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Containerless Ripple Turbulence

One of the longest standing unsolved problems in physics relates to the behavior of fluids that are driven far from equilibrium such as occurs when they become turbulent due to fast flow through a grid or tidal motions. In turbulent flows the distribution of vortex energy as a function of the inverse length scale [or wavenumber 'k'] of motion is proportional to 1/k(sup 5/3) which is the celebrated law of Kolmogorov. Although this law gives a good description of the average motion, fluctuations around the average are huge. This stands in contrast with thermally activated motion where large fluctuations around thermal equilibrium are highly unfavorable. The problem of turbulence is the problem of understanding why large fluctuations are so prevalent which is also called the problem of 'intermittency'. Turbulence is a remarkable problem in that its solution sits simultaneously at the forefront of physics, mathematics, engineering and computer science. A recent conference [March 2002] on 'Statistical Hydrodynamics' organized by the Los Alamos Laboratory Center for Nonlinear Studies brought together researchers in all of these fields. Although turbulence is generally thought to be described by the Navier-Stokes Equations of fluid mechanics the solution as well as its existence has eluded researchers for over 100 years. In fact proof of the existence of such a solution qualifies for a 1 M$ millennium prize. As part of our NASA funded research we have proposed building a bridge between vortex turbulence and wave turbulence. The latter occurs when high amplitude waves of various wavelengths are allowed to mutually interact in a fluid. In particular we have proposed measuring the interaction of ripples [capillary waves] that run around on the surface of a fluid sphere suspended in a microgravity environment. The problem of ripple turbulence poses similar mathematical challenges to the problem of vortex turbulence. The waves can have a high amplitude and a strong nonlinear interaction. Furthermore, the steady state distribution of energy again follows a Kolmogorov scaling law; in this case the ripple energy is distributed according to 1/k (sup 7/4). Again, in parallel with vortex turbulence ripple turbulence exhibits intermittency. The problem of ripple turbulence presents an experimental opportunity to generate data in a controlled, benchmarked system. In particular the surface of a sphere is an ideal environment to study ripple turbulence. Waves run around the sphere and interact with each other, and the effect of walls is eliminated. In microgravity this state can be realized for over 2 decades of frequency. Wave turbulence is a physically relevant problem in its own right. It has been studied on the surface of liquid hydrogen and its application to Alfven waves in space is a source of debate. Of course, application of wave turbulence perspectives to ocean waves has been a major success. The experiment which we plan to run in microgravity is conceptually straightforward. Ripples are excited on the surface of a spherical drop of fluid and then their amplitude is recorded with appropriate photography. A key challenge is posed by the need to stably position a 10cm diameter sphere of water in microgravity. Two methods are being developed. Orbitec is using controlled puffs of air from at least 6 independent directions to provided the positioning force. This approach has actually succeeded to position and stabilize a 4cm sphere during a KC 135 segment. Guigne International is using the radiation pressure of high frequency sound. These transducers have been organized into a device in the shape of a dodecahedron. This apparatus 'SPACE DRUMS' has already been approved for use for combustion synthesis experiments on the International Space Station. A key opportunity presented by the ripple turbulence data is its use in driving the development of codes to simulate its properties.

Putterman, Seth↗

SLS Navigation Model-Based Design Approach

The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and management of design requirements to the development of usable models, model requirements, and model verification and validation efforts. The models themselves are represented in C/C++ code and accompanying data files. Under the idealized process, potential ambiguity in specification is reduced because the model must be implementable versus a requirement which is not necessarily subject to this constraint. Further, the models are shown to emulate the hardware during validation. For models developed by the Navigation Team, a common interface/standalone environment was developed. The common environment allows for easy implementation in design and analysis tools. Mechanisms such as unit test cases ensure implementation as the developer intended. The model verification and validation process provides a very high level of component design insight. The origin and implementation of the SLS variant of Model-based Design is described from the perspective of the SLS Navigation Team. The format of the models and the requirements are described. The Model-based Design approach has many benefits but is not without potential complications. Key lessons learned associated with the implementation of the Model Based Design approach and process from infancy to verification and certification are discussed

Oliver, T. Emerson↗

Reactor Pressure Vessel Fracture Mechanics Development and Concrete Application Testing for Grizzly

The Grizzly code is being developed to address degradation issues in nuclear reactor structures and components. For light-water reactors, Grizzly currently has capabilities to simulate degradation processes and their effects on structural integrity in two key areas: reactor pressure vessels (RPVs) and reinforced concrete structures. This report documents improvements made to Grizzly’s ability to address both of these structural systems. For RPVs, the reduced-order models (ROMs) used in fracture mechanics calculations have been expanded to allow their application over a broader range of the parameter space than was permitted by the previous models. The ROMs currently used in Grizzly for the evaluation of flaws that are fully embedded within the RPV (as opposed to surface-breaking flaws) are based on a model that is known to be conservative, indicating higher stress intensity factors than would be obtained from direct simulations. A more accurate model that eliminates these excess conservatisms has been recently included in the American Society of Mechanical Engineers Boiler and Pressure Vessel Code but was not applicable for flaws near the RPV surface, which is where the most critical flaws are usually located. That model has recently been extended for increased applicability in this near-surface region. The ROMs for embedded flaws in the Grizzly code have been expanded to include these recent extensions, which permit their use in a much broader set of cases than previously possible. Direct 3D simulations have been used to check these ROMs and have shown good agreement in most cases, although there are still some cases that need further investigation. There are considerable benefits to using these these more accurate and less conservative ROMs for embedded flaws. On a benchmark probabilistic fracture mechanics problem tested here, the conditional probability of fracture initiation computed for a population of flaws in a single plate in an RPV decreased by over a factor of 3. To address aging in reinforced concrete structures, a capability to simulate multiple degradation mechanisms, including alkali-silica reaction and radiation-induced volumetric expansion has been developed in Grizzly over the past several years. This had previously been demonstrated on laboratory-scale specimens but not on full-scale nuclear concrete structures with reinforcement. To demonstrate the applicability of Grizzly to the analysis of large-scale structures of interest, a full 3D model of a representative reinforced concrete structure, including a complex arrangement of reinforcing bars, was developed and demonstrated in Grizzly.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Effects of Chlorine Capture and a Proposed Density Law on the Reactivity of Plutonium Solution Systems

During fissionable material processing, all normal and credible abnormal conditions must remain safely subcritical. Nuclear Criticality Safety (NCS) uses a number of methods to determine subcriticality, one of which is the use of neutron transport codes such as MCNP6. In order to create models for use with MCNP6, both the geometry and materials in fissionable material processes must be known, or assumptions must be made and quantified for the impact to bias. One of the systems with a significant amount of bias due to material modeling assumptions is in the area of aqueous plutonium processing. These solutions are typically plutonium nitrate solutions or plutonium chloride solutions, which are modeled as fictitious plutonium metal-water mixtures because little is known about the actual density of the solution and there is no current predictive capability approved for use at Los Alamos National Laboratory (LANL) for modeling them. This research is currently underway to fill the gap and develop an algorithm for use with MCNP6 to model the density of plutonium chloride solutions. The method is to be validated with experimental data for density, and also validated with critical experiments using MCNP6. Note that the Chlorine Worth Study (CWS) was performed in December 2021 to help bridge the gap in chlorine data for critical experiments, and is currently awaiting International Criticality Safety Benchmark Evaluation Project (ICSBEP) review. This study was performed by LANL at the National Criticality Experiments Research Center (NCERC) at the Nevada National Security Site (NNSS). Additional information regarding this experiment may currently be found in LA-UR- 22-29180. Additionally, the Chemistry-Actinide Analytical Chemistry (C-AAC) at LANL has performed a number of solution density measurements for PuCl 3 -HC 1 -H 2 O, allowing for such data be used to create a semi-empirical density via the Pitzer method. The published dataset for the measurements is documented in LA-UR-22-25454. This method has already been tested successfully for aqueous plutonium nitrate solutions in SCALE. Current solution density measurements exist of plutonium concentrations of 0-~142g/L, all at 2M HC1, at temperatures 20-40°C. Additional data was taken for HC1-corrected density values, which essentially mimics the data for a pure PuCl x -water solution. The calculations in this report aim to support the current research by demonstrating the difference in system reactivity for the current modeling method when compared to the new proposed modeling with a density law implementation, which is being written as a Python tool to be used with MCNP6.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Prefabricated High-Strength Rebar Systems with High-Performance Concrete for Accelerated Construction of Nuclear Concrete Structures

This project aimed to reduce the field construction times and fabrication costs of reinforced concrete (RC) nuclear structures through the use of: 1) high-strength steel deformed reinforcing bar (rebar); 2) prefabricated high-strength rebar (HSR) assemblies with headed anchorages; and 3) high-strength concrete (HSC). The focus of the project was not to develop new innovations on materials, but rather to fill a major knowledge gap on the effectiveness, code conformity, and viability (i.e., practicality, commercial availability) of existing high-strength materials in nuclear structures, especially in shear walls, their connections/joints, and around penetrations. These advances promote the Nuclear Energy Enabling Technologies Advanced Methods for Manufacturing (NEET-1) goals of accelerating deployment schedules by at least 6 months and reducing component fabrication costs by 20% or more. Toward this vision, the following objectives were identified and completed: Develop limit-benefit and cost-benefit analysis frameworks: The structural and economic limits and benefits of HSR and HSC in nuclear walls were evaluated. Importantly, it was found that modest increases in concrete strength up to 10.0 ksi and rebar yield strength up to 100 ksi result in the most economic designs and improved structural performance (Barbachyn et al., 2017a and Barbachyn et al., 2017b). Also, an industry survey was distributed to determine the cost benefits associated with prefabrication. Importantly, on-site worker-hours are significantly reduced, allowing for significantly accelerated construction schedules (Devine et al. 2018b). Develop an optimization methodology for structural design: An optimization study was deemed not necessary since the trivial solution with maximized use of high-strength materials and prefabrication always resulted in the largest cost and time savings. Instead, the benefits (and limits) of high-strength materials and prefabrication on construction costs and on-site construction time were investigated through a parametric study. Cost-reductions through the use of HSR and HSC were found to be greater than 40%. Also, on-site construction time of nuclear shear walls can be reduced by up to 83% through the use of prefabricated rebar assemblies. Conduct experimental evaluations of nuclear shear walls and wall-foundation joints: A large scale experimental program was completed on shear-critical RC cantilever deep beams. From these experiments, it was demonstrated that increasing rebar yield strength had a greater effect on increasing lateral strength than increasing the concrete compressive strength. Further, using HSR together with HSC resulted in the highest lateral strength and displacement ductility (Devine et al. 2018a). Additionally, large-scale reversed-cyclic lateral load tests were conducted on RC shear walls. It was demonstrated that through the utilization of HSR and HSC, a wall with 55% reduced vertical and horizontal rebar area was able to achieve 91% of the peak lateral strength of a conventional wall using state-of-practice materials with the same geometry. Further, trim reinforcement with headed anchorages around the penetrations proved to be effective. Develop validated numerical simulation models: Numerical modeling was completed in two phases during this project using 3 different finite element software packages. The first phase used existing measured data from previous experimental studies on stocky RC walls to validate simplified predictive models. Models using two different programs were validated based on a database of 38 stocky walls (Barbachyn et al., 2017a). The second phase occurred after experimental testing using a third and more detailed finite element package. Prediction improvements for the initial stiffness, lateral deformations, damage propagation, and failure mechanisms were targeted. The resulting detailed models more accurately predicted the peak lateral strength, initial and secant stiffnesses, lateral deformations, and cracking patterns of the wall test specimens subjected to reversed-cyclic lateral loading as compared to the simplified pretest models. Develop validated design procedures, tools, and criteria: This project evaluated the accuracy of existing closed-form design equations from U.S. building design standards and previous research (Barbachyn et al. 2017a and Devine et al. 2018a). It was shown that the current predictive equations for shear strength capacity need to be revisited as they provide significant scatter and gross overestimates, indicating the potential for unconservative designs. Further, for both the deep beam and shear wall specimens, the numerical models and flexural capacity predictions provided the most accurate strength predictions. Develop cost-effective field construction procedures: To promote the use of prefabricated rebar assemblies, the following construction conditions where prefabrication would be used instead of in-place rebar tying were identified from an industry survey: 1) to save on construction schedule; 2) to improve safety and/or quality control; 3) for areas with heavy rebar congestion; and 4) for structures with significant repetition in rebar layout. All of these conditions directly apply and benefit nuclear construction where construction costs and schedules are extensive, safety and quality are of utmost importance, the reinforcement is extremely dense, and the reinforcement layout is repetitive in many regions of the shear walls. Additionally, an experimental study was conducted to investigate the changes in bar spacing (with respect to code-required rebar spacing and placement tolerances) when a horizontally assembled prefabricated two-dimensional (2D) rebar mat or three-dimensional (3D) rebar cage is lifted (or tripped) to a vertical position. It was found that the bars involved in both the lateral translation of the rebar assemblies (i.e., movement of the assembly in its horizontal position) and the tripping process were most susceptible to large spacing changes, and thus, their positions within the assembly would need to be checked after the placement of the assembly in place within the formwork. Importantly, the spacings of all of the other bars in the assembly were not affected significantly by the lateral translation and tripping process, thereby eliminating the need to recheck their positions within the assembly (Devine et al. 2018b).

36 MATERIALS SCIENCE↗

Investigation of Spiral Bevel Gear Condition Indicator Validation Via AC-29-2C Using Damage Progression Tests

This report documents the results of spiral bevel gear rig tests performed under a NASA Space Act Agreement with the Federal Aviation Administration (FAA) to support validation and demonstration of rotorcraft Health and Usage Monitoring Systems (HUMS) for maintenance credits via FAA Advisory Circular (AC) 29-2C, Section MG-15, Airworthiness Approval of Rotorcraft (HUMS) (Ref. 1). The overarching goal of this work was to determine a method to validate condition indicators in the lab that better represent their response to faults in the field. Using existing in-service helicopter HUMS flight data from faulted spiral bevel gears as a "Case Study," to better understand the differences between both systems, and the availability of the NASA Glenn Spiral Bevel Gear Fatigue Rig, a plan was put in place to design, fabricate and test comparable gear sets with comparable failure modes within the constraints of the test rig. The research objectives of the rig tests were to evaluate the capability of detecting gear surface pitting fatigue and other generated failure modes on spiral bevel gear teeth using gear condition indicators currently used in fielded HUMS. Nineteen final design gear sets were tested. Tables were generated for each test, summarizing the failure modes observed on the gear teeth for each test during each inspection interval and color coded based on damage mode per inspection photos. Gear condition indicators (CI) Figure of Merit 4 (FM4), Root Mean Square (RMS), +/- 1 Sideband Index (SI1) and +/- 3 Sideband Index (SI3) were plotted along with rig operational parameters. Statistical tables of the means and standard deviations were calculated within inspection intervals for each CI. As testing progressed, it became clear that certain condition indicators were more sensitive to a specific component and failure mode. These tests were clustered together for further analysis. Maintenance actions during testing were also documented. Correlation coefficients were calculated between each CI, component, damage state and torque. Results found test rig and gear design, type of fault and data acquisition can affect CI performance. Results found FM4, SI1 and SI3 can be used to detect macro pitting on two more gear or pinion teeth as long as it is detected prior to progressing to other components or transitioning to another failure mode. The sensitivity of RMS to system and operational conditions limit its reliability for systems that are not maintained at steady state. Failure modes that occurred due to scuffing or fretting were challenging to detect with current gear diagnostic tools, since the damage is distributed across all the gear and pinion teeth, smearing the impacting signatures typically used to differentiate between a healthy and damaged tooth contact. This is one of three final reports published on the results of this project. In the second report, damage modes experienced in the field will be mapped to the failure modes created in the test rig. The helicopter CI data will then be re-processed with the same analysis techniques applied to spiral bevel rig test data. In the third report, results from the rig and helicopter data analysis will be correlated. Observations, findings and lessons learned using sub-scale rig failure progression tests to validate helicopter gear condition indicators will be presented.

gears↗

SWIPE: Spectral Water Inversion Processor and Emulator

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will be discussing the progress made developing SWIPE: Spectral Water Inversion Processor and Emulator. SWIPE is a platform for advanced modeling of coastal and inland aquatic habitats. The goal is create a comprehensive and cohesive system to leverage recent advancements in computation and machine learning to develop a synthetic training ground for sensitivity studies and algorithm development. The four principal facets of SWIPE include: 1. Advanced two-layer coated sphere bio-optical modeling and GPU radiative transfer modeling, 2. Big Data involving massive synthetic spectral libraries of optical properties of various global aquatic particles, surface reflectance, and top-of-atmosphere reflectance, all at hyperspectral resolution leveraging high-end computing systems at NASA Ames Research Center, 3. Deep Learning for algorithm development for water quality inversion of concentrations of common biogeophysical variables as well as optics, full uncertainty characterization by water type, and forward emulation, and lastly, 4. Image Processing for application of developed retrieval algorithms for both hyperspectral and multispectral sensors with experimental corrections for global adjacency, noise, sunglint, and benthic reflectance. This presentation will demonstrate the Equivalent Algal Populations (EAP) two-layer coated sphere scattering model which has been used develop spectral libraries of hyperspectral inherent optical properties of roughly 80 species of phytoplankton, covering 15 different classes and nine taxonomic functional types. The EAP model was also used to derive spectral properties of 10 different non-algal particle functional types. Examples of how the SMART-G (Speed-up Monte-carlo Advanced Radiative Transfer using GPU) radiative transfer code is used to model optically complex aquatic signals will be presented and discussed in the context of creating a massive synthetic database which can leverage the full power of next generation machine learning techniques and high end computing for water quality inversion. We will discuss our active investigation in things like appropriate model architectures, dimensionality reduction techniques such as PCA and autoencoders, uncertainty quantification and abstaining, and which variables actually benefit most from hyperspectral information versus multispectral resolution. We are also curious about questions relating to cost/benefit analysis in terms of computation resources, neural network complexity, and data volumes. Answers to these questions will hopefully elaborate on cost efficiency for potential future sensor design considerations.

SWIPE↗

Test Plan for the Horizontal Dry Cask Simulator

The thermal performance of commercial spent nuclear fuel dry storage casks is evaluated through detailed numerical analysis. These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission(NRC). Canistered dry storage cask systems rely on ventilation between the inner canister and the overpack to convect heat away from the canister to the surrounding environment for both horizontal and vertical configurations. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a cask in part by increasing the efficiency of internal conduction pathways and by increasing the internal convection through greater canister helium pressure. Carefully measured data sets generated from testing of full sized casks or smaller cask analogs are widely recognized as vital for validating these models. While several testing programs have been previously conducted, these earlier validation studies did not integrate all the physics or components important in a modern, horizontal dry cask system. The purpose of the investigation described in this test plan is to produce data sets that can be used to benchmark the codes and best practices presently used to determine cladding temperatures and induced cooling air flows in modern horizontal dry storage systems. The horizontal dry cask simulator(HDCS) has been designed to generate this benchmark data and add to the existing knowledgebase. The pressure vessel representing the canister has been designed, fabricated, and pressure tested for a maximum allowable pressure(MAWP)rating of 2,400 kPa at400 °C. An existing electrically heated but otherwise prototypic boiling water reactor(BWR), Incoloy-clad test assembly will be deployed inside of a representative storage basket and canister. An insulated sheet metal enclosure will be used to mimic the thermal properties of the concrete vault enclosure used in a modern horizontal storage system. Radial and axial temperature profiles along with induced cooling air flow will be measured for a wide range of decay powers and representative(and higher)cask pressures using various backfills of helium, argon, or air. The single assembly geometry with well-controlled boundary conditions simplifies computational requirements while preserving relevant physics. The proposed test apparatus integrates all the underlying thermal-hydraulics important to defining the performance of a modern horizontal storage system. These include combined-mode heat transfer from the electrically-heated assembly to the canister walls and the primarily natural-convective heat transfer from the canister to the cooling air flow passing through the horizontal vault enclosure. The objective of the HDCS is not to reproduce the performance of a commercial dry storage system for any given set of operational parameters. Rather ,the objective is to capture the dominant physics in a well-characterized test apparatus. The close coupling between the thermal response of the canister system and the resulting induced cooling air flow rate is of particular importance. While incorporating the best available information based on thermal-hydraulic scaling arguments as well as previous vertical testing, this test plan is subject to changes due to improved understanding or from as built deviations to designs. As-built conditions and actual procedures will be documented in the final test report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Conversion-Integration of MSFC Nonlinear Signal Diagnostic Analysis Algorithms for Realtime Execution of MSFC's MPP Prototype System

NASA's advanced propulsion system Small Scale Magnetic Disturbances/Advanced Technology Development (SSME/ATD) has been undergoing extensive flight certification and developmental testing, which involves large numbers of health monitoring measurements. To enhance engine safety and reliability, detailed analysis and evaluation of the measurement signals are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce the risk of catastrophic system failures and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. During the development of SSME, ASRI participated in the research and development of several advanced non- linear signal diagnostic methods for health monitoring and failure prediction in turbomachinery components. However, due to the intensive computational requirement associated with such advanced analysis tasks, current SSME dynamic data analysis and diagnostic evaluation is performed off-line following flight or ground test with a typical diagnostic turnaround time of one to two days. The objective of MSFC's MPP Prototype System is to eliminate such 'diagnostic lag time' by achieving signal processing and analysis in real-time. Such an on-line diagnostic system can provide sufficient lead time to initiate corrective action and also to enable efficient scheduling of inspection, maintenance and repair activities. The major objective of this project was to convert and implement a number of advanced nonlinear diagnostic DSP algorithms in a format consistent with that required for integration into the Vanderbilt Multigraph Architecture (MGA) Model Based Programming environment. This effort will allow the real-time execution of these algorithms using the MSFC MPP Prototype System. ASRI has completed the software conversion and integration of a sequence of nonlinear signal analysis techniques specified in the SOW for real-time execution on MSFC's MPP Prototype. This report documents and summarizes the results of the contract tasks; provides the complete computer source code; including all FORTRAN/C Utilities; and all other utilities/supporting software libraries that are required for operation.

Jong, Jen-Yi↗

Hyper-fidelity depletion coupled with discrete pebble motion in pebble bed reactors

Pebble bed reactors have raised new interest during the past decade due to their attractive characteristics. Therefore, accurate simulations must be performed to better understand these systems and ensure optimal and safe designs. Most current methods use lower fidelity approaches with representative unit-cells or macro-zones with uniform fluxes, which have accuracy and flexibility limitations. A novel hyper-fidelity method for pebble bed reactors depletion is presented and internally couples Serpent 2 and a pseudo-motion routine. Pseudo-motion is applied handling vertical shifts of compositions in a static pebble bed, random reinsertion of used pebbles, insertion of fresh pebbles and used pebbles discarding. Associated with individual depletion to correctly determine the flux spectrum and composition in each pebble, this hyper-fidelity approach paves the way towards more accurate depletion calculation in pebble bed reactors. Using this method, a demonstration is completed on a small-scale reactor. In this application, the core reaches equilibrium, and the following data is extracted: core-wise parameters evolution, pebble-wise spatial and statistical distribution. Discarded pebbles are analyzed, and relevant information is shown. This work proves the feasibility of hyper fidelity depletion with Serpent 2, and the range of use for this method: reactor design and analysis for equilibrium and slow transients, lower fidelity methods validation and feeding fuel performance, thermal-hydraulics, or waste management models. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SAM Code Development for Source Term Modeling in Fluoride-salt-cooled High-temperature Reactors

The SAM code is under development and supported by DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. These advanced reactor concepts incorporate novel and improved approaches to achieve safety and economic feasibility. Many concepts leverage higher operating temperatures for improved efficiency with a variety of coolants and structural materials to support those needs. Such design choices may also pose unique radiological source term risks. There are continuous efforts to incorporate new physics and phenomena relevant to advanced reactor concepts, including capabilities to enable system-level source term modeling. The Pebble-Bed Fluoride-salt-cooled High-temperature Reactor (PB-FHR) is a promising candidate among advanced nuclear reactor concepts with its improved passive safety characteristics and high thermal efficiency. In addition to past efforts to support the development and utilization of SAM for PB-FHR safety analysis, the species transport modeling capabilities in SAM have been extended to simulate source term phenomena in concepts like the PB-FHR. The PB-FHR concept utilizes pebble-form TRISO fuel and FLiBe salt coolant to provide robust barriers to the release of almost all fission products and radiological source terms. However, tritium poses a unique radiological risk due to its significant production from neutron interactions with 6 Li and 9 Be in the FLiBe as well as its high mobility at elevated temperatures where it can permeate through structural metals. Secondly, the use of graphite at elevated temperatures poses the risk of oxidation damage to any structural components or fuel pebbles that are exposed to accidental air ingress. This report summarizes progress made in modeling these phenomena in SAM, which leverages the system-level multi-physics thermal hydraulic simulation to support an effective engineering-scale source term modeling capability. A tritium transport model is developed to simulate the various transport pathways in FHR and MSR concepts and is presented through verification and validation examples as well as demonstrations simulating experimental test loops and reference plant FHR models. A graphite oxidation model is also introduced to calculate local oxidation rates and is presented with initial validation results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

qSIEVE: Efficient qLDPC Memory via Systolic Movement in Atom Arrays

As quantum machines have scaled up in their number of qubits, significant research has turned towards increasing their fidelity with quantum error correction codes. Although promising results have been shown with the surface code, which only requires near-neighbor connections between qubits, the high qubit overhead of such local codes promises to be problematic. Consequently, recent work has explored non-local quantum LDPC (qLDPC) codes, which have good asymptotic encoding rates. Despite theoretical progress, hardware implementations of these codes have been a longstanding challenge. At the experimental level, demonstrations of movement based communication on atom arrays suggest this is a powerful new primitive to achieve non-local connectivity. Leveraging this, we present a protocol for implementing non-local qLDPC codes in hardware. Our protocol, qSIEVE, is a co-design of such codes with movement in atom arrays. qSIEVE defines a restricted family of qLDPC codes that can be implemented efficiently with systolic movement. We then quantify the utility of qSIEVE in the context of a complete fault tolerant architecture. We compare the cost of implementing benchmark programs in a standard, surface code only architecture and a mixed architecture where data is stored in qLDPC memory with qSIEVE and loaded to surface codes for computation.

Quantum error correction↗

Genome-Scale 13 C Fluxomics Modeling for Metabolic Engineering of Saccharomyces cerevisiae .

Synthetic biology is a rapidly developing field that pursues the application of engineering principles and development approaches to biological engineering. Synthetic biology is poised to change the way biology is practiced, and has important practical applications: for example, building genetically engineered organisms to produce biofuels, medicines, and other chemicals. Traditionally, synthetic biology has focused on manipulating a few genes (e.g., in a single pathway or genetic circuit), but its combination with systems biology holds the promise of creating new cellular architectures and constructing complex biological systems from the ground up. Enabling this merge of synthetic and systems biology will require greater predictive capability for modeling the behavior of cellular systems, and more comprehensive data sets for building and calibrating these models. The so-called "-omics" data sets can now be generated via high throughput techniques in the form of genomic, proteomic, transcriptomic, and metabolomic information on the engineered biological system. Of particular interest with respect to the engineering of microbes capable of producing biofuels and other chemicals economically and at scale are metabolomic datasets, and their insights into intracellular metabolic fluxes. Metabolic fluxes provide a rapid and easy to understand picture of how carbon and energy flow throughout the cell. Furthermore, we present a detailed guide to performing metabolic flux analysis and modeling using the open source JBEI Quantitative Metabolic Modeling (jQMM) library. This library allows the user to transform metabolomics data in the form of isotope labeling data from a 13 C labeling experiment into a determination of cellular fluxes that can be used to develop genetic engineering strategies for metabolic engineering.The jQMM library presents a complete toolbox for performing a range of different tasks of interest in metabolic engineering. Various different types of flux analysis and modeling can be performed such as flux balance analysis, 13 C metabolic flux analysis, and two-scale 13 C metabolic flux analysis (2S- 13 C MFA). 2S- 13 C MFA is a novel method that determines genome-scale fluxes without the need of every single carbon transition in the metabolic network. In addition to several other capabilities, the jQMM library can make model based predictions for how various genetic engineering strategies can be incorporated toward bioengineering goals: it can predict the effects of reaction knockouts on metabolism using both the MoMA and ROOM methodologies. In this chapter, we will illustrate the use of the jQMM library through a step-by-step demonstration of flux determination and knockout prediction in a complex eukaryotic model organism: Saccharomyces cerevisiae ( S. cerevisiae ). Included with this chapter is a digital Jupyter Notebook file that provides a computable appendix showing a self-contained example of jQMM usage, which can be changed to fit the user's specific needs. As an open source software project, users can modify and extend the code base to make improvements at will, allowing them to share their development work and contribute back to the jQMM modeling community.

-Omics data↗

An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer

Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.

Clifford↗

Biogeochemistry simulations for the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX)

Coastal ecosystems have been largely ignored in Earth system models but are important zones for carbon and nutrient processing. Interactions between water, microbes, soil, sediments, and vegetation are important for mechanistic representation of coastal processes and ecosystem function. To investigate the role of these feedbacks, we used a reactive transport model (PFLOTRAN) that has the capability to be connected to the Energy Exascale Earth System Model (E3SM). PFLOTRAN was used to incorporate redox reactions and track chemical species important for coastal ecosystems as well as define simple representations of vegetation dynamics. Our goal was to incorporate oxygen flux, salinity, pH, sulfur cycling, and methane production along with plant-mediated transport of gases and tidal flux. Using porewater profile and incubation data for model calibration and evaluation, we were able to create depth-resolved biogeochemical soil profiles for saltmarsh habitat and use this updated representation to simulate direct and indirect effects of elevated CO2 and temperature on subsurface biogeochemical cycling. We found that simply changing the partial pressure of CO2 or increasing temperature in the model did not fully reproduce observed changes in the porewater profile, but the inclusion of plant or microbial responses to CO2 and temperature manipulations was more accurate in representing porewater concentrations. This indicates the importance of characterizing tightly coupled vegetation-subsurface processes for developing predictive understanding and the need for measurement of plant-soil interactions on the same time scale to understand how hotspots or moments are generated.Included in this data package are PFLOTRAN input (PFLOTRAN input files and chemical database) files for simulating single column biogeochemistry, root, and tide interactions at the Global Change Research Wetland (Kirkpatrick Marsh; Edgewater, MD). The biogeochemical network includes soil organic matter decomposition, nitrogen, iron, and sulfur cycling, and methanogenesis. Reduced species can be oxidized and plant processes include oxygen and nutrient priming, methane release, and nutrient uptake.Inputs:TAI_database.dat - geochemical database for reactions, more information on database structure and variables can be found here https://www.pflotran.org/documentation/user_guide/cards/pages/geochemical_database.htmlswamp.in - input file for biogeochemical network in PFLOTRANswamp_eCO2.in - input file for biogeochemical network in PFLOTRAN with input gas partial pressures/concentrations adjusted for elevated CO2 treatmentsOutputs:swamp_obs_0.tec - hourly porewater concentrations from from multiple depths in the soil columnswamp_eCO2_obs_0.tec - hourly porewater concentrations from multiple depths in the soil column for elevated CO2 treatmentsPFLOTRAN code access: https://github.com/fmyuan/pflotran-elm-interface.git

54 ENVIRONMENTAL SCIENCES↗

Environmental Flow Requirements from FERC Licenses Across the US

Environmental flow requirements included in Federal Energy Regulatory Commission (FERC) hydropower licenses are important for balancing natural properties and benefits of river ecosystems (e.g., healthy species, recreation, water supply, flood control) supporting hydropower production. In some cases, environmental flow requirements may limit operational flexibility given current operational schemes and make a hydropower plant less able to provide power to the electric grid on demand. Hydropower plants may gain some flexibility as hydropower scheduling time periods are made to be more responsive to the short-term needs of an energy grid increasingly reliant on intermittent renewables. However, many flow requirements focus on the daily, monthly, or seasonal flow fluctuations which matches the time scale of most paradigms linking flow alterations to the health of river ecosystems. This dataset seeks to provide a greater understanding of how flexibility in environmental requirements can be leveraged to create positive outcomes for both the power system and the environment. It contains information on environmental flow requirements from the Protection, Mitigation, and Enhancement section of 50 randomly selected FERC licenses: 25 issued from 1998-2013 that were also included in the ORNL Mitigation Database (Schramm et al. 2015) and 25 issued from 2014-present. The information on environmental flow requirements was extracted from the PM&E section of 50 randomly selected FERC licenses: 25 issued from 1998-2013 that were also included in the ORNL Mitigation Database (Schramm et al. 2015) and 25 issued from 2014-present. The flow requirements were then categorized into flow augmentation categories based on whether the license stated a specific water management purpose for the given requirement called augmentation categories (i.e., fisheries or habitat, recreation or boating, industry, and general or unspecified; Table B). Requirements were also grouped into flow type categories (e.g., minimum flow rate, maximum flow rate, ramping rate). Additional information related to flow requirements such as the augmentation time-period and whether the flow rate was continuous (i.e., condition must be present at all-times) or instantaneous (i.e., condition present at a point in time) was also extracted from the licenses. Some licenses had specific flow requirements based on whether the project was in a wet, dry, or normal water year. If that information was presented in the license, it was also included in the data set. The location within the project was noted, hereafter, zone, in the dataset for flow requirements relating to specific areas of hydropower projects (Dam, Powerhouse, Bypass Reach). Maximum discharge capacities of hydropower facilities were also extracted from both the Existing Hydropower Assets (EHA) data set and the National Inventory of Dams (NID) databases. Each facility was coded with project identification codes from the EHA dataset to facilitate cross-referencing between datasets.

13 HYDRO ENERGY↗

High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP): Design Guidelines and Specifications for DC Distribution-Based Charging Hub

Managed under U.S. Department of Energy (DOE)-funded EVs@Scale Consortium, High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project aims to design and develop a high-power, interoperable charging experimental platform to research, develop, and demonstrate the integration and control approaches for a DC distribution-based high-power charging (HPC) system. The eCHIP project addresses the crucial need to design and validate efficient, low-cost, reliable, and interoperable solutions for DC-coupled charging hub ('DC hub' for short). This report explains the design, development, and implementation process of the experimental platform for the DC hub. The utilization of DC distribution holds significant potential for enhancing the operation of an HPC station architecture. However, there are challenges establishing the DC hub, including interoperability, commoditization, distributed energy resource integration, stability, DC protection, and lack of common system level controllers. To address these challenges, a testing setup is required that accommodates commercial off-the-shelf (COTS) products as well as novel, in-house designed solutions to evaluate different use cases at rated power and voltage levels.

33 ADVANCED PROPULSION SYSTEMS↗

Institute for Sustained Performance, Energy, and Resilience (SuPER)

The University of Tennessee (UTK) and University of Texas at El Paso (UTEP) partnership supported the three main thrusts of the SUPER project---performance, energy, and resilience. The UTK-UTEP effort thus helped advance the main goal of SUPER, which was to ensure that DOE's computational scientists can successfully exploit the emerging generation of high performance computing (HPC) systems. This goal is being met by providing application scientists with strategies and tools to productively maximize performance, conserve energy, and attain resilience. The primary vehicle through which UTK provided performance measurement support to SUPER and the larger HPC community is the Performance Application Programming Interface (PAPI). PAPI is an ongoing project that provides a consistent interface and methodology for collecting hardware performance information from various hardware and software components, including most major CPUs, GPUs and accelerators, interconnects, I/O systems, and power interfaces, as well as virtual cloud environments. The PAPI software is widely used for performance modeling of scientific and engineering applications---for example, the HOMME (High Order Methods Modeling Environment) climate code, and the GAMESS and NWChem computational chemistry codes---on DOE supercomputers. PAPI is widely deployed as middleware for use by higher-level profiling, tracing, and sampling tools (e.g., CrayPat, HPCToolkit, Scalasca, Score-P, TAU, Vampir, PerfExpert), making it the de facto standard for hardware counter analysis. PAPI has established itself as fundamental software infrastructure in every application domain (spanning academia, government, and industry), where improving performance can be mission critical. Ultimately, as more application scientists migrate their applications to HPC platforms, they will benefit from the extended capabilities this grant brought to PAPI to analyze and optimize performance in these environments, whether they use PAPI directly, or via third-party performance tools. Capabilities added to PAPI through this grant include support for new architectures such as the lastest GPU and Xeon Phi accelerators, and advanced power measurement and management features. Another important topic for the UTK team was providing support for a rich ecosystem of different fault management strategies in the context of parallel computing. Our long term efforts have been oriented toward proposing flexible strategies and providing building boxes that application developers can use to build the most efficient fault management technique for their application. These efforts span across the entire software spectrum, from theoretical models of existing strategies to easily assess their performance, to algorithmic modifications to take advantage of specific mathematical properties for data redundancy and to extensions to widely used programming paradigms to empower the application developers to deal with all types of faults. We have also continued our tight collaborations with users to help them adopt these technologies to ensure their application always deliver meaningful scientific data. Large supercomputer systems are becoming more and more power and energy constrained, and future systems and applications running on them will need to be optimized to run under power caps and/or minimize energy consumption. The UTEP team contributed to the SUPER energy thrust by developing power modeling methodologies and investigating power management strategies. Scalability modeling results showed that some applications can scale better with respect to an increasing power budget than with respect to only the number of processors. Power management, in particular shifting power to processors on the critical path of an application execution, can reduce perturbation due to system noise and other sources of runtime variability, which are growing problems on large-scale power-constrained computer systems.

42 ENGINEERING↗