-Five Thousand Drum Legacy - 20064

Cameco Corporation's (Cameco) Port Hope Conversion Facility (PHCF) was previously owned by the federal Crown Corporation, Eldorado Nuclear, which held a significant inventory of legacy waste material at the time Cameco was formed in 1988. As a result, Cameco was granted an allocation of 150,000 cubic metres of space in the Long-Term Waste Management Facility (LTWMF) located in the Municipality of Port Hope (MPH), which opened to the receipt of Cameco material in June 2018. Cameco is currently undertaking a major site cleanup and renewal of its Port Hope Conversion Facility (PHCF) which is known as the Vision in Motion (VIM) project. Over its operating history, Eldorado accumulated an inventory of over 35,000 drums of accumulated waste that was primarily stored at two offside warehouse locations. In 2017 and 2018, the project focused on repackaging two well characterized legacy wastes (magnesium fluoride slag and depleted uranium titanium oxide) from one of the two offsite locations. At the conclusion of this work, approximately 15,000 drums of these wastes had been repackaged and disposed of at the LTWMF. There remained approximately 1000 drums from this location that either could not be repackaged safely or were different waste types and required further verification and/or processing. The buildings at this location were scheduled for demolition in early 2019, which triggered the development of a process for triaging legacy drums in August 2018, which allowed for preparation and shipment of approximately half of these drums to the LTWMF by March 2019, with the remainder moved to the second offsite warehouse location in February 2019 for further characterization which is ongoing. This paper will discuss key lessons learned as the drummed legacy waste disposal inventory has been reduced to approximately half of the initial inventory. This will include the development of an alternate packaging process; prioritization of characterization activities and selection of techniques where minimal inventory information is available; determination of next step(s) for each drum as it is assessed; key safety considerations; and how to make inroads into an overwhelming task while under public and regulatory scrutiny. In a relatively short period of time, significant progress has been made to organize and gather information about the legacy waste, update the inventory records and determine the most appropriate pathways (i.e. LTWMF disposal, disposal at another appropriate facility, site storage until future processing and/or disposal). Since 2017 the volume of the decades-old legacy waste inventory has decreased significantly. With the majority of the known materials safely disposed of at the LTWMF, every drum removed from the endless rows of 20,000 pyramidally-stacked waste drums with limited history that is safely characterized, prepared and shipped is considered a win. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗