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At least 289 records · Page 16

Results of the Short-Term Analyses of the Salt (Macro) Batch 5 Tank 41H Qualification Sample (Resample)

Savannah River National Laboratory (SRNL) analyzed samples from Tank 41H in November 2021 in support of qualification of Salt Waste Processing Facility (SWPF) Salt Batch 5. This document reports the short-term results of the analyses of samples of Tank 41H. Analysis of the Tank 41H Salt Batch 5 sample indicates that the material does not display any unusual characteristics or observations, such as floating solids, the presence of large amounts of solids, or unusual colors. Further sample results will be reported in a future document. This report satisfies part of Deliverable 3 of the Technical Task Request (TTR). After a data review it was found that the original results reported in the revision 0 of this document were actually from Salt Batch 4 (Tank 21H). A new set of samples was sent for analysis to satisfy deliverable 3 of the TTR. The results from the original analyses have been replaced with the recent analyses of the actual Salt Batch 5 sample.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Solid state NMR Investigation of Structural Differences in Pelletized DEB Samples

Upon hydrogenation of DEB pellets, which are composed of 75% virgin DEB and 25% of nanometer scale Pd catalysts on activated carbon, the uptake rate is strong, and the hydrogenation process is fast. However, the last batch of DEB pellets from KCNSC uptakes 10 times slower than traditional DEB pellets after ~ 50% consumption. In addition, the last batch of DEB getter pellets also became partially molten/wet during the hydrogenation process. This molten/wet phase during hydrogenation has only been observed with DPB and never with DEB formulation. DRIFT (diffuse reflection infrared Fourier transform) and XRD (x-ray diffraction) confirm that the questionable batch of DEB pellets from KCNSC are truly 100% DEB and not a mixture of DEB and DPB. So, there must be something different in the composition (like concentration and distribution of Pd) or interaction between the DEB molecules with the surrounding environment (activated carbon spreading medium). The possibility of some chemical contamination in the processing of this batch of questionable DEB getter pellets also comes to mind. Due to the ability of NMR to detect intermolecular interaction and sensitivity to small chemical concentration, NMR investigation was requested for this questionable batch of DEB getter pellets from KCNSC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated Basin De-Inventory Maximum Fissile Estimate

The Accelerated Basin De-inventory (ABD) program increases processing of Spent Nuclear Fuel (SNF) in H-Canyon to accelerate the closure of L Basin. The dissolved SNF will be dispositioned to Sludge Batches that will be processing in the Defense Waste Processing Facility and converted to glass. The fissile glass loading directly impacts the amount of glass canisters made. This memorandum provides an estimated maximum quantity of total fissile expected to be transferred to a Sludge Batch to support increasing the fissile glass loading and thus reducing the number of canisters created across the lifetime of the ABD mission.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Analytical Results from Salt Batch 10 Routine DSSHT and SEHT Monthly Samples

Strip Effluent (SE) Hold Tank (SEHT) and Decontaminated Salt Solution (DSS) Hold Tank (DSSHT) samples from several “microbatches” of the Integrated Salt Disposition Project (ISDP) “macrobatch” Salt Batch 10 have been analyzed for 238 Pu, 90 Sr, 137 Cs, cations (via Inductively Coupled Plasma Emission Spectroscopy - ICPES), and in some cases anions (via Ion Chromatography Anions - IC-A). The analytical results from the current microbatch samples are similar to those from previous macrobatches. In the Modular Caustic-Side Solvent Extraction Unit (MCU), the Cs removal continues to exceed process requirements. The bulk chemistry of the DSSHT and SEHT samples do not show any signs of unusual behavior except for slightly elevated amounts of sodium in the SE samples. This summary represents the final Salt Batch processed through MCU prior to commencement of process and transfer line tie-ins to support the startup of the Salt Waste Processing Facility (SWPF).

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Technology Development and Integration for Volume Production of High Purity Rare Earth Metals from Phosphate Processing

Under this project and in collaboration with Pacific Northwest National Laboratory (PNNL), Oak Ridge National Laboratory (ORNL), Florida International University (FIU), and Mosaic, the FIPR Institute successfully developed and demonstrated on laboratory batch scale a complete processing technology for production of high-purity rare earth elements (REE) in the form of mixed rare earth oxides (MREO) and rare earth metals (REM) using phosphoric acid sludge (a byproduct from phosphate mining) as the REE feedstock. Based on the research results, a technical research plan has been developed with expanded team members to elevate the technology readiness level (TRL) of the subject technology from 4 to 6 by conducting continuous testing of the processing flowsheet with the ultimate goal of producing about 900 tons per year of REM using the phosphate mining byproduct. Those 900 tons of REM would contain approximately 180 tons of Y, 120 tons of Nd, 50 tons of Gd, 37 tons of Dy, 33 tons of Sm, and 31 tons of Pr, meeting the US demand of roughly 39%, 6%, 42%, 48%, 101% and 7% for these elements, respectively. The advanced technologies for REE separation and purification involves three technology companies: K-Technologies, Inc. would test their continuous-ion-exchange/continuous-ion chromatography technologies on both the REE leachate and solvent extraction concentrate for 4 production of high-purity individual or binary REM. Rare Earth Salts would test their innovative electrochemical technology on the REE leachate or re-dissolved MREO in dilute acid for production of high-purity individual or binary REM. Rare Earth Technologies, Inc. would evaluate their advanced chromatographic separation technology on the dissolved MREO product for production of high-purity individual or binary REM.

36 MATERIALS SCIENCE↗

Summary of Expedited Results from Samples Supporting Tank Closure Cesium Removal (TCCR) Batch 3

Savannah River Remediation (SRR) is currently operating the Tank Closure Cesium Removal (TCCR) process to remove 137 Cs from tank waste supernate using an ion exchange process. As part of that process, Savannah River National Laboratory (SRNL) receives and analyzes samples in support of the qualification of each batch to be processed. SRNL recently received supernate samples retrieved from Tank 10H as well as in-tank batch contact samples for characterization in support of qualifying Batch 3 for processing through the TCCR unit. SRNL received and characterized a set of dip samples collected from Tank 10H (one surface and one variable depth sample). No solids were observed in either sample and therefore the samples were combined, and a suite of analyses were performed on the composite sample. The density of the combined sample was 1.174 g/mL (0.18 %RSD), which was consistent with the measured sodium concentration of 3.54 M (0.08 %RSD). The 137Cs activity in the sample was 4.75E+07 dpm/mL (4.28 %RSD) and the total Cs concentration was calculated to be 1.54 mg/L (1.16E-05 M). The in-tank batch contact samples consist of 0.1 g of crystalline silicotitanate (CST) contained within a teabag device. Duplicate samples were submerged in Tank 10H supernate for a period of about 13 days, after which time they were retrieved and transferred to SRNL for analysis. At SRNL the CST was rinsed to remove excess salt solution and the CST was then air dried before being digested for analysis. Results of the analysis indicated a 137 Cs loading of 3.66E+10 ± 1.40E+09 dpm/g or 16.5 ± 0.63 Ci/kg CST . This value represents a bounding upper limit as it includes the addition of two sigma uncertainty from replicate analysis of the individual teabag samples as well as the addition of the small amount of 137 Cs activity measured in the rinse solutions. The above values are based on the air-dried mass of CST. Correcting to the true dry mass using a F-factor of 0.8191 results in a maximum loading of 20.2 ± 0.77 Ci/kg CST .

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Influence of porous aluminosilicate grain size materials in experimental and modelling Cs + adsorption kinetics and wastewater column process

This paper focuses on the influence of the grain size of a geopolymer based adsorbent on its Cs + adsorption performances both in batch and fixed-bed process. The geopolymer phase was used as a binder to support NaY zeolite particle in a 20 wt% charged porous composite with 160 m 2 .g –1 of porous surface area. These samples were shaped with three grain sizes (50 /100/500 µm) to remove 80–90 mg/g of Cs + in batch and column operations. After their microstructural and porous characterizations, their efficiency and adsorption characteristics were investigated through adsorption isotherms and kinetic in the two processes. While the grain size has no influence on the maximal extraction capacity of the adsorbent, it strongly affects the sorption kinetic. By coupling experimental data and a modelling approach, the complex sorption mechanism was highlighted, suggesting a new insight of the contaminant sorption kinetic. Then, comparison of batch and column adsorption experiments illustrates the detailed explanation of various process parameters for column study. The results show challenges for fixed-bed column utilization by the choice of the appropriate grain size as a compromise between the material sorption kinetic and hydrodynamic considerations. Furthermore, this is of high importance to more accurately optimize the design of column adsorption to assess the transport of Cs+ in multi-porous tailored grain size materials.

36 MATERIALS SCIENCE↗

High Solids Loading Aqueous Slurry Formation of Corn Stover Before Pretreatment in a Fed-batch Bioreactor

With the increase on population the world will depend on renewable sources to meet the increasingly energy needs. Use of lignocellulosic biomass as a renewable source has been proven efficient for conversion to cellulosic ethanol and capable of contributing to achieve the threshold on energy demand while reducing greenhouse gases in 90% when compared with fossil fuels (Wang et al., 2007, 2012). However, the processing of biomass encounters limitations in feeding and flow within biorefineries due to the system plugging by compaction and slurry high yield stress, preventing transport of biomass materials and in some cases unexpected plant shutdowns that results in high operational costs (dos Santos et al., 2021; Ximenes et al., 2021). Different solutions for biomass handling and slurry formation from densified materials like pellets have been studied. Cellulosic biomass residues are typically processed in pretreatment reactors to which acid or base is added (Humbird et al., 2002). Other pretreatments such as liquid hot water (LHW) and steam explosion that act without the addition of chemicals use pressures above the saturation vapor of water, to disrupt biomass structure (Ruiz et al., 2021). Although these methods are widely known, the use of pretreatments like acid digestion and LHW present challenges like waste disposal and could be energy inefficient (Mosier et al., 2005). Alternatively other approaches like enzymatic liquefaction have been applied for biomass transformation into slurries with promising results and without the use of pretreatments (dos Santos et al., 2021). Nevertheless, enzymatic liquefaction implementation faces difficulties due to the recalcitrant properties of biomass, its variability, and the release of enzyme inhibitors. While it has been proven that chemical composition properties in biomass have effects on enzyme inhibition (Huang et al., 2022; Kim et al., 2011; Zhai et al., 2018), hindering the efficiency of the liquefaction, not ample research has been conducted in understanding the physical properties as particle size, porosity, water adsorption retention and their effect in the ability to form a slurry at high solids concentration (Yan et al., 2020). In order to improve lignocellulosic biomass handling and formation of biomass slurries, enzyme assisted liquefaction for slurry creation from corn stover at solids loadings up to 30% is reported in this work. Two different kinds of biomass (pelleted corn stover and cobs) were liquefied in a fed-batch process using commercial enzymes Celluclast 1.5L or Ctec-2 at 1FPU or 3 FPU per gram of dry solids in 10 mM sodium citrate buffer solution (pH 4.8). Pellets were fed into a 1 L stirred bioreactor according to a predefined fed-batch protocol over the first 5 hours until reaching 30% of solids loading. After 6, 24 and 96 hours, samples were taken and characterized with respect to their sugar composition, rheology and water absorption. Successful slurry creation with dramatically reduced yield stress was achieved for corn stover for both assessed enzymes. Yield stresses of 178±7 Pa (3 FPU, Celluclast 1.5L) and 79±6 Pa (3 FPU, Ctec-2) were measured for corn stover at 24 hours, compared to 6,000 Pa for samples without enzyme. Yield stress was 155± 29 Pa (3FPU, Ctec-2) and 257 ± 72 Pa (1 FPU, Celluclast 1.5L) for corn cobs at 24 hours. Yield stress decreased when residence time increased with an enhanced fluidity noted for higher enzyme concentrations. A profile for 6, 24 and 96h of yield stress measurements is presented.

Gutierrez, Diana↗

Integrated Model, Batch and Domain Parallelism in Training Neural Networks

We propose a new integrated method of exploiting model, batch and domain parallelism for the training of deep neural networks (DNNs) on large distributed-memory computers using minibatch stochastic gradient descent (SGD). Our goal is to find an efficient parallelization strategy for a fixed batch size using $P$ processes. Our method is inspired by the communication-avoiding algorithms in numerical linear algebra. We see $P$ processes as logically divided into a $P_r \times P_c$ grid where the $P_r$ dimension is implicitly responsible for model/domain parallelism and the $P_c$ dimension is implicitly responsible for batch parallelism. In practice, the integrated matrix-based parallel algorithm encapsulates these types of parallelism automatically. We analyze the communication complexity and analytically demonstrate that the lowest communication costs are often achieved neither with pure model nor with pure data parallelism. We also show how the domain parallel approach can help in extending the theoretical scaling limit of the typical batch parallel method.

97 MATHEMATICS AND COMPUTING↗

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBS

The increasing demand for lithium-ion batteries (LIBs ) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCam).During this project ,samples of high-purity recycled NMC hydroxide (~2kg each) were received from Nth Cycle. In the first received batch some impurities like cadmium, calcium, and sodium are present in quantities that would negatively impact battery performance. Nth Cycle indicated that the impurities such as cadmium are present due to poor battery separation and co-shredding of NiCd batteries with with LIB. Cadmium was not present in the two subsequent batches as Nth Cycle processed cadmium free black mass. Thus, effective recycled battery sorting is critical to closed-loop LIB recycling into active electrode materials.

99 GENERAL AND MISCELLANEOUS↗

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBS

The increasing demand for lithium-ion batteries (LIBs) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCam). During this project , samples of high-purity recycled NMC hydroxide (~2 kg each) were received from Nth Cycle. In the first received batch some impurities like cadmium, calcium, and sodium are present in quantities that would negatively impact battery performance. Nth Cycle indicated that the impurities such as cadmium are present due to poor battery separation and co-shredding of NiCd batteries with with LIB. Cadmium was not present in the two subsequent batches as Nth Cycle processed cadmium free black mass. Thus, effective recycled battery sorting is critical to closed-loop LIB recycling into active electrode materials.

25 ENERGY STORAGE↗

MDLoader: A Hybrid Model-Driven Data Loader for Distributed Graph Neural Network Training

Scalable data management is essential for processing large scientific dataset on HPC platforms for distributed deep learning. In-memory distributed storage is preferred for its speed, enabling rapid, random, and frequent data access required by stochastic optimizers. Processes use one-sided or collective communication to fetch remote data, with optimal performance depending on (i) dataset characteristics, (ii) training scale, and (iii) interconnection network. Empirical analysis shows collective communication excels with larger mini-batch sizes and/or fewer processes, whereas one-sided communication outperforms at larger scales. We propose MDLoader, a hybrid in-memory data loader for distributed graph neural network training. MDLoader features a model-driven performance estimator that dynamically selects between one-sided and collective communication at the beginning of training using Tree of Parzen Estimators (TPE). Evaluations on NERSC Perlmutter and OLCF Summit show MDLoader outperforms single-backend loaders by up to 2.83 × and predicts the suitable communication method with 96.3% (Perlmutter) and 94.3% (Summit) success rate.

Bae, Jonghyun↗

Sample Results From The Extraction, Scrub, And Strip Test For The Blended NGS Solvent

This report summarizes the results of the extraction, scrub, and strip testing for the September 2013 sampling of the Next Generation Solvent (NGS) Blended solvent from the Modular Caustic Side-Solvent Extraction Unit (MCU) Solvent Hold Tank. MCU is in the process of transitioning from the BOBCalixC6 solvent to the NGS Blend solvent. As part of that transition, MCU has intentionally created a blended solvent to be processed using the Salt Batch program. This sample represents the first sample received from that blended solvent. There were two ESS tests performed where NGS blended solvent performance was assessed using either the Tank 21 material utilized in the Salt Batch 7 analyses or a simulant waste material used in the V-5/V-10 contactor testing. This report tabulates the temperature corrected cesium distribution, or D Cs values, step recovery percentage, and actual temperatures recorded during the experiment. This report also identifies the sample receipt date, preparation method, and analysis performed in the accumulation of the listed values. The calculated extraction D Cs values using the Tank 21H material and simulant are 59.4 and 53.8, respectively. The DCs values for two scrub and three strip processes for the Tank 21 material are 4.58, 2.91, 0.00184, 0.0252, and 0.00575, respectively. The D-values for two scrub and three strip processes for the simulant are 3.47, 2.18, 0.00468, 0.00057, and 0.00572, respectively. These values are similar to previous measurements of Salt Batch 7 feed with lab-prepared blended solvent. These numbers are considered compatible to allow simulant testing to be completed in place of actual waste due to the limited availability of feed material.

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Pseudo-dynamic Aspen Plus{sup R} Model of the Defense Waste Processing Facility - 18475

The Defense Waste Processing Facility (DWPF) at the Savannah River Site converts legacy high-level waste from the Cold War into borosilicate glass for permanent disposal in a geological repository. The waste sludge is chemically adjusted by the addition of acid, mixed with frit, and concentrated in the DWPF Chemical Process Cell (CPC) to ensure that the final glass has the desired properties. The resulting mixture is fed into the melter where the waste is melted and poured into stainless steel storage canisters. We present an Aspen Plus{sup R} model of the DWPF CPC, which is being developed to aid chemical processing decisions pertaining to the current flowsheet and to aid decisions regarding optimizing future processing. Given a waste feed composition with acid and frit additions, the model will predict the sludge and off-gas compositions throughout the processing, as well as the final melter feed composition. This allows different processing scenarios to be investigated easily, reducing the reliance on experimental testing, and hence saving time and money. The model has multiple potential applications, including calculating the acid and frit additions required to give acceptable glass properties, off-gas permitting, tracking mercury steam-stripped from the waste in the off-gas system, tracking flammable gases in the offgas system, investigating the effect of reducing air purges in the condensers, and general process optimization. The waste is processed in the CPC in batches, requiring dynamic simulation to track the time-dependent operations. Accurate modeling of the processing also requires calculations of phase and electrolyte chemical equilibria and parallel rate-dependent reactions. Due to existing technical limitations with dynamic simulation of the complex chemical system, we have adopted a pseudo-dynamic approach in which time intervals are treated as consecutive steady-state operations in Aspen Plus{sup R}. Thus, the model consists of ∼100 replicas of the processing vessel and its off-gas system, with the sludge output by one replica (representing one time interval) becoming the feed to the next (representing the next time interval). By examining the results from these replicas in sequence, one can see the time evolution of the model. This general approach can be used wherever simultaneous calculation of phase and electrolyte chemical equilibria in a dynamically evolving system is needed. In addition to describing the general structure and chemistry of the model, we present results from tests of the model against experimental data. These data are from laboratory-scale process simulations of the CPC with a nonradioactive waste sludge simulant. These tests include the model's predictions of the offgas composition, the sludge pH, and the final sludge composition. We will also discuss planned future developments of the model. (authors)

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Commissioning of a GeoMelt Vitrification Plant at the Central Laboratory on the Sellafield Site - 17561

The National Nuclear Laboratory (NNL) and Kurion Veolia (Kurion) have installed a GeoMelt{sup R} In-Container Vitrification (ICV){sup R} radioactive waste treatment system in the Central Laboratory Active Rig Hall at Sellafield. This installation was completed in 2016. GeoMelt incorporates a range of patented and proprietary vitrification processing technologies that are configured in a variety of ways depending on the project and the waste. GeoMelt transforms hazardous chemical and radioactive wastes into an inert vitreous monolith. Hazardous organics are destroyed by pyrolysis and heavy metals and radionuclides are immobilized within the glass matrix where they are not preferentially leached into the environment. GeoMelt IVC produces a durable wasteform for a large variety of input wastes. The batch nature of the process which involves single-use refractory offers a wide range of process benefits over traditional vitrification technologies including: - a wide range of waste chemistries allowing high waste loadings; - compatibility with heterogeneous wastes including wastes with high metal content; - a technological simple solution without stirrers, bubblers, etc.; - No refractory corrosion concerns or melter drain failure scenarios; - Flexibility in glass chemistry and melter/disposal container configuration allows the wasteform to be specifically tailored to the storage or disposal site requirements. As part of the 2016 system commissioning at NNL's Central Laboratory, three demonstration melts were performed, one funded by Sellafield Ltd. and two by the Nuclear Decommissioning Authority (NDA). The first melt processed inactive soil with an inactive caesium tracer. The second melt processed inactive soil with a Cs-137 tracer. The third melt processed active waste soil from a variety of NDA nuclear licensed sites. The work conducted during commissioning was multi-purpose; it successfully demonstrated the benefits that the GeoMelt technology could bring to the UK NDA estate while performing equipment testing/troubleshooting and operator training. A significant benefit of the GeoMelt ICV technology is volume reduction for wastes which would otherwise experience a volume increase if encapsulated. Another benefit is the ability to treat difficult radioactive waste streams not amenable to encapsulation (e.g., reactive and/or organic wastes) with a very low energy consumption. The purpose of the first commissioning melt, Plant Performance Demonstration (PPD)-1, was to operate the GeoMelt system under typical conditions and to perform a post-melt mass balance of the caesium as a surrogate for Cs-137 in order to access retention of caesium in the final glass product. The melt processed a mixture of inactive soil obtained near the Sellafield site (as analogue for contaminated Sellafield soil), additives, and glass frit. An inactive caesium tracer was added to this melt as Cs{sub 2}CO{sub 3}. The purpose of the second commissioning melt, PPD-2, was to operate the GeoMelt system under typical conditions and to perform a post-melt activity balance using a Cs-137 tracer in order to assess retention of Cs-137 in the final glass product. Materials processed were inactive soil, glass frit, additives, and a radioactive caesium tracer (CsCl). The purpose of the third melt, Experiment-1 (EX-1) was to treat active waste and inactive waste simulant, as a demonstration of simultaneous processing of multiple waste streams. EX-1 consisted of processing active soil, Magnox sludge simulant, inactive soil, additives, and frit. The active soil used for this melt was obtained from the Hunterston A, Bradwell, Capenhurst, and Sellafield nuclear licensed sites. Since most soils are high in silica, the concept for this experiment was to use the active soils to provide glass formers while co-processing Magnox sludge simulant which does not contain glass formers. Beyond demonstration of capability areas of focus of this series of demonstrations included processing efficiency (kWh/kg treated) and caesium retention (%). This paper summarizes operations and results of the three melts. (authors)

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Characterization of Tank 9H Dissolution Batches in Support of Tank Closure Cesium Removal (TCCR) 1A Batch 1 Preparations

Savannah River Remediation (SRR) is currently preparing the first batch of material to be processed through the Tank Closure Cesium Removal (TCCR) 1A system. The feed for TCCR 1A will consist of dissolved saltcake from Tank 9H. Two batches of salt (Batch 1A and Batch 1B) have been dissolved in Tank 9H and subsequently transferred to Tank 10H to prepare Batch 1 for TCCR 1A. Savannah River National Laboratory (SRNL) received samples from each batch of dissolved salt prior to transfer for characterization. SRNL received both a surface and a variable depth sample from Batches 1A and 1B. In both cases no solids were observed in the surface sample, but were observed in the depth sample. For Batch 1A the variable depth sample was only slightly cloudy, while for Batch 1B the variable depth sample contained a significant amount (10.14 wt%) of solids. The solids were determined to be primarily aluminum containing phases, with only a small fraction (0.22 wt%) being sludge solids. In general, the samples from Batch 1A were more concentrated salt solutions than Batch 1B, with sodium concentrations of 8.53 and 8.57 M for the surface and filtered depth samples in Batch 1A, respectively. The sodium concentrations in Batch 1B samples ranged from 4.27 M for the surface sample to 7.57 M for the depth sample filtrate, indicating some stratification within the tank. The 137 Cs activity as well as the total Cs concentration in the filtered Batch 1A depth sample were approximately double the activity and concentration measured in the filtrate from the Batch 1B depth sample. The total Cs concentration in the Batch 1A depth sample filtrate was 22.4 mg/L, while for the Batch 1B depth sample filtrate the total Cs concentration was calculated to be 12.0 mg/L. These Cs concentrations are significantly higher than was measured in Batches 1-3 from Tank 10H dissolved saltcake which was previously processed through the original TCCR unit.

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Impact of axial velocity and transmembrane pressure (TMP) on ARP filter performance

The Savannah River Site (SRS) is currently treating radioactive liquid waste with the Actinide Removal Process (ARP) and the Modular Caustic Side Solvent Extraction Unit (MCU). Recently, the low filter flux through the ARP of approximately 5 gallons per minute has limited the rate at which radioactive liquid waste can be treated. Salt Batch 6 had a lower processing rate and required frequent filter cleaning. Savannah River Remediation (SRR) has a desire to understand the causes of the low filter flux and to increase ARP/MCU throughput. One potential method for increasing filter flux is to adjust the axial velocity and transmembrane pressure (TMP). SRR requested SRNL to conduct bench-scale filter tests to evaluate the effects of axial velocity and transmembrane pressure on crossflow filter flux. The objective of the testing was to determine whether increasing the axial velocity at the ARP could produce a significant increase in filter flux. The authors conducted the tests by preparing slurries containing 6.6 M sodium Salt Batch 6 supernate and 2.5 g MST/L, processing the slurry through a bench-scale crossflow filter unit at varying axial velocity and TMP, and measuring filter flux as a function of time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Cesium Ion Exchange Using Crystalline Silicotitanate with 5.6 M Sodium Simulant

The Low-Activity Waste Pretreatment System (LAWPS) facility is planned to pretreat Hanford tank waste supernate by filtering to remove solids and processing through ion exchange columns to remove cesium. The ion exchange media is currently (since 2018) targeted to be crystalline silicotitanate (CST). This material has been produced as an engineered form (generally spherical beads) by Honeywell UOP LLC (Des Plaines, IL). Previous forms of this media have been tested in a wide array of simulants and process scales, but column breakthrough and batch contact testing to date on actual tank waste has been limited to a few tank wastes. Washington River Protection Solutions requested a series of studies to demonstrate Cs load behavior in a small column format and determine if a simple batch contact test with CST can be used to qualify tank waste supernate prior to processing it in the LAWPS. The goal of the batch contact testing is to determine if there are any issues with the tank waste that would preclude Cs removal by the ion exchanger. Testing was conducted with IONSIV TM R9140-B CST provided by Honeywell UOP in 2018 (Batch 2081000057). The CST was received in the sodium (Na) form, so no pretreatment conditioning to convert to the Na form was required. Before use in testing, the CST was passed through a #25 sieve (710-micron openings) and collected on a #60 sieve (250-micron openings) with the intent of removing any large and fine particles. Physical properties were measured on the CST including particle size distribution (d50 = 570 microns) and scanning electron micrographic examination. The CST was rinsed with water until the contact solution was visually nearly clear. The CST bed density (1.00 g/mL) and CST bed void fraction (0.656) were measured on the sieved and rinsed CST. The batch contact testing varied Cs concentration in a 5.6 M Na simple simulant solution. Testing was conducted in a liquid volume to solids mass ratio of 200. The distribution coefficient (K d ) was determined to be 770 mL/g at the Cs equilibrium condition of 8.0 μg/mL; with a bed density of 1.00 g/mL, this corresponds to a predicted 50% Cs breakthrough of 770 bed volumes (BVs). The Cs load capacity at 8.0 μg/mL equilibrium condition was determined to be 6.16 mg Cs/g dry CST. The column testing was prototypic to the intended LAWPS operations in a lead-lag column format, albeit on a small-scale basis with 10-mL CST beds. The feed was processed downflow through the lead column and then through the lag column. Three flowrates were tested: 1.19, 1.99, and 4.56 BV/h. The feed was displaced with 0.1 M NaOH, and then the columns were rinsed with water sequentially through the lead then lag columns. One column system was evaluated top to bottom with a gamma scanner to assess the axial Cs loading. Table ES.1 summarizes the relevant Cs loading characteristics.

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