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On-Line Monitoring and Real-Time Characterization of Low Level Waste and Off-Gas Condensate Samples using Raman Spectroscopy

The demand for Hanford waste property analysis is expected to significantly increase as the U.S. Department of Energy River Protection Project progresses toward transferring waste to the Hanford Waste Treatment and Immobilization Plant. The analysis of waste includes chemical, radionuclide, and physical property characterizations, with the goal of achieving safe/informed transfer and processing. Waste sampling followed by offline laboratory analysis is the current baseline analytical approach. The addition of field-deployed/in situ instruments has the potential to provide improvements and benefits over offline analysis in the areas of 1) Worker Safety: by reducing the need for sampling and thereby reducing the need for worker interaction with waste during sample handling; 2) Operational Efficiency: by reducing analysis turnaround times and offsetting demand on analytical laboratories; and 3) Accuracy: continuous analysis of a flowing waste stream allows cumulative results to be produced for the batch, which is likely to be more representative than discrete samples of batch properties. This paper describes the development and application of an online monitor to provide chemical characterizations; specifically, Raman spectroscopy is utilized to identify and quantify tank components. Accurate quantification is achieved through the use of chemometric analysis, which can be configured to provide real-time analysis in field deployment settings.

Lines, Amanda M.↗

SRNL Report on Vendor Solicitation and Selective Ion-Electrode Testing

Effective operation of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) will require information collected from sampling and/or monitoring to maintain environmental compliance, product quality, and operating efficiency. The U.S. Department of Energy (DOE) – Office of River Protection (ORP) recognizes the potential long-term benefit of developing real-time, in-line monitoring (RTIM) at the WTP to improve the current strategy of collecting tens of thousands of samples and analyzing them. In-line monitoring can decrease processing time associated with waiting for sample analysis, reduce workers’ exposure to radiation and chemical hazards, decrease secondary waste volumes, potentially improve product quality, and provide production support and enhance overall operational control. The Assistant Manager, WTP chartered an Integrated Technical Team (ITT), which includes personnel from the Savannah River National Laboratory (SRNL), Bechtel National, Inc., and DOE-ORP, to evaluate the capability and potential benefits of replacing routine sample collection requirements with real-time, in-line monitoring. The initial focus of the ITT is the Direct Feed Low Activity Waste (DFLAW) Program. This work scope is being performed in multiple phases. Phase 1 is Requirements and Opportunities Analysis, Phase 2 is Applications and Benefits Determination, and Phase 3 is Qualification and Demonstration. Phase 1 included 6 tasks and was completed by SRNL in 2017. The tasks in Phase 1 were: (1) determining the functional requirements for determining analytes and properties of streams, (2) determining the technical basis for process control, (3) determining the sampling points within the Low Activity Waste (LAW) facility and Effluent Management Facility (EMF), (4) data quality and management, (5) process control challenges, and (6) preparing a Preliminary Analysis Plan. DOE-ORP was briefed on the findings from the Phase 1 tasks and requested that Phase 2 work focus on establishing a basis for a materials balance approach that minimized process sampling. The Phase 2 work scope contains tasks to evaluate a materials balance only approach as well as continuing scoping evaluations for instruments that could be used for RTIM. The Phase 2 work scope was completed by both SRNL and Pacific Northwest National Laboratory (PNNL). The tasks performed in Phase 2 were: 1. Overall program administration and technical oversight 2. Evaluation of a Material Balance Approach, a. Evaluation of uncertainty of this approach compared to uncertainty of current methods b. Evaluation of automating the material balance within the framework of existing control software, c. Development of the methodology to obtain and evaluate data during cold commissioning to support a material balance approach, and d. Development of a framework to utilize during presentation of the revised approach to stakeholders and regulators. 3. Screening Evaluations of Instruments to Supplement the Material Balance Approach, a. AP-105 melter condensate evaluations, and b. Screening testing with simulants. 4. Evaluation of the current DFLAW feed qualification program to identify analytes that could be eliminated, a. Inorganic analytes, b. Radionuclides, and c. Organic analytes. This report describes the results of Task 3b, Screening testing with simulants. The Savannah River National Laboratory requested demonstrations of commercially available analytical instruments by the vendors or laboratory demonstration. The techniques tested included: Raman spectroscopy, Infrared spectroscopy (IR), laser induced breakdown spectroscopy (LIBS), X-Ray Fluorescence Spectroscopy (XRF), and ion-selective electrochemical probes. Additionally, the instrumentation would need to be durable enough to withstand the environment of the plant, preferably with little to no maintenance. The insertion point of the instrument would be dependent upon the instrumentation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sensitive Top-Down Proteomics Analysis of a Low Number of Mammalian Cells Using a Nanodroplet Sample Processing Platform

Top-down proteomics is a powerful tool for characterizing genetic variations and post-translational modifications at intact protein level. That being said, one significant technical gap of top-down proteomics is the inability to analyze low amount of biological samples, which limits its access to isolated rare cells, fine-needle aspiration biopsies, and tissue substructures. Herein, we developed an ultrasensitive top-down platform by incorporating a microfluidic sample preparation system, termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples), into a top-down proteomics workflow. A unique combination of a nonionic detergent dodecyl-ß-D-maltopyranoside (DDM) with urea as protein extraction buffer significantly improved both protein extraction efficiency and sample recovery. We hypothesize that the DDM detergent improves protein recovery by efficiently reducing non-specific adsorption of intact proteins on container surfaces, while urea serves as a strong denaturant to disrupt noncovalent complexes and release intact proteins for downstream analysis. The nanoPOTS-based top-down platform reproducibly and quantitatively identified ~170 to ~620 proteoforms from ~70 to ~770 HeLa cells containing ~10 to ~115 ng of total protein. A variety of post-translational modifications including acetylation, myristoylation, and iron binding were identified using only less than 800 cells. We anticipate the nanoPOTS top-down proteomics platform will be broadly applicable in biomedical researches, particularly where clinical specimens are not available in amounts amenable to standard workflows.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Radionuclide Inventory Calculations for the Calcined Solid Storage Facility Performance Assessment - 19292

Originally named the Idaho Chemical Processing Plant when it was constructed in the early 1950's, the Idaho Nuclear Technology and Engineering Center reprocessed SNF to recover highly enriched uranium and other nuclear-related products for the U.S. DOE. Reprocessing SNF generated millions of gallons of aqueous radioactive waste. Calcination was a process developed at the INL Site to convert liquid waste into a solid, granular form from 1963 to 2000. The calcination process produced a safer product for storage while reducing the volume of stored liquid waste by an average factor of seven. Calcine is currently stored in the Calcined Solids Storage Facility (CSSF). The CSSFs are often called 'bin sets' because each CSSF (CSSFs 1 through 6) contains several stainless-steel storage bins housed in a concrete vault. The CSSF is an interim waste storage facility. In the future, calcine will be retrieved, treated (if necessary), and sent to an off-Site facility for storage or disposal. To close the CSSF, the bulk of the calcine will be removed and stored or disposed of elsewhere. The bins and vaults will then be placed in a configuration that is protective of human health and the environment. For purposes of the performance assessment, the depth of the residual calcine at closure was assumed to be 5-cm in each bin. The 5-cm of residual calcine in each bin is assumed to be mixed in grout during closure. The activities of the residual radionuclides are the inventory used for the dose assessment calculations for the CSSF performance assessment. The objective of this analysis was to calculate the radionuclide activity in the residual calcine remaining in the CSSF after closure. The purpose of this paper is to present the approach used to calculate the radionuclide inventory of the calcine currently stored in CSSF and the residual calcine in the CSSF after closure using data from the calcined waste Historical Processing Model (HPM). Limited sampling and analysis of the calcine in the CSSF bins was conducted in the past. Future similar calcine sampling and analysis efforts would be costly, generate additional mixed waste, and may not provide the desired detailed calcine composition data. However, during the later years of calcining, an alternative to calcine sampling and analysis was developed and the information was captured in the HPM. The HPM uses multiple sources to provide definitive calcine volume, mass, and composition, including: compositions and volumes of the liquid wastes that were calcined, ORIGEN2 - and ORIGEN-ARP-based radioactivity calculations, calciner and CSSF operating data, and process knowledge of INTEC fuel and waste-processing systems. HPM calcine composition was used to develop an inventory of radionuclides for use in the performance assessment evaluation for closure of CSSF. There are 43 bins that contain calcine, with six to twelve segments in each bin for a total of 337 bin segments for which the HPM calculates the average calcine composition. The HPM calculates the composition of each of the nearly 7,000 batches of material (startup bed, nonradioactive material, and radioactive waste) charged to the calciners. The calculations use the CSSF dimensions, including the CSSF number of bins, heights, outside diameters, annular air space diameter (if necessary), and volume of calcine currently in the bins. For each of the CSSFs, for a 5-cm residual, the percent of total calcine was calculated along with the residual activity for the radionuclides. Residual activity was estimated for 148 different radionuclides. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Data Validation Package, April and June 2016 Groundwater and Surface Water Sampling at the Gunnison, Colorado, Processing Site, October 2016

This event included annual sampling of groundwater and surface water locations at the Gunnison, Colorado, Processing Site. Sampling and analyses were conducted as specified in Sampling and Analysis Plan for US Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lm/downloads/sampling-and­ analysis-plan-us-department-energy-office-legacy-management-sites). Samples were collected from 28 monitoring wells, three domestic wells, and six surface locations in April at the processing site as specified in the draft 2010 Ground Water Compliance Action Plan for the Gunnison, Colorado, Processing Site. Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. Domestic wells 0476 and 0477 were sampled in June because the homes were unoccupied in April, and the wells were not in use. Duplicate samples were collected from locations 0126, 0477, and 0780. One equipment blank was collected during this sampling event. Water levels were measured at all monitoring wells that were sampled. See Attachment 2, Trip Reports for additional details. The analytical data and associated qualifiers can be viewed in environmental database reports and are also available for viewing with dynamic mapping via the GEMS (Geospatial Environmental Mapping System) website at http://gems.lm.doe.gov/#. No issues were identified during the data validation process that requires additional action or follow-up. An assessment of anomalous data is included in Attachment 3. Interpretation and presentation of results, including an assessment ofthe natural flushing compliance strategy, will be reported in the upcoming 2016 Verification Monitoring Report. U.S.

54 ENVIRONMENTAL SCIENCES↗

A statistical analysis of the effects of urease pre-treatment on the measurement of the urinary metabolome by gas chromatography–mass spectrometry

Urease pre-treatment of urine has been utilized since the early 1960s to remove high levels of urea from samples prior to further processing and analysis by gas chromatography-mass spectrometry (GC-MS). Aside from the obvious depletion or elimination of urea, the effect, if any, of urease pre-treatment on the urinary metabolome has not been studied in detail. Here, we report the results of three separate but related experiments that were designed to assess possible indirect effects of urease pre-treatment on the urinary metabolome as measured by GC-MS. In total, 235 GC-MS analyses were performed and over 106 identified and 200 unidentified metabolites were quantified across the three experiments. The results showed that data from urease pre-treated samples 1) had the same or lower coefficients of variance among reproducibly detected metabolites, 2) more accurately reflected quantitative differences and the expected ratios among different urine volumes, and 3) increased the number of metabolite identifications. Altogether, we observed no negative consequences of urease pre-treatment. In contrast, urease pretreatment enhanced the ability to distinguish between volume-based and biological sample types compared to no treatment. Taken together, these results show that urease pretreatment of urine offers multiple beneficial effects that outweigh any artifacts that may be introduced to the data in urinary metabolomics analyses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling

Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP and NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.

60 APPLIED LIFE SCIENCES↗

A method for monitoring deposition at a solid cathode in an electro-refiner for a two-species system using electrode potentials

Currently, process monitoring of spent nuclear fuel electrorefining relies upon sampling and destructive analysis methods coupled with extrapolated thermodynamic process models for non-interrupted operations. An 'inverse' model was developed to predict the product deposition rates on a cathode using the cell current, cathode potential, and fundamental relations of electrochemistry. The model was applied to the following cases: pure uranium deposition, co-deposition of uranium and plutonium, and co-deposition of uranium and zirconium. The deposition rates predicted by this 'inverse' model were compared to those of a 'forward' model, ERAD. On average, the predicted deposition rates had relative errors of 3.88 % and 2.84 % for U and Pu, respectively, in the case of U/Pu co-deposition and 4.16 % and 7.44 % for U and Zr, respectively, in the case of U/Zr co-deposition. Thus, the 'inverse' model was able to predict the deposition rates without requiring information regarding the feed and salt composition, as the forward model, ERAD, does.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Deep Learning Segmentation of Complex Features in Atomic-Resolution Phase-Contrast Transmission Electron Microscopy Images

Phase-contrast transmission electron microscopy (TEM) is a powerful tool for imaging the local atomic structure of materials. TEM has been used heavily in studies of defect structures of two-dimensional materials such as monolayer graphene due to its high dose efficiency. However, phase-contrast imaging can produce complex nonlinear contrast, even for weakly scattering samples. It is, therefore, difficult to develop fully automated analysis routines for phase-contrast TEM studies using conventional image processing tools. For automated analysis of large sample regions of graphene, one of the key problems is segmentation between the structure of interest and unwanted structures such as surface contaminant layers. In this study, we compare the performance of a conventional Bragg filtering method with a deep learning routine based on the U-Net architecture. We show that the deep learning method is more general, simpler to apply in practice, and produces more accurate and robust results than the conventional algorithm. We provide easily adaptable source code for all results in this paper and discuss potential applications for deep learning in fully automated TEM image analysis.

47 OTHER INSTRUMENTATION↗

A Method for Monitoring Deposition at a Solid Cathode in an Electrorefiner for a Two-Species System Using Electrode Potentials

Currently, process monitoring of spent nuclear fuel electrorefining relies upon sampling and destructive analysis methods coupled with extrapolative thermodynamic process models for non-interrupted operations. Corrections to those models are performed infrequently, jeopardizing both the control of the process and safeguarding of nuclear material. Furthermore, the timeliness of obtaining the results is inadequate for application of international safeguards protocol. Alternatively, a system that dynamically utilizes electrical data such as electrode potentials and cell current can hypothetically be used to achieve real-time process monitoring and more robust control as well as improved safeguards. Efforts to develop an advanced model of the electrorefiner to date have focused on a forward modeling approach by using feed and salt compositions to determine the product composition, cell current and electrode potential response. Alternatively, an inverse model was developed, and reported here, to predict the product deposition rates on a cathode using the cell current, cathode potential, and fundamental relations of electrochemistry. The model was applied to the following cases: pure uranium deposition, co-deposition of uranium and plutonium, and co-deposition of uranium and zirconium. The deposition rates predicted by the inverse model were compared to those of a forward model, ERAD.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Measuring Signatures of Fuel Irradiation in Large Particle Samples

Understanding the operating history of a nuclear facility is one of the key goals in nuclear safeguards, enabling the verification of declared activities. This is accomplished via a number of mechanisms, including the analysis of samples collected at the facility. The best metrics for understanding and verifying the history of nuclear fuel are (1) actinide isotopic content and (2) actinide inter-element ratios. While techniques have long existed for measuring these values with high accuracy and precision in bulk samples, as samples become smaller – such as may be collected in environmental collection – new methods are required both for clean processing of pure samples, and for analysis of these small samples. This study describes a new extraction chromatography technique for recovering U, Pu, and Am from single small aliquots, and advanced mass spectrometry methods for high-precision and high-accuracy analysis of trace and ultra-trace levels of actinides. These techniques are applied to particle samples cut from fuel from a historic nuclear reactor. Ages calculated from Pu–Am chronometry of particles are in excellent agreement with the known operating history of the reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A data analysis method to rapidly characterize gallium concentration in plutonium matrices using LIBS

The processing of actinide samples is a complex and costly endeavor that requires compositional analysis at various stages. Laser-induced breakdown spectroscopy (LIBS) has been used to analyze actinide-containing samples in many nuclear applications including waste management, fuel processing and forensics. The LIBS spectrum obtained from actinide materials are generally extremely complex, exhibiting many thousands of strong emission lines. This makes it difficult to identify other elements within the sample of interest, given the rich and dominant actinide spectrum. Here, in this article, we describe a recent effort to identify and quantify impurities and alloying constituents in plutonium matrices using a hand-held LIBS instrument that is used to rapidly and efficiently measure an emission spectrum from a material sample. We tabulate the emission line positions and intensities of plutonium. We report the development of machine-learning software that can identify gallium and quantify its concentration in plutonium matrices. This work has the potential to provide a rapid and nearly non-destructive technique that allows more confidence in characterizing the composition of materials that are present within complex actinide associated targets. We describe how our LIBS measurements and data analysis methods have successfully quantified the gallium concentration in a variety of samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

Nanoscale or single cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (Nanodroplet Processing in One pot for Trace Samples) platform as a major advance in overall sensitivity. NanoPOTS dramatically enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive LC-MS, nanoPOTS allows identification of ~1500 to ~3,000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins were consistently identified from as few as 10 cells. Furthermore, we demonstrate robust quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.

Environmental Molecular Sciences Laboratory↗

Framework for custom event sample augmentations for ATLAS analysis data

For HEP event processing, data is typically stored in column-wise synchronized containers, such as most prominently ROOT’s TTree, which have been used for several decades to store by now over 1 exabyte. These containers can combine row-wise association capabilities needed by most HEP event processing frameworks (e.g. Athena for ATLAS) with column-wise storage, which typically results in better compression and more efficient support for many analysis use-cases. One disadvantage is that these containers, TTree in the HEP use-case, require to contain the same attributes for each entry/row (representing events), which can make extending the list of attributes very costly in storage, even if those are only required for a small subsample of events. Since the initial design, the ATLAS software framework features powerful navigational infrastructure to allow storing custom data extensions for subsamples of events in separate, but synchronized containers. This allows adding event augmentations to ATLAS standard data products (such as DAOD-PHYS or PHYSLITE) avoiding duplication of those core data products, while limiting their size increase. For this functionality, the framework does not rely on any associations made by the I/O technology (i.e. ROOT), however it supports TTree friends and builds the associated index to allow for analysis outside of the ATLAS framework. A prototype based on the Long-Lived Particle search is implemented and preliminary results with this prototype will be presented. At this point, augmented data are stored within the same file as the core data. Storing them in separate files will be investigated in future, as this could provide more flexibility, e.g. certain sites may only want a subset of several augmentations or augmentations can be archived to tape once their analysis is complete.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Materials and Methods for Streamlined Laboratory Analysis of Environmental Samples, FY 2016 Report

The International Atomic Energy Agency (IAEA) relies upon laboratory analysis of environmental samples (typically referred to as “swipes”) collected during on-site inspections of safeguarded facilities to support the detection and deterrence of undeclared activities. Unfortunately, chemical processing and assay of the samples is slow and expensive. A rapid, effective, and simple extraction process and analysis method is needed to provide certified results with improved timeliness at reduced costs (principally in the form of reduced labor), while maintaining or improving sensitivity and efficacy. To address these safeguard needs the Pacific Northwest National Laboratory (PNNL) explored and demonstrated improved methods for environmental sample (ES) analysis. Improvements for both bulk and particle analysis were explored. To facilitate continuity and adoption, the new sampling materials and processing methods will be compatible with existing IAEA protocols for ES analysis. PNNL collaborated with Oak Ridge National Laboratory (ORNL), which performed independent validation of the new bulk analysis methods and compared performance to traditional IAEA’s Network of Analytical Laboratories (NWAL) protocol. ORNL efforts are reported separately. This report describes PNNL’s FY 2016 progress, which was focused on analytical application supporting environmental monitoring of uranium enrichment plants and nuclear fuel processing. In the future the technology could be applied to other safeguard applications and analytes related to fuel manufacturing, reprocessing, etc. PNNL’s FY 2016 efforts were broken into two tasks and a summary of progress, accomplishments and highlights are provided below. Principal progress and accomplishments on Task 1, Optimize Materials and Methods for ICP-MS Environmental Sample Analysis, are listed below. • Completed initial procedure for rapid uranium extraction from ES swipes based upon carbonate-peroxide chemistry (delivered to ORNL for evaluation). • Explored improvements to carbonate-peroxide rapid uranium extraction chemistry. • Evaluated new sampling materials and methods (in collaboration with ORNL). • Demonstrated successful ES extractions from standard and novel swipes for a wide range uranium compounds of interest including UO 2 F 2 and UO 2 (NO 3 ) 2 , U 3 O 8 and uranium ore concentrate. • Completed initial discussions with commercial suppliers of PTFE swipe materials. • Submitted one manuscript for publication. Two additional drafts are being prepared. Principal progress and accomplishments on Task 2, Optimize Materials and Methods for Direct SIMS Environmental Sample Analysis, are listed below. • Designed a SIMS swipe sample holder that retrofits into existing equipment and provides simple, effective, and rapid mounting of ES samples for direct assay while enabling automation and laboratory integration. • Identified preferred conductive sampling materials with better performance characteristics. • Ran samples on the new PNNL NWAL equivalent Cameca 1280 SIMS system. • Obtained excellent agreement between isotopic ratios for certified materials and direct SIMS assay of very low levels of LEU and HEU UO 2 F 2 particles on carbon fiber sampling material. Sample activities range from 1 to 500 CPM (uranium mass on sample is dependent upon specific isotope ratio but is frequently in the subnanogram range). • Found that the presence of the UF molecular ions, as measured by SIMS, provides chemical information about the particle that is separate from the uranium isotopics and strongly suggests that those particles originated from an UF6 enrichment activity. • Submitted one manuscript for publication. Another manuscript is in preparation.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Real Time, In-line Monitoring of Hanford Tank Wastes - Year 1 Report

The team comprised of students, postdocs, early, mid and senior career scientists from Los Alamos National Laboratory, Savanah River National Laboratory, Georgia Tech and Florida International University, with the guidance of H2C, is developing a suite of in-line instruments for the Hanford high level waste (HLW) and low active waste (LAW) processes to provide near-real-time analysis of waste form physical properties and composition. The work builds on results from the recent DOE-ORP, EM Technology Development and other projects that demonstrated promise for the use of real-time in-line monitoring (RTIM) to measure chemical compositions of slurries of up to 20 weight % solids. The goal is for this instrument suite is to substantially reduce the need for sampling for process control. Sample waste, exposure associated with sample analysis, and the demand for an external laboratory facility would be greatly reduced. The throughput of waste treatment systems would be improved by elimination of the downtime caused by waiting for sample results. This translates into reduced process storage as process knowledge will be continuously updated in near-real-time. These breakthrough technologies would significantly reduce the life cycle cost and accelerate the schedule for the Hanford tank waste mission.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Estimation of process steady state with autoregressive models and Bayesian inference

To improve efficiency, separations engineers will typically design process circuits containing recirculating streams, which mix one or more of the process outputs with the feed material. Doing so can improve efficiency, but will cause a delay in the system reaching steady state conditions until the recirculating load mass flows stabilize. In testing separation circuits, engineers will often test a variety of factors and complete an analysis from sample results. Knowledge of if a process is at steady state, as well as the steady state conditions of a process, is essential for a valid techno-economic analysis. However, the definition of process steady state is often poorly defined, or does not include uncertainty quantification. If the performance of a process operating under two different sets of conditions are compared, an engineer who does not test for steady state or quantify steady state conditions risks producing a faulty analysis. In this work, a Bayesian statistical method for testing if all streams are at steady state is further motivated and then derived. Then after testing for steady state, the same model is used with a prior distribution that enforces a steady state assumption to estimate steady state conditions. Further, these methods were validated in a solvent extraction pilot plant where steady state conditions for all outflows were inferred with uncertainty quantification. Analysis is completed with functions available to the reader as part of the BayesMassBal (V 1.1.0) software package written in R.

01 COAL, LIGNITE, AND PEAT↗

Radiochemical capabilities for astrophysics experiments at the national ignition facility

The Nuclear and Radiochemistry Group at Lawrence Livermore National Laboratory (LLNL) has developed a suite of diagnostics and techniques that can be used for astrophysics experiments at the National Ignition Facility (NIF). Capabilities have been developed to add material to the outside of NIF hohlraum assemblies as well as to the interior of NIF target capsules or the fill gas. The ability to place very small amounts of material close to the NIF target enables activation with very large, short-pulse neutron fluxes. The Solid Radiochemistry Diagnostic can be used to collect solid debris from a NIF shot within 2 h of the execution of a shot, and this can be analyzed for radioactive signatures with or without post-shot chemical processing. The Radiochemical Analysis of Gaseous Samples diagnostic system can be used to collect gaseous products produced during a NIF shot. Capsule doping and radiochemical analysis capabilities at NIF will be discussed. The application of these techniques to astrophysical measurements will be discussed as well as some preliminary results.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗