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At least 973 records · Page 54

A Generalized Nuclear Code of Accounts for Cost Estimation Standardization

This is a joint INL-EPRI study. Link to corresponding page at the Electric Power Research Institute (EPRI): https://www.epri.com/research/products/000000003002028937 Recent Advanced Reactor (AR) designs typically offer features and attributes that depart from traditional water-cooled reactors in terms of fuel forms, coolants, structural materials, size, safety margins, and other important design and operational aspects. These departures, relative to the industry experience, will likely present a challenge for potential owner-operators when evaluating one or more AR designs for commercial deployment on a like-for-like basis. This is further exacerbated with new classes of reactors gaining prominence (e.g., microreactors) and new emerging applications (e.g., floating barge reactors or space propulsion reactors). The differences in design-specific technologies are compounded by the differences in approach to cost estimation. The lack of consistency in build up toward cost estimates creates a challenge when comparing competing concepts and evaluating their associated cost drivers. The outcome of a 2019 Scoping Study conducted by the Electric Power Research Institute (EPRI) indicated the need for a cost modeling guide (CMG), which would be underpinned by a technology-neutral and inclusive Generalized Nuclear Code of Accounts (GN-COA). A code of accounts (COA) is a tool by which costs are identified in even more specific categories, providing clarity on what specific costs are included in an estimate. A parallel independent effort was meanwhile taking place at Idaho National Laboratory via funding by the Systems Analysis Integration (SA&I) campaign of the Office of Nuclear Energy under the U.S. Department of Energy (U.S. DOE-NE) to also update the COA structure to enable more flexibility and encompass a wider variety of reactor technologies. After being made aware of these synergistic efforts, the two parties decided to combine efforts and develop a joint new standard format for nuclear cost estimation that builds on previous structures. This document describes the development of this joint GN-COA and provides guidance on the implementation of the tool, which is provided as the associated GN-COA Excel document. The main attributes of this novel COA format are that all items are functionally defined (in order to be technology and application agnostic) and grouped into logical arrangements that facilitate the tabulation of costs for reactor constructions under consideration. The intent is for the GN-COA to form a standard that is endorsed by future vendors and customers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Leveraging metal hydrides for strategic thermal energy control

Attributes of Sensible Heat Materials • Typically based on highly abundant and lowcost materials • Store thermal energy based on the heat capacity (or specific heat) of the material • Duration of thermal energy storage depends on how well the system is insulated • Has the lowest thermal energy storage density • Can be pumped as a fluid Attributes of Latent Heat Materials • Also based on highly abundant materials, but typically cost slightly more than sensible heat materials • Store thermal energy based on the heat of the phase change (i.e., heat of fusion) and the specific heat of the material • Duration of thermal energy storage depends on how well the system is insulated • Has a higher thermal energy storage density than sensible heat materials, but cannot be pumped as a fluid

WARD, PATRICK↗

Corrosion-Resistant Non-Carbon Electrocatalyst Supports for PEFCS

Insufficient durability of commercial catalysts is a persistent issue for PEFC applications.1 Herein, Pt on Nb-doped-TiO 2 is reported as a highly durable electrocatalyst on which the direct 4-electron reduction of oxygen to water is more facile compared to Pt/C. All performance metrics are reported comparing Pt/Nb-TiO2 with a 15% Pt loading, against a commercial Pt/C catalyst (46.5% Pt loading, Tanaka, K. K.). Nb-doped-TiO 2 with high surface area and high electronic conductivity was synthesized using the supercritical fluid method. Initially, the durability of the catalyst was characterized using accelerated stability tests (ASTs) involving 10,000 high potential cycles (DOE/FCCJ protocol) and the Pt/Nb-TiO 2 was found to retain 78% of its initial electrochemically active surface area (ECSA) compared to the 57.6 % retained by Pt/C. These observations were in excellent agreement with previous reports that the Pt particle size of Pt/C grew from 2nm to 8nm during the AST protocol along with severe corrosion and amorphization of the carbon surface.2, 3 TEM and XPS studies of the Pt-Nb-doped-TiO 2 catalyst showed that the Pt particle size grew from 3nm to 6nm and the Nb(IV) and Ti(III) in the support were oxidized to Nb(V) and Ti(IV) after the durability test. Thus, the improvement in Pt/Nb-TiO 2 ECSA retention was attributed to the lower extent of particle growth and lack of oxidative support loss upon oxidation as compared to Pt/C. The oxygen reduction reaction (ORR) performance was characterized by linear polarization using a rotating disk electrode (RDE). The electrochemical surface areas of Pt/Nb-TiO 2 and Pt/C were found to be 48m2·g -1 and 83m2·g -1 respectively, and the mass activity for the ORR at 0.9V vs. RHE were found to be 150 mA·mg-1Pt and 124 mA·mg-1Pt respectively. The improved mass activity on Pt/Nb-TiO 2 was attributed to strong metal support interaction (SMSI) between the Nb-TiO 2 support and the Pt catalyst based on the 625 meV decrease in the binding energy of the Pt4f x-ray photo-electron spectroscopy (XPS) peaks of Pt/Nb-TiO 2 compared to Pt/C. To quantify the impact of the SMSI, a kinetic model was applied to calculate the elementary reaction rate constants for the various steps of the ORR on both catalysts. The reaction rate constant (k1) for the direct 4-electron transfer pathway to produce H 2 O was significantly larger in Pt/Nb-TiO 2 as compared to Pt/C. Thus, the reduction in the electron binding energy as observed in the XPS was found to aid the facile filling of the higher energy 2p orbitals of O 2 thereby leading to improved 4-electron transfer kinetics and improved overall activity.

08 HYDROGEN↗

Source characterization of volatile organic compounds at Carlsbad Caverns National Park

Carlsbad Caverns National Park (CAVE), located in southeastern New Mexico, experiences elevated ground-level ozone (O 3 ) exceeding the National Ambient Air Quality Standard (NAAQS) of 70 ppbv. It is situated adjacent to the Permian Basin, one of the largest oil and gas (O&G) producing regions in the US. In 2019, the Carlsbad Caverns Air Quality Study (CarCavAQS) was conducted to examine impacts of different sources on ozone precursors, including nitrogen oxides (NO x ) and volatile organic compounds (VOCs). Here, we use positive matrix factorization (PMF) analysis of speciated VOCs to characterize VOC sources at CAVE during the study. Seven factors were identified. Three factors composed largely of alkanes and aromatics with different lifetimes were attributed to O&G development and production activities. VOCs in these factors were typical of those emitted by O&G operations. Associated residence time analyses (RTA) indicated their contributions increased in the park during periods of transport from the Permian Basin. These O&G factors were the largest contributor to VOC reactivity with hydroxyl radicals (62%). Two PMF factors were rich in photochemically generated secondary VOCs; one factor contained species with shorter atmospheric lifetimes and one with species with longer lifetimes. RTA of the secondary factors suggested impacts of O&G emissions from regions farther upwind, such as Eagle Ford Shale and Barnett Shale formations. The last two factors were attributed to alkenes likely emitted from vehicles or other combustion sources in the Permian Basin and regional background VOCs, respectively. Implications: Carlsbad Caverns National Park experiences ground-level ozone exceeding the National Ambient Air Quality Standard. Volatile organic compounds are critical precursors to ozone formation. Measurements in the Park identify oil and gas production and development activities as the major contributors to volatile organic compounds. Emissions from the adjacent Permian Basin contributed to increases in primary species that enhanced local ozone formation. Observations of photochemically generated compounds indicate that ozone was also transported from shale formations and basins farther upwind. Therefore, emission reductions of volatile organic compounds from oil and gas activities are important for mitigating elevated O 3 in the region.

54 ENVIRONMENTAL SCIENCES↗

Countering Weapons of Mass Destruction (CWMD) Device Cybersecurity Characterization Process and Profile

Countering Weapons of Mass Destruction (CWMD) recognizes that threats in the cyberspace domain continue to grow, which requires CWMD devices and supporting systems to be both cybersecure (ability to protect or defend from cyber-attacks) and resilient (ability to maintain required capability in the face of adversity) to cyber threats. The CWMD cybersecurity characterization approach in this document supports existing cyber resilience activities within the Acquisition Lifecycle Framework. Similarly, this process supports existing Department of Homeland Security Cyber Resilience Test and Evaluation activities, which consist of iterative processes, starting at the initiation of system acquisition and continuing throughout the entire device and system life cycle. Cyber resilience is the ability of an information system to continue to operate while under attack, even if in a degraded or debilitated state, and to rapidly recover operational capabilities for essential functions after a successful attack. The goal of the security characterization task for CWMD is to support the development of a CBRN device-dependent profile that aligns with device network capabilities and maps to recommended security controls to create a characterization security profile impact levels. The impact levels for CWMD devices should be characterized as Low (L), Moderate (M), High (H) to align with the low, moderate, high control baselines. To estimate the impact levels, the device’s security-related attributes are translated into the security objectives: Confidentiality (C), Integrity (I), and Availability (A), known as the CIA triad. The potential impact for each device can be L, M, H, for devices that connect and transmit different types of data and may have different impact levels. National Institute of Standards and Technology Federal Information Processing Standards Publication 199 states, “the potential impact values assigned to the respective security objectives shall be the highest value from among those security categories that have been determined for each type of information resident on the information system.” As CWMD is determining the cybersecurity impact levels of CBRN devices based on network connections and data transfers, the impact levels are aligned with the associated attributes of network connections and communications. For example, if the device system is connected to a wireless network and transmits different data types based on the confidentiality of the data, the highest impact value for each security objective should represent the device’s CIA impact level. This document is intended to be used by test managers, test team, and program managers.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Well-Log Derived Geomechanical Analysis of Microseismicity in the Mt. Simon Saline Aquifers (Illinois Basin - Decatur Project)

The Illinois Basin Decatur Project (IBDP) successfully demonstrated the safe geologic storage of carbon dioxide at a commercial scale. Within the IBDP project three deep wells (injection (CCS1), monitoring (VW1), geophysical (GM1)) were competed and geophysical logs were recorded. During injection and post-injection periods microseismic monitoring was conducted to create a miscoseismic catalog. The correlations between microseimic attributes and geomechanical well logs define major geomechanical drivers of microseismic expression to understand a reservoir response to CO2 injection in geological context. Utilizing standard sonic and density well logs, the dynamic elastic moduli were calculated and employed to correlate with microseismic pseudo-logs. A multi-dimensional Mu-rho and Lambda-rho (MRLR) hyperdimensional plots display of meaningful data and uncovered subtle relationships between elastic properties of sandstones and the seismological attributes of recorded microseismicity.

Myshakin, Evgeniy↗

Active High Assurance Authentication Protocol (AHAAP)

The AHAAP Maturation Project involves maturation and evaluation of a patented zero-trust tamper-resistant high-assurance session-less dynamic and active device authentication protocol that simultaneously authenticates identity and provides integrity verification in a single step, substantially reducing the risk of cyberattack, and eliminating the need for costly and complex conventional communication security systems requirements (i.e., cryptography, Public Key Infrastructure (PKI), and key management). These cybersecurity attributes of the technology must be preserved when applying the technology to different cybersecurity solutions, including Command & Control (C&C), Over-the-Air (OTA) update, Common Access Card (CAC), and distributed energy resource (DER) implementations, among others. The technology research objective is to test and verify that the cybersecurity attributes of the technology are not degraded in different cybersecurity applications. The primary technology development objective is to build minimum viable products to demonstrate the technology addresses today’s cybersecurity threats so that prospective investors, strategic partners, regulatory agencies, and commercial customers can interact with and assess the protection assured by the technology. The AHAAP Maturation Project goal is to develop, test, and validate one or more AHAAP implementations. The AHAAP Maturation Project tasks are: (i) engineer AHAAP implementation software, (ii) build a functional prototype that implements the AHAAP software for demonstration, testing, analysis, and evaluation purposes, and (iii) generate a report detailing the results of the AHAAP C&C software and hardware implementation. The final project deliverables are: (i) AHAAP software implementation and prototype, (ii) a report from Sandia National Laboratories detailing the results of the AHAAP implementations.

97 MATHEMATICS AND COMPUTING↗

Data Integration Aggregated Model and Ontology for Nuclear Deployment (DIAMOND): Preliminary Model and Ontology

The data of a nuclear utility or plant are stored in various isolated forms in different systems. These data have different structures and tools and are, therefore, used independently. The integration of data sources is often performed manually and on an as-needed basis to achieve a targeted cost saving. A holistic approach to the integration of the data would enable creating a data warehouse for a single nuclear power plant (NPP) or multiple plants. A data warehouse results in direct and indirect cost saving because it automates the manual search for data, enables sharing and comparison of data from various tools of a single or multiple plants, enable digital transformation of data, increase frequencies of needed data that are sparse in nature (such as failures signatures), reduces the need for training on various tools for plant staff, enables a holistic staff perception of plant activities, reveals cost-saving opportunities, and improves the visual perception of all parts a plant necessary for operations and maintenance. One of the main challenges to deploy a data warehouse is associated with the integration of data sources into a consistent data model using a standard ontology that is developed by and for the nuclear power industry. This model is non-existent and is a necessity to enable the nuclear data warehouse role. A data model contains objects that make up a given domain along with their attributes and relationships. It provides domain standardization and maintainability, setting forth the objects, attributes, and relationships within that domain and acting as the guide by which the various applications within that domain will structure their data and interchange. An ontology is defined as “a set of concepts and categories in a subject area or domain that shows their properties and the relations between them”. Ontologies consist of a taxonomy or directed rooted tree. A survey of the models and ontologies available to support a data integration aggregated model and ontology for nuclear deployment (DIAMOND) was performed and different standards that address specific aspects of the needed model and ontology were leveraged and integrated in this effort. In specific, the Basic Formal Ontology (BFO) and Lifecycle Modeling Language (LML) were leveraged for the base ontology. The ISO 4224 and 15926 were leveraged in the development of the overlapping nuclear and fossil data aspects. The electric power research institute (EPRI) power distribution common information model (CIM) was also reviewed and the experience gained was leveraged in the power generation scope of DIAMOND. The initial aim targeted by this effort was to develop the ontology definitions and model structure. This report documents the resulting model and ontology to develop DIAMOND. The report describes the various elements of the model development based on a growing tree development approach, i.e. DIAMOND’s tree structure is established with the core data aspects and is populated with a preliminary level of details. Fifteen sources of data in a nuclear power plant were considered and incorporated into DIAMOND at this stage of development, representing the majority of operations data sources in nuclear power plants. Additional data sources, scope, and a higher level of fidelity will be incorporated into DIAMOND next in collaboration with the nuclear industry and relevant stakeholders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Translation of "Contribution a l'etude du diagramme pression-temperature du beryllium pur" (Contribution to the Study of the Pressure-Temperature Diagram of Pure Beryllium)

An unusual feature of beryllium’s phase diagram is the transition from a hexagonal close packed (hcp, or α) to a body-centered cubic (bcc, or β) structure ~20 K below the normal melting temperature of T melt ≈ 1560 K. An early thermal analysis of 99.7% pure Be found two arrests1 : one at 1533-1536 K and another at 1551-1557 K. Without ruling out an allotropic transformation in Be itself, Sloman attributed the first of these to solidification of a Be-BeO eutectic. Losano observed only the higher of the two in 99.962% Be, seeming to confirm the notion that the lower feature was an artifact of impurity. Teitel (99.4%) also measured two arrests and attributed the lower to impurity, but questioned whether oxygen was the culprit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FY24 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and data analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and crack formation in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), or,in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or more of: height, color, and 16-bit grayscale values as functions of position in a plane projection) to detect signs of surface corrosion and cracking after being trained on similar data, with the features to be detected. Although the initial scope included screening for broader indicators of corrosion, e.g., pitting, identification of potential cracks was prioritized for the past several years at the request of program leadership. Labeled training data is essential to developing the ML algorithm, and enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the large volume of data required to train ML algorithms and the relative rarity of cracks in the ICCWR data set. The updated program will read binary data from either LCM, WAMS or SEM files, interrogate data attributes, facilitate user labeling of data for training ML algorithms, execute ML algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. In FY24, hourglass neural networks (HNNs) that were initiated in FY22 were further developed and tested using available LCM data, and their performance was tested against that of the alternative U-Net Neural Network algorithm structure. HNNs along with previously developed Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) comprise a suite of ML tools for identification of cracks in the ICCWR

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Proteomics Analysis of Human Contaminant Proteins

Complete characterization of unknowns via proteomics remains challenging. There exist regions of mass spectrometry-based proteomics data where empirical measurements are not attributed to peptides, and/or sequenced peptides from mass spectra are not attributed to any source. These uncharacterized regions are known as the “dark” proteome. Many proteomics tools rely on some a priori knowledge of sample composition; few tools allow for investigation of unknowns without relying on composition assumptions. Further, the potential low abundance of minor traces in these uncharacterized regions can make elucidation of the “dark” proteome challenging. Herein, we describe the development and evaluation of approaches to study the “dark” proteome and move towards an untargeted approach for more complete characterization, namely by studying minor human protein traces in non-human samples and combining that approach with non-human source organism identification without relying on assumptions. Human protein markers, in the form of genetically variant peptides, have been extensively examined in a variety of human matrices, including blood, plasma, and hair, but have yet to be investigated in non-human samples, such as cell cultures, as human contaminant traces. Genetically variant peptides are those that are found in proteins carrying single nucleotide polymorphisms. In this work, we aimed to (1) investigate the feasibility of detecting human contaminant genetically variant peptides (GVPs) in a diverse set of non-human organisms using public proteomics data and a computational pipeline, as well as to (2) develop a combined capability for untargeted source organism characterization and GVP detection. To our knowledge, this is the first report of applying these approaches towards a more complete proteomic characterization of unknowns. We successfully demonstrate the feasibility of broad human contaminant GVP detection in proteomics data, develop a better understanding of GVP detectability, characterize the sample-to-sample variability in GVP detection, and identify a core set of GVPs that can potentially be used as markers indicative of the human contaminant traces portion of the “dark” proteome. Further, we developed and evaluated a combined pipeline, MARLOWE-GVP, that enables both untargeted source organism characterization and GVP detection. We show high accuracy of correct source organism characterization and high degree of similarity of human contaminant GVP detection compared to the conventional approach. Success on both these efforts have allowed us to advance our understanding and characterization of the “dark” proteome.

59 BASIC BIOLOGICAL SCIENCES↗

Countering Weapons of Mass Destruction (CWMD) Device Cybersecurity Characterization Process and Profile

Countering Weapons of Mass Destruction (CWMD) recognizes that threats in the cyberspace domain continue to grow, which requires CWMD devices and supporting systems to be both cybersecure (ability to protect or defend from cyber-attacks) and resilient (ability to maintain required capability in the face of adversity) to cyber threats. The CWMD cybersecurity characterization approach in this document supports existing cyber resilience activities within the Acquisition Lifecycle Framework. Similarly, this process supports existing Department of Homeland Security Cyber Resilience Test and Evaluation activities, which consist of iterative processes, starting at the initiation of system acquisition and continuing throughout the entire device and system life cycle. Cyber resilience is the ability of an information system to continue to operate while under attack, even if in a degraded or debilitated state,1 and to rapidly recover operational capabilities for essential functions after a successful attack.2 The goal of the security characterization task for CWMD is to support the development of a CBRN device-dependent profile that aligns with device network capabilities and maps to recommended security controls to create a characterization security profile impact levels. The impact levels for CWMD devices should be characterized as Low (L), Moderate (M), High (H) to align with the low, moderate, high control baselines. To estimate the impact levels, the device’s security-related attributes are translated into the security objectives: Confidentiality (C), Integrity (I), and Availability (A), known as the CIA triad. The potential impact for each device can be L, M, H, for devices that connect and transmit different types of data and may have different impact levels. National Institute of Standards and Technology Federal Information Processing Standards Publication 199 states, “the potential impact values assigned to the respective security objectives shall be the highest value from among those security categories that have been determined for each type of information resident on the information system.”3 As CWMD is determining the cybersecurity impact levels of CBRN devices based on network connections and data transfers, the impact levels are aligned with the associated attributes of network connections and communications. For example, if the device system is connected to a wireless network and transmits different data types based on the confidentiality of the data, the highest impact value for each security objective should represent the device’s CIA impact level. This document is intended to be used by test managers, test team, and program managers.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

CO2-Locate: A Dynamic Database and Tool for Accessing National Oil and Gas Well Data to Inform Carbon Storage Projects

The CO2-Locate Database is a growing compilation of publicly available wellbore resources that have been merged based on common attributes across data sources with an attribute schema developed to be consistent across disparate resources, reduce data gaps, and eliminate record redundancy. The first version of CO2-Locate has been published to Energy Data eXchange (EDX) and includes the integrated public wells dataset as well as additional geospatial summary layers of key wellbore characteristics to protect proprietary resources. Additionally, the CO2-Locate database has been deployed into a web application, enabling easy access, data filtering capabilities, and visualization of U.S. wellbore infrastructure by stakeholders to inform injection site selection and risk assessments.

Dyer, Alec S. [NETL Site Support Contractor, Natio↗

Energy Services Interface: Architecture, Requirements, and Agreements

This report continues and extends the development of the Energy Services Interface (ESI) that recently has been led by the U.S. Department of Energy’s Grid Modernization Laboratory Consortium. The ESI is intended to facilitate the coordination of multiple, flexible energy resources that work in tandem to satisfy grid objectives by using performance attributes encoded within an ESI Service Template. The ESI relies on a pair of interfaces, representing the service requestor (the consumer of a service) and a service provider (who manages its resources per the agreed performance attributes) to achieve what is commonly known as a “grid service”. Due to its performance-driven approach, the ESI is hypothesized to be able to satisfy all common grid needs via only six common ESI service types. This report first reviews the status of ESI development, including its fundamental tenets. The report makes three important contributions to ESI development: First, it recognizes the similarity between service level agreements and the contract-like agreements that would be needed between energy service requestors and providers and recommends that ESI service agreements be modeled after the web services agreement specification. Second, whereas prior development efforts had focused on a flat, five-stage lifecycle, this report asserts that the ESI should have three behavioral layers in its architecture—the discovery, agreement, and service layers. Finally, this report offers concrete requirements that should be useful toward the development of the service requestors’ and service providers’ respective communications interfaces.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Dual-Comb Spectroscopy to Tethered Balloon System (DCS to TBS) Field Campaign Report

There is a critical need for the ability to detect, quantify, and attribute sources and sinks of greenhouse gases (GHGs) with high temporal and spatial resolution. Current methods are typically based on continuously operating near-surface point sensors or intermittent aerial/satellite observations. Dual optical frequency comb spectroscopy (“dual-comb spectroscopy”; DCS) is a laser-based technique that can bridge this sensing gap by providing high-precision, high-accuracy, and high-temporal-resolution detection and quantification of trace gases over kilometer-length scales, connecting local and regional observations. A single DCS system can also provide spatial resolution for source/sink attribution with the addition of a few minor optical elements, enabling cross-validation of other observations (e.g., Total Carbon Column Observing Network [TCCON], Orbiting Carbon Observatory [OCO-2/3], Greenhouse Gases Observing Satellite [GOSAT-1/2][).

54 ENVIRONMENTAL SCIENCES↗

Initial Mobility Analysis for ORNL VA-EDH Synthetic Populations

Travel burdens are a major barrier to healthcare access among US Veteran patient populations, particularly those residing in rural areas. Spatial accessibility to points of care for US Veteran populations is commonly assessed in two ways. The first approach uses open data from the US Census to represent collective travel burdens, for example the distance between population-weighted census tract centroids and VHA points of care. The second approach uses restricted-access VHA patient data to measure travel costs (e.g., distance, time) for accessing points of care with respect to geolocated patient addresses and real or approximated transportation networks. While the advantage of the open data approach lies in its reproducibility, it has notable limitations in its tendency to infer individual travel behavior from aggregate population characteristics, a problem known as ecological fallacy. Conversely, while the patient data approach is able to account for individual travel behavior, its ability to account for localized access disparities (e.g., a neighborhood with exceptionally high transportation costs) and patient demographics is limited as protecting individual patient data requires their storage in closed systems with limited capacity for adequately modeling real-world travel patterns or for supplementing patient attributes. Additionally, the patient data approach cannot account for veterans who are not enrolled in the VHA system but who may be eligible for care. These challenges limit the ability to perform “what if” analyses on the effects of place-specific interventions on veteran populations with high access barriers to healthcare. To address these challenges, we explore the application of realistic synthetic populations to examine travel burdens and spatial accessibility issues among veteran patient populations. Synthetic populations provide a virtual, individually-resolved and cross-sectional representation of the veteran patient population that enables investigation of spatial access to points of care in ways in which aggregate data and patient data do not. First, synthetic populations allow one to directly assess how individuals access points of care, from synthesized residential locations to outpatient facilities on real-world transportation networks. Modeling access to points of care at the individual scale addresses the ecological fallacy problem associated with using aggregated census data to represent veteran populations and patterns of movement. Second, synthetic populations provide a means of completely representing an area’s veteran population using only publicly available, anonymized census microdata from the American Community Survey (ACS) to ensure the privacy of real-world individuals. Generating synthetic populations from the ACS also expands descriptive characteristics beyond what patient data typically offers to include socio-demographic, economic, housing, and mobility attributes. More detailed profiles of both VHA patient populations and veterans not enrolled in the VA system will provide a comprehensive picture of groups that may benefit from interventions or outreach. As an initial exercise for using synthetic populations to measure veteran travel burdens to VA care, we apply Oak Ridge National Laboratory’s (ORNL) UrbanPop capability to generate a series of synthetic VHA patient populations for 9 Veterans Integrated Services Networks (VISN) market areas in 9 Census Divisions across the continental United States, which are listed in Table 1. We use UrbanPop to produce synthetic populations for the VISN markets selected for each US Census Division, then assign VA outpatient clinic destinations to synthetic VHA patients based on travel about each VISN market’s road network. To demonstrate using the synthetic populations to evaluate healthcare travel burdens, we compare the time-based impedance between simulated home locations and VA outpatient clinics in each VISN market. We then perform validation exercises on the synthetic populations with respect to neighborhood (block group) demographic composition as well as patient mobility, comparing aggregate origin-destination statistics for the synthetic population to outpatient visits available in restricted patient data from the VA’s Corporate Data Warehouse (CDW) database.

97 MATHEMATICS AND COMPUTING↗

Automated Air Sealing Demonstration: Denver Federal Center Building 40

This project aimed to demonstrate building airtightness achieved by automated air sealing in a commercial building setting. The automated air sealing demonstrated in this project uses a modified blower door to pressurize and distribute the sealing aerosol to achieve the required building airtightness. To demonstrate this technology, Building 40 at the Denver Federal Center, a federally owned campus under the jurisdiction, custody and control of the U.S. General Services Administration (GSA), was selected for testing (Figure 2). This building is currently undergoing several retrofit projects, including increasing insulation, installing high-performance windows, and adding advanced equipment, control systems, and automated air sealing. This demonstration project involved installing automated air sealing and measuring the improvements in the building's airtightness. The automated air sealing was installed over two days by AeroBarrier, the vendor. An external blower door test contractor measured the airtightness of the demonstration space before and after air sealing. The new airtightness value and the percentage increase in airtightness were used to evaluate the energy savings potential of automated air sealing. These airtightness values were used to compute the energy savings and CO 2 emissions reduction for different climate zones, building types, and initial airtightness conditions. In addition, the heating, ventilation and air conditioning (HVAC) load reduction attributable to the reduced building air leakage was studied. This study included research to determine the cost and time reduction of automated air sealing. Finally, the automated air sealing performance was evaluated qualitatively using a focus group discussion that included GSA and Bristol, the general contractor. The installation has shown the demonstration site, with a floor size of 4,462 ft 2 , air leakage has reduced by more than 50% in less than 7 hours, including preparation, site sealing, and cleanup. The performance objectives were classified as quantitative or qualitative based on the evaluation metrics used to assess the project’s success. The key performance objectives for this project were the level of airtightness achieved, the time and cost required to perform the sealing, and the HVAC load reduction attributable to air sealing. Table 1 shows the quantitative performance objectives.

42 ENGINEERING↗

129 I, 99 Tc, and U Distribution Coefficients of Subsurface Sediments Collected from the Proposed Site of the Environmental Management Disposal Facility

Performance Assessment calculations were completed in 2020 to evaluate the Environmental Management Disposal Facility (EMDF), a proposed new low-level radioactive waste (LLW) disposal facility on the U.S. Department of Energy’s Oak Ridge Reservation (ORR). Among the large number of input parameters needed for such calculations, are distribution coefficients (K d values; radionuclide concentration solid: liquid ratio) that provide a measure of the tendency of radionuclides to bind to sediments. The objective of this study was to measure K d values of three radionuclides that may pose a disproportionately large amount of risk, U, iodine-129 ( 129 I) and technetium-99 ( 99 Tc). The average 129 I K d value for the 14 geological materials recovered from the proposed EMDF site was 37.8 mL/g and ranged from 0.45 to 140.9 mL/g. These values were consistent, but somewhat larger than previous measurements made with ORR sediments and were about an order of magnitude greater than those used in previous EMDF PA calculations. The median 99 Tc K d value was 365.7 mL/g, much greater than previously reported using ORR geological materials. Five of the 14 tested geological materials sorbed large quantities of 99 Tc, suggesting that the weakly sorbing 99 Tc(VII) species had been reduced to the sparingly soluble 99 Tc(IV) species. The five strongly sorbing sediments had apparent 99 Tc solubility values of approximately <10 -8 mol/L. The median U K d value was 5,726 mL/g. All of the tested geological materials had large K d values, ranging from 625 to >10,208 mL/g. Among the sediment samples that exhibited strong U binding, the apparent solubility value was approximately <10 -9 mol/L. Based on sediment properties and general ORR geological considerations, it was proposed that much of the 129 I and 99 Tc retention could be attributed to the site materials exhibiting low pH (average pH = 4.94), and/or the elevated levels of iron oxides, manganese oxides, and natural organic matter. Similarly, the extremely high U binding measured in these sediments may also be attributed to the low conditions of carbonates, which can complex and therefore solubilize uranyl in these tests due to the low pH, and also the relatively high concentrations of iron and organic coatings on these samples. An implication of this study is that the areas of the EMDF subsurface environment may have natural properties for attenuating 129 I, 99 Tc, and U movement, and potentially other radionuclides, thereby possibly reducing risk posed by burial of LLW at this site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗