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At least 631 records · Page 35

Cost Impacts of Risk-Based Methods for Defining AoR and PISC Duration of a CO 2 Storage Project Using NRAP Tools and FE/NETL CO 2 Saline Storage Cost Model

The purpose of this analysis is to assess the fiscal impact of using risk-based methods to define the area of review (AoR) and post-injection site care (PISC) duration for a geologic carbon dioxide (CO 2 ) storage project. The Office of Fossil Energy (FE)/National Energy Technology Laboratory (NETL) CO 2 Saline Storage Cost Model (“cost model”) was utilized to evaluate CO 2 storage economics in this study. The cost model is a widely used tool for evaluating CO 2 storage costs in geologic settings. It estimates costs for storage operations conducted under compliance to the United States Environmental Protection Agency (EPA) Underground Injection Control (UIC) Class VI regulations. This analysis evaluates and compares the costs of storage (on a first-year break-even dollar per tonne [2018$] basis) at the proposed FutureGen 2.0 site as a case study storage location by implementing different approaches to determine AoR and PISC given the prevailing geologic conditions and injection volume and duration considerations. The approaches include the use of 1) risk-based methods to define AoR and PISC duration, 2) an EPA-approved AoR and PISC documented in the FutureGen 2.0 UIC Class VI permit applications, and 3) cost model default settings that utilize uncertainty multipliers to estimate CO 2 plume and pressure front extent as part of AoR determination, as well as a 50-year PISC default. From all three sources, the AoR and PISC specified in the Class VI permit applications for FutureGen 2.0 were the largest and longest relative to the other two sources.

54 ENVIRONMENTAL SCIENCES↗

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↗

US Department of Energy, Office of Science High Performance Computing Facility Operational Assessment 2021: Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory’s (ORNL’s) Leadership Computing Facility (OLCF) continues to surpass its operational target goals of supporting users; delivering fast, reliable computational ecosystems; creating innovative solutions for high-performance computing (HPC) needs; contributing to the community to build the next generation HPC workforce, and managing risks, safety, and security associated with operating some of the most powerful computers in the world. The results can be seen in the cutting-edge science conducted by users and the praise from the research community. Calendar year (CY) 2021 saw continued excellence in research supported by the OLCF’s leadership-class computing resources, including Summit (the nation’s most powerful supercomputer), the global scratch file system Alpine, the Scalable Protected Infrastructure (SPI), the Exploratory Visualization Environment for Research in Science and Technology (EVEREST), and the archival mass-storage resource High-Performance Storage System (HPSS). While maintaining access and exceptional user support for Summit, the OLCF continued to make progress on the installation and deployment of Frontier, which will be the nation’s first exascale system when it comes online at the start of CY 2023. Users have already begun running and optimizing scientific codes on Crusher, the OLCF test and development system equipped with Frontier’s architecture. Throughout the year, the OLCF maintained a strong culture of operational excellence, including risk management, workplace safety, and cybersecurity. The OLCF’s rigorous risk management strategy anticipated and mitigated risks, and at this time there are no high-priority operational risks. Similarly, ORNL and the OLCF were committed to operating under the US Department of Energy’s (DOE’s) safety regulations that ensure a safe workplace. Technical staff tracked and monitored existing threats and vulnerabilities within the OLCF while continually developing tools and practices to enhance operations without increasing the facility’s risk. CY 2021 was filled with outstanding results and accomplishments, including a very high rating from users on overall satisfaction for the eighth consecutive year; a tremendous number of node hours delivered to 1,671 researchers on Summit; and the successful delivery of the allocation split of roughly 60%, 20%, and 20% of core-hours offered for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE), Advanced Scientific Computing Research Leadership Computing Challenge (ALCC), and Director’s Discretionary (DD) programs, respectively (Section 2). COVID-19 research remained a focus in 2021, and the ALCC and DD programs allocated over 1 million Summit hours to the COVID-19 High Performance Computing Consortium. These accomplishments, coupled with the high utilization rates (i.e., overall and capability usage), represent the fulfillment of the promise of leadership class machines: efficient facilitation of leadership-class computational applications.

97 MATHEMATICS AND COMPUTING↗

Triton Field Trials - Changes in Habitats, a Literature Review of Monitoring Technologies

Marine energy devices are installed in highly dynamic environments and have the potential to affect benthic and pelagic habitats around them. Regulatory bodies often require baseline characterization and/or post-installation monitoring to determine whether changes in these habitats are being observed. However, a great diversity of technologies is available for surveying and sampling marine habitats. Selecting the most suitable instrument to identify and measure changes in habitats at marine energy sites can become a daunting task. We conducted a thorough review of journal articles, survey reports, and grey literature to extract information about the technologies used, the data collection and processing methods, and the performance and effectiveness of these instruments. We examined documents related to marine energy development, offshore wind farms, oil and gas offshore sites, and other marine industries around the world over the last 20 years, as well as national and international guidelines for surveying habitats around offshore activities. A total of 120 different technologies were identified across six main habitat categories: seafloor, sediment, infauna, epifauna, pelagic, and biofouling. The technologies were organized into 12 broad technology classes: acoustic, corer, dredge, grab, hook and line, net and trawl, plate, remote sensing, scrape samples, trap, visual, and others. Visual was the most common and the most diverse technology class, with applications across all six habitat categories. Sampling designs varied considerably among the reviewed studies but transect was the predominant design for surveying seafloor, epifauna, and pelagic habitats. The most common data analyses were univariate and multivariate statistical analyses aimed at calculating and comparing biodiversity indices, characterizing faunal assemblages or sediment classes, or modeling the distribution of animals related to abiotic parameters. Technologies and sampling methods adaptable and designed to work efficiently in energetic environments have greater success at marine energy sites. In addition, sampling designs and statistical analyses should be carefully thought through to identify differences in faunal assemblages and spatiotemporal changes in habitats.

16 TIDAL AND WAVE POWER↗

Compact, high-power superconducting radio-frequency accelerators for environmental applications

Electron-beam irradiation has been proven to destructively reduce or eliminate a wide variety of organic chemicals, viruses and bacteria from wastewater, as well as reducing sulfur and nitrous oxides emission from coal-fired power plants. It is estimated that there are approximately 30,000 such particle accelerators in use worldwide for industrial processes including surface and bulk processing of material, medical sterilization, and environmental remediation. Maximum beam power from accelerators used in these applications is currently limited to less than 500 kW, and a higher beam power is needed to reduce treatment costs. The market availability of continuous-wave (CW) electron-beam accelerators with power of the order of ~100 kW is also very limited. Superconducting radio-frequency (SRF) linear accelerators (linacs) are commonly used at basic research laboratories throughout the world due to their exceptionally high efficiency as compared to current industrial varieties. Recent advances in cryogenics, SRF thin films and high-power magnetrons allow for the design of increasingly compact and efficient CW SRF electron linacs in the energy range 1-10 MeV, with up to 1 MW of beam power. A new class of compact, high-efficiency electron-beam accelerators may provide cost-effective solutions for a range of industrial and environmental remediation applications, particularly with respect to tackling one such class of contaminants so-called “forever chemicals”, including per- and polyfluoroalkyl substances (PFASs), which are ubiquitous in a wide range of products and for which there is currently no effective destruction technology. We have recently demonstrated the key technologies required for such accelerators by: 1) operating a Nb3Sn SRF accelerating cavity cooled by commercial cryocoolers up to an accelerating gradient of 12.4 MV/m and 2) demonstrating the phase-locking as well as a high-efficiency power combining scheme for industrial magnetron transmitters. In this presentation, we will introduce the principles and benefits of MW-class SRF linacs, based on the conduction-cooled SRF technology that we have demonstrated for environmental remediation. We propose the development of a 4 MeV, 20 kW prototype to be built at Jefferson Lab as a first accelerator demonstrator unit. We will also present the results from samples study on the effect of electron-beam irradiation on so-called “forever chemicals” such as 1,4-dioxane and PFAS, using an existing multi-purpose 10 MeV, low-power, CW SRF linac at Jefferson Lab.

Ciovati, Gianluigi↗

Development of Transformational Solvents for CO2 Separations

The primary objective of this CRADA activity is to use a combined molecular modeling and experimental validation approach to refine and develop transformational solvents for carbon capture. PNNL’s role on this project is currently funded by the Department of Energy’s (DOE) Office of Fossil Energy (OFE). PNNL is developing advanced molecular modeling based on their CO2BOLs solvent platform as a demonstration solvent for the activity; the model was developed and compared against measured data for CO2BOL derivatives. Here, a CRADA with PNNL and GE will leverage their current molecular models and apply them to solvent classes that operate on carbamate chemistry, specifically GE’s aminosilicone solvent class. The molecular models will be used to predict physical and thermodynamic properties, such as viscosity, as a means to predict advanced formulations with reduced viscosity compared to current aminosilicone derivatives, enabling optimized thermodynamic and kinetic metrics for economical carbon capture for this class of materials. Together, PNNL and GE will develop a comprehensive means of linking molecular modeling parameters to intermediate physical properties as a means to improve solvent performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing A New NG Super-Absorbent Polymer (NG-SAP) for a Practical NG Storage System with Low Pressure, Ambient Temperature, and High Energy Density

This R&D project proposed a systematical study to develop a new class of NG super-absorbent polymer (NG-SAP) with the objective to achieve similar CNG volumetric storage level ~250 cm 3 -STP/cm 3 and fast sorption-desorption kinetics at ambient temperature but lower operational pressure (<100 bar). We suggested two consecutive research phases, including (i) a systematical investigation of various polymer systems to identify the suitable classes that can exhibit methane (C1) binding energy in the range of 20-25 kJ/mol and then (ii) focusing on the potential class polymers to identify the specific structure and morphology that can achieve the project objective.In first research phase (1st year), the major tasks included design and synthesis of several representative polymers with various structure attributes, examining their molecular structures, pore morphology, and BET surface area as the prepared samples, and then studying their C1 binding energy and sorption capacity.

03 NATURAL GAS↗

FY2023 NSTTF Annual Report

The National Solar Thermal Test Facility (NSTTF) is a DOE Core Capability and Technology Deployment Center located in Albuquerque, NM. It is operated by Sandia National Laboratories (Sandia) for the U.S. Department of Energy (DOE). The NSTTF is the only multi-mission, multi-use, multi-story test facility of its type in the United States. The NSTTF was founded in 1978 and began testing with high heat flux that same year. Over the past 45 years, the NSTTF has been at the forefront of the research, design, fabrication, and testing of many of the critical Concentrating Solar Power (CSP) technologies. These technologies have allowed costs to be dramatically reduced from over $\$ $0.40 /kWh to $\$$0.12 /kWh since the conception of this renewable energy technology. The NSTTF has worked to make the Solar Energy Generating Systems (SEGS) parabolic trough plants successful, while also working with the Solar One and Solar Two facilities for successful implementation. Over the four decades since its founding, the mission of the NSTTF has grown to include new receiver technologies, like our generation 3 falling particle system (G3P3 Tower), optical metrology techniques like SOFAST, molten salt testing, thermal energy storage, solar thermal chemistry, and more. We continue to expand our capabilities in pursuit of the DOE SETO mission and the DOE SunShot 2030 goals: unsubsidized LCOE of $\$$0.05/kWh for CSP that includes 12 or more hours of thermal energy storage. To support both the DOE SETO mission and support the CSP sector as a whole, we are working to develop our operations and maintenance framework to provide a world class testing facility in support of our technological achievements. To accomplish both of these missions, the NSTTF draws on the decades of experience and expertise of our staff along with the world-class facilities at Sandia National Laboratories to further the science of concentrated solar thermal technologies in diverse applications. We remain a trusted partner for high-quality and impactful research in both fundamental and applied arenas. We are able to provide our partners with both one-of-a-kind testing platforms as well as world-class analytics.

14 SOLAR ENERGY↗

Assessment of tank designs for hydrogen storage on heavy duty vehicles using metal hydrides

The objective of this project was to evaluate material-based hydrogen storage solutions as a replacement for high-pressure hydrogen gas or liquid hydrogen on Class 7 or 8 tractor fuel cell electric vehicles. The project focused on low-density main-group hydrides, a well-known class of materials for hydrogen storage. Prior research has considered metal amides as storage materials for light-duty vehicles but not for heavy-duty applications. The project established the basis for further development of storage systems of this type for heavy duty vehicles (HDV). Systems analysis of an HDV storage system comprised of a tank and associated balance of plant (piping, coolant tubes, burner) was performed to determine the usable hydrogen capacity. A composite storage material comprised of a metal hydride mixed with a high thermal-conductivity carbon is predicted to have a usable hydrogen volumetric capacity comparable to or exceeding that of 700 bar pressurized hydrogen gas. The gravimetric capacity of this material is also predicted to be competitive with pressurized gas, particularly if costly carbon fiber composite Type III or Type IV tanks are excluded. The storage system design parameters and material properties served as inputs to a second model that simulates fuel cell operation in conjunction with the storage system during an HDV drive cycle. The results show that sufficient hydrogen pressure can be produced to operate a Class 8 HDV, yielding a range of ~480 miles. These results are particularly relevant for high-impact regions, such as the South Coast Air Quality Management District, for which an economical vehicular hydrogen storage system with minimal impact on cargo capacity could accelerate adoption of heavy-duty fuel cell electric vehicles. An additional benefit is that knowledge generated by this project can assist in development of material-based storage for stationary applications such as microgrids and backup power for data centers.

08 HYDROGEN↗

IEA Wind TCP Task 49: Reference Site Conditions for Floating Wind Arrays

This report, prepared within Work package 1 of IEA Wind Task 49, presents reference site conditions for floating wind arrays to serve as a design basis for the techno-economic design of reference floating wind arrays. Data of the reference sites presented here are publicly available in an open database and thus support fast development and comparable design of floating wind arrays for various relevant conditions. The development of these reference sites drew on existing open access datasets and ongoing research projects of task participants. Six classes were identified that describe relevant key conditions for the design and development of floating wind arrays: met-ocean conditions, seabed conditions, coastal infrastructure, environmental impact, socio-economic impact, as well as regulations and permissions. The reference sites for the techno-economic design of floating wind arrays are based on a concept with building blocks to synthesize purpose-built site representations. In each of the identified classes with influencing design factors, building blocks are used to describe the characteristic properties and their spread. However, the latter three classes (i.e., environmental impact, socio-economic impact, regulations and permissions) are not included in the reference site conditions due to limited knowledge and lack of reliable criteria to quantify their impact on the techno-economic design in numeric parameters. Building blocks with key parameters for the techno-economic design of floating wind arrays are provided for met-ocean conditions, seabed conditions, and coastal infrastructure. For met-ocean conditions, multiple sites were selected for detailed analysis that represent a range of conditions across the pipeline of floating wind projects. Wind conditions and sea states are separated, and each location considers both the severity of wind and waves e.g. one site may have a moderate wave condition but severe wind condition. From this pipeline, eleven representative sites were selected where both site-specific analysis was available within the consortium, and where they represent different parts of the global pipeline. The eleven sites are: Hannibal (Italy), Humboldt (US), Ulsan (South Korea), MoneyPoint One (Ireland), Havbredey (UK), Fukushima (Japan), Utsira Nord (Norway), Gulf of Maine (US), Sud de la Bretagne II (France), Sorlige Nordsjo II (Norway). Each of these sites is summarized in the main report while more details about the studies and analyses behind the datasets are provided in the appendix. For seabed conditions, general information about the geotechnical parameters is provided and a baseline is established for the geotechnical parameters and stratigraphy that may be encountered on the sites. A set of six 'synthetic cases' is defined as building blocks providing the different parameters required for design under each case/soil condition. For the coastal infrastructure, general information about the main requirements is provided that a port should comply with to provide a satisfactory service during the construction of floating offshore wind arrays. Minimum port infrastructural requirements are provided for three types of ports.

17 WIND ENERGY↗

Application of Partial Least Squares Approaches to Pyroprocessing ER Data

Multivariate approaches show promise for application to process monitoring for safeguards of pyroprocessing. Past MPACT work explored the application of Principal Component Analysis (PCA) to detect off-normal conditions in pyroprocessing electrorefiner (ER) data from in the Hot Fuel Examination Facility (HFEF) at Idaho National Laboratory (INL) known as the Scalable Pyrochemical Recycling testbed (SPyRe) ER. PCA, however, does not consider the output variables. In FY24, multivariate analysis was extended from PCA to Partial Least Squares (PLS) analysis. PLS maximizes the variance between both the input signals and output variables. In the case of this work, PLS was applied in two different manners: Predictive PLS and Discriminant PLS. Predictive PLS maximizes the covariance between the process variables of the ER and the measured U concentration from in-situ voltammetry. Discriminant PLS maximizes the covariance between the process variables and a set of training process “states” such as known off-normal conditions. By projecting into the latent variable space in PLS, the process variables can be regressed onto the outputs and predictions can be made for new data sets. In this work, by applying predictive PLS, a penalized non-linear PLS approach was able to make predictions of concentration based on test and training data and detect when operations were off-normal. However, the predictive PLS does not classify the signals to which off-normal operations are attributable. Discriminant PLS can be used to classify off-normal operations but is inadequate to properly classify specific off-normal classes like power supply faults when the Discriminant PLS model is only specifically trained to detect that off-normal class. When all faults are trained against the observation data, all three operational classes are accurately classified and distinguished. Thus, future application of latent variable techniques should not select any given method, but should use a mixture of PCA, Predictive PLS, and Discriminant PLS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Carbon Storage Site Mapping Inquiry Tool (MapIT)

To date, 48 projects, consisting of 139 wells, are currently under review with the Environmental Protection Agency’s (EPA) Underground Injection Control (UIC) Program for Class VI – wells used for geologic sequestration of carbon dioxide. The number of applications submitted is expected to increase in coming years with the increase of the 45Q tax credit available to projects that initiate construction prior to 2033. The amount of data collected to submit a Class VI permit is vast, and often disparate, coming from state, federal, and commercial entities, as well as field-specific data collected within an area of interest. When preparing for site selection and permitting, the initial aggregation of relevant public data can be time intensive. The Carbon Storage Site Mapping Inquiry tool (MapIT) was created to support and accelerate the discovery and accessibility of open-source data and information available across the USA. Data was aggregated and organized based on data types described within the EPA UIC Class VI permit documentation. The online tool enables users to explore hundreds of geospatial data layers and connect to additional external resources, leveraging API and REST services where possible to ensure updates to data in real time. MapIT enables users to explore state and federal data related to geologic, geophysical, structural, hydrologic, and contextual information. In addition to displaying spatial data and linking to external resources, MapIT leverages custom widgets to ensure that internal data and external data are discoverable and accessible. The widgets connect users to resources such as the USGS publications and the USGS Earthquake Catalog based on a user-defined location. This talk will describe data aggregation workflows, data types, data preparation, and tool development for MapIT. The Carbon Storage Site Mapping Inquiry Tool and underlying database are valuable, intuitive resources that empower government, academic, commercial and industry stakeholders to explore, analyze, and acquire carbon storage related data.

Morkner, Paige↗

Developing a Prototype Methodology to Rank CO2-EOR Wells and Assess Their Reuse Potential for Geologic Carbon Sequestration

This study presents a prototype methodology for evaluating the reuse potential of Class II CO₂-enhanced oil recovery (CO₂-EOR) wells as Class VI wells for geologic carbon sequestration. The approach focuses on assessing wellbore construction materials—casing, cement, tubing, and packers—based on U.S. Environmental Protection Agency (EPA) Class VI well conversion guidelines. Utilizing Python scripts and JSON representations, the methodology automates checks on digitized Texas Railroad Commission (TRRC) data to rank wells based on regulatory and integrity criteria. Key factors include casing integrity, cementing techniques, tubing compatibility, and packer selection. Due to limitations in digitized data, manual verification is required for certain sections. Future enhancements include incorporating non-digitized data via web scraping and machine learning. This research provides a practical framework for well owners and regulators, supporting informed decision-making for sustainable CO₂ storage.

carbon sequestration↗

Findings on subtask 3.3 – applicability of automated brine chemistry determinations for treatment and recovery processes through facility automation/modularization: engineering design study

Under the Energy & Environmental Research Center’s (EERC’s) ~$\$$22 million Phase II Brine Extraction and Storage Test (BEST) Program, a multimillion-dollar brine treatment technology test bed facility was established in western North Dakota to provide a platform for evaluating developing technologies and approaches for brine treatment and volume reduction. The initial facility, and associated research effort, was funded by the U.S. Department of Energy (DOE), with in-kind contributions provided by several industry participants and the state of North Dakota. Since its opening, the Brine Technology Test Facility (BTTF) has supported performance evaluations of desalination technologies capable of treating high-salinity produced water (PW) and enabled data collection for multiple approaches of PW management and critical material recovery. As part of the decommissioning process for the original project, facility ownership and liability were transferred to Select Water, which is providing the EERC with a continuing site access option for state or federal research and/or commercial technology development. This report documents the findings from a design study conducted by the EERC and the engineering firm that was originally contracted to design and construct the facility (Advanced Engineering and Environmental Services, LLC [AE2S]) that evaluated the current status of BTTF and its systems and developed a retrofit design to increase the facility’s capabilities through automation and modularization of its PW treatment infrastructure. The proposed retrofit will provide DOE and industry with an expanded range of conditioned PW that can be produced at the facility for evaluating fit-for-purpose water treatment technologies, online instrumentation for brine chemistry determination, and systems that recover critical materials like lithium and magnesium. The current facility consists of an 9600-square-foot facility that includes a 40-foot by 65-foot Class 1, Division 2-rated demonstration area and associated control rooms and lab-ready space capable of sourcing oil and gas PW and wastewater from industrial sources or tailoring brine compositions up to 300,000 mg/L total dissolved solids (TDS) and supplying them at rates up to 25 gpm for extended-duration technology demonstrations. The colocation of the facility with Select Water’s water management facilities allows for access and unloading of more than 10,000 bbl/day of trucked water delivered to site and associated access to on-site Class I and Class II brine disposal wells and nearby hazardous waste landfills operated and/or contracted by Select Water to dispose of concentrate and/or effluents associated with the testing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ULTIMATE Phase I project: Development of Niobium-based alloys for Turbine Applications

Current Ni-based alloys used in turbine blade applications are operating at 1100°C which is approximately 90% of the solidus of Ni-based alloys. Further increases in temperature can be achieved only through the use of alloys with higher solidus temperatures such as refractory alloys which include Mo, Nb, W, Ta alloys. Niobium has a unique combination of physical properties that include a high melting point (2468°C), lowest density (8.57 g/cc), and the lowest modulus amongst refractory alloys, a good thermal conductivity that increases from 45 W/mK at room temperature to 62 W/mK at 1093°C, good ductility with fabricability using traditional techniques, high strength, good creep resistance, and general chemical inactivity. Hence niobium alloys offer many advantages for use at the desired temperature of 1300°C. One of the major deterrents to the use of niobium and its alloys at high temperatures is achieving good oxidation resistance. In addition, achieving balanced properties of room temperature strength, ductility, fracture toughness, high temperature strength, and creep resistance required for 1300°C operation at a density of 9 g/cm 3 is extremely challenging since the addition of W which is a potent strengthener increases the density of the alloy. This project seeks to enable the development of a tri-layered turbine blade that can operate continuously at 1300°C with the core of the turbine blade providing good creep resistance, the second layer providing improved oxidation resistance over the core layer, and the third layer being an environmental barrier providing oxidation resistance. The objective of this Phase 1 project was to use computational modeling and advanced characterization tools to develop two classes of Nb alloys which could be used as the core layer and the transition layer. The first class of alloys developed in this project was a Nb-alloy designed to serve as the turbine blade core with excellent room temperature strength, ductility, and high temperature strength and creep resistance required for 1300°C operation. These alloys were designed to contain sufficient solute solution strengthening elements (W, Mo) but constrained by the density of alloy, along with the addition of elements such as Zr, Hf, Ta, C, and N to achieve a combination of primary and secondary carbide precipitation. A total of 38 “creep-resistant” alloys were designed and cast during the duration of the project. Processing techniques were developed to keep the oxygen contents as low as possible with typical oxygen contents less than 250 ppm. One alloy with a density of < 9.5 g/cc was successful in meeting the Phase 2 intermediate project mechanical property milestone requirements of room temperature ductility greater than 1.0%, 1200°C creep strain of less than 3% at 150 MPa and 100 hours in vacuum, and with solidus temperature greater than 1500ᵒC. The second class of alloys was designed to be a Nb-rich alloy with improved oxidation resistance when compared to the core layer and was designed specifically to be compatible with the core layer and the outer environmental barrier coating. This Nb- alloy will be specifically designed to be microstructurally stable at these temperatures when in contact with the core alloy and provide protection against catastrophic failure of the barrier coating. Two alloys were cast and processed but further development was discontinued to focus on the development of the creep resistant alloy.

36 MATERIALS SCIENCE↗

ASME Code change proposal to implement new universal high temperature constitutive models for Section III, Division 5

This report completes work on a universal high temperature constitutive model suitable for use with the ASME Boiler & Pressure Vessel Code Section III, Division 5 rules for the design by inelastic analysis of Class A nuclear reactor components. The goals of this work are to provide a simple model form that adequately captures the high temperature response of materials and can be applied to any future Code material. Additionally, the report describes an automated process for calibrating a model against test data. The idea is to simplify the effort required to generate a constitutive model for an arbitrary material, provided test data is available. This will accelerate the process of qualifying new Code materials in the future. In addition, the report provides calibrated models and detailed validation comparisons to test data for five currently-qualified or soon-to-be qualified materials: 316H, Grade 91, Alloy 800H, Alloy 617, and Alloy 709. The report surveys the available data for the remaining two ASME Class Materials --- 2.25Cr-1Mo and 304H --- concluding that there is enough data data to generate a model for 2.25Cr-1Mo steel provided some additional sources of non-public data can be included in the test database, but that a dedicated cyclic test campaign would be needed for 304H. Supplemental material includes the full text of an ASME Code change proposal to incorporate the models for the four currently-qualified Class A material, detailed validation comparisons to test data for the five material models, and input files for reference implementations of the constitutive models in the NEML and NEML2 modeling frameworks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluation of Pozzolan-substituted Cast Stone for Pretreated Hanford Tank Waste

Portland cement. The future availability of quality Class F fly ash has come into question as coal-fired power plants are being converted to gas or taken offline. Consequently, alternative pozzolanic reagents are being evaluated for fly ash replacement in cementitious matrices for treating radioactive waste and debris. In 2023 and 2024, Savannah River National Laboratory (SRNL) was funded to evaluate natural pozzolans for the replacement of Class F fly in the Savannah River Site (SRS) Saltstone formulation. Based on the promising results and uncertain availability of Class F fly ash in the northwestern US, Hanford Tank Waste Operations & Closure, LLC (H2C) requested SRNL to evaluate the potential for substituting natural pozzolans in the Hanford West Area Pretreated Low Activity Tank Waste (PTW/LAW) Cast Stone formulation1 . Task 1 in this request was to determine the change in Cast Stone volume resulting from stabilization/solidification of 1 L of PTW/LAW tank waste. The densities of three (Hess Pumice, tephra pumice, and clinoptilolite zeolite) pozzolan-substituted Baseline Cast Stone mixes were determined, and volume changes relative to the fly ash-Baseline Mix with a water-to-dry mix = 0.40 were calculated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

LDR Inorganic Spiked Simulants in Pozzolan-Substituted Cast Stone for Hanford Pretreated Low-Activity Tank Waste

Pretreated Low Activity Waste (PTW/LAW) at the Hanford Site, is currently projected for disposition through a cementitious waste form. The current standard formulation, Cast Stone, uses Class F fly ash, blast furnace slag, and Portland cement. However, the future availability of Class F fly ash is uncertain, as many coal-fired power plants—the source of this byproduct—are being decommissioned or converted to natural gas. This issue has prompted research into identifying and evaluating suitable alternative materials to replace fly ash in the cementitious waste forms used by the Department of Energy (DOE). The Savannah River National Laboratory (SRNL) successfully identified four natural pozzolans for the replacement of Class F fly ash in the current Savannah River Site (SRS) low-level waste (LLW) form, Saltstone.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗