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DOE OSTI2023

Advanced Simulation and Computing: ASC FY24 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. The ASC program is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification process, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This work requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions. The ASC program focuses on increasing the predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The Program continues to improve its unique tools for understanding and solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further from the original test base. While the focus remains on the U.S. nuclear weapons program, where possible, the Program also enables the use of high-performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and nuclear counterterrorism. The 2022 Nuclear Posture Review (NPR) calls for NNSA to “deliver a modern, adaptive nuclear security enterprise based on an integrated strategy for risk management, production-based resilience, science and technology innovation, and workforce initiatives.” Furthermore, “NNSA will establish a Science and Technology Innovation Initiative to accelerate the integration of science and technology (S&T) throughout its activities.” Executing this strategy necessitates the continued emphasis on developing and sustaining high-quality scientific and engineering staff, as well as supporting computational and experimental capabilities. These components constitute the foundation of the nuclear weapons program. The continued success of the SSP and LEPs is predicated upon the ability to credibly certify the stockpile, without a return to underground nuclear tests (UGTs). Shortly after the nuclear test moratorium entered into force in 1992, the Accelerated Strategic Computing Initiative (ASCI) was established to provide an extensive simulation capability to underpin stockpile certification. While computing and simulation have always been essential to the success of the nuclear weapons program, the program goal of ASCI was to execute NNSA’s vision of using these tools in support of the stockpile stewardship mission. The ASCI program was essential to the successful demonstration of the SSP, providing critical nuclear weapons simulation and modeling capabilities. ASCI officially evolved into the ASC program in fiscal year (FY) 2005, but the mission remains essentially the same: provide the simulation and computational capabilities that underpin the ability to maintain a safe, secure, effective nuclear weapon stockpile, without returning to underground nuclear testing. The capabilities that the ASC program provides at the national laboratories play a vital role in the nuclear security enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Stockpile Management and Production Modernization programs (formerly Directed Stockpile Work) also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these life extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Evapotranspiration partitioning estimates from 8 methods from 47 NEON sites, 2019-2021

This dataset provides daily estimates of evapotranspiration (ET) and the transpiration-to-evapotranspiration ratio (T/ET) across 47 terrestrial National Ecological Observatory Network (NEON) sites spanning diverse environmental and biome conditions in the United States across three years of data (2019-2021). Daily ET is reported in both energy units (MJ m⁻² day⁻¹) and equivalent water depth (mm day⁻¹), assuming a constant latent heat of vaporization of 2.45 MJ/kg. The primary method uses a hybrid recurrent neural network–Penman–Monteith framework (RNN-PM), which integrates physically based surface energy balance constraints with data-driven learning to partition ET into transpiration and evaporation components. Model inputs include in situ meteorological observations (air temperature, vapor pressure deficit, wind speed, and radiation) combined with satellite-derived land surface temperature, leaf area index, and soil moisture. For benchmarking and uncertainty assessment, T/ET estimates from seven additional models are included: Priestley-Taylor Jet Propulsion Laboratory (PT-JPL), Penman-Monteith (P-M), Two-Source Energy Balance (TSEB), Support Vector Regression (SVR), and Categorical Boosting (CatBoost), among others—spanning empirical, machine-learning, and process-based approaches (see methods section or linked publication for detailed descriptions). Data Package Contents: The dataset a csv files containing daily ET and T/ET estimates for each site and model, along with associated metadata files these variables. Data can be accessed using common spreadsheet software (e.g., Microsoft Excel, LibreOffice) or programming environments such as R or Python. Together, these data support cross-site comparisons of ecosystem water use, evaluation of ET partitioning methods, and development of improved land–atmosphere exchange models.

EARTH SCIENCE > ATMOSPHERE↗

DOE OSTI2026

Technoeconomic Analysis of a Novel Microwave Process to Produce Ethylene from Methane

Ethylene is a critical feedstock in industrial processes, serving as a raw material in the petrochemical industry to produce plastics and commodity chemicals. Conventional ethylene production routes are energy-intensive and contribute substantially to the carbon footprint of chemical manufacturing. In this study, an industrial-scale novel microwave process was simulated using ASPEN Plus to assess its economic viability. Technoeconomic analysis confirmed the economic competitiveness of the novel microwave process, with a levelized cost of ethylene of USD 0.51/kg compared to USD 0.56/kg for the conventional base case. Key economic drivers of the process were identified, and sensitivity analyses were conducted to evaluate their impact on project economics. Furthermore, 87.7% of the total utility consumption in the novel microwave process is electricity, highlighting its potential to contribute to the electrification of the chemical industry. The findings of this study confirm the economic feasibility of both industrial-scale microwave reactors and modular plant configurations for the production of ethylene from methane, offering a promising alternative to conventional processes.

electromagnetic radiation↗

DOE OSTI2025

Pathogenic SIV infection is associated with acceleration of epigenetic age in rhesus macaques

HIV infection accelerates biological aging, but the contribution of the host’s age to this process is unknown. We investigated the influence of SIV infection in macaques (SIVmac) on the risk of comorbidities and aging in young and old rhesus macaques (RMs) by assessing pathogenesis markers, DNA methylation–based epigenetic age (EA), and EA acceleration (EAA) in blood and tissues. Initially, upon SIV infection, the young RMs showed greater resilience to CD4 + T cell depletion, better control of T cell activation, hypercoagulation, and excessive inflammation, yet this resilience was progressively lost in the advanced stages of infection. During the late stages of infection, the young RMs, but not the aged ones, showed an increase in EA in PBMCs; also, EAA in the cerebellum and heart of young RMs was higher compared with old RMs. SIV infection was more pathogenic in aged animals in early stages, leading to a more rapid disease progression; however, accelerated aging mostly affected young animals, so that the levels of multiple key pathogenesis markers in the young RMs converged toward those specific to aged ones in the late stages of infection. We conclude that SIV infection–driven age acceleration is tissue specific, and that host age influences the susceptibility of different tissues to enhanced aging.

Research & Experimental Medicine↗

DOE OSTI2022

Integrated Issues and Risk Management: A Theoretical Framework Overview

The contractor requirements document for DOE O 226.1B, Implementation of Department of Energy Oversight Policy, requires DOE/NNSA contractors to establish an assurance system that includes, among other things, “Rigorous, risk-informed, and credible self-assessment and feedback and improvement activities. Assessment programs must be risk-informed, formally described and documented, and appropriately cover potentially high consequence activities” and “Contains an issues management process that is capable of categorizing the significance of findings based on risk and priority and other appropriate factors….” However, the term “risk-informed” is not defined in this or any other DOE order, and no formal guidance on how to integrate the two concepts currently exists. The Risk Management Guide for Defense Programs released by NA-18, Office of Systems Engineering and Integration (SE&I), states it is “a framework and general guidance to program office personnel on the effective management of program risks and issues”, however it then defines issues as “events with 100% likelihood of affecting program objectives” and states “unless specified otherwise, the term “risk” will also serve to represent issues for the remainder of this plan,” severally limiting its ability to provide adequate guidance on this topic. Outside of DOE scope, the U.S. Nuclear Regulatory Commission (U.S. NRC) imposes similar requirements. ASME NQA-1-2015 Requirement 16 states “Conditions adverse to quality shall be identified promptly and corrected as soon as practicable. In the case of a significant condition adverse to quality, the cause of the condition shall be determined, and corrective action taken to preclude recurrence. The identification, cause, and corrective action for significant conditions adverse to quality shall be documented and reported to appropriate levels of management. Completion of corrective actions shall be verified”. The purpose of this document is to provide a best-in-class framework for an integrated risk and issues management process. This process would provide a robust feedback loop between risk management and issues management to: Enhance risk identification and characterization, use risk handling principles to improve corrective action planning, and ensure regulatory compliance.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2022

Revisiting Current Paradigms: Subject Matter Expert Views on High Consequence Facility Security Assessments

Security assessments support decision-makers' ability to evaluate current capabilities of high consequence facilities (HCF) to respond to possible attacks. However, increasing complexity of today's operational environment requires a critical review of traditional approaches to ensure that implemented assessments are providing relevant and timely insights into security of HCFs. Using interviews and focus groups with diverse subject matter experts (SMEs), this study evaluated the current state of security assessments and identified opportunities to achieve a more "ideal" state. The SME-based data underscored the value of a systems approach for understanding the impacts of changing operational designs and contexts (as well as cultural influences) on security to address methodological shortcomings of traditional assessment processes. These findings can be used to inform the development of new approaches to HCF security assessments that are able to more accurately reflect changing operational environments and effectively mitigate concerns arising from new adversary capabilities.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Assessing Historical Extreme Weather Event Impacts

Resilience planning, particularly energy and water resilience planning, has been a key priority for the federal government for many years, leading federal agencies to develop processes for identifying and addressing critical resilience gaps at their facilities and sites. Furthermore, recent federal policy is driving agencies to prioritize climate change impacts as a more central component of their resilience planning efforts. To achieve this, federal sites must understand their vulnerability to climate change, which involves identifying climate hazards projected to impact the site (known as exposure), as well as understanding the sensitivity (the degree to which a site, including its people and the things they value, could be harmed by that exposure), and adaptive capacity of the site (the degree to which the site could lessen bathe potential for harm by taking action to reduce exposure and sensitivity). To assess and understand sensitivity and adaptive capacity, it is important to first obtain a baseline and understand how a site has been impacted by past events, in addition to considering the potential for unprecedented impacts based on climate projections. This information paper highlights current limitations for developing event history assessments and suggests a framework for more consistently capturing key data points. The purpose of this paper is to help inform how organizations could begin structuring a comprehensive process for recording the impacts of extreme weather events in order to facilitate climate vulnerability assessments, and thus, resilience planning.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Autonomous System Subversion Tactics: Prototypes and Recommended Countermeasures

One of the fielding requirements for Advanced and Small Modular Reactors (AR/SMR) is the ability to support remote and autonomous operations. Autonomous Control Systems (ACS) are found on platforms such as Autonomous Space Vehicles, Cruise Missiles, and advanced driver-assistance systems. Each of these ACS implementations depends upon a set of decision support subsystems responsible for supporting Autonomous Mission Managers (names vary based upon field and author preferences). These Autonomous Mission Managers receive inputs from system sensors (e.g., LIDAR collection from an automobile travelling down a street; transients from a nuclear reactor), and perform a set of classifications (e.g., Red Traffic Light; Small Pedestrian at 10m; Load Rejection; Single Coolant Pump Trip), and then use these classifications in combination with recommendation algorithms to achieve platform goals (e.g., Stop the Vehicle at the Traffic Light, Avoid the Small Pedestrian; Trip the Reactor to prevent a Safety Event). The design, implementation, and fielding of an ACS capability will alter the cyber-attack surface such that existing risk management plans will need to be updated to include how to protect and defend against data-science and decision-support-system attack classes. These attack classes would include protection of the design and training environments where algorithm selection and testing and training data would be obvious attack vectors. These attack classes would also require an informed set of detection and response procedures to identify anomalous behaviors and document best practices for anomaly assessment and vulnerability mitigation and remediation. Last year we published a Cyber Threat Assessment Methodology for Autonomous and Remote Operations for AR/SMRs along with a companion publication on Cyber Attack and Defense Use Cases. The focus of the methodology was on describing and enumerating ACS processes, components, and functions such that security engineers could: evaluate subversion options against the target; identify threat actor attributes and capabilities derived from each subversion option; and identify security controls and response countermeasures. The Use Cases document offered detailed methodology examples including an assessment of a Military Base SMR, an Autonomous System Decision Loop, and implementation of AR/SMR Machine Learning algorithms. Our proposal at the end of last year was to focus on implementation of subversion prototypes related to the last Use Case area: AR/SMR Machine Learning (ML) Algorithms. We included six attack scenarios in our Use Cases paper: a Poisoning Attack against ML functions implemented using an FPGA; a Trojaning Attack against ML classifiers exploiting the excitability of Nuclear Engineers; a Backdooring Attack against ML Training environments to ensure persistence of an attack vector; a False Positive Evasion Attack against multi-factor Access Control Systems using clever inputs; an Inference Attack against ML models by an Insider with access to the Operational environment; and an Adversarial Reprogramming Attack against a Material Access Control Video Surveillance System. At the beginning of this year these six attack scenarios were provided to our research teams at Georgia Tech and Idaho State University and each team successfully implemented a subversion attack against a ML implementation to include transient misclassifications. While this is a notable outcome from this type of research, this paper offers the reader insight into not only how to structure and execute these types of attacks, but into the thought process behind how the researcher investigated the problem space, performed initial algorithm implementation, and the trial-and-error behind arriving at the successful subversion prototypes. We include in this paper a set of associated Scenarios on how these subversion prototypes could be implemented and an initial set of guidance for AR/SMR architects, Nuclear Regulators, and Cyber Defenders to implement awareness and defense capabilities into their current operational portfolios.

42 ENGINEERING↗

DOE OSTI2021

Software-defined Networking for Energy Delivery Systems (SDN4EDS): An Architectural Blueprint (Final Summary Report)

This is the initial version of a reference for suppliers and energy companies of all sizes to deploy networks based on software-defined networking technology (SDN) to improve reliability, reduce cyber security attack surface, and facilitate mitigation of adversarial behavior. It is a living document and will progress over the life cycle of the Software-Defined Networking for Energy Delivery Systems (SDN4EDS) project. Version 2 of this report provides information on the Red Team tabletop assessment performed against the initial reference architecture. Version 3 of this report updates the reference architecture with lessons learned from the Red Team tabletop assessment, as well as provides additional details for the use cases. It also provides information on the decision process that could be used by an organization when considering deploying SDN in their environment. The final version of this report consolidates all the interim reports generated by the project into a final report. It also draws from PNNL’s experience in deploying SDN to make recommendations on how SDN could be deployed in a utility environment, and provides rationale for those decisions allowing individual utilities to make risk-based and knowledge-based decisions on how to best deploy SDN in their own environment. This summary report provides a higher-level overview of the project reports. Readers interested in additional detail, including results of the Red Team assessments and the final configuration, are encouraged to read the full final report.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

CoDCon Project (Final Report)

The co-decontamination (CoDCon) project was established in FY 2016 with the objectives of (a) evaluating the uncertainty in the uranium (U)/plutonium (Pu) ratio in a mixed U/Pu product from a tributyl phosphate (TBP)–based solvent extraction flowsheet, and (b) developing and demonstrating on-line optical spectroscopy for real-time monitoring of key components (e.g., Pu, U, and HNO 3 concentrations) in the process solutions. We were interested in assessing the accuracy and precision to which a specific uranium-to-plutonium (U/Pu) ratio can be achieved, which for the purposes of this project was set at a U/Pu mass ratio of 7/3. The uncertainty associated with achieving this specific target U/Pu ratio was investigated during five flowsheet tests using laboratory-scale solvent extraction equipment. In addition, optical spectroscopic techniques were incorporated into the CoDCon solvent extraction testing system, allowing real time monitoring of all input and output process streams. Two CoDCon flowsheet tests were performed in FY 2018 using a simple dissolved fuel simulant containing only U (~1 M) and Pu (~15 mM) in nitric acid (HNO 3 ; ~3 M). In FY 2019, two additional flowsheet tests were performed. For the first of these (CoDCon Run 3), the dissolved fuel simulant was similar to that used in the first two tests, with the inclusion of 1 mM neptunium (Np). The second test conducted in FY 2019 (CoDCon Run 4) used a more representative dissolved fuel simulant, including addition of non-radioactive fission product elements. A fifth CoDCon flowsheet test (CoDCon Run 5) was conducted in FY 2020, with the following additional objectives: (1) routing of the technetium (Tc) in the simulated dissolved fuel solution to the solvent extraction raffinate, and (2) routing of the Np in the simulated dissolved fuel solution to the U/Pu product. All tests used a bank of sixteen 2 cm centrifugal contactors. The tests involved first loading the solvent (30 vol% TBP dissolved in n-dodecane) with U and Pu (and Np, for Run 5), then the Pu (and Np) was stripped from the loaded solvent with a U(IV) solution (~50 mM) and the flowsheet conditions were adjusted such that some U partitioned into the Pu-containing product stream. The amount of U accompanying the Pu was monitored in real time using optical spectroscopic techniques coupled with chemometric modeling. Based on the real-time spectroscopic measurement of the U/Pu ratio, adjustments were made to the flowrate of the fresh TBP solvent phase used to scrub U from the aqueous Pu-containing product. This proved to be a very effective way to control the U/Pu mass ratio in the product. This report presents the results of the CoDCon Run 5 test. The flowsheet tested in Run 5 was substantially different than that run in the prior tests, especially the solvent loading section of the flowsheet. Two key changes were made. First, based on the objective to extract all the Np and route it with the U/Pu product, pentavalent vanadium [V(V)] was added to the feed and scrub solutions. The purpose of the V(V) was to convert all the Np to the +6 oxidation state, which is extractable by TBP. Second, a high acid (8 M HNO 3 ) scrub was added to the flowsheet to scrub the Tc from the solvent. This was followed by a low acid scrub (0.05 M HNO 3 ) to reduce the residual HNO 3 concentration in the solvent prior to the Pu stripping step. The output from the low acid scrub was collected separately, rather than routing towards the raffinate. The modifications to the solvent loading part of the flowsheet were only partially successful. The treatment with V(V) was effective at converting the Np to Np(VI). Only 1.3% of the Np remained in the raffinate solution. However, ~40% of the Np stripped out of the solvent in the low acid scrub step; nearly 20% of the Pu also was stripped from the solvent during the low acid scrub. For further development, either modifications to the flowsheet, or concentration and recycle of the low acid stream into the

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Guideline for Characterizing and Evaluating a Candidate Project Site for Solar Thermal Applications

This document presents a structured procedure for characterizing and evaluating candidate project sites for concentrating solar power (CSP) and solar heat for industrial processes (SHIP) applications. The objective is to provide project developers, researchers, and other stakeholders with a consistent, technology-agnostic framework for early-stage site assessment, enabling informed decision-making prior to significant investment in project development. Site selection is a critical factor in project success or failure for both CSP and SHIP projects. Key factors such as solar resource availability, land characteristics, environmental and regulatory constraints, infrastructure availability, and community context are determined by the choice of project site and can materially impact project performance, cost, schedule, and overall viability. This procedure is designed to systematically evaluate these factors, identify potential fatal flaws, and prioritize the most favorable candidate sites for further development. The process begins with rapid screening-level evaluation, using publicly available data to assess solar resource, land availability and suitability, zoning and land-use compatibility, and exclusion zones such as protected lands or sensitive habitats. Sites that meet the minimum screening criteria advance to a more detailed characterization. Subsequent sections of this report provide guidance for a next-level assessment of the most important technical and environmental parameters, including: 1) Solar resource quality, variability, and uncertainty using multiyear datasets and, where appropriate, on-site measurement campaigns; 2) Meteorological conditions such as wind, temperature, extreme weather events, and soiling impacts; 3) Land characteristics including slope, shading, and geotechnical conditions; and 4) Environmental and regulatory considerations, including permitting processes, endangered species, cultural resources, and visual impacts. The procedure also addresses infrastructure and integration considerations, including: 1) Grid interconnection requirements for CSP power generation projects; 2) Electrical and operational integration for SHIP facilities; 3) Water availability, quality, and permitting constraints, which are particularly critical for CSP in arid regions; and 4) Site access, construction logistics, and availability of workforce and supporting services. Recognizing the importance of social and economic context, the procedure includes evaluation of community engagement factors, such as stakeholder sentiment, proximity to sensitive visual receptors, workforce development opportunities, and local economic incentives. The outputs of these assessments are synthesized in a cost and risk evaluation, translating site characteristics into expected impacts on capital cost, operating cost, schedule, and technical risk. This is complemented by screening-level performance modeling, including 8760 simulations and long-term projections, to quantify expected energy or thermal output, assess variability thereof, and support comparison between candidate sites. Finally, the procedure provides high-level guidance on a structured go/no-go decision framework, categorizing sites based on identified risks and constraints, and outlining a clear path forward to feasibility studies and front-end engineering design for viable projects. By standardizing the site characterization process across both CSP and SHIP applications, this guideline aims to: 1) Improve consistency and transparency in early-stage project evaluation; 2) Reduce development risk and avoid investment in nonviable project sites; 3) Support collaboration between developers, researchers, and public agencies; and 4) Accelerate successful deployment of concentrating solar technologies for both power generation and industrial process heat.

14 SOLAR ENERGY↗

DOE OSTI2023

Multi-Sourced Collaboration for the Production and Refining of Rare Elements and Critical Metals (Final Technical Report)

The project objective was to develop a feasible and cost-effective method for recovering rare earth elements (REEs) and critical materials (CMs) from coal and coal byproducts, resulting in high-purity individually separated REEs and CMs. The targeted REEs included Y, Pr, Nd, Gd, Dy, and Sm, with a purity of over 99.5%, while the CMs included Co, Mn, Ga, Sr, Li, Ni, Zn, and Ge, with a purity of over 90%. The project aimed to design a prototype facility capable of producing 1-3 tonnes/day of high-purity REO mixes. The work was divided into four designated circuits: 1) REE extraction and concentration, 2) REE separation and purification, 3) RE metal production, and 4) CM production. To achieve these goals, the project involved 11 tasks, including technology reviews, research, process flow diagram development, mass balance estimation, and preliminary technical-economic analysis. The project team included researchers from the University of Kentucky, University of Alabama and Virginia Tech as well as process specialists from Argonne National Laboratory. MP Materials provided technical support regarding rare earth markets and processing while Alliance Coal performed resource assessment. The project included a market analysis for Nd/Pr, Tb, Dy, Gd, Y, Co, Mn, Li, Sr, Ga, Ni, Zn, and Ge. These analyses provided insights into the supply and demand trends as well as historic and future projections of market price relative to purity requirements for these elements. Two coal resources were selected for the project: the West Kentucky No. 13 (Baker) Seam and an undisclosed lignite resource in the Illinois coal basin. The estimated quantities of REEs in these resources were calculated based on production samples and drilling data. It was estimated that there is adequate supply for an operation producing one metric ton daily of higher purity mixed rare earth oxides (MREO) for approximately 20 years at a site located in western Kentucky. In Circuit 1, project data was obtained from a pilot heap leach and REE concentration facility. It was concluded that the existing circuit, which generated a MREO concentrate, two types of CM mixed products, and Li- and Sr-containing waters, would be suitable feed for circuits 2-4. Data from the first-of-its-kind coal coarse refuse heap leach pilot pad played a crucial role in estimating reliable elemental concentrations of the pregnant leaching solution (PLS). The average total REE concentration in the PLS was found to be 28.6 ppm. In Circuit 2, several concepts were explored including a novel process referred to as solvent-assisted chromatography (SAC). This concept involved a novel columnar reactor that incorporated multiple mixer/settlers, thereby enabling the operation of counter-flowing aqueous and organic phases. Unfortunately, due to project time constraints, a complete fundamental modeling analysis could not be completed to fully evaluate the technology. Molten salt electrowinning was considered as an alternative for circuit 3 following circuit 2 purification circuit utilizing the novel SAC process. A mass and energy balance of Nd reduction to metal in a fluoride containing molten salt electrolyte was conducted. Comparisons were made with the current state of Asian molten salt electrorefining, and potential improvements in siphoning rare earth metals (REM) from the reactor were presented. A cost estimate was performed for the production of 1 tonne per day, which yielded a total of $2.29 million for the nine electrowinning (EW) cells required. The selected option for circuits 2 and 3 was a plasma distillation process, which initially separates rare earth elements (REEs) from other elements. This is followed by selective electrowinning in various ionic liquids. The selection was made on the basis of thermodynamic modeling and experimental data previously published by a project partner. The combination offers an innovative approach to integrated refining and RE metal production. For Circuit 4, an extensive literature review was conducted for the processing of the CMs. The ultimate decision was to utilize a combined plasma and ionic liquid process as well to produce individual high-purity concentrates of Zn, Ni, Co, Mn, and Mg. A separate flowsheet for Li and Sr was recommended, which would yield carbonates of these elements. Due to the lack of suitable experimental data at this time, a process recommendation could not be provided but several methods have been proposed for consideration. Lastly, a techno-economic analysis (TEA) was conducted to assess the effectiveness of the proposed process for further investigation. The TEA results revealed a capital expense (CapEx) of $737 million and an annual operational expense (OpEx) of $220 million. Due to the selected elements, the hypothetical heap leach pad can produce 1 metric tonne per day of REO equivalent, but a conscious decision was made to only treat targeted REEs, resulting in the production of 0.4 metric tonne of REM. An estimated annual revenue of $90.87 million was projected based on standard market pricing information provided by the funding agency. During the TEA, ten different modules were evaluated for costing purposes. The precipitation circuit was identified as the largest single operational expense, followed by the Mg/Mn process due to the amount of treated metal. In terms of capital expenditures, the heap leach process incurred the highest cost, followed by the Mg/Mn process. The scalability of the plasma process is a crucial consideration since the reactors cannot be scaled beyond the largest demonstrated size due to their reliance on surface area of the slag and vapor phase. The purity estimate for the REEs are generally 98%±2% to produce a metal. The purity level being lower than the project objective was due to the lack of specific experimental data needed to tighten the tolerance of the estimates. Based on literature and previous experience, the CMs are estimated as follows; Ga (95%+, metal), Sr (95%+, carbonate), Li (95%+, carbonate), Ni (98%±2%, metal), Zn (95%+, metal sponge), Ge (95%+, metal), Co (98%±2%, metal), and Mn (98%±2%, metal).

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression

Here, we use Gaussian stochastic weight averaging (SWAG) to assess the epistemic uncertainty associated with neural-network-based function approximation relevant to fluid flows. SWAG approximates a posterior Gaussian distribution of each weight, given training data, and a constant learning rate. Having access to this distribution, it is able to create multiple models with various combinations of sampled weights, which can be used to obtain ensemble predictions. The average of such an ensemble can be regarded as the 'mean estimation', whereas its standard deviation can be used to construct 'confidence intervals', which enable us to perform uncertainty quantification (UQ) with regard to the training process of neural networks. We utilize representative neural-network-based function approximation tasks for the following cases: (i) a two-dimensional circular-cylinder wake; (ii) the DayMET dataset (maximum daily temperature in North America); (iii) a three-dimensional square-cylinder wake; and (iv) urban flow, to assess the generalizability of the present idea for a wide range of complex datasets. SWAG-based UQ can be applied regardless of the network architecture, and therefore, we demonstrate the applicability of the method for two types of neural networks: (i) global field reconstruction from sparse sensors by combining convolutional neural network (CNN) and multi-layer perceptron (MLP); and (ii) far-field state estimation from sectional data with two-dimensional CNN. We find that SWAG can obtain physically-interpretable confidence-interval estimates from the perspective of epistemic uncertainty. This capability supports its use for a wide range of problems in science and engineering.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Development and application of an environmental risk register for marine energy device and project developers

The marine energy industry is steadily advancing as more devices are deployed worldwide. However, several challenges and barriers remain, such as lingering uncertainty regarding the potential environmental effects of marine energy devices on marine animals, habitats, and ecosystems. Concerns have led to difficulty navigating permitting and consenting processes and receiving authorization to deploy devices in the marine environment, including extended timelines and costs. Based on existing risk registers, a novel marine energy environmental risk register was created to help the marine energy industry move beyond these barriers. This risk register aims to aid marine energy device and project developers identify and assess potential environmental risks early in device design or project planning, document and track potential environmental interactions, prioritize risks and determine risk responses, and make decisions throughout device or project development. It can also be used as a tool to assist in communicating with regulators and advisors during permitting processes and to inform stakeholder and community engagement efforts. This paper details the methods and process to develop a risk register specific to environmental effects of marine energy and describes two use cases (one for wave energy and another for tidal energy) to highlight example results. Due to the tool's novelty, the paper showcases its application for the marine energy industry and acknowledges limitations and possible future improvements. Overall, the environmental risk register shows promise to support marine energy developers when identifying, tracking, and addressing potential environmental risks and to help successfully navigate permitting and deploy marine energy devices responsibly.

Environmental effects↗

DOE OSTI2024

Aviation security screening optimizer for risk and throughput (ASSORT)

The increasing number of air travelers each year presents a challenge as many airports are near their capacity in terms of resources and space for passenger screening. Fortunately, advancements in technologies like next-generation millimeter wave scanning offer solutions to ease this strain. The focus remains on managing risk while enhancing the passenger experience for the traveling public. The risk model presented in this paper known as the Aviation Security Screening Optimizer for Risk and Throughput (ASSORT) is designed to assess risk-based approaches for passenger screening and checkpoint operations. Additionally, ASSORT is exploring various traveler categories — general, trusted, and trusted-plus — along with different checkpoint screening Concept of Operations tailored to each traveler type. For instance, travelers with a higher trust level may experience fewer screening technologies, resulting in quicker processing times at the checkpoint. The output of ASSORT provides a risk score for predefined threat scenarios, as well as the overall risk to the checkpoint, aircraft, and airport by traveler type. In conclusion, benefits of using this tool include assessing the trade-offs between the overall risk associated with checkpoints and the throughput rate of passengers screened. We show for example the impact that different passenger volumes at the checkpoint can have on risk.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

The Potential of Hydrogeodesy to Address Water-Related and Sustainability Challenges

Increasing climatic and human pressures are changing the world's water resources and hydrological processes at unprecedented rates. Understanding these changes requires comprehensive monitoring of water resources. Hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changes over time, delivers a range of novel monitoring tools that are complementary to traditional hydrological methods. It encompasses geodetic technologies such as Altimetry, Interferometric Synthetic Aperture Radar (InSAR), Gravimetry, and Global Navigation Satellite Systems (GNSS). Beyond quantifying these changes, there is a need to understand how hydrogeodesy can contribute to more ambitious goals dealing with water-related and sustainability sciences. Addressing this need, we combine a meta-analysis of over 3,000 articles to chart the range, trends, and applications of satellite-based hydrogeodesy with an expert elicitation that systematically assesses the potential of hydrogeodesy. We find a growing body of literature relating to the advancements in hydrogeodetic methods, their accuracy and precision, and their inclusion in hydrological modeling, with a considerably smaller portion related to understanding hydrological processes, water management, and sustainability sciences. The meta-analysis also shows that while lakes, groundwater and glaciers are commonly monitored by these technologies, wetlands or permafrost could benefit from a wider range of applications. In turn, the expert elicitation envisages the potential of hydrogeodesy to help solve the 23 Unsolved Questions of the International Association of Hydrological Sciences and advance knowledge as guidance toward a safe operating space for humanity. It also highlights how this potential can be maximized by combining hydrogeodetic technologies simultaneously, exploiting artificial intelligence, and accurately integrating other Earth science disciplines. Finally, we call for a coordinated way forward to include hydrogeodesy in tertiary education and broaden its application to water-related and sustainability sciences in order to exploit its full potential.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Techno-economic Analysis and Life Cycle Assessment of Gluconic Acid and Xylonic Acid Production from Waste Materials

Organic acid-based bioleaching has attracted significant research interest for the recovery of rare earth elements(REEs) and other critical metals. Utilizing biologically produced leaching agents, known as biolixiviants, derived from waste materials holds great promise for enhancing the economic viability and environmental sustainability of bioleaching processes. Here this study focuses on the modeling and optimization of biolixiviant production using corn stover (CS), date palm clippings (DP), and nonrecyclable paper (NP). Techno-economic analysis revealed that gluconic acid production from NP is more cost-effective than that from CS and DP, with respective costs of $0.04/kg, $0.06−0.08/kg, and $0.06−0.09/kg of the biolixiviant, yielding gluconic acid concentrations of 135.39, 172.90, and 176.87 mM, respectively. Life cycle assessment demonstrated that biolixiviant production from NP exerts the lowest environmental impact compared with the other evaluated substrates. When applied to the bioleaching of a neodymium−iron−boron magnet swarf, the biolixiviant derived from NP exhibits the highest leaching efficiencies, confirming its cost and environmental competitiveness in comparison to CS and DP

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Biomanufacturing and Scale-Up: Pathways to Biochemicals, Biofuels, and Biomaterials

Advancing the bioeconomy requires the development of large-scale microbial bioprocesses capable of converting waste carbon streams into biofuels, biochemicals, and biomaterials at industrially relevant scales. While biomanufacturing has been successfully demonstrated at the laboratory scale for a wide range of chemicals, only a few have reached industrial-scale production. This is partly due to the inherent complexity of microbial systems, which rely on living cells with intricate metabolic pathways that are highly sensitive to environmental changes, making large-scale production difficult to optimize and predict. As a result, scaling-up bioprocesses remains a high-stakes challenge that requires deeper exploration. This involves integrating feedstock and microbial selection, upstream and downstream processes, and computational modelling, among other research efforts. Bulk and specialty chemicals derived from biological processes also face competition from fossil-based production routes, which have been refined through decades of technological advancements. While biologically derived molecules may offer more environmentally friendly production pathways than traditional chemical manufacturing, their widespread adoption depends on achieving cost parity-or superiority-relative to fossil-based methods. This emphasizes the importance of holistic research, including techno-economic analyses and life cycle assessments, to ensure both economic viability and environmental sustainability. This editorial and special issue explores state-of-the-art strategies for converting waste carbon sources into valuable products. It discusses how enzymes, single microbes (e.g., extremophiles), and microbiomes (e.g., through division of labor) can be integrated with upstream and downstream process innovations-such as consolidated bioprocessing and in situ product recovery-to improve the efficiency and scalability of biomanufacturing. The editorial further highlights the role of computational modelling in understanding, predicting, and controlling bioprocess performance across scales, and concludes by emphasizing the importance of techno-economic modelling to identify technologies that can move to market.

09 BIOMASS FUELS↗