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At least 1,441 records · Page 80

DR Argillite Disposal R&D at LBNL

Within the Natural Barrier System (NBS) group of the Used Fuel Disposition (UFD) Campaign at the Department of Energy’s (DOE) Office of Nuclear Energy, LBNL’s research activities have focused on understanding and modeling EDZ evolution and the associated coupled processes and impacts of high temperature on parameters and processes relevant to performance of a clay repository to establish the technical base for the maximum allowable temperature. This report documents results from some of these activities. These activities address key Features, Events, and Processes (FEPs), which have been ranked in importance from medium to high, as listed in Table 7 of the Used Fuel Disposition Campaign Disposal Research and Development Roadmap (FCR&D-USED-2011-000065 REV0) (Nutt, 2011). Specifically, they address FEP 2.2.01, Excavation Disturbed Zone, for clay/shale, by investigating how coupled processes affect EDZ evolution; FEP 2.2.05, Flow and Transport Pathways; and FEP 2.2.08, Hydrologic Processes, and FEP 2.2.07, Mechanical Processes, and FEP 2.2.09, Chemical Process—Transport, by studying near-field coupled THMC processes in clay/shale repositories. The activities documented in this report also address a number of research topics identified in Research & Development (R&D) Plan for Used Fuel Disposition Campaign (UFDC) Natural System Evaluation and Tool Development (Wang 2011), including Topics S3, Disposal system modeling – Natural System; P1, Development of discrete fracture network (DFN) model; P14, Technical basis for thermal loading limits; and P15 Modeling of disturbed rock zone (DRZ) evolution (clay repository).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Low-Enriched Uranium (LEU) option for the conversion of FRM II

The Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II) is Germany’s most powerful research reactor and uses Highly Enriched Uranium (HEU) fuel enriched at 93 %. The Technical University of Munich (TUM) operates the reactor and has been mandated to convert the FRM II to a lower-enrichment fuel. In preparation for the lower-enrichment fuel downselection, planned for 2023, TUM is evaluating multiple conversion scenarios. In this paper, it is demonstrated that a conversion of FRM II to Low-Enriched Uranium (LEU) is scientifically possible when using the novel monolithic U-10Mo fuel system, which is currently in the qualification process. As a research reactor, safety criteria, neutron flux distribution and cycle length are key metrics. To begin, neutronic and thermal-hydraulic models were created based on current technical drawings and relevant material properties. Specifically tailored computational methods and coupling schemes have also been developed to properly evaluate all relevant characteristics for the conversion of the FRM II reactor. Using these models and methods, a systematic parameter study was performed to explore the defined design space. The results of that study indicate that many LEU designs using monolithic U-10Mo appear to be viable to convert FRM II to LEU. One example of an LEU solution for the FRM II reactor that fulfills the stated safety, compatibility and scientific performance requirements is discussed in more detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Energy Model to Evaluate Thermal Energy Storage Integrated with Air Source Heat Pumps: Preprint

Full decarbonization in buildings requires the replacement of combustion appliances with electric ones, and air source heat pumps (ASHP) are a candidate alternative. However, technical limitations, such as the efficiency decrease when operating in cold weather, limit their adoption in the global heating market. Among several options to improve ASHP efficiency operating in colder climates, thermal energy storage (TES) has been considered, as it may provide heating when it is cold and shift ASHP operation to times when the weather is warmer. It may also take advantage of time of use electricity rates and support defrosting when necessary. The evaluation of ASHP-TES systems, however, is still limited because traditional metrics do not capture their full economic and environmental benefits. In this work, a python framework is presented to model the ASHP with and without the presence of TES. Metrics are proposed to analyze the system performance in terms of costs, equivalent CO2 emission, and efficiency metrics to evaluate and compare alternative systems. Model validation against experimental data obtained for a commercial heat pump is provided, as well as an application example using Denver, Colorado, to highlight the model capabilities.

cold climate↗

Study of Synthetic Vision Systems (SVS) and Velocity-vector Based Command Augmentation System (V-CAS) on Pilot Performance

This study investigated the effects of synthetic vision system (SVS) concepts and advanced flight controls on single pilot performance (SPP). Specifically, we evaluated the benefits and interactions of two levels of terrain portrayal, guidance symbology, and control-system response type on SPP in the context of lower-landing minima (LLM) approaches. Performance measures consisted of flight technical error (FTE) and pilot perceived workload. In this study, pilot rating, control type, and guidance symbology were not found to significantly affect FTE or workload. It is likely that transfer from prior experience, limited scope of the evaluation task, specific implementation limitations, and limited sample size were major factors in obtaining these results.

Liu, Dahai↗

Study of Synthetic Vision Systems (SVS) and Velocity-vector Based Command Augmentation System (V-CAS) on Pilot Performance

This study investigated the effects of synthetic vision system (SVS) concepts and advanced flight controls on single pilot performance (SPP). Specifically, we evaluated the benefits and interactions of two levels of terrain portrayal, guidance symbology, and control-system response type on SPP in the context of lower-landing minima (LLM) approaches. Performance measures consisted of flight technical error (FTE) and pilot perceived workload. In this study, pilot rating, control type, and guidance symbology were not found to significantly affect FTE or workload. It is likely that transfer from prior experience, limited scope of the evaluation task, specific implementation limitations, and limited sample size were major factors in obtaining these results.

Liu, Dahai↗

Criteria for Retention of 3013 S1 Containers Based on Relative Risk and Expert Judgment

An evaluation was performed to assess the suitability of thirty-three 3013 containers proposed for retention. These containers have moisture levels greater than 0.08 wt.% – the S1 population. The remainder of the S1 population stored at SRS will be down blended and disposed of by the end of 2028. Based on field surveillance and shelf-life data available to date as well as informed technical judgment, no container is currently expected to fail in its 50-year storage period. However, corrosion risk varies across the S1 population. Relative risks were evaluated using predicted Consensus Scores and their 95% Upper Prediction Limits (UPLs). The predicted values are based on a statistical model of Consensus Score as a function of moisture, chloride, and whether the packaged material was electrorefining scrap packaged at Hanford. Consensus Score has been shown to be a useful indicator of corrosion potential, and the UPL captures uncertainty in the model predictions, providing a conservative indicator of corrosion potential. Using UPLs to determine relative risks, together with expert review, three containers were identified as not suitable for retention, and the remainder were determined to be suitable.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Lunar-base construction equipment and methods evaluation

A process for evaluating lunar-base construction equipment and methods concepts is presented. The process is driven by the need for more quantitative, systematic, and logical methods for assessing further research and development requirements in an area where uncertainties are high, dependence upon terrestrial heuristics is questionable, and quantitative methods are seldom applied. Decision theory concepts are used in determining the value of accurate information and the process is structured as a construction-equipment-and-methods selection methodology. Total construction-related, earth-launch mass is the measure of merit chosen for mathematical modeling purposes. The work is based upon the scope of the lunar base as described in the National Aeronautics and Space Administration's Office of Exploration's 'Exploration Studies Technical Report, FY 1989 Status'. Nine sets of conceptually designed construction equipment are selected as alternative concepts. It is concluded that the evaluation process is well suited for assisting in the establishment of research agendas in an approach that is first broad, with a low level of detail, followed by more-detailed investigations into areas that are identified as critical due to high degrees of uncertainty and sensitivity.

Boles, Walter W.↗

Deer Isle and Stonington Energy Reliability Opportunities

The towns of Deer Isle and Stonington, located on the island of Deer Isle in Maine, partnered with the U.S. Department of Energy's Energy Technology Innovation Partnership Project (ETIPP) to examine options to enhance energy resilience, reduce dependence on imported fuels, and mitigate high energy costs. With technical support from the National Laboratory of the Rockies (NLR), Lawrence Berkeley National Laboratory (LBNL), and regional partner the Island Institute, the project focused on evaluation of the local electricity distribution infrastructure, examination of ongoing activities to reduce the frequency of outages, review of the applicable policy and regulatory environment, and identification of potential on-site energy solutions. Key findings revealed the island's reliance on a single distribution line, and limited hosting capacity for additional distributed energy resources. Solar photovoltaics (PV) technology, with and without battery storage, was found to be the most viable technology given economic, technical, and social considerations. While also technically feasible, wind energy faces more difficult siting and less public acceptance compared to PV. Marine energy technologies were determined to be infeasible due to technology immaturity and lengthy permitting timelines. Modeling of potential building-scale PV plus storage systems resulted in successful grant applications for installations at two local facilities. Analysis of community scale energy generation and storage options resulted the local utility, Versant, submitting a grant application for a proposed community-scale battery storage system to increase grid resilience and hosting capacity. This initiative has strengthened the communities' energy planning capabilities and laid the groundwork for future clean energy development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

TCCSP Project Implementation Plan

The TCCSP CarbonSAFE Phase II efforts focused on developing the technical, community, and economic foundation for a commercial-scale regional geologic storage complex for CO 2 captured. TCCSP has conducted a thorough evaluation of the regional, local, and site-specific geology, legacy well infrastructure, injection site design, and project planning as part of the CarbonSAFE Phase II TCCSP. Specially, the work performed under the CarbonSAFE Phase II has significantly furthered the advancement towards the commerciality of the TCCSP storage complex by delivering on the following objectives: Objective 1: Acquire site-specific characterization data to validate carbon dioxide (CO 2 ) storage estimates of reservoir units and the competency of confining layers in the region to prevent CO 2 leakage to develop a commercial-scale CO 2 project. Objective 2: Assess technical, economic, regulatory, and stakeholder aspects of the TCCSP.

54 ENVIRONMENTAL SCIENCES↗

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗

Magnetic Nanoparticles Impregnated, Cross-Linked, Porous Chitosan Microspheres for Efficient Adsorption of Methylene Blue from Pharmaceutical Waste Water

The study demonstrates the preparation of MnFe{sub 2}O{sub 4} impregnated chitosan-microspheres (CMMS) as adsorbents for efficient removal of cationic thiazine dye, methylene blue. A facile approach with great economic and technical advantages to obtain highly crystalline manganese ferrite nanoparticles by solution combustion method is accounted. CMMS were characterized and evaluated for MB adsorption using linear forms of Freundlich and Langmuir adsorption isotherms, pseudo-first order, pseudo-second order and Elovich kinetic models. Application of CMMS to pharmaceutical waste, desorption of MB and reusability of CMMS are reported. Significantly, MB concentration in treated real sample was reduced by ~ 18 times to that of initial concentration. Graphic Abstract: .

36 MATERIALS SCIENCE↗

Addressing technical barriers for reliable, safe removal of fluoride from drinking water using minimally processed bauxite ores

Throughout the developing world, over 200 million people drink groundwater containing fluoride concentrations surpassing the World Health Organization's maximum recommended contaminant level (WHO-MCL) of 1.5 mg F - /L, resulting in adverse health effects ranging from mottled tooth enamel to debilitating skeletal fluorosis. Existing technologies to remove fluoride from water, such as reverse osmosis and filtration with activated alumina, are expensive and are not accessible for low-income communities. Our group and others have demonstrated that minimally-processed bauxite ores can remove fluoride to safe levels at a fraction of the cost of activated alumina. We report results from testing for some technical challenges that may arise in field deployment of this technology at large scale, particularly in a sufficiently robust manner for application in development contexts. Anticipating possible modes of failure and addressing these challenges in advance in the laboratory is particularly important for technologies for vulnerable communities where the opportunity to re-launch pilot projects is limited and small failures can keep solutions from the people that need them most. This work addresses three potential technical barriers to reliable removal of fluoride from drinking water with bauxite ore from Visakhapatnam, Andhra Pradesh, India. We evaluate competition from co-occurring ions, adsorption reversibility, and potability of the product water with regards to leaching of undesirable ions during treatment with various adsorbent materials including raw and thermally activated bauxite, and synthetic gibbsite (a simple model system). Under the conditions tested, the presence of phosphate significantly impacts fluoride adsorption capacity on all adsorbents. Sulfate impacts fluoride adsorption on gibbsite, but not on either bauxite adsorbent. Nitrate and silicate (as silicic acid), tested only with gibbsite, do not affect fluoride adsorption capacity. Both thermally activated bauxite and gibbsite show non-reversible adsorption of fluoride at a pH of 6. Raw bauxite leached arsenic and manganese in a TCLP leaching test at levels indicating the need for ongoing monitoring of treated water, but not precluding safe deployment of bauxite as a fluoride remediation technology. Understanding these phenomena is crucial to ensure field deployment over large diverse geographical areas with aquifers varying in groundwater composition, and for ensuring that the appropriate engineering processes are designed for field implementation of this innovation.

42 ENGINEERING↗

Scaling open-weight large language models for hydropower regulatory information extraction: A systematic analysis

Information extraction from regulatory and technical documents using large language models (LLMs) involves practical trade-offs between extraction quality and computational cost. We evaluate eight open-weight LLMs spanning 0.6B–70B parameters on hydropower licensing documents and report deployment-oriented evidence under a unified extraction schema and evaluation protocol. Across the model set, we observe clear scale-dependent trends in both baseline extraction quality and the effectiveness of reflective reasoning (self-checking) under our fixed-prompt, no-augmentation setting. Mid-scale models often provide a favorable balance of accuracy and efficiency, whereas the smallest models show limited or inconsistent gains from the reasoning variants tested. Larger models achieve the highest overall F1 scores but incur substantially greater compute and infrastructure requirements. We further find that reliability failure modes can distort conventional metrics in this domain: in particular, high recall can coincide with systematic extraction errors when models fabricate values for fields that are absent from the source text, underscoring the importance of conservative null handling and evidence-grounded evaluation. Overall, our study provides a reproducible resource–performance comparison for open-weight LLM-based extraction in hydropower regulatory documentation and offers practical guidance for model selection under different deployment constraints.

Evaluation protocol↗

Co-simulation of transactive energy markets: A framework for market testing and evaluation

The proliferation of distributed energy resources (DER)—and the ability to intelligently control these assets—is re-defining the electrical distribution system. As the number of controllable devices rapidly expands, grid operators must determine how to incorporate these assets while delivering reliable, equitable, and affordable electricity. One possible approach is to establish distribution-level electricity markets and allow devices/aggregations of devices to participate in price establishment. While this approach purports some of the same benefits as the highly successful wholesale electricity markets (i.e., open competition, efficient price discovery, reduced communication overhead), this needs to be researched and quantified via an analysis platform that models distribution-level markets at the appropriate fidelity. Specifically, the simultaneous evaluation of market performance, DER performance, DER bidding approaches, and distribution feeder power quality requires modeling that spans multiple technical areas. Co-simulation has emerged as a powerful tool in addressing this type of problem, where outputs depend on a range of underlying areas of expertise and associated models. In this paper we describe a solution, as implemented in the HELICS co-simulation platform, where we include (1) high fidelity house models, (2) intelligent bidding agents, (3) a modular market integration/design, and (4) a distribution feeder model. We then present a case study where we test two different market designs: (1) a pseudo-wholesale double-blind auction, and (2) an asynchronous matching market. In this work, the markets are run under two DER penetration levels and economic results are compared to full retail net energy metering and avoided cost net metering scenarios that bookend current approaches to remuneration of DER participation. We show the potential for transactive markets to provide increased value for most customers relative to net metering (and all customers relative to avoided cost scenarios) while decreasing costs for the utility.

24 POWER TRANSMISSION AND DISTRIBUTION↗