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At least 127 records · Page 7

Gemma V&V/UQ/Credibility Activities: FY2020 Progress

This report describes the credibility activities undertaken in support of Gemma code development in FY20, which include Verification & Validation (V&V), Uncertainty Quantification (UQ), and Credibility process application. The main goal of these activities is to establish capabilities and process frameworks that can be more broadly applied to new and more advanced problems as the Gemma code development effort matures. This will provide Gemma developers and analysts with the tools needed to generate credibility evidence in support of Gemma predictions for future use cases. The FY20 Gemma V&V/UQ/Credibility activities described in this report include experimental uncertainty analysis, the development and use of methods for optimal design of computer experiments, and the development of a framework for validation. These initial activities supported the development of broader credibility planning for Gemma that continued into FY21.

97 MATHEMATICS AND COMPUTING↗

Hierarchical Conceptual Model Event and Activity Domains for Forecasting State-Sponsored Civil Nuclear Power Activities

In FY20, the Savannah River National Laboratory and the Sanghani Center for Artificial Intelligence and Data Analytics (Virginia Tech) entered a collaboration funded by the Department of Energy’s Office of Defense Nuclear Nonproliferation Research and Development to develop a machine learning based modeling pipeline to extract proliferation events of interest from open data sources. The prototype modeling pipeline that was developed relies on the use of time dependent word embedding models to identify contextual shifts in key words and phrases that act as indicators of events of interest. The FY20- 21 efforts were focused on a narrow topical domain of forecasting “fissile core fabrication” at the Savannah River Site prior to its official announcement in 2018. In FY22, the research team was funded to continue development of the modeling pipeline by applying it to the problem of forecasting new, and/or significant changes to existing, civil nuclear power reactors around the world. In this effort, the development will focus on proving applicability to a broader topical domain and in data environments that may contain more sparse information, relative to the United States. In this report, the worldwide landscape of civil nuclear reactors is outlined, the timeline of interest is defined, and a hierarchical conceptual model is established to identify the activity domains of interest and the event domains of interest. This preliminary effort will guide the curation of a glossary of key terms for data acquisition, as well as the downstream modeling efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

FY2021 Rotating Bed Reactor for Iodine Removal from ETF Feed to Support DFLAW Start-Up

In FY20, Washington River Protection Solutions, LLC (WRPS) began a program of work to evaluate potential technologies for removal of iodine from the ETF feed. Work at the Pacific Northwest National Laboratory (PNNL) focused on ion exchange media and conventional column based deployment while Atkins and VSL focused on ion exchange media in a Rotating Bed Reactor (RBR) system. In the RBR system, the ion exchange media is loaded into a packed bed, which is rotated in the liquid to be treated. The work described in this report builds on the results from FY20 work, in particular, with regard to improving iodate removal, extending the data set to support process modeling, further comparison of RBR versus column performance, and RBR scale-up testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Corrosion-Resistant Coatings on Spent Nuclear Fuel Canisters to Mitigate and Repair Potential Stress Corrosion Cracking (FY22 Status)

This report summarizes the activities performed by Sandia National Laboratories in FY22 to identify and test coating materials for the prevention, mitigation, and/or repair of potential chloride-induced stress corrosion cracking in spent nuclear fuel dry storage canisters. This work continues efforts by Sandia National Laboratories that are summarized in previous reports in FY20 and FY21 on the same topic. The previous work detailed the specific coating properties desired for application and implementation to spent nuclear fuel canisters (FY20) and identified several potential coatings for evaluation (FY21). In FY22, Sandia National Laboratories, in collaboration with four industry partners through a Memorandum of Understanding, started evaluating the physical, mechanical, and corrosion-resistance properties of 6 different coating systems (11 total coating variants) to develop a baseline understanding of the viability of each coating type for use to prevent, mitigate, and/or repair potential stress corrosion on cracking on spent nuclear fuel canisters. This collaborative R&D program leverages the analytical and laboratory capabilities at Sandia National Laboratories and the material design and synthesis capabilities of the industry collaborators. The coating systems include organic (polyetherketoneketone, modified polyimide/polyurea, modified phenolic resin), organic/inorganic ceramic hybrids (silane-based polyurethane hybrid and a quasi-ceramic sol-gel polyurethane hybrid), and hybrid systems in conjuncture with a Zn-rich primer. These coatings were applied to stainless steel coupons (the same coupons were supplied to all vendors by SNL for direct comparison) and have undergone several physical, mechanical, and electrochemical tests. The results and implications of these tests are summarized in this report. These analyses will be used to identify the most effective coatings for potential use on spent nuclear fuel dry storage canisters, and also to identify specific needs for further optimization of coating technologies for their application on spent nuclear fuel canisters. In FY22, Sandia National Laboratories performed baseline testing and atmospheric exposure tests of the coating samples supplied by the vendors in accordance with the scope of work defined in the Memorandum of Understanding. In FY23, Sandia National Laboratories will continue evaluating coating performance with a focus on thermal and radiolytic stability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Additive Component Manufacturing

State-of-the-art technology like additive manufacturing has not yet been thoroughly applied to fluid control valves. Many valve manufacturing issues such as flow passage machining, deep hole boring, and bi-metallic joining could successfully be addressed with this new technology. The goal of this project was to apply additive manufacturing technology specifically to the problems that fluid control valves present. In order to properly apply additive manufacturing processes to the design of control valves, the plan was to manufacture samples using metals compatible with low temperature, high pressure oxygen service and then tested. While vetting this project with manufacturers, it was determined that the materials chosen were not ideal for additive manufacturing due to their high reflectivity. Therefore, materials for this project were currently undergoing reevaluation and materials that are better suited for additive manufacturing may be substituted. During FY20, additional alloys were selected that would be both appropriate for high pressure oxygen environments as well appropriate for additive manufacturing processes. However, final bid for manufacturing was six times larger than the available funding for this project. Based on previous additive manufacturing projects, the scope and funding for this project were appropriate, but a suitable manufacturer willing to provide a reasonable proposal, was not found. Therefore, funds were de-obligated for this project, and then re-obligated to augment another FY20 CIF project.

Jonathan Dickey↗

Development and Application of a Risk Analysis Toolkit for Plant Resources Optimization

This report summarizes the R&D activities of the Risk Informed Asset Management (RIAM) project during fiscal year 2020 (FY20). This project focuses on the development of methods designed to optimize plant operations (e.g., maintenance/replacement schedule, optimal maintenance posture) provided system/component health/cost data. This project development lives in cooperation with the Plant Health Management (PHM) project which focuses on the development of methods that integrate component health data and propagate such information at the system level to evaluate most relevant sources of risk. This year’s activities for the RIAM project focused on the continuation of schedule optimization algorithms developed in FY19. While in FY19 we focused on both deterministic and stochastic capital budgeting methods, in FY20 we moved forward by implementing two versions of schedule optimization methods. The first one reformulates the capital budgeting problem in a distributionally robust form which allows the user to rely on data directly rather than proposing a distribution from the data itself. The second version reformulates the capital budgeting explicitly using risk measures as variables to maximize/minimize. Lastly, we focused on the development of methods designed to identify the optimal maintenance posture based on the Pareto Frontier analysis. Rather than performing a tradeoff analysis (i.e., identify the absolute best posture), the Pareto Frontier analysis performs a trade space exploration approach (i.e., identify value and costs of several postures and have the analyst perform the task of imposing desired value and cost constraints). This is performed by identifying maintenance postures that maximize value (e.g., system availability) and minimize operational costs, i.e., the Pareto frontier in a value-cost trade space.

97 MATHEMATICS AND COMPUTING↗

REST Interface Generator (RESTInG) v0.1

From a single data description file, this package generates a simple but complete RESTful web interface to a relational database, in the form of containers that run in a Docker environment. This initial version produces containers that are intended for use on the NERSC Spin platform. It was developed as a foundation for the smart catalog created for LDRD FY20 ACTS: Accelerating COVID-19 Testing with Screening.

Higa, Kenneth↗

Production of Biocrude in an Advanced Photobioreactor-Based Biorefinery

Algenol Biotech, the National Renewable Energy Laboratory (NREL), Georgia Institute of Technology, Arizona State University, and Reliance Industries formed a team to advance the state of the art in algal biomass production and downstream processing technologies, with the end goal of a sustainable, economically viable biofuel intermediate (BFI, biocrude) product. The project included examination of high value co-product production as a market entry strategy and for enhancing the economics of a biorefinery for BFI production. The project targeted innovations in biology, operations, and engineering. The goals of the project were: BFI productivity greater than 4,000 gal-BFI/acre-yr on an annualized basis; energy efficient innovations in downstream operations resulting in an energy expenditure less than 10% of the BFI energy content and a carbon footprint reduction of more than 60% compared to fossil alternatives; and a comprehensive Techno-Economic Analysis (TEA) that identifies limiting factors for commercial viability of a photobioreactor (PBR)-based biofuel product. The project achieved the overall objectives. Strain development efforts led to the identification of a strain (Cyanobacterium sp. AB1166) that, relative to the previous best strain (Cyanobacterium sp. AB1), exhibited a ~10% increase in productivity under commercially-relevant cultivation conditions and also resulted in cultures with a >50% reduction in viscosity such that harvesting efficiency was improved; these results represent achievement of key project milestones. Progress was also made at NREL in altering the biochemical composition of algal biomass to improve the yield of BFI produced via HTL. These strain enhancements coupled with improved outdoor cultivation practices, including semi-continuous operation, increased areal biomass productivity by nearly 80% over the established baseline productivity. The annualized productivity achieved (26.8 g/m2-d), paired with HTL conversion yields realized at NREL and RIL (38% ± 2% BFI), translates to 4,100 gal-BFI/acre-yr, exceeding the FY20 BETO goal of 3,700 gal-BFI/acre-yr. Significant progress was also demonstrated in large scale PBR-based production system design, operability, and cost reduction. A 24,000-L production module comprised of 240 interlinked PBRs was constructed and successfully operated outdoors for over one year in Fort Myers, Florida. Aided by a state-of-the-art productivity model, the productivities achieved convincingly demonstrated scalability of laboratory results determined at the mL to L scale to large-scale outdoor operations exceeding 20,000 L. The system was used to cultivate Arthrospira platensis (Spirulina), an industrially-relevant cyanobacterium and source for phycocyanin, an approved blue food colorant that Algenol is developing as a risk reduction strategy for future biofuel projects and as a potential business opportunity. A key project milestone to develop phycocyanin extraction and purification technologies was achieved ahead of schedule, and product samples received positive feedback from potential customers. The production and downstream operations data generated in this project were used to conduct and refine Techno-Economic and Life Cycle Assessments to provide research guidance for reducing the costs and environmental footprint of algal biofuel and co-product manufacturing plants. Several CO 2 supply scenarios for an algal biorefinery were identified as being capable of providing a large (>60%) reduction in carbon footprint in comparison to gasoline. The TEA assessments incorporated detailed comparisons of PBR versus open pond production systems, yielding a 3-fold higher areal productivity for PBRs and suggesting overall production cost parity for the two systems. The progress in this ABY2 project addressed many of the the barriers identified for the Advanced Algal Systems R&D Program and are directly relevant to achieving the established BETO goals associated with large scale biofuel production and cost reduction.

09 BIOMASS FUELS↗

Prototype for Unclassified Algorithm

Continuing previous efforts to investigate and develop the Unclassified Radioisotope Algorithm, the goal of the FY19-FY20 effort was to develop a prototype detector system which uses the algorithm to confirm warhead attributes related to the presence of either weapons grade plutonium (WGPu) or highly enriched uranium (HEU). The final deliverable is a prototype attribute measurement system built with common, commercially available gamma radiation detector components, capable of confirming the presence of specific, complex radioactive sources of interest, without the collection and storage of gamma energy spectra. This is accomplished by processing each gamma pulse as it is received, applying weight values based on the energy and incrementing or decrementing scalar counters which can be compared with expected values to determine if the measured source is consistent with WGPu or HEU. This report documents the design of the prototype system as well as the development of the algorithm and performance testing results. While the previously conceptualized, simple algorithm resulted in a prohibitive amount of false positives, the goal for a simple attribute measurement system capable of verifying Ba-133 and Ra-226 (weapons grade plutonium and highly enriched uranium surrogate testing sources) at over 95% accuracy with sub 5% false positive rate was demonstrated.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Compare linear-system solver and preconditioner stacks with emphasis on GPU performance and propose phase-2 NGP solver development pathway

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. In this report we evaluated GPU-performance baselines for the linear solvers in the Trilinos and hypre solver stacks using two representative Nalu-Wind simulations: an atmospheric boundary layer precursor simulation on a structured mesh, and a fixed-wing simulation using unstructured overset meshes. Both strong-scaling and weak-scaling experiments were conducted on the OLCF supercomputer Summit and similar proxy clusters. We focused on the performance of multi-threaded Gauss-Seidel and two-stage Gauss-Seidel that are extensions of classical Gauss-Seidel; of one-reduce GMRES, a communication-reducing variant of the Krylov GMRES; and algebraic multigrid methods that incorporate the afore-mentioned methods. The team has established that AMG methods are capable of solving linear systems arising from the fixed-wing overset meshes on CPU, a critical intermediate result for ExaWind FY20 Q3 and Q4 milestones. For the fixed-wing strong-scaling study (model with 3M grid-points), the team identified that Nalu-Wind simulations with the new Trilinos and hypre solvers scale to modest GPU counts, maintaining above 70% efficiency up to 6 GPUs. However, there still remain significant bottlenecks to performance: matrix assembly (hypre), AMG setup (hypre and Trilinos) In the weak-scaling experiments (going from 0.4M to 211M gridpoints), it's shown that the solver apply phases are faster on GPUs, but that Nalu-Wind simulation times grow, primarily due to the multigrid-setup process. Finally, based on the report outcomes, we propose a linear solver path-forward for the remainder of the ExaWind project. Near term, the NREL team will continue their work on GPU-based linear-system assembly. They will also investigate how the use of alternatives to the NVIDIA UVM (unified virtual memory) paradigm affects performance. Longer term, the NREL team will evaluate algorithmic performance on other types of accelerators and merge their improvements back to the main hypre repository branch. Near term, the Trilinos team will address performance bottlenecks identified in this milestone, such as implementing a GPU-based segregated momentum solve and reusing matrix graphs across linear-system assembly phases. Longer term, the Trilinos team will do detailed analysis and optimization of multigrid setup.

17 WIND ENERGY↗

Options for Future Fuel/Basket Modifications for DPC Disposition

Deliverable Description: Identify and evaluate options for fuel and basket modifications, for dual-purpose canisters (DPCs) to be loaded in the future, that would substantially reduce the probability of post closure criticality after waste package breach and flooding with ground water. Planned work in FY20 will examine the feasibility of criticality control features, particularly neutron absorbing inserts or replacement channels for boiling water reactor (BWR) fuel assemblies. The expected outcome is additional engineering information that can be used to guide the R&D program, and to support future stakeholder interactions. This document will be incorporated into planned deliverable DPC Disposal Concepts of Operation (M3 SF-20SNO10305052, 18S ep20).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Tribal Colleges and Universities/Advanced Manufacturing Network Initiative (Q3 FY2020 Progress Report)

The National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) to 1) align investments in a university capacity and workforce development with the NNSA mission to develop the needed skills and talent for NNSA's enduring technical workforce at the laboratories and production plants, and 2) to enhance research and education at under-represented colleges and universities. Out of this effort, MSIPP launched a new consortium in early FY17 focused on Tribal Colleges and Universities (TCUs) known as the Advanced Manufacturing Network Initiative (AMNI). This consortium has been extended for FY20 and FY21. The following report summarizes the status update during this quarter.

42 ENGINEERING↗

Deuterium Concentration Effects on Cell Cycle Progression

Deuterium (D), which is found in natural water at ~ 150 ppm, seems to play an important role in biology. For example, D concentrations above 150 ppm are known to produce toxic effects in many organisms. There is also evidence to suggest D levels significantly less than 150 ppm can cause delays in progression through the normal mitotic cell cycle. Some have even theorized that the D:H ratio in cells may impact an organism’s radiation resistance. Therefore, evaluating the role of D and the D:H ratio in eukaryotic and prokaryotic cells should lead to a better understanding of cell cycle progression and radiation resistance in these organisms. Research in this field has likely been stalled by the limited availability of D 2 O with varying D concentrations needed to accurately study the deuterium effects. However, SRNL can currently manufacture D 2 O in varying concentrations, and we have assembled a unique team of radiation biologists, microbiologists, radiochemists, and health physics to form an interdisciplinary research group to study the cell cycle as a function of D concentration in order to address several fundamental science questions. Proposed work in FY20 was a collaborative effort with Augusta University to utilized BSL-2 mammalian cell lines. Lab work was halted due to the COVID-19 pandemic. An intensive literature review was performed and identified pertinent knowledge gaps that could be filled in future research efforts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Demonstration of a new unstructured mesh IMC x-ray transport capability in LAP codes

In this document, the Advanced Simulation and Computing (ASC) Transport Project’s Jayenne team presents evidence that the Los Alamos National Laboratory (LANL) Level 2 milestone statement, Demonstrate a new unstructured mesh IMC x-ray transport capability in LAP codes, due Q4 FY20, has been satisfied with the release and integration of the Jayenne team’s Implicit Monte Carlo (IMC) solver libraries into the lumos multiphysics solver. The Jayenne project’s software includes the algorithms and features prescribed by the milestone description. The lumos software is maintained by the Lagrangian Applications Project (LAP) along with the hydrodynamics code flag and operates under the same ASC program as Jayenne. A set of demonstration problems has been specified, executed, and analyzed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Metal-Organic Framework Glasses as Rad Contaminant Sequesters and Nuclear Waste Forms

Remediation of Tc remains an unresolved problem at SRS and other DOE sites. The objective of this project was to develop novel metal organic framework (MOF) glasses for radioactive contaminant sequestration and stabilization from aqueous media. During FY20, we synthesized, characterized and evaluated additional cetyltrimethylcimmonium bromide (CTAB)-functionalized and F - , Cl - , I - , CF 3 SO 3 - exchanged MIL-101-Cr samples. MIL-10l-Cr-NO 3 -CTAB was demonstrated to have high ReO 4 - removed capacity (139 mg/g sorbent) from artificial groundwater (AGW). Re chemical specicition and binding mechanism on MIL-101-CTAB were also studied by synchrotron X-ray absorption spectroscopy. ReO 4 - was demonstrated as being in the pore structure with slightly larger Re-O bond distances than those in NciReO 4 and binding with the positively charged sites of CTAB. In addition, a new Ni-TIPA MOF was demonstrated to be very stable, selective and effective for TcO 4 - removed from the SRS tank waste stream (~90% removed). The Ni-TIPA MOF sample containing ReO 4 - was prepared and shipped/planned for vitrification studies by a high-pressure technique. This research may provide a highly applicable platform for solving critical DOE and industrial problems related to nuclear environmental stewardship and nuclear power production.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Reflector coatings development (FY2020 End of Year Report)

X-ray detection instrumentation has been developed and manufactured at LANL for various DOE programs. One way to improve light collection efficiency, for a scintillator type detector, is to apply suitable reflectors. The coating capability and fabrication procedure for Al reflective coatings was established in FY19 at MST-7. Al reflective coatings with good stability, good adhesion to LSO, and reflectivity (R) up to 78% were fabricated. Materials with higher diffuse reflectivity (such as Teflon tape R=99%) are desirable. A literature search revealed a number of materials in the form of paint or free standing tape with diffuse R = 98- 99%. However, for the intended application such reflectors have to be applied in the form of a coating with strong adhesion to LSO crystals. The purpose of the FY20 project was to develop thin film coating techniques for PTFE (known as Teflon) reflectors and fabricate reflective coatings on provided LSO crystals.

36 MATERIALS SCIENCE↗