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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Evaluating Lunar Water Processing System Model Configurations for Small Scale Oxygen and Hydrogen Production Within JAXA'S ISRU Technology

Introduction: In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s) range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant. System Model: In FY24, the System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team developed a lunar water processing system model using the Mission Analysis and Integration Tool (MAIT) to estimate the M/V/P for ISRU subsystems operating under a wide range of Hydrogen (H2) and Oxygen (O2) production targets for the Space Technology Mission Directorate (STMD) [1]. Based on Japan Aerospace Exploration Agency’s (JAXA) surface operational requirements, this system architecture was modified to include the ability to excavate consolidated icy regolith (versus granular ice excavation using Kennedy Space Center’s (KSC) ISRU Pilot Excavator, IPEx) and explore the feasibility of processing the lunar water both inside and outside of the PSR. For the consolidated icy regolith case study, excavation was performed via a mobility transport chassis outfitted with The Regolith Ice Drill for Exploring New Terrain (TRIDENT) for drilling [2] and the Cold Operable Lunar Deployable Arm (COLDArm) [3] for regolith transfer. The system model determines the required rover and payload. M/V/P to handle the required regolith processing rates. The regolith is then sorted and heated to sublimate the ice (via an auger dryer). The exiting high temperature, low pressure vapor is cleaned of volatiles (via cold trap) and electrolyzed to produce H2 and O2. These products are then dried, liquified with 20 K and 90 K cryocoolers (for H2 and O2, respectively), and stored in cylindrical tanks. Study Goals: Due to the different ConOps options of regolith transport to the ridge for processing versus processing it directly inside the PSR, as well as the unknown regolith/water-ice composition, new excavation techniques and their power configurations are being evaluated within a ISRU system architecture for production targets less than NASA’s pilot plant (1 mT). This analysis investigates the feasibility of numerous excavation techniques, power architectures, and logistical operations and determines an optimal system configuration with regards to M/V/P. It aims to investigate which parameters, both locally and globally, have the greatest effect on each subsystem within the plant. This can be used to identify the most critical components of the plant, and guide future decisions on allocating funding for research and development. The results from this study may provide subsystem developers with appropriate interfaces with excavation subsystems and downstream processes, and assessing the overall feasibility of each excavation technique, power architecture, and logistical timeframe. References: [1] Carlson, A. et. al. (2024) ICES. [2] Zacny, K., et. al. (2024) “ASCE Earth and Space”. [3] McCormick, R., et. Al. (2024) IEEE Xplore.

ISRU↗
DOE OSTI2017

Evaluating Indicators and Life Cycle Inventories for Processes in Early Stages of Technical Readiness

This presentation examines different methods for analyzing manufacturing processes in the early stages of technical readiness. Before developers know much detail about their processes, it is valuable to apply various assessments to evaluate their performance. One type of assessment evaluates performance indicators to describe how closely processes approach desirable objectives. Another type of assessment determines the life cycle inventories (LCI) of inputs and outputs for processes, where for a functional unit of product, the user evaluates the resources used and the releases to the environment. These results can be compared to similar processes or combined with the LCI of other processes to examine up-and down-stream chemicals. The inventory also provides a listing of the up-stream chemicals, which permits study of the whole life cycle. Performance indicators are evaluated in this presentation with the U.S. Environmental Protection Agency's GREENSCOPE (Gauging Reaction Effectiveness for ENvironmental Sustainability with a multi-Objective Process Evaluator) methodology, which evaluates processes in four areas: Environment, Energy, Economics, and Efficiency. The method develops relative scores for indicators that allow comparisons across various technologies. In this contribution, two conversion pathways for producing cellulosic ethanol from biomass, via thermochemical and biochemical routes, are studied. The information developed from the indicators and LCI can be used to inform the process design and the potential life cycle effects of up- and down-stream chemicals.

09 BIOMASS FUELS↗
DOE OSTI2020

Process Development of the Vaporizing Foil Actuator Welding Technique

The industrial focus on continuous improvement for products is leading design engineers to consider multi-material design concepts more frequently. The design concepts use the advantages of each material while simultaneously minimizing the drawbacks. It also allows for the overall weight of the products to be reduced. Some traditional joining methods, though, struggle to join dissimilar material combinations. A technique known as vaporizing foil actuator welding, which was developed around ten years ago, is a solid-state joining method that has the potential to overcome the barriers to dissimilar material joining. The biggest drawbacks of vaporizing foil actuator welding are that it is still exclusively used in laboratory settings and early in the technology development process. As such, there is not enough confidence in the process for it to be transitioned to manufacturing environments yet. This work begins by analyzing the current state of the technology and identifying a roadmap to achieve a transition to manufacturing. The analysis found that increased confidence in the technology requires sample to sample repeatability to be improved. Beyond that, the process also needs to be fully automated before it can be considered as a viable technique for mass production. In order to further develop the technique, a fully automated work cell was constructed. By removing the human element from the process, this cell helped identify iii the aspects which contribute to process variability. The positioning of the vaporizing foil actuator was identified as the most important factor in process stability. A small set of samples were made in the automated cell with the addition of one component epoxy adhesive around the perimeter of the weld. These samples showed improved process repeatability compared with the samples made without adhesive. This indicates that small amounts of adhesive may be critical in using the process in industrial settings. Additionally, work was performed with manual positioning and adhesive dispensing. This work found that a hybrid joint behaves like traditional weld bonding, where the addition of adhesive makes the joint stronger than if either of the two joining methods were used on their own. To realize this performance with vaporizing foil actuator welding, though, the adhesive needs to be protected from burning during the rapid compression of air during the impact process.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Sensitivity-informed, Process Model Abstraction Implementation in GoldSim - 19276

System-level Performance Assessment (PA) models rely on specific process-level models for some inputs, such as infiltration. For probabilistic PA, the value of the process model output depends on the values of input parameters that also vary in the PA model. The simplest conceptual solution is to draw values of the input parameters from their distributions, run the process level model at these values, and then use the output where it is needed in the PA model. However, this solution is unsatisfactory for multiple reasons: (1) the PA Model should be set up such that new runs can be made and distributions can change without having to go back and run the process-level model; (2) calling the process model from the system model is possible, but technical difficulties remain in coupling the two; and (3) there is no uncertainty in the process-level model results incorporated into the PA model. Therefore, it is desirable to develop a method that maps the values of PA Model inputs to process level model outputs, in real time within the PA Model set up and using as simple of a map as possible without losing key features of the relationship. This has been termed 'model abstraction' because information about process model runs is 'abstracted' to be used with the PA model. A simple 'nearest neighbor' abstraction approach is presented to overcome these problems, in which a sensitivity-informed distance metric is used to map a system-level model realization to the most appropriate process-level model realization. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Comparison of Silicon Decarbonization Methods to Reduce Process Emissions and Energy Consumption

The demand for silicon is rising due to its use in solar cells, electronics, and alloying as part of the green transition. However, these products require silicon metal (metallurgical grade silicon, >98% Si) as their main raw material before undergoing further chemical refining, usually via gas phase in methods such as the Siemens process. Silicon metal is currently produced in a submerged arc furnace via carbothermic reduction of quartz, which results in 10-12 tCO2/tSi. More than 40% of these emissions are process emissions, meaning they do not include contributions from electricity generation or transport. This talk will discuss promising methods to reduce or eliminate these process emissions. These include the use of biocarbon and carbon capture, aluminothermic reduction, electrochemical reduction with molten salts, and use of hydrogen in a modified Siemens process. Biocarbon and carbon capture is a straightforward method to reduce the net carbon emissions of the process, but long-term sustainable production of high-quality charcoal is a challenge. Aluminothermic reduction makes good use of aluminum byproducts such as dross but is perhaps limited in its applications to aluminum-silicon alloy products. Electrochemical reduction is promising as a method of producing high purity Si from quartz, without further need for the Siemens process, but is still in early stages of research and slow processing times are a concern. Finally, the use of hydrogen in a modified Siemens process would also result in a high purity Si product from quartz, however the process has considerable logistical challenges with corrosive and unstable gases at high temperatures. This talk will further expand on the potential merits and challenges of each method, while comparing their potential to reduce emissions and/or energy consumption while meeting global demand.

decarbonization↗
DOE OSTI2025

A fast computational framework for the design of solvent-based plastic recycling processes

Multicomponent plastics cannot be processed using mechanical recycling technologies, hindering efforts to deal with plastic waste. Multicomponent plastics include multilayer plastic films, which are widely used for food and healthcare packaging. Multilayer films combine several layers (potentially dozens) of different polymers to protect products from external factors (e.g., oxygen, water, temperature, shock, and light). Solvent-based separation processes have emerged as a promising alternative to recycle these complex materials. For instance, the Solvent-Targeted Recovery and Precipitation (STRAP TM ) process uses sequential solvent washes to selectively dissolve and separate constituent polymers from multicomponent plastic waste, including films. STRAP TM process design (separation sequence, type of solvents, and operating conditions) changes significantly depending on the design of the multilayer plastic film (e.g., number, types, and proportions of polymers). The ability to quickly quantify the economic and environmental benefits of diverse STRAP TM process designs is essential to accelerate the development of sustainable recycling processes and more recyclable multilayer film products. In this work, we present a fast computational framework that integrates molecular-scale models, process modeling, and techno-economic and life cycle analysis to quickly evaluate STRAP TM designs. The computational framework is general and can be used to study the processing of complex multilayer plastic waste streams that contain many layers. Furthermore, we highlight the different uses of the framework via targeted case studies.

Computational framework↗
DOE OSTI2019

Fatigue of additive manufactured Ti-6Al-4V, Part I: The effects of powder feedstock, manufacturing, and post-process conditions on the resulting microstructure and defects

Additive manufacturing provides an appealing means to process titanium alloy parts with new levels of conformability, complexity, and weight reduction. However, due to the heating/cooling rates and heat transfer associated with directed energy source material processing, the as-built AM parts contain unique material and microstructural features. In order to confidently manufacture fatigue critical additive manufactured (AM) Ti-6Al-4V parts, a better understanding of the interrelationships between powder feedstock, AM processes, structure of the processed parts, their resulting mechanical properties, and their performance under realistic loadings is necessary. Part I of this two-part collection focuses on the powder-process-structure relationships and how powder feedstock, manufacturing, and post-processing conditions can affect the microstructure and defect features that ultimately contribute to the fatigue performance of Ti-6Al-4V parts. The material and physical phenomena inherent to the AM process of Ti-6Al-4V are discussed in detail and related to the phase composition/structure, grain morphology, surface characteristics, defect size/distribution, and post-process treatments available for AM parts. This investigation is the foundation for the structure-performance relationships that will be covered in detail in Part II.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A high-throughput approach for statistical process optimization in Laser Powder Bed Fusion

Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.

Laser Powder Bed Fusion↗
DOE OSTI2021

EGS Collab Experiment 1: Circulation Testing Processed data

This submission includes processed and reduced data for circulation testing that was conducted at the 164' fracture on the 4850 ft level of the Sanford Underground Research Facility. The circulation tests were done to test the flow through the 164' fracture in the EGS Collab Experiment 1 testbed on the 4850 ft level of the Sanford Underground Research Facility in order to validate computer models concerned with flow processes and heat exchange processes in EGS. This data was processed from raw data that is available in the GDR submission linked below: "EGS Collab Circulation Testing Raw Data and Documentation." Python scripts used to process and reduce the data are included. The scripts also serve as "documentation" as well as examples for data processing. More information about the test itself as well as the rationale and process of data processing is available at wiki page linked below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Process Control Plan to Monitor Acceptable Levels of Flux and other residues

IPC J-STD –001G, Amendment 1 requires that the assembler have a sampling plan to assure that the process remains in control once qualified and validated. It is well documented that electrochemical failures occur at component sites where flux residues are not fully activated. It is also well known that specific components have a higher risk of electrochemical failure. Selecting a control plan that monitors the process and its performance on challenging components provides assurance that the process maintains control once established during process qualification. The test board used to qualify the process establishes an upper and lower spec limit for each of the component types on the test board. Surface Insulation Resistance upper and lower control limits, using challenging components that are representative of production hardware, represent a golden process condition. The golden image is a measure of process deviations that represents the performance of a resistance curve within a specific period. The objective is to judge whether the process in or out of control.

42 ENGINEERING↗
DOE OSTI2023

Reinforcement learning for real-time process control in high-temperature superconductor manufacturing

With high efficiency and low energy loss, high-temperature superconductors (HTS) have demonstrated their profound applications in various fields, such as medical imaging, transportation, accelerators, microwave devices, and power systems. The high-field applications of HTS tapes have raised the demand for producing cost-effective tapes with long lengths in superconductor manufacturing. However, achieving the uniform and enhanced performance of a long HTS tape is challenging due to the unstable growth conditions in the manufacturing process. Although it is confirmed that the process parameters during the advanced metal organic chemical vapor deposition (A-MOCVD) process influence the uniformity of the produced HTS tapes, the high-dimensional process parameter signals and their complicated interactions make it difficult to develop an effective control policy. In this paper, we propose a local measure for the uniformity of HTS tapes to provide instant feedback for our control policy. Then, we model the manufacturing of HTS tapes as a Markov decision process (MDP) with continuous state and action spaces to assess the instant reward in real time in our feedback control model. As our MDP involves continuous and high-dimensional state and action spaces, a neural fitted Q-iteration (NFQ) algorithm is adopted to solve the MDP with artificial neural network (ANN) function approximation. The collinearity of process parameters can restrict our capability of adjusting the process parameters, which is addressed by the principal component analysis (PCA) in our method. The control policy adjusts the PCA of process parameters using the NFQ algorithm. In conclusion, based on our case studies on real A-MOCVD dataset, the obtained control policy increases the average uniformity of tapes by 5.6% and performs especially well on sample HTS tapes with a low uniformity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Predictive process mapping for laser powder bed fusion: A review of existing analytical solutions

One of the main challenges in the laser powder bed fusion (LPBF) process is making dense and defect-free components. These porosity defects are dependent upon the melt pool geometry and the processing conditions. Power-velocity (PV) processing maps can aid in visualizing the effects of LPBF processing variables and mapping different defect regimes such as lack-of-fusion, under-melting, balling, and keyholing. This work presents an assessment of existing analytical equations and models that provide an estimate of the melt pool geometry as a function of material properties. The melt pool equations are then combined with defect criteria to provide a quick approximation of the PV processing maps for a variety of materials. Finally, the predictions of these processing maps are compared with experimental data from the literature. Here, the predictive processing maps can be computed quickly and can be coupled with dimensionless numbers and high-throughput (HT) experiments for validation. The present work provides a boundary framework for designing the optimal processing parameters for new metals and alloys based on existing analytical solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A manufacturing process design for producing a membrane-based energy recovery ventilator with high aspect ratio support ribs

Heating, ventilation, and air conditioning systems represent nearly half of building energy usage in the United States. Recent building regulations requiring increased air turnover within buildings will result in even greater air conditioning usage. To alleviate these concerns, membrane-based heat-and-moisture exchangers known as energy recovery ventilators have been developed to reduce the energy expenditure of air conditioning systems by pre-conditioning incoming air through sensible and latent heat transfer with building air exhaust. Here in this work, we propose and validate a manufacturing process design for channel lamination based on surface mount adhesives capable of meeting the process requirements of a membrane-based ventilator. In particular, the device requires rib supports with height-to-width aspect ratios greater than one. The proposed manufacturing process design is capable of meeting this process requirement by stretching the adhesive after initial adhesive tacking. A manufacturing process flow diagram, a machine tool specification and a cost model are proposed for meeting process requirements. A set of design constraints are developed detailing the adhesive requirements necessary for meeting requirements. The cost model is validated by building a sub-scale mesochannel array demonstrating the ability to meet process requirements. Results show that additional work is needed to validate the curing step but that the process is capable of producing a mesochannel array with an acceptable level of variation.

42 ENGINEERING↗
DOE OSTI2020

Database development and exploration of process–microstructure relationships using variational autoencoders

The paper demonstrates graphical representation of a large database containing process–microstructure relationships using an unsupervised machine learning algorithm. Correlating microstructural features to processing is an essential first step to answer the difficult problem of process sequence design. Here, a large database of 346,200 orientation distribution functions resulting from a variety of process sequences is constructed, where each sequence comprises up to four stages of tension, compression and rolling along different directions in various permutations. This open-source database is constructed for collaborative development of process design algorithms. The paper demonstrates a novel application of the large database: graphical representation of texture–process relationships. A variational autoencoder is used to reduce the entire database to a two dimensional latent space where variations in processes and properties can be visualized. Using proximity analysis in this latent space, we can quickly unearth multiple process solutions to the problem of texture or property design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Closed-loop pressure retarded osmosis draw solutions and their regeneration processes: A review

Pressure-Retarded Osmosis (PRO) is an osmotic process that has been used to harvest energy from salinity gradients using a semi permeable membrane. A comparison between open-loop PRO (OLPRO) and closed-loop PRO (CLPRO) was made regarding their performance and costs. In CLPRO, where the diluted draw solution is re-concentrated in the regeneration system to be reutilized in the process, has recently received an intensive focus as the most viable configuration for a standalone power plant. The choice of the PRO draw solution in CLPRO is crucial to garner a high osmotic pressure as the key for the feasibility of the process. Here, in this review, the draw solutions are critically evaluated in the literature in terms of energy output as well as the method of regeneration used to recirculate them. A set of practical criteria has been suggested to appraise the adequacy of the solution for CLPRO application. It was concluded that NH 3 – CO 2 theoretically can produce 170 W/m 2 of power density. Inorganic draw solutes such as NaCl can generate high power density up to 87 W/m 2 . Organic draw solutes with their remarkably low reverse salt flux (RSF) have promising potential for future application in PRO. Similarly, the regeneration systems of the diluted draw solutions have also been reviewed and discussed. How the energy consumption of the regeneration process affects the feasibility of CLPRO is explained. For the specific case of osmotic heat engines (OHEs), when the energy of the regeneration process is supplied by heat waste, the range of applicability of the heat waste in CLPRO in terms of efficiency is defined and compared to Organic Rankine Cycle (ORC). The results showed that CLPRO has better efficiency than ORC for temperatures T < 80 °C, which makes it a promising process or low-grade heat energy recovery. In addition, a PRO-RO hybrid system coupled with solar power can reduce the net specific energy consumption (SEC) to 0.39 kWh/m 3 . The conditions that regeneration processes should operate under to make PRO viable are discussed in the last section. Overall, the study indicates the key factors for optimizing the performance of CLPRO process.

42 ENGINEERING↗
DOE OSTI2018

Solution-Processed Layered Gallium Telluride Thin-Film Photodetectors

Using scalable solution processing, layered gallium telluride (GaTe) nanoflake dispersions are produced in surfactant-free, low-boiling-point, water–ethanol cosolvent mixtures. During exfoliation, chemical degradation of the ambient-reactive GaTe crystals is minimized by using deoxygenated solvents in a sealed tip ultrasonication system. The structural and chemical integrity of the solution-processed GaTe nanoflakes is subsequently confirmed with a comprehensive suite of microscopic and spectroscopic analyses. Furthermore, field-effect transistors and phototransistors based on individual solution-processed GaTe nanoflakes show electronic and optoelectronic properties, respectively, that are comparable to micromechanically exfoliated GaTe. Minimal solution-processing residues from the surfactant-free, low-boiling-point cosolvent dispersion medium coupled with the high intrinsic hole doping of GaTe produces the highest electrical conductivity among solution-processed layered nanoflake thin films without post-treatment. Large-area photodetectors based on these electrically percolating thin films of solution-processed GaTe nanoflakes show a positive correlation between responsivity and illumination intensity, with a high photoconversion gain that is explained by a combination of defect-mediated optical processes and photothermal effects. Finally, overall, this study establishes solution-processed layered GaTe nanoflakes as a leading candidate for high-performance, large-area, thin-film photodetectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Frog: Asynchronous Graph Processing on GPU with Hybrid Coloring Model

GPUs have been increasingly used to accelerate graph processing for complicated computational problems regarding graph theory. Many parallel graph algorithms adopt the asynchronous computing model to accelerate the iterative convergence. Unfortunately, the consistent asynchronous computing requires locking or atomic operations, leading to significant penalties/overheads when implemented on GPUs. As such, coloring algorithm is adopted to separate the vertices with potential updating conflicts, guaranteeing the consistency/correctness of the parallel processing. Common coloring algorithms, however, may suffer from low parallelism because of a large number of colors generally required for processing a large-scale graph with billions of vertices. We propose a light-weight asynchronous processing framework called Frog with a preprocessing/hybrid coloring model. The fundamental idea is based on Pareto principle (or 80-20 rule) about coloring algorithms as we observed through masses of realworld graph coloring cases. We find that a majority of vertices (about 80%) are colored with only a few colors, such that they can be read and updated in a very high degree of parallelism without violating the sequential consistency. Accordingly, our solution separates the processing of the vertices based on the distribution of colors. In this work, we mainly answer three questions: (1) how to partition the vertices in a sparse graph with maximized parallelism, (2) how to process large-scale graphs that cannot fit into GPU memory, and (3) how to reduce the overhead of data transfers on PCIe while processing each partition. Here, we conduct experiments on real-world data (Amazon, DBLP, YouTube, RoadNet-CA, WikiTalk and Twitter) to evaluate our approach and make comparisons with well-known non-preprocessed (such as Totem, Medusa, MapGraph and Gunrock) and preprocessed (Cusha) approaches, by testing four classical algorithms (BFS, PageRank, SSSP and CC). On all the tested applications and datasets, Frog is able to significantly outperform existing GPU-based graph processing systems except Gunrock and MapGraph. MapGraph gets better performance than Frog when running BFS on RoadNet-CA. The comparison between Gunrock and Frog is inconclusive. Frog can outperform Gunrock more than 1.04X when running PageRank and SSSP, while the advantage of Frog is not obvious when running BFS and CC on some datasets especially for RoadNet-CA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Selection of glasses in support of the Sludge Batch 9 variability study for coupled operation with the Salt Waste Processing Facility

Prior to the processing of Sludge Batch 9 (SB9) with Frit 803 at the Defense Waste Processing Facility (DWPF), assessments and experimental glass work were completed to support the qualification of SB9 coupled processing with streams from the Actinide Removal Process (ARP) and Modular Caustic Side Solvent Extraction Unit (MCU). This previous work did not address coupled processing with streams from the Salt Waste Processing Facility (SWPF) because the Product Composition Control System (PCCS) models limited the TiO 2 concentration in glass to 2 weight percent (wt.%). These high activity streams from SWPF include monosodium titanate (MST) and sludge solids from the Sludge Solids Receipt Tank as well as Cs-containing strip effluent. The incorporation of these SWPF streams is expected to reach TiO2 concentrations in glass greater than 2 wt.% based on an MST addition of 0.4 g MST/L of salt solution. If double strike operation is required, then the MST addition is increased to 0.8 g MST/L of salt solution. Therefore, revisions to the models contained in PCCS were completed to allow the evaluation of glasses containing greater than 2 wt.% TiO 2 , but less than 6 wt.%. To support the implementation of the revised PCCS for SB9 – Frit 803 processing at DWPF prior to SWPF startup, the applicability of the new durability models for the SB9 variability study glasses was verified. Since the initial SB9 qualification for ARP-MCU coupled operation, additional Tank 40 analyses have been completed, which served as the basis for an updated projection of the SB9 blend composition in Tank 40. To identify a frit optimized for SB9 coupled operation with SWPF, the Savannah River National Laboratory (SRNL) performed a paper-study by utilizing Measurement Acceptance Region (MAR) assessments with DWPF PCCS. Based on these MAR assessment results, Frit 625 was recommended for processing both single and double MST strike scenarios. Savannah River Remediation (SRR) requested that SRNL perform a variability study with both Frit 803 and Frit 625 for SB9 coupled operation with SWPF. The objective of the variability study is to demonstrate that the Product Consistency Test (PCT) responses of the glasses are acceptable relative to the chemical durability of the Environmental Assessment (EA) reference glass and predictable by the current DWPF PCCS models for durability. This report documents the development of a test matrix that will support the variability study. To provide operational flexibility prior to SWPF startup, the predictability of glasses within the glass region for Frit 625-SB9 coupled operation with ARP-MCU was also confirmed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗