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At least 217 records · Page 12

Development of a Solar Heat and Power Co-Generation System. Final CRADA Report

Final Report CRADA No. TC02152.0 Date Technical Work Ended: October 28, 2013. This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Tassajara Technologies, Inc. (TTI), to develop, fabricate and demonstrate a Solar Heat and Power Co-generation System. The technical objectives of this CRADA were to engineer, design and build a prototype Solar Thermal Process Heat and Power Demonstration System that would be suitable for use at the Arc of Hilo food processing facility. This would be accomplished in two phases. The first phase would entail the building of a prototype at Tassajara facilities. Base design parameters, including the subsystem interactions that would produce reliable performance at the lowest cost per watt of energy generated with the desired balance of power and heat to meet the requirements of the designated food processing applications from Arc of Hilo, would be provided by LLNL. The data and design development would be integrated into the second phase engine prototype and solar thermal system that would be built and delivered, with interface requirements to the Miko Building.

14 SOLAR ENERGY↗

Subsurface Seismic Structure Around the Sanford Underground Research Facility

To address the fundamental challenges of understanding processes associated with enhanced or engineered geothermal systems (EGS), teams from the EGS Collab SIGMA-V project are conducting stimulations at the Sanford Underground Research Facility. Various modalities of geophysical observations are collected and analyzed, and different types of parameters are modeled to help investigate these critical processes. Among these parameters, the three-dimensional stress field is one of the primary objectives. Seismic velocity models have been used to estimate the 3D stress field for other regions. A detailed seismic velocities and density model can help us infer spatial variations of the stress field in the study area. We inverted the 3D seismic structure around the site by using body-wave travel times, surface-wave dispersions and gravity observations simultaneously. The resulting model will be a starting point for more detailed investigations and could also be used to study subsurface geological and stress field variations of the broad area.

Chai, Chengping↗

Subsurface Seismic Structure Around the Sanford Underground Research Facility

To address the fundamental challenges of understanding processes associated with enhanced or engineered geothermal systems (EGS), teams from the EGS Collab SIGMA-V project are conducting stimulations at the Sanford Underground Research Facility. Various modalities of geophysical observations are collected and analyzed, and different types of parameters are modeled to help investigate these critical processes. Among these parameters, the three-dimensional stress field is one of the primary objectives. Seismic velocity models have been used to estimate the 3D stress field for other regions. A detailed seismic velocities and density model can help us infer spatial variations of the stress field in the study area. We inverted the 3D seismic structure around the site by using body-wave travel times, surface-wave dispersions and gravity observations simultaneously. The resulting model will be a starting point for more detailed investigations and could also be used to study subsurface geological and stress field variations of the broad area.

Chai, Chengping↗

Monitoring system for high-tech equipment

Many organizations and automated data-processing systems are involved in analysis of the logistical support (ALS) of high-tech equipment. Therefore, the initial data and the results of analysis must be presented in standardized form. That calls for an integrated informational model describing all the relevant data elements, their attributes, and their relationships. In ALS, the instruments that monitor the operation of the high-tech equipment form an important component of the information system.

42 ENGINEERING↗

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗

Bayesian, Multifidelity Operator Learning for Complex Engineering Systems–A Position Paper

Abstract Deep learning has significantly improved the state-of-the-art in computer vision and natural language processing, and holds great potential to design effective tools for predicting and simulating complex engineering systems. In particular, scientific machine learning seeks to apply the power of deep learning to scientific and engineering tasks, with operator learning (OL) emerging as a particularly effective tool. OL can approximate nonlinear operators arising in complex engineering systems, making it useful for simulating, designing, and controlling those systems. In this position paper, we provide a comprehensive overview of OL, including its potential applications to complex engineering domains. We cover three variations of OL approaches: deterministic OL for modeling nonautonomous systems, OL with uncertainty quantification (UQ) capabilities, and multifidelity OL. For each variation, we discuss drawbacks and potential applications to engineering, in addition to providing a detailed explanation. We also highlight how multifidelity OL approaches with UQ capabilities can be used to design, optimize, and control engineering systems. Finally, we outline some potential challenges for OL within the engineering domain.

Computer Science↗

Comparison of Electron Beam and Laser Beam Powder Bed Fusion Additive Manufacturing Process for High Temperature Turbine Component Materials, Phase II. CRADA Final Report

The evolving additive manufacturing (AM) technology is now at the point where some metallic turbine components are being fabricated for both development and production purposes. The goal of this phase II project is to continue the evaluation of AM Nickel Alloy X fabricated by electron beam (EB) or laser beam (LB) powder bed fusion (PBF) process for gas turbine applications. Microstructure, mechanical and oxidation properties characterization was conducted on test specimens produced with powders of different chemistries within the typical material specification range. Powders with high Silicon (Si) content for the LB-PBF and low Si content for the EB-PBF displayed significant cracking levels in the AM Nickel Alloy X material. Accordingly, optimum fatigue performance would require careful control of powder chemistry, optimization of the fabrication parameters for a given powder and use of hot isostatic pressing (HIP) post treatment. Oxidation testing conducted at 1472°F (800ºC) in air showed that the roughness of the EB-PBF specimens led to an increase in specimen mass change, but overall the AM specimens exhibited oxidation behavior at 1472°F (800ºC) that is appropriate for applications in gas turbine engines. Assessment of the geometric capability of the LB-PBF and EBPBF systems using artifacts representative of turbine component geometries revealed that the LB-PBF process is well-suited for the fabrication of intricate geometries needed for turbine engine fuel injector components, but further process development is required to improve the EB-PBF system feature resolution.

36 MATERIALS SCIENCE↗

Reliable SOFC Systems

The goal of this U.S. Department of Energy (DOE) sponsored project was to advance the reliability, robustness and endurance of low-cost SOFC technology suitable for ultimate deployment in ≥100 MWe Integrated Gasification Fuel Cell (IGFC) or Natural Gas Fuel Cell (NGFC) systems capable of ≥97% CO2 capture. The ultimate SOFC program goals are ≤ 0.2% per 1000 hours power degradation over a 5-plus year stack life, high-volume (≥ 250 MW/year) stack production cost of ≤$225/kWsystem net AC, and “power block” (exclusive of fuel supply, contaminant removal, and CO2 capture subsystems) capital cost of ≤ 900/kWsystem net AC (in year 2011). To progress towards the ultimate program goals, the specific objectives of this project were to achieve an SOFC stack power degradation rate of ≤1.5% per 1000 hours in a 100 kW (125 kW Peak) Modular Power Block (MPB) stand-alone power system under thermally self-sustained normal operating conditions and to verify the prospects for high volume SOFC stack production cost below the DOE target of ≤ 225/kW. This final technical report summarizes the progress made during the project period of 36 months. Significant progress was made in the areas of cell and stack technology development, Modular Power Block (MPB) development, sub-MW MPB system development, and MW-class SOFC System Development and Costing. The work focused on areas necessary for comprehensive development of an SOFC fuel cell system, including, active cell improvement, contaminant resistance, process engineering, and development of non-repeat module components. Additionally, several custom built balance-of-plant components were designed and fabricated to support the fuel cell system. SOFC cell and stack development focused on improving cell performance and durability. Enhancements were achieved in areas of electrode stability and impurity tolerance. Additionally, several quality control techniques and tools were developed to ensure predictable and repeatable fabrication of SOFC stacks. Module development continued previous development efforts to achieve footprint reduction and higher efficiency by incorporating balance-of-plant functional equipment into the fuel cell containment module. Several improvements were made to prior design. Control and instrumentation hardware was integrated within the module for serviceability and size reduction. The design efforts culminated in a complete SOFC power plant system. The designed plant was constructed and tested at FCE. Stack and system costs were updated, reflecting advances made in this program.

20 FOSSIL-FUELED POWER PLANTS↗

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum of compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.

97 MATHEMATICS AND COMPUTING↗

MODEL BASED BIOMASS SYSTEM DESIGN OF FEEDSTOCK SUPPLY SYSTEMS FOR BIOENERGY PRODUCTION

Engineering feedstock supply systems that deliver affordable, high-quality biomass remains a challenge for the emerging bioenergy industry. Cellulosic biomass is geographically distributed and has diverse physical and chemical properties. Because of this feedstock supply systems that deliver cellulosic biomass resources to biorefineries require integration of a broad set of engineered unit operations. These unit operations include harvest and collection, storage, preprocessing, and transportation processes. Design decisions for each feedstock supply system unit operation impact the engineering design and performance of the other system elements. These interdependencies are further complicated by spatial and temporal variances such as climate conditions and biomass characteristics. This paper develops an integrated model that couples a SQL-based data management engine and systems dynamics models to design and evaluate biomass feedstock supply systems. The integrated model, called the Biomass Logistics Model (BLM), includes a suite of databases that provide 1) engineering performance data for hundreds of equipment systems, 2) spatially explicit labor cost datasets, and 3) local tax and regulation data. The BLM analytic engine is built in the systems dynamics software package PowersimTM. The BLM is designed to work with thermochemical and biochemical based biofuel conversion platforms and accommodates a range of cellulosic biomass types (i.e., herbaceous residues, short- rotation woody and herbaceous energy crops, woody residues, algae, etc.). The BLM simulates the flow of biomass through the entire supply chain, tracking changes in feedstock characteristics (i.e., moisture content, dry matter, ash content, and dry bulk density) as influenced by the various operations in the supply chain. By accounting for all of the equipment that comes into contact with biomass from the point of harvest to the throat of the conversion facility and the change in characteristics, the BLM evaluates economic performance of the engineered system, as well as determining energy consumption and green house gas performance of the design. This paper presents a BLM case study delivering corn stover to produce cellulosic ethanol. The case study utilizes the BLM to model the performance of several feedstock supply system designs. The case study also explores the impact of temporal variations in climate conditions to test the sensitivity of the engineering designs. Results from the case study show that under certain conditions corn stover can be delivered to the cellulosic ethanol biorefinery for $35/dry ton.

09 BIOMASS FUELS↗

Scaleup and Site-Specific Engineering Design for Global Thermostat Direct Air Capture Technology

The overall goal of the project is completion of an initial design of a commercial-scale, Carbon Capture, Utilization, and Storage Direct Air Capture (CCUS-DAC) plant design at three different sites that captures a net of at least 100,000 tonnes per year (TPY) carbon dioxide (CO 2 ) from the atmosphere and considers compression and conditioning of the captured CO 2 for purpose of pipeline transportation to different geological formation sites for deep well injection and underground storage. In addition to the leading system consisting of a scaled-up Global Thermostat DAC unit, overall plant design includes a combined Heat and Power (CHP) unit integrated with a conventional liquid amine-based carbon capture system (90% capture) and compression facilities. These are considered balance of plant (BOP) systems and are required to provide low carbon-intensity steam and power to the DAC process. A second approach involving provision of DAC units modified to directly capture emissions from the CHP unit was initially assessed as an alternative and it was determined to be less mature than considered approach and not included in the scaled-up plant design efforts. Three geographically diverse continental United States locations were selected to better understand the effect of local/regional ambient conditions on scaled-up DAC system performance and project costs: Bucks, Alabama (hot wet climate), Odessa, Texas (dry hot climate), and Goose Creek, Illinois (mid continental climate). The team focused on initial engineering design activities, including the development of project design criteria, initiation of site-specific studies and investigations, completion of DAC system process and equipment design, and definition of balance of plant (BOP) engineering. The purpose of the activities were to develop Technoeconomic Analysis (TEA), Life-Cycle Analysis (LCA), and Environmental, Health, and Safety (EH&S) analysis, and Business Case Analysis (BCA) to validate that the project engineering and scale-up plans of the DAC systems, at each of the three distinct case studies considered, are technically, economically, and environmentally feasible for commercial-scale operation.

20 FOSSIL-FUELED POWER PLANTS↗

Cyber-Informed Engineering Guidance—Implementing CIE in Early Systems Engineering Lifecycle Stages

Traditionally, cybersecurity is not considered in the design process. Design engineers typically focus on building safety and reliability into their products and applications. Security against malicious cyber incidents is often an afterthought, resulting in deployment of security solutions during installation or operation. Unfortunately, waiting to consider cybersecurity until later in the systems engineering lifecycle often results in less effective and more expense security. Idaho National Laboratory (INL) developed the concept of Cyber-Informed Engineering (CIE) in 2015 to provide a framework that enables cybersecurity to be built into systems beginning at the conceptual design stage. In addition to ongoing research by INL, the U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response has recently developed a National CIE Strategy document for incorporating CIE into the design and operation of infrastructure systems reliant on digital monitoring or controls. This paper provides a brief review of this National CIE Strategy as well as a roadmap to historical, current, and future CIE research by INL through the U.S. DOE Office of Nuclear Energy (NE) Cybersecurity Crosscutting Technology Development Program. A near-term focus of the DOE-NE’s research and development is to extend the foundational CIE work into detailed guidance for implementation during initial systems engineering stages in nuclear digital instrumentation and control projects and to demonstrate use of the guidance in an integrated energy systems project.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Smoothing-based compressed state Kalman filter for joint state-parameter estimation: Applications in reservoir characterization and CO 2 storage monitoring

The operation of most engineered hydrogeological systems relies on simulating physical processes using numerical models with uncertain parameters and initial conditions. Predictions by such uncertain models can be greatly improved by Kalman-filter techniques that sequentially assimilate monitoring data. Each assimilation constitutes a nonlinear optimization, which is solved by linearizing an objective function about the model prediction and applying a linear correction to this prediction. However, if model parameters and initial conditions are uncertain, the optimization problem becomes strongly nonlinear and a linear correction may yield unphysical results. In this paper, we investigate the utility of one-step ahead smoothing, a variant of the traditional filtering process, to eliminate nonphysical results and reduce estimation artifacts caused by nonlinearities. Here, we present the smoothing-based compressed state Kalman filter (sCSKF), an algorithm that combines one step ahead smoothing, in which current observations are used to correct the state and parameters one step back in time, with a nonensemble covariance compression scheme, that reduces the computational cost by efficiently exploring the high-dimensional state and parameter space. Numerical experiments show that when model parameters are uncertain and the states exhibit hyperbolic behavior with sharp fronts, as in CO 2 storage applications, one-step ahead smoothing reduces overshooting errors and, by design, gives physically consistent state and parameter estimates. We compared sCSKF with commonly used data assimilation methods and showed that for the same computational cost, combining one step ahead smoothing and nonensemble compression is advantageous for real-time characterization and monitoring of large-scale hydrogeological systems with sharp moving fronts.

42 ENGINEERING↗

Application of a Comprehensive Lagrangian–Eulerian Spark-Ignition Model to Different Operating Conditions

Increasing engine efficiency is essential to reducing emissions, which is a priority for automakers. Unconventional modes such as boosted and highly dilute operation have the potential to increase engine efficiency but suffer from stability concerns and cyclic variability. To aid engineers in designing ignition systems that reduce cyclic variability in such engine operation modes, reliable and accurate spark-ignition models are necessary. Here, in this article, a Lagrangian–Eulerian spark-ignition (LESI) model is used to simulate electrical discharge, spark channel elongation, and ignition in inert or reacting crossflow within a combustion vessel, at different pressures, flow speeds, and dilution rates. First the model formulation is briefly revisited. Then, the experimental and simulations setups are presented. The results showcase the model’s ability to predict the secondary circuit voltage, current, and power signals, in addition to the spark channel elongation, for the inert cases, or flame front growth, for the reacting cases. The results also compare simulation spark channel and flame growth plots to experimental Schlieren images at different instants in time. This work serves to highlight LESI’s ability to predict the characteristics of discharge and ignition across a variety of operating conditions.

42 ENGINEERING↗

Analysis of AP1000 Small-Break Loss-of-Coolant Accident Using Reactor Transient Simulator

The Westinghouse Electric Company’s Advanced Passive Reactor (AP1000) is characterized by the incorporation of passive safety systems (PSSs) designed to ensure core cooling during transient events. The assessment of PSSs requires evaluation of their performance through a combination of experiments and simulations employing various thermal-hydraulic codes. In addition, detailed evaluation of PSSs for a specific reactor system transient analysis such as loss-of-coolant-accident analysis supports understanding representative integral effects test facility development and the further evolution model development and assessment process. Developing a reactor system code is a complex and time-consuming process that requires significant engineering expertise and effort. It can take several months to even years to complete in the early stages of reactor system design and analysis. However, this process can be expedited through the use of transient simulator models for similar reactor systems, which can be used for lesson learning and training purposes. This study uses the Personal Computer Transient Analyzer (PCTRAN) code. The main advantage of PCTRAN is its ease of use and ability to run faster than real time. This study presents the results obtained for a small-break loss-of-coolant accident (SBLOCA) for two breaks using the full version (licensed) of PCTRAN. The purpose of this investigation is to evaluate the overall system behavior during the postulated SBLOCA event as well as assess the capability of the PCTRAN code to reproduce the system response during transient events. The obtained results were compared with the Westinghouse NOTRUMP system code. The PCTRAN code proved to be reliable in predicting the qualitative behavior of the system in both transient cases. As for the system response, it was found that it is contingent on the activation time of the PSSs. The differences in reactor coolant system pressure between the two codes were attributed to the critical flow model and simplification of mass and energy balance. Despite PCTRAN’s limitations, it can still provide a reasonable prediction of various reactor parameters such as pressure, mass flow rate, and void fraction during a SBLOCA scenario. It is worth noting that PCTRAN currently employs a bulk approach similar to that of the Modular Accident Analysis Program (MAAP) and MELCOR codes. However, the upcoming version of PCTRAN will include an artificial intelligence–based detection and accident prevention system, as well as different models for different reactor components. Consequently, PCTRAN has the potential to be upgraded to match the system thermal-hydraulic codes of the U.S. Nuclear Regulatory Commission and become more widely used in cybersecurity to safeguard nuclear power plants from cyberattacks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Prototype HB650 Transportation Validation For The PIP-II Project

The PIP-II Project at Fermilab is centered around a superconducting 800 MeV proton linac to upgrade and modernize the Fermilab accelerator complex, allowing increased beam current to intensity frontier experiments such as LBNF-DUNE. PIP-II includes strong international collaborations, including the delivery of 12 cryomodules from European labs to FNAL (3 from STFC-UKRI in the UK and 9 from CEA in France). The transatlantic shipment of these completed modules is identifed as a serious risk for the project. To mitigate this risk, a rigorous and systematic process has been developed to design and validate a transport system, including specifcation, procedures, logistics, and realistic testing. This paper will detail the engineering process used to manage this effort across the collaboration and the results of the first major validation testing of the integrated shipping system prior to use with a cryomodule.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of partial vapor pressures of salt mixtures via combined horizontal transpiration and thermogravimetric analysis

A method combining thermogravimetric analysis (TGA) and horizontal transpiration with elemental analysis via inductively coupled plasma mass spectrometry or ion chromatography enabled calculation of partial pressures of individual salts in molten mixtures. TGA quantified total mass loss, while transpiration identified vapor-phase composition. Furthermore, two chloride (NaCl-MgCl 2 , NaCl-MgCl 2 + UCl 3 ) salts and one mixed halide (LiCl-LiF + Li 2 O) salt were analyzed at 750 °C and 550 °C, respectively. NaCl and MgCl 2 vapor pressures were 2.19–2.61 × 10 -4 atm and 2.47–2.48 × 10 -5 atm (dependent upon the identity of the invesitgated mixture); UCl 3 was 1.42 × 10 -7 atm. LiCl and LiF vapor pressures at 550 °C were 1.53 × 10 -6 and 6.32 × 10 -6 atm, respectively. Additionally, the TGA method was validated against values from the literature for unary LiCl and LiF.

36 MATERIALS SCIENCE↗