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DOE OSTI2021

MHD flow in liquid metal blankets: Major design issues, MHD guidelines and numerical analysis

The design of breeding blankets represents the major challenge for fusion reactor engineering because of performance requirements and severe operating conditions in terms of heat load and neutron flux. Liquid metal alloys such as lead-lithium, due to their lithium content, can be used to breed tritium, one of the plasma fuel components, and owing to their high thermal conductivity, they may serve as coolants. On the other hand, there are technical issues related to the fact that the liquid metals are electrically conducting and interact with the plasma-confining magnetic field. Induced electric currents and generated electromagnetic forces affect velocity and pressure distribution in the blankets. Magnetohydrodynamic (MHD) flows for fusion applications have been often investigated in simplified geometries, such as pipes, ducts, bends, with focus on their fundamental features. These analyses are essential, since results remain valid as background for the development of blanket designs, even when a concept is dismissed. However, the conceptual study of fusion blankets requires to take into account the global multiple effects, that arise when the full system is considered. Progress made in fusion-related MHD research results from combined numerical and experimental activities. In this paper we review and summarize features of 2D and 3D MHD flows that are typical in liquid metal blankets, together with available correlations for MHD pressure losses. This knowledge can provide simple design MHD guidelines that support a preliminary estimate of MHD effects in a blanket concept, in terms of pressure drop and flow distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

U.S. Efforts in Support of Examinations at Fukushima Daiichi- November 2020 Meeting Notes with Updated Information Requests

Much is still not known about the end-state of core materials in each unit that was operating on March 11, 2011 at the Fukushima Daiichi Nuclear Power Station (Daiichi). Information obtained from Daiichi is required to inform Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2021 (FY2021) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy (DOE-NE), is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Since its inception, annual reports were issued that document significant safety insights being obtained in areas of special emphasis: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Reduced uncertainties in modeling the events at Daiichi improve the realism of reactor safety evaluations that inform future D&D activities. A key aspect of prior U.S. efforts, the updated list of information requests, is included in this FY2021 report to ensure that they are transmitted to organizations within Japan. This report also continues to emphasize how information obtained from the affected reactors at Daiichi has been and will continue to be used to update severe accident management strategies and reduce uncertainties in systems analysis code models. In addition, recommendations are included that would expand the use of this information to provide insights regarding maintenance, radiation protection, design, and siting activities for existing and new reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Progress on Demonstration of a MOOSE-Based Coupled Capability for Hot Channel Factors in Fast Reactors

Hot channel factors (HCFs) are computed values that account for the impact on predicted peak fuel, cladding, and coolant temperatures due to uncertainties in the as-built reactor’s material properties and geometry as well as uncertainties due to modeling approximations. Reduction in computed HCF values via reduction or elimination of modeling approximations may translate to significant economic savings if the reactor power can be raised due to the extra temperature margin gained. While limited historical datasets exist for sodium-cooled fast reactors (SFRs), there are no available HCF data for lead-cooled fast reactors (LFRs) outside of work generated previously within NEAMS. The computation of HCFs involves insights from reactor physics, thermal fluids and heat conduction calculations to determine how the peak temperatures respond to various uncertainties in the design. Due to the significant advantages for multi-physics coupling offered by the MOOSE framework, Griffin (MOOSE-based reactor physics code), MOOSE Heat Conduction Module, and Cardinal (MOOSE-wrapped multi-physics application which includes the NekRS thermal fluids code) are being coupled together using the MOOSE MultiApp System to develop a highfidelity multi-physics modeling capability for HCF simulations. This high-fidelity coupling workflow may also be beneficial for other fast reactor applications in the future. In previous work, Griffin and NekRS were individually assessed to ensure the necessary capabilities were in place. This work describes initial efforts to couple the codes (including folding in the MOOSE Heat Conduction Module) and determining the workflow for the perturbed calculations which will leverage the Stochastic Tools Module (STM). To our knowledge, this is the first coupling of Griffin and NekRS as well as the first exploratory use of Stochastic Tools Module for Cardinal. In this report, the neutronics code Griffin, the heat conduction solver in MOOSE, and the MOOSE-wrapped application containing NekRS (Cardinal) are linked together to demonstrate the coupled capability. Griffin and Cardinal are linked dynamically by specifying shared libraries. Different coupling hierarchies are tested for selecting the most appropriate coupling strategy. A coupling scheme is selected based on the efficiency of calculation and ease of data communication. Multiple tests are performed to choose suitable mesh structure, model configurations, scheme setup and boundary conditions to avoid loss of energy due to data interpolation between different modules or weak imposition of fluxes in finite element codes. Computational experiments are performed to study the tolerance control of each type of iteration to avoid false convergence. The coupled capability is demonstrated in both single pin and 7-pin models based on LFR materials and geometry. The study finds that the use of too large a time step size in the heat conduction module can lead to temperature oscillation even though the heat conduction equation does not have a time-derivative kernel, but only the time-dependent boundary condition. A 7-pin model without duct region achieved good convergence in the coupled calculation while a 7 pin model with duct region experienced data communication issues which need to be resolved.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Materials for Advanced Ultra-Supercritical (A-USC) Steam Turbines --- A-USC Component Demonstration

The U.S. Advanced Ultra-Supercritical (A-USC) Consortium was formed in 2001 as a government/industry program, sponsored by the U.S. Department of Energy (DOE) and the Ohio Coal Development Office (OCDO) and cost shared by industrial and not-for-profit partners. The purpose of the consortium was to advance the state of the art for power generation by evaluating and developing materials that allow the use of advanced steam cycles in coal-based power plants. These advanced cycles, with steam temperatures up to 1400°F (760°C), can increase the efficiency of coal-fired boilers from an average of 35% (current U.S. fleet) to more than 45% higher heating value (HHV) (>49% lower heating value [LHV]). The increase in a plant’s efficiency is limited unless new materials able to withstand these higher operating temperatures and pressures are identified and approved for use. The A-USC Consortium identified these needed materials during earlier phases of the program. It developed the welding and joining techniques along with manufacturing processes for casting and wrought products made from these new high-nickel alloys. It subjected these materials to extensive laboratory and steam loop testing. It then obtained ASME code approval for their use in U.S. boiler systems. The program’s successes leave this last remaining activity (ComTest Phase 2) that the U.S. utility industry has recommended to be accomplished prior to commercialization. The focus of the activity is the evaluation and demonstration of commercial readiness for “full scale” components to be made from these nickel-based alloy materials and provided by a U.S. domestic supply chain that is new to working with these alloys. According to studies completed by the Electric Power Research Institute (EPRI), the cost of an A-USC plant is approximately 20% higher than a non-A-USC plant because of its use of nickel-based alloys needed for the high temperature operating conditions. However, CO 2 reductions of approximately 30% from the current fleet average provide a strong incentive for its consideration. The actual costs and perceived value for CO 2 abatement will determine whether new or retrofitted plants are undertaken, although decisions to build A-USC plants in India would indicate its economic feasibility while also being part of a global carbon emissions strategy. The work by the A-USC Consortium, prior to the start of the ComTest project, has included lab scale and pilot scale materials testing, both in air and oxy-combustion. This testing has included air-cooled and steam-cooled “loops” that were installed into existing operating utility boilers to gain exposure of these materials to realistic conditions of high temperature and corrosion caused by the constituents in the coal ash. The A-USC Consortium also gained ASME Code approval of the Inconel 740 material, has cast and extruded the largest high nickel precipitation hardened alloys, and developed unique welding techniques to avoid problems identified by the competing European program. However, as valuable as these material test loops and accomplishments have been for obtaining information, their scale is below that required to minimize the risk associated for a U.S. utility to build a multibillion-dollar A-USC power plant. To reduce the final identified risk barrier to full-scale commercialization of these advanced materials and systems, the A-USC Consortium (guided by a utility industry advisory committee) has identified the key areas of the technology they desire to see as being capable of full-scale manufacturing and/or fabrication from an identified, capable U.S. domestic supplier base. A significant amount of work was accomplished during Phase 1 to identity the components, as well as the component size, that would be manufactured from advanced alloys such as Inconel 740H or Haynes 282 alloys. Pathways to supply these components for ComTest have been identified, as well as any further development that would be required. The Phase 2 effort used Phase 1 findings for designing these key full-scale components for A-USC boilers and turbines to include large castings; extrusions, forgings, fabrication of water walls and steam loops with headers from advanced materials, raw material (such as pipe extrusion billets) are at the commercial readiness level to permit advancement to a demonstration project. The Phase 2 work scope was addressed by a diverse team, including government, industry, and not-for-profit partners. The work scope under Phase 2 addressed fabrication of components identified as being outside of the proven capabilities of the existing supply chain, including the following: Steam turbine rotor forging and Haynes 282 nozzle carrier casting Superheater and reheater header and tube assemblies Large-diameter pipe extrusions and forgings Test valve articles to support ASME Code approval. In addition, key fabrication steps were completed, including boiler weld overlays and simulated field repairs. Throughout, extensive inspection and quality assurance testing of the components were performed. The team worked to advance ASME Code approval for key components and processes. Although much of the focus of ComTest Phase 2 was the high-temperature nickel-based alloy materials, a broader range of materials were incorporated, which would be representative of the materials used in full-scale A-USC power plant applications and have cross-cutting applicability on other high-temperature power generation options, such as advanced nuclear, supercritical CO 2 cycles, and central solar receivers. This report that has been submitted is organized in the following manner: Section 1 contains an Executive Summary. Section 2 discusses the ComTest project background and organization. Section 3 discusses project management and reporting. Section 4 discusses the procurement of nickel-based alloy and other A-USC materials and components. Section 5 discusses the fabrication of procurement of nickel-based alloy and other A-USC materials and components. Section 6 discusses the fabrication of cast nickel-based A-USC steam turbine components. Section 7 discusses the fabrication of forged nickel-based A-USC steam turbine piping and steam pipe components. Section 8 discusses the qualification of pressure relieve valves (PRVs) for A-USC power plants. Section 9 discusses proposed plans for future evaluation of A-USC components. Section 10 contains the summary and conclusion.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Microstructural Characterization of A709 Commercial Heats with Precipitation Treatment

This report discusses work conducted at Idaho National Laboratory in fiscal year 2022 associated with the precipitates in Alloy 709 (A709). The purpose of this work is to support the development of the A709 Code Cases to qualify A709 in Section III, Division 5 of the American Society of Mechanical Engineers Boiler and Pressure Vessel Code. This would permit the use of A709 for elevated-temperature nuclear construction. This work encompassed two broad goals. The first goal was to understand the microstructure of the second commercial heat of plate A709 purchased through the Advanced Reactors Technologies Program in both the solution-annealed and precipitation-treated conditions. Transmission electron microscopy was utilized to characterize these microstructures. Direct comparisons were then made between the solution-annealed and precipitation-treated conditions as well as between the first and second commercial heats of plate A709. The second goal was to understand the impact of variations in the time and temperature of the precipitation treatment on the properties of A709. The precipitation treatment temperature was varied from 750°C to 800°C for times ranging from 3 hours to 30 hours. The hardness of each precipitation treatment variation was measured. All of the precipitation treatment variations investigated besides a specimen from the second commercial heat of plate A709 precipitation treated at 800? for 9 hours met the room-temperature hardness requirement specified in ASTM A213 and SA-213 for UNS S31025. The hardness measured for the specimen from the second commercial heat of plate A709 that was precipitation treated at 800? for 9 hours is considered an outlier. The next step is to look at the extremes of the precipitation treatment variations investigated and conduct elevated-temperature mechanical testing. The purpose of this testing would be to assess if these time and temperature variations have any impact on the mechanical performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Develop a new integrated macro→micro←nano (MMN) multiscale modeling framework to optimize high strength aluminum alloys and processes for vehicle light-weighting​

Bending tests provide a means to study plane strain fracture performance of 6000 series aluminum alloys. Metrics from bending tests have been correlated with self-pierce riveting (SPR) performance of a high strength AA6111 automotive aluminum alloy in previous works. Using the ORNL HPC resources, this project developed an innovative macro→micro←nano (MMN) multiscale microstructure-based finite element (FE) code to further understanding of the relationship between microstructure and fracture properties of high-strength 6000-series alloys. This work started with microstructural characterization in both mesoscale and nanoscale and bending performance characterization of AA6111 HS2-T6 alloy at Ford, the MMN framework was applied to this alloy to simulate 3-point VDA bending. From the results of the macro-modeling of 3-point VDA bending, the critical region of fracture was identified, and the region geometry was used to construct the micro-model. The fracture criterion of micron-scale precipitates and aluminum matrix which contains submicron and nano particles (AL-SMP-NP) in the micro-model was calibrated and validated by comparing simulated and measured bending results. With the AL-SMP-NP fracture strain obtained, the fracture strain of Al-matrix containing nano particles (ALNP) will similarly be determined by a submicron scale-model using an edge-constrained FE modeling approach developed by Hu et al. With the ALNP fracture strain obtained, the fracture strain of Al-matrix containing no particles will similarly be determined by a nano scale-model using an edge-constrained FE modeling approach. After the MMN framework is built and fracture criterion calibrated, nano-model FE simulations with virtual microstructures was performed to obtain a reduced order model (ROM) of the fracture criterion of the ALNP as a function of volume fraction, size, and distribution of the nanoparticle. This nano→submicron→micro modeling part allows exploration of the influence of different material nanostructures from different process conditions on the bending properties within the multiscale bending simulation framework and the ROM of material bendability as a function of nanoparticle size and shape was established. This obtained reduced order model (ROM) could help guide the design and selection of materials to improve existing SPR process models that could replace trial-and-error rivet/die selection and help to design new rivet/die combinations capable of robustly joining new higher strength 6000 5 series alloys in automotive body structures. This would enable lightweighting of Ford vehicles leading to greater fuel efficiency and reduce manufacturing time and energy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

60 years of science in ICF: from conception to scientific breakeven on the National Ignition Facility

The recent achievements of a burning plasma, fusion ignition, and scientific energy gain with deuterium-tritium (DT) fuel at Lawrence Livermore National Laboratory’s National Ignition Facility (NIF) represents a major milestone in the development of inertial confinement fusion (ICF) and all of fusion research. In these experiments, fuel pressures well in excess of hundreds of GBars were achieved in the compressed fuel, and robust alpha heating of the fuel, far in excess of the energy provided by the implosion, were demonstrated for the first time. These achievements occurred 60 years after the inception of ICF and the first laser demonstration, and were made possible by more than five decades of research at laser facilities around the world. Advances in laser technology both in wavelength and precision, motivated by improved understanding of laser-plasma interaction physics and the demands of targets; improvements in target fabrication inspired by the need to control and minimize hydrodynamic instabilities in the implosion; and multi-dimensional simulations and diagnostics have been critical to this achievement. This paper will summarize the scientific and technical advances, the surprises, and the challenges that had to be overcome to achieve these goals.

fusion↗
DOE OSTI2023

Analysing the effects of heating and gas puffing in Proto-MPEX helicon and auxiliary heated plasmas

The Material Plasma Exposure Experiment (MPEX) is being constructed at Oak Ridge National Laboratory to investigate critical fusion reactor issues, such as plasma–material interactions (PMIs) under reactor-relevant conditions and time scales. The linear device Proto-MPEX was used as a test bed to address anticipated research and development issues associated with heating scenarios and establish the physics basis for MPEX. The SOLPS-ITER code suite has been applied to understand plasma and neutral transport in Proto-MPEX and to increase confidence in predictive simulations for MPEX. Coupling between COMSOL and SOLPS is performed to implement a 2D electron heating profile of the helicon source. The simulations show reasonable agreement with the experimental data for plasma with helicon and auxiliary electron cyclotron heating (ECH). Both Bohm and constant diffusion (D$_\perp$: 0.5 m 2 s –1 and $\chi_\perp$: 1 m 2 s –1 ) simulations show similar levels of agreement with respect to the sparse experimental data available, assuming a few per cent impurity concentration. ECH significantly increases the target electron temperature, however, the target electron density is reduced compared to helicon-only heated plasmas due to an increase in flow velocity and radial losses. The simulations show that further increasing the ECH power results in an increase in the target electron density due to increased recycling flux and ionization. The results indicate that ECH significantly enhances the target heat flux, with ECH power of 50 kW increasing the target heat flux from 0.4 to 17 MW m –2 . It is found that a small amount of gas puffing (GP) near the target plate can further increase the target heat fluxes at the higher ECH power cases, but the target heat flux is reduced at higher GP conditions due to a significant reduction in electron temperature via radiation. ECH and GP scenarios can generate a higher target flux, facilitating improved PMI studies with more reactor-relevant plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Test Report for the Regulatory Testing of the Welded Isotek-SFC-W-3 Special Form Capsule

Two prototypes the welded ISOTEK-SFC-W-3 special form capsules (SFCs) of the same design were evaluated to determine if the requirements of Title 49, Code of Federal Regulations (CFR), Part 173.469, Tests for Special Form Class 7 (Radioactive) Materials, were met. The results of the special form tests are documented in this test report. This report describes the special form testing activities performed on the two welded ISOTEK-SFC-W-3 capsules. The test units were designated as TU-1 and TU-2. TU-1 was subjected to leak testing, percussion testing, and impact testing. TU-1 was leak tested using the leak rate test specified in 49 CFR 173.469(a)(4)(i). The impact test on TU-1 was conducted according to the requirements in 49 CFR 173.469 (b)(1). The percussion test that was carried out on TU-1 was conducted in accordance with 49 CFR 173.469 (b)(2). TU-2 was subjected to a leak rate test as specified in 173.469(a)(4)(i) and a heat test as specified in 49 CFR 173.469(b)(4). Each test unit was leak tested before and after these respective tests. The leak rate tests performed were helium back-pressure tests and bubble tests, as specified in American National Standards Institute (ANSI) N14.5-2014. The measured leak rates were converted to standard condition leak rates as specified in American Society for Testing and Measurement (ASTM) E 493. The determined standardized leak rates obtained from the test and the calculations for all the test units met the requirements for special form certification. The testing was performed under the direction of the Oak Ridge National Laboratory (ORNL) Package Testing Program (PTP).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Gamma Spectrometry Code Rodeo for Uranium Enrichment—FY 2021 Report

In FY22, the participating Department of Energy (DOE) laboratories continued the work on the project “Gamma Spectrometry Code Rodeo for Uranium Enrichment”. Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory (LLNL) continued their efforts to acquire spectra using uranium sources. A collimator (with side and back shields) was custom designed and constructed at ORNL. Spectra were acquired at ORNL using the uranium enrichment standards supplied by New Brunswick Laboratory (NBL) and the collimated M400 detector. Spectra were also acquired using steel absorbers of different thickness placed between the source and the collimated M400 detector. The plan was to ship the collimator to LLNL so that spectra could be acquired using the LLNL detector in collimated geometries. This activity was suspended since problems were noticed with the performance of the LLNL M400 detector. Also, it was brought to light to the project team that some of the aspects of the M400 detector had been updated by the vendor H3D in response to requests by the IAEA. In February 2021, the ORNL and LLNL M400 detectors were returned to the H3D factory in order to resolve the problems with the LLNL detector and to update ORNL and LLNL detectors to the same configuration as the M400 supplied to the IAEA. H3D repaired the LLNL M400 and performed the IAEA updates on both the ORNL and LLNL detectors. ORNL and LLNL received the detectors in April 2021. Data acquisition was continued using the upgraded detectors. ORNL re-collected the spectra using point sources and the NBL standards in uncollimated and collimated geometries. The collimator was shipped from ORNL to LLNL. Spectra were acquired at LLNL through Q4 of FY22. When the ORNL spectra were examined closely, it became apparent that there were spurious artifacts present in some of the spectra. This rendered suspect the ORNL spectra collected in June/July 2021 time frame. ORNL contacted H3D and per H3D’s advice, the M400 detector was returned to H3D for repairs in mid-August 2021. H3D diagnosed the problem and established that the root cause was the extra tight packaging that created a strain on the CZT crystals, causing one of them to break down. The repaired M400 was returned to ORNL in early September 2021. ORNL re-started data acquisition for the third time. Data was continued to be acquired at ORNL and LLNL through September 2021. The ORNL and LLNL data will be shared with the principal investigators from the analyzing laboratories. The GADRAS code and FRAM have been developed to have the capability to analyze the M400 spectra. Good quality spectra from FY21 have been analyzed using modified versions of GADRAS and FRAM. The spectra have also been analyzed using the GEM code. The analysis results from GADRAS, FRAM and GEM codes are presented and discussed in this report. Some preliminary results from FRAM and GEM analysis were presented in February 2021 at the U-Pu Isotopics Workshop sponsored by the IAEA. CZTU code is being modified to analyze M400 spectra. Data collection, code development and analysis will be continued in FY22 as per the FY22 Project Work Plan (PWP).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Evaluation of PBR Spent Fuel Criticality and Dose Rate Compliance for Storage and Transportation

Spent tri-structural isotropic (TRISO)–based fuels have a strong track record in storage and transportation without documented incidents. This work seeks to reduce uncertainty to aid in more informed spent fuel management of TRISO-based fuels by modeling both fresh and spent pebble bed reactor (PBR) fuel and comparing the results to the regulatory standards from 10 CFR 71. SCALE was used for all modeling due to it having fast and accurate methods for handling PBR fuel modeling, as well as having an efficient method for shielding calculations in monaco with automated variance reduction using importance calculations (MAVRIC), which utilizes the consistent adjoint-driven importance sampling (CADIS) and the forward-weighted consistent adjoint-driven importance sampling (FW-CADIS) methods. KENO-VI was used for all criticality calculations, TSUNAMI was used for uncertainty quantification on k-effective, TRITON and the Oak Ridge isotope generation code (ORIGEN) were both used for depletion of the fuel, and MAVRIC was used for shielding calculations. For criticality assessments, this study focused on the requirement that the value of the neutron multiplication factor, k-effective (k-eff), would not exceed a peak value of 0.95, including uncertainty, with 95% confidence. Criticality was initially examined by modeling fresh fuel from three different designs—HTR-10 fuel, PBMR-400 fuel, and demonstration fuel representative of a TRISO-fueled modern high-temperature gas reactor (HTGR) design, henceforth referred to as Demo HTGR—and placing them into various sized containers with conditions described in 10 CFR 71 to quantify the peak k-eff state. When the peak value of 0.95 k-eff was exceeded, mitigation methods were examined in those scenarios. Burnup credit, pebble displacement in areas of strong neutron multiplication, and random pebble replacement using pebbles of various compositions and replacement fractions were examined. In summary, the criticality of PBR fuels can be well accounted for by restricting container size, taking credit for burnup, or by displacing/replacing pebbles. Uncertainty of the k-eff due to nuclear data uncertainties was recorded at ~0.6644%Δk/k, or roughly 664% mil (pcm). The nuclear data–induced uncertainty was relatively small and should not require significant modification in the design to be accounted for. Revisions to the evaluated nuclear data file values have been shown to have a larger impact than nuclear data–induced uncertainty. For dose rate aspects, U.S. Nuclear Regulatory Commission regulations require a maximum dose rate of 10 millirem per hour (mrem/h) at 2 meters. In examining the dose rate behavior of spent PBR fuel, the representative Demo HTGR fuel was modeled exclusively due to it possessing the highest target burnup of the examined fuels. Equilibrium cycle modeling methods were used to produce a higher-fidelity discharge isotopic composition than simple assumptions, such as reflected pebbles. The discharge composition was used as a source term in the fixed-source transport shielding calculations, and dose rates were calculated at 2 m for the shortest possible cooling time. The low concentration of fuel material led to dose rates that were in line with regulatory limits, despite the high burnup when compared to traditional light water reactor fuels. In conclusion, the methods employed in this study would require more work to further verify and validate and are limited to the criticality and dose rate analyses performed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Core Design of the Holos-Quad Microreactor

The Holos-Quad micro-reactor concept, developed by HolosGen LLC, is equipped with a 22 MWt (Mega-Watt thermal) core and an integral power conversion system converting the core thermal energy into approximately 10 MWe (Mega-Watt electric). This design can be configured to support a wide range of applications. It is a very innovative high-temperature gas-cooled reactor concept using TRI-structural ISOtropic particle fuel (TRISO) distributed in graphite hexagonal blocks, cooled with helium in a direct Brayton cycle independently executed by four Subcritical Power Modules (SPMs) fitted into a hardened 40-foot container whose dimensions are in compliance with ISO shipping containers requirements. In FY2019 HolosGen LLC was awarded by the Department of Energy Advanced Research Project Agency-Energy (DOE ARPA-E) under the MEITNER funding program. As part of the MEITNER award, the Argonne National Laboratory (ANL) contributed expertise through two specialized teams: The “Design Team” and the “Resource Team”. The Design Team was dedicated to validate feasibility of the Holos-Quad core and to optimize its core design through neutronics analyses. The Resource Team was dedicated to feasibility verification via high-fidelity codes of Holos-Quad thermal-hydraulic, heat transfer, shielding, and structural aspects. This report summarizes the activities conducted by ANL Design Team. A rigorous design approach based on multi-criteria optimization and code-to-code comparison involving stochastic and high-fidelity deterministic solutions was developed and employed at several evolutionary stages of the Holos-Quad design. Several generations of the Holos-Quad core were designed within this project before converging to the current full-scale Gen 2+ design that is detailed in this report. Figure EA-1 illustrates a cross-sectional view of Gen 2+ Holos-Quad core configuration, and Figure EA-2 provides a simplified perspective view of 1-of-4 SPMs. The Holos-Quad uses four thermal-hydraulically independent SPMs locked into stationary positions during power operation, surrounded by BeO reflector and structural component fully comprised within the dimensional constraints represented by traditional ISO containers. One of the benefits of this approach is to enable transportation of each SPM promptly after irradiation in shielded containers. The core is designed to operate for approximately 8 full-power years while the reactivity controls and power conversion system enable load-following operations. The reactivity controls are represented by independent, diversified, and redundant reactivity control systems based on control drums and redundant sets of shutdown rods. The high-fidelity simulation tools were used to assess detailed power and flux distributions of the three-dimensional full-core or quarter-core of the Gen 2+ configuration. Single-physics and multi-physics simulations of the neutronics code PROTEUS and the thermal-hydraulic code System Analysis Module (SAM) were performed to analyze the Holos design configurations with detailed high-fidelity solutions. The design work performed confirmed feasibility of the Holos-Quad concept, provided realistic design description for detailed design of the operational system, and identified several core design improvements to be further considered for future reactor development activities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Design of Nuclear Criticality Safety Framework for Hands-on Construction of Fast Systems Over Ranges of Multiplication

Since 1945, Los Alamos National Laboratory (LANL) has performed critical experiments, primarily at the Los Alamos Critical Experiments Facility (LACEF) at Technical Area 18 (TA-18). Since 2011, these experiments have been conducted by the National Criticality Experiments Research Center (NCERC), operated by LANL, at the Device Assembly Facility (DAF) in the Nevada National Security Site (NNSS). These experiments utilize various types of Special Nuclear Material (SNM). Some of these experiments utilize what is referred to as the Rocky Flat Shells, which are called such as they came from the Rocky Flats Plant. These concentric hemi-shells are made of Highly Enriched Uranium (HEU), which is 93 w/o 235U. Fig. 1. Subset of the Rocky Flat Shells LANL is designing a new subcritical hands-on experiment with the goal of achieving a neutron multiplication in the range of 50 to 200, which correlates to Keff values of 0.98 to 0.995. ANSI/ANS-1 is the standard for Conduct of Critical Experiments which governs critical operations at NCERC. Section 3.9 of ANSI/ANS-1 states that when manipulating a critical assembly by hand, the predicted k eff of a known configuration should not exceed 0.95 (a neutron multiplication of 20). This presents a challenge, as this system would have a higher multiplication than 20 and the assembly would have to remain subcritical in normal and credible accident scenarios. To ensure the safety of such an assembly, the different normal and abnormal conditions that could alter the criticality 1 MCNP® and Monte Carlo N-Particle® are registered trademarks owned by Triad National Security, LLC, manager and operator of Los Alamos National Laboratory. Any third party use of such registered marks should be properly of the system must be considered and analyzed. If such a condition is deemed to be credible, it will be further investigated using the Monte Carlo N-Particle (MCNP) transport code. If the results of these simulations show that a k eff larger than one could be possible, modifications to the assembly will be made until such an event is deemed no longer possible.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Supporting information for Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

In this work, we use few-shot learning to segment the body and vein architecture of P. trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the vein density trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code (see https://github.com/jlager/few-shot-leaf-segmentation), we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes. The data folder includes all images, ground truth segmentations, predicted segmentations, and extracted leaf traits. All images encode the sample ID in the file name by indicating the treatment, block, row, position, and leaf side, respectively. For example, the file, C_1_1_2_bot.jpeg, indicates the control treatment, block 1, row 1, position 2, and the bottom side of the leaf. Tabulated results include position IDs as well as the corresponding genotype IDs. The images folder includes the 2,906 high-resolution leaf scans taken in the field. The leaf_masks folder includes 50 ground truth segmentations used for training the leaf tracing algorithm. The leaf_preds folder includes the 2,906 predicted segmentations from the leaf tracing algorithm. The vein_masks folder includes 8 ground truth segmentations used for training the vein growing algorithm. The vein_preds folder includes the 1,453 predicted segmentations from the vein growing algorithm. The vein_probs folder includes the 1,453 predicted probability maps from the vein growing algorithm before thresholding. The genomes folder includes the set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes with a README file detailing the steps taken. The results folder includes: (i) raw values of the 68 predicted leaf traits in digital_traits.tsv, (ii) manually measured values of petiole length and width in manual_traits.tsv, (iii) thin plate spline (TPS) adjusted values of the vein density trait in vein_density_tps_adj.tsv, (iv) best linear unbiased prediction (BLUP) adjusted values of the vein density trait in vein_density_blups.tsv, and (v) GWAS results for the vein density trait, including chromosome positions and corresponding P values, in gwas_results.csv.

09 BIOMASS FUELS↗
DOE OSTI2024

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Diversion Path Analysis: A Proposed Methodology to Develop an MC&A Approach for Liquid-Fueled Molten Salt Reactors

Nuclear material control and accounting (MC&A) is a critical element of both the US Nuclear Regulatory Commission (NRC) and US Department of Energy (DOE)’s domestic safeguards and security requirements. NRC licensees are required, under Title 10 of the Code of Federal Regulations (10 CFR) Part 74 to establish and maintain an MC&A program that captures and records the quantities and locations of special nuclear material (SNM) at the facility. Along with physical protection, MC&A is a key element of domestic nuclear material safeguards that enables the NRC to ensure that SNM is controlled and accounted for. SNM, per 10 CFR Part 74, refers to plutonium, 233 U, and uranium enriched in the isotope 233 U or 235 U, but does not include source material. Periodic physical inventories, coupled with material balance evaluations, are effective and demonstrated tools to account for and detect theft or diversion of SNM in facilities containing SNM in bulk material form (i.e., not in discrete, countable items). Historically in the United States, these types of facilities have included fuel fabrication, conversion, and enrichment facilities. In comparison, reactors have relied on item counting of assemblies and control of SNM while in containment (e.g., a sealed reactor pressure vessel) because, to date, reactor fuel has been in item form. In liquid-fueled molten salt reactors (MSRs), unlike traditional light water reactors (LWRs) or bulk facilities, bulk SNM quantities can change significantly during operation as a result of depletion and transmutation. This introduces challenges to the use of traditional periodic physical inventories and material balance evaluations to detect theft or diversion of SNM in reactors that use SNM in bulk material form. Liquid-fueled (i.e., salt-fueled) MSR facilities are MSRs that use SNM within a salt eutectic as the fuel. The SNM is in a bulk material form any time it is outside of fresh or spent fuel storage containers. Some examples of when SNM will be in bulk form in the facility are during addition of fuel to the reactor system, while fuel is circulating in operation, and while fuel is in a drain tank. Periodic physical inventories and material balance evaluations can likely be effectively applied to many portions of an MSR facility, including all areas where depletion and transmutation are not significantly changing the quantities of SNM within the control area. Within an MSR facility, this would include fresh fuel receipt and loading, waste streams that may contain SNM, irradiated fuel storage outside of the reactor core, and any irradiated fuel processing that may happen after SNM has been removed from the reactor. All of these process steps could rely on measurements of SNM quantities compared with documented inventories. Any discrepancies from predicted (i.e., book) inventories and measured inventories could be quantified as inventory differences, consistent with traditional MC&A guidance from the NRC (e.g., in NUREG-1065 Revision 2, NUREG-2159 Revision 1, and RG 5.29 Revision 2). Within the reactor system, additions and removals to the book inventory include depletion of the SNM (e.g., fission of 235 U), which complicates the use of physical inventories. SNM control, however, can also likely be effectively applied to detect theft of SNM throughout a liquid-fueled MSR facility. To complement these approaches, prior technical reports have identified that a diversion path analysis may be a useful, risk-informed, and performance-based tool to determine suitable elements of an MC&A approach for the reactor system within a liquid-fueled MSR facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

High-dimensional Data-driven Energy optimization for Multi-Modal Transit Agencies (HD-EMMA) (Final Technical Report)

Public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. Electric vehicles (EVs) can have a much lower environmental impact than comparable internal combustion engine vehicles (ICEVs), especially in urban areas. Unfortunately, EVs are also much more expensive than ICEVs. As a result, many public transit agencies can afford only mixed fleets of transit vehicles, consisting of EVs, hybrids (HEVs), and ICEVs. Transit agencies that operate such mixed fleets of vehicles face a challenging optimization problem: these agencies need to decide which vehicles are assigned to serving which transit trips. Since the advantage of EVs over ICEVs varies depending on the route and time of day (e.g., the benefit of EVs is higher in slower traffic with frequent stops and lower on highways), the assignment can have a significant effect on energy use and, hence, environmental impact. Through this project, we have developed reference data about energy collections and constructed a set of machine learning models that can accurately predict the energy consumption for the whole fleet at the level of each trip. We have used these models to develop a scheduling and assignment strategy that can rotate the different vehicle types across the transit agencies’ routes. The optimization algorithm ensures that the vehicles are matched to trips considering weather patterns, expected congestion, and road gradients to minimize the overall energy usage. We list the key observations from our project for other practitioners below. Details are available in the report, and the list of source code and our publications are included in the appendix. 1. We have demonstrated the feasibility of collecting, merging and analyzing large volumes of high-resolution real-world telemetry data from a mixed vehicle fleet. To mitigate the inherent noise of the recorded GPS points, the team developed an algorithm that filters data and maps the points onto a street. The algorithm considers previous and subsequent location measurements and different characteristics of nearby streets to determine how likely the vehicle travels on them. Then, the team segmented the time series into disjoint contiguous samples based on adjacent road segments and repeated the outlier detection and removal. For each data point, the team added features corresponding to elevation changes within the samples, weather features, such as temperature, and traffic data, such as speed ratio between actual speed and free-flow speed. 2. We have developed two forms of machine learning models that be used to understand and analyze the energy operations of a mixed vehicle transit fleet. The micro prediction model provides estimates of instantaneous energy prediction for all types of buses (diesel, hybrid, and electric). Such a model is important in evaluating the energy impacts of real-time bus operation strategies, but it is challenging due to diversified driving cycles of transit buses. The model can help the drivers understand the impact of their driving behaviors and short-term congestions. The macro prediction models estimate average energy consumption across the whole trip considering the features: distance traveled, various road-type features, elevation change, day of the week, time of day, various weather features (temperature, humidity, etc.), and traffic features (speed ratio and jam factor). 3. We have demonstrated that it is possible to transfer the machine learning models we have developed in this project to other teams and cities by using inductive transfer learning. We also showed that the performance of the macro energy prediction models can be improved using a multi-task learning approach where the learning parameters are shared between the models being developed for different vehicle types. The advantage of this approach is improved learning performance as the models can exploit common spatio-temporal and environmental characteristics. 4. Finally, we have developed trip and vehicle assignment and scheduling algorithms that use the energy prediction models and develop a trip to vehicle type (diesel, electric, hybrid) assignment for the whole operation to reduce overall emissions and cost. We have shown through simulations that the proposed algorithms can save $\$$ 48,910 in energy costs and 175 metric tons of CO 2 emission annually for CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Design Study for Bio-Oil Production from Biomass Using a Dual Fluidized-Bed Reactor

To evaluate the re-design and reconfiguration of a dual-fluidized bed (DFB) gasification system into a recirculating pyrolysis reactor, Computation Fluid Dynamic (CFD) simulations of the system were conducted. The Barracuda Virtual Reactor® computational particle fluid dynamic code was used to perform simulations of the pyrolysis process. Modeling of the chemical reaction kinetics for both gas phase and solid particle phase were included. The recirculating pyrolysis reactor shown in Fig. 1a is based on a bubbling-bed biomass pyrolyzer and a riser combustor to convert the remaining char. The operational differences in the re-configuration of the DFB gasification system into a recirculating pyrolysis system for the production of bio-oil are (1) replacement of a low-surface area inert bed material with a high-surface-area bed material that has acidic properties to provide catalytic activity for the production of bio-oil with reduced oxygen content, (2) lower temperature and residence time for bio-oil production from pyrolysis, (3) replacement of the fluidization gas in the bubbling bed pyrolyzer from steam to nitrogen, and (4) the reduction of pyrolyzer freeboard volume. The bed material used for catalytic pyrolysis is Sasol 300 (300-micron dia., bulk density 0.94 kg/l, and surface area 130 m2/g) and is a theta-alumina with mild acidity. This is in comparison with previous standard bed material Carbo HSP (430-micron dia., bulk density 2.01 kg/l, and surface area 0.03 m2/g) used for gasification. For bio-oil production, pyrolysis in the bubbling bed requires temperatures in the range of 550 C in comparison with gasification temperatures near 850 C. To attain this lower temperature requires management of the energy mass balances, with control of the bed material recirculation rate between bubbling bed pyrolyzer and riser combustor, the introduction of a nitrogen purge in the pyrolyzer, and adjusting the pressure balance between the two vessels. To extract bio-oil from the pyrolysis reactor with a snorkel, two different freeboard configurations were evaluated. In Fig. 1 b the existing high freeboard configuration is shown and in Fig. 1 c the reduced freeboard design is presented. The introduction of a nitrogen purge for the high free board configuration provided the highest bio-oil production from the CFD simulations. To decrease the bed-material circulation rate, primary and secondary air on the combustor side were reduced, and the pressure on the combustor was slightly increased. A portion of the biomass and bio-oil was observed to be transported to the combustor, leading to a smaller pyrolysis yield. The control of the pyrolyzer temperature is performed by controlling the circulation rate. Good fluidization of the bubbling bed and cascade PID control are required to keep the temperature from oscillating due to large time delay experienced when changing primary and secondary air. (a) (b) (c) Figure 1. (a) Dual Fluidized Bed pyrolysis system configuration, (b) mole fraction of nonpolar biooil in high freeboard configuration, and (c) mole fraction of nonpolar bio-oil in low freeboard configuration with nitrogen purge introduced in both configurations.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗