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At least 289 records · Page 16

On-Line Analysis of Physiologic and Neurobehavioral Variables During Long-Duration Space Missions

The goal of this project is to develop reliable statistical algorithms for on-line analysis of physiologic and neurobehavioral variables monitored during long-duration space missions. Maintenance of physiologic and neurobehavioral homeostasis during long-duration space missions is crucial for ensuring optimal crew performance. If countermeasures are not applied, alterations in homeostasis will occur in nearly all-physiologic systems. During such missions data from most of these systems will be either continually and/or continuously monitored. Therefore, if these data can be analyzed as they are acquired and the status of these systems can be continually assessed, then once alterations are detected, appropriate countermeasures can be applied to correct them. One of the most important physiologic systems in which to maintain homeostasis during long-duration missions is the circadian system. To detect and treat alterations in circadian physiology during long duration space missions requires development of: 1) a ground-based protocol to assess the status of the circadian system under the light-dark environment in which crews in space will typically work; and 2) appropriate statistical methods to make this assessment. The protocol in Project 1, Circadian Entrainment, Sleep-Wake Regulation and Neurobehavioral will study human volunteers under the simulated light-dark environment of long-duration space missions. Therefore, we propose to develop statistical models to characterize in near real time circadian and neurobehavioral physiology under these conditions. The specific aims of this project are to test the hypotheses that: 1) Dynamic statistical methods based on the Kronauer model of the human circadian system can be developed to estimate circadian phase, period, amplitude from core-temperature data collected under simulated light- dark conditions of long-duration space missions. 2) Analytic formulae and numerical algorithms can be developed to compute the error in the estimates of circadian phase, period and amplitude determined from the data in Specific Aim 1. 3) Statistical models can detect reliably in near real- time (daily) significant alternations in the circadian physiology of individual subjects by analyzing the circadian and neurobehavioral data collected in Project 1. 4) Criteria can be developed using the Kronauer model and the recently developed Jewett model of cognitive -performance and subjective alertness to define altered circadian and neurobehavioral physiology and to set conditions for immediate administration of countermeasures.

Brown, Emery N.↗

Core sample depth relationships - Apollo 14 and 15.

The depth relationships for the Apollo 14 and 15 core tubes and the Apollo 15 drill core are presented, as determined from laboratory simulation studies. Sample at a depth of 40 cm in the Apollo 14 double core tube (virtually the same as the Apollo 12 tubes) represents material from a depth of approximately 58 cm in the lunar surface. The new design of the Apollo 15 core tube results in much less sample disturbance and the depth relationship is practically one-to-one, with sample recovery approaching 100%. The depth relationship for the drill core is also probably close to one-to-one, and its recovery ratio was also 100%.

Carrier, W. D., III↗

Evaluation of Stratospheric Transport in New 3D Models Using the Global Modeling Initiative Grading Criteria

The Global Modeling Initiative (GMI) Team developed objective criteria for model evaluation in order to identify the best representation of the stratosphere. This work created a method to quantitatively and objectively discriminate between different models. In the original GMI study, 3 different meteorological data sets were used to run an offline chemistry and transport model (CTM). Observationally-based grading criteria were derived and applied to these simulations and various aspects of stratospheric transport were evaluated; grades were assigned. Here we report on the application of the GMI evaluation criteria to CTM simulations integrated with a new assimilated wind data set and a new general circulation model (GCM) wind data set. The Finite Volume Community Climate Model (FV-CCM) is a new GCM developed at Goddard which uses the NCAR CCM physics and the Lin and Rood advection scheme. The FV-Data Assimilation System (FV-DAS) is a new data assimilation system which uses the FV-CCM as its core model. One year CTM simulations of 2.5 degrees longitude by 2 degrees latitude resolution were run for each wind data set. We present the evaluation of temperature and annual transport cycles in the lower and middle stratosphere in the two new CTM simulations. We include an evaluation of high latitude transport which was not part of the original GMI criteria. Grades for the new simulations will be compared with those assigned during the original GMT evaluations and areas of improvement will be identified.

Strahan, Susan E.↗

High-Temperature Gas-Cooled Reactors Multiphysics Simulation Demonstration and Code Validation

This study presents a comprehensive benchmarking and verification effort of several thermal-hydraulic and multiphysics capabilities for high-temperature gas-cooled reactor applications. The first part of this effort focuses on the running-in verification of Griffin’s multiphysics capabilities, specifically for simulating the evolution of pebble-bed reactor cores from startup to equilibrium. Since Fiscal Year 2024, improvements and enhancements have been implemented in Griffin, including simplifying the process to specify streamlines and developing the online cross-section generation capability. In the absence of validation data, code-to-code comparisons are conducted with kugelpy, showing good agreement for integral quantities like k-eff predictions and predictions for maximum power density. However, accuracy issues are noted for more detailed quantities like the spatial distribution of fission rate densities which will require further work to address. The second part of this report presents an improved System Analysis Module (SAM) core channel model where the effects of cross flow are considered during the pressurized loss of forced cooling transient, resulting in an improved agreement of the predicted pebble temperature with respect to the predictions from the SAM 2D porous media model. Additionally, the wall channeling effect due to variable porosity at the near wall region of the core is also investigated. Furthermore, to demonstrate Griffin’s online cross-section generation capability, a Multiphysics simulation is performed by coupling Griffin to the SAM core channel model. In the third part of the report, as a part of the Organisation for Economic Co-operation and Development/Nuclear Energy Agency (OECD/NEA) thermal-hydraulic code validation benchmark activity for a high-temperature gas-cooled reactor, the High Temperature Test Facility (HTTF) is investigated first using the NekRS computational fluid dynamics (CFD) code to study the flow mixing phenomenon in the lower plenum of the facility. Then, code-to-code and code-to-data comparisons are performed for Test PG27, which is a pressurized conduction cooldown (PCC) test, using five different codes by six organizations from five countries. The different simulations show good agreements in terms of the general trend but there are differences in some results such as the peak temperatures of different regions and heat removal rate.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model

Abstract. Urban overheating and its ongoing exacerbation due to global warming and urban development lead to increased exposure to urban heat and increased thermal discomfort and heat stress. To quantify thermal stress, specific indices have been proposed that depend on air temperature, mean radiant temperature (MRT), wind speed, and relative humidity. While temperature and humidity vary on scales of hundreds of meters, MRT and wind speed are strongly affected by individual buildings and trees and vary on the meter scale. Therefore, most numerical thermal comfort studies apply microscale models to limited spatial domains (commonly representing urban neighborhoods with building blocks) with resolutions on the order of 1 m and a few hours of simulation. This prevents the analysis of the impact of city-scale adaptation and/or mitigation strategies on thermal stress and comfort. To solve this problem, we develop a methodology to estimate thermal stress indicators and their subgrid variability in mesoscale models – here applied to the multilayer urban canopy parameterization BEP-BEM within the Weather Research and Forecasting (WRF) model. The new scheme (consisting of three main steps) can readily assess intra-neighborhood-scale heat stress distributions across whole cities and for timescales of minutes to years. The first key component of the approach is the estimation of MRT in several locations within streets for different street orientations. Second, mean wind speed and its subgrid variability are downscaled as a function of the local urban morphology based on relations derived from a set of microscale LES and RANS simulations across a wide range of realistic and idealized urban morphologies. Lastly, we compute the distributions of two thermal stress indices for each grid square, combining all the subgrid values of MRT, wind speed, air temperature, and absolute humidity. From these distributions, we quantify the high and low tails of the heat stress distribution in each grid square across the city, representing the thermal diversity experienced in street canyons. In this contribution, we present the core methodology as well as simulation results for Madrid (Spain), which illustrate strong differences between heat stress indices and common heat metrics like air or surface temperature both across the city and over the diurnal cycle.

Geology↗

Convection, nucleosynthesis, and core collapse

We use a piecewise parabolic method hydrodynamics code (PROMETHEUS) to study convective burning in two dimensions in an oxygen shell prior to core collapse. Significant mixing beyond convective boundaries determined by mixing-length theory brings fuel (C-12) into the convective regon, causing hot spots of nuclear burning. Plumes dominate the velocity structure. Finite perturbations arise in a region in which O-16 will be explosively burned to Ni-56 when the star explodes; the resulting instabilities and mixing are likely to distribute Ni-56 throughout the supernova envelope. Inhomogeneities in Y(sub e) may be large enough to affect core collapse and will affect explosive nucleosynthesis. The nature of convective burning is dramatically different from that assumed in one-dimensional simulations; quantitative estimates of nucleosynthetic yields, core masses, and the approach to core collapse will be affected.

Bazan, Grant↗

Sirius: Simulation and Evaluation of Tactical Conflict Management in an Urban Environment

This presentation provides an overview of the SIRIUS framework, updates to the ICAROUS core modules, and highlights the results of recent simulation and evaluation of tactical deconfliction in an urban environment. The SIRIUS simulation framework provides a fast time method for simulation a large number of aircraft in parallel. Updates to the ICAROUS core modules highlighted in the presentation include the evaluation of the encounter type geometry and changes to the resolution type selection based on the encounter type and following right of way (ROW) rules. The main objective of the simulation was to evaluate the use of strategic and tactical conflict management strategies using a set of simulated UAM scenarios.

Andrew Peters↗

Spectroscopy of the Perseus Cluster

We present preliminary results of a XMM-Newton 50 ks observation of the Perseus Cluster that provides an unprecedented view of the central 0.5 Mpc region. The projected gas temperature declines smoothly by a factor of 2 from a maximum value of approx. 7 keV in the outer regions to just above 3 keV at the cluster center. Over this same range, the heavy-element abundance rises slowly from 0.4 to 0.5 solar as the radius decreases from 14 ft. to 5 ft., and then it rises to a peak of almost 0.7 solar at 1&farcm;25 before declining to 0.4 at the center. Th global east-west asymmetry of the gas temperature and surface brightness distributions, approximately aligned with the chain of bright galaxies, suggests an ongoing merger, although the modest degree of the observed asymmetry certainly excludes a major merger interpretation. The chain of galaxies probably traces the filament along which accretion started some time ago and is continuing at the present time. A cold and dense (low-entropy) cluster core like Perseus is probably well "protected" against the penetration of the gas of infalling groups and poor clusters, whereas in non-cooling core clusters such as Coma and A1367, infalling subclusters can penetrate deeply into the core region. In Perseus, gas associated with infalling groups may be stripped completely at the outskirts of the main cluster and only compression waves (shocks) may reach the central regions. We argue, and show supporting simulations, that the passage of such a wave(s) can qualitatively explain the overall horseshoe shaped appearance of the gas temperature map (the hot horseshoe surrounds the colder, low-entropy core) as well as other features of the Perseus Cluster core. These simulations also show that as compression waves traverse the cluster core, they can induce oscillatory motion of the cluster gas that can generate multiple sharp "edges" on opposite sides of the central galaxy. Gas motions induced by mergers may be a natural way to explain the high frequency of "edges" seen in clusters with cooling cores.

Jones, Christine↗

Low spontaneous Brillouin scattering in anti-resonant hollow-core fibers in GHz frequency range

Brillouin light scattering (BLS) is a powerful experimental tool that can be used to gain insights into the fundamental and applied properties of matter, like dispersions of quasiparticles in a solid, as well as their spatiotemporal dynamics. Many applications of light scattering favor the use of optical fibers in place of free-space optics. In this study, we compare the performance of anti-resonant hollow core fibers to that of conventional solid core fused silica fibers for BLS experiments in the GHz frequency range. Conventional fibers are barely suitable for low-noise measurements because of the spontaneous scattering of photons on various phononic modes present in the core and cladding. In the case of the hollow-core fiber, we identify a range of discrete phononic modes and associate them with the various acoustic modes of the structure surrounding the hollow core using finite-element numerical simulations. The measured relative intensity of the spontaneous BLS signal from these modes is orders of magnitude smaller than that of a solid-core fiber, making anti-resonant hollow-core fibers one of the best solutions for the single-mode light guidance for BLS and potentially other low-noise photonic experiments.

36 MATERIALS SCIENCE↗

Demonstration and Verification of Thermo-Mechanical Bowing in a Limited Free-Bow SFR Concept Using MOOSE

Core bowing due to thermal gradients and irradiation induced swelling and creep introduces significant reactivity feedback effects in liquid metal-cooled fast spectrum reactors. During startup, normal operations, and transient events, differential thermal and flux gradients cause expansion, creep, and swelling, which results in bowing in preferential directions depending on local material properties and load-pad and restraint-ring design. The bowing phenomenon produces negative reactivity during accident conditions provided the restraint system has been properly designed to optimally guide the deformation outwards in the active core region. Under the Department of Energy Nuclear Energy Advanced Modeling and Simulation program, a Multiphysics Object Oriented Simulation Environment (MOOSE)-based multiphysics approach to model core bowing is being developed. The present work expands on previous modeling of simpler International Atomic Energy Agency (IAEA) verification problems with these tools by modeling IAEA Verification Problem 4, which involves a symmetric sector of a reactor core with ducted assemblies undergoing differential thermal expansion due to thermal gradients bowing outward with duct-to-duct contact. This model is available on the National Reactor Innovation Center Virtual Test Bed repository. This example was verified against benchmark participant results, which includes bowing deformation evaluation and duct-to-duct interactions at load pads with mechanical contact.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Accelerating Climate and Weather Simulations through Hybrid Computing

Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

hybrid computing↗

A strategy for automated core design to increase economic viability and minimize fuel fragmentation, relocation, and dispersal susceptibility in high-burnup cores

The nuclear industry aims to increase the cycle length of pressurized water reactors from 18 to 24 months to increase power plant capacity factors and economic viability. These cycle length extensions will inherently require fuel rods to exceed the current peak rod average burnup limit of 62 GWd/MTU. A chief concern of operating beyond the current burnup limit is the fuel fragmentation, relocation, and dispersal (FFRD) phenomenon in which pulverized fuel fragments can axially relocate and escape through a burst in the cladding formed during a loss-of-coolant accident. In this work, we demonstrate an approach for automating core design employing an optimization tool based on a penalty-free, parallel simulated annealing algorithm to produce pressurized water reactor core designs with two different optimization objectives. The two objectives were to produce core designs with (1) mitigated FFRD susceptibility while achieving 24-month cycle lengths (2) maximum cycle length with no regard for the likelihood of FFRD. Batch size was considered in tandem with both cases to maximize economic viability. The PARCS nodal model was the primary reactor physics tool used in the optimizations and used nuclear cross sections calculated with 2D Polaris lattice physics models. Reactor performance and safety characteristics of the optimized cores were verified using high-fidelity Virtual Environment for Reactor Applications models. The core designs produced by the optimization tool are compared with each other and to a high-burnup core design produced and analyzed in previous works to highlight the fuel management strategies that may enhance high-burnup reactor safety and economic viability. The optimized cores satisfied their respective objective functions, producing a maximum cycle length of 720 effective full-power days in one core design and one that may reduce FFRD susceptibility by up to 50% based on the first-order approximation to FFRD risk formulated in this work. The optimized cores met most constraints but exceeded the hot channel factor limit, especially in FFRD cases where fresh fuel carried more power. Furthermore, this highlights the need for future lattice-level optimizations and broader assembly options.

Cycle length↗

Local Electric Field Effects on Water Dissociation in Bipolar Membranes Studied Using Core–Shell Catalysts

The local electric field strength is thought to affect the rate of water dissociation (WD) in bipolar membranes (BPMs) at the catalyst–nanoparticle surfaces. Here, we study core–shell nanoparticles, where the core is metallic, semiconducting, or insulating, to understand this effect. The nanoparticle cores were coated with a WD catalyst layer (TiO2 or HfO2) via atomic layer deposition (ALD), and the morphology was imaged with transmission electron microscopy. Irrespective of the core material, these core–shell catalysts displayed comparable WD overpotentials at optimal mass loading, despite the hypothesized differences in the electric field strength across the catalyst particle suggested by continuum electrostatic simulations. Substantial atomic interdiffusion between the core and shell was ruled out by X-ray absorption spectroscopy, X-ray photoelectron spectroscopy, and diffuse reflectance optical measurements. However, the optimal mass loading of catalyst was roughly 1 order of magnitude higher for the conductive and high dielectric core materials than for the low dielectric insulating cores. These findings are consistent with the hypothesis that electric field screening within the core material focuses the electric field drop between particles such that larger film thicknesses can be tolerated. Collectively, these data support the idea that it is the local electric field at the molecular level that controls proton-transfer rates and that the metal core/dielectric-shell constructs introduced here modulate that field. Further materials and synthetic design may enable optimization of the electric field strength across the proton-transfer trajectory at the material surface.

Sarma, Prasad V↗

New capabilities for rapid depletion analysis of pebble-bed reactors in SCALE

The SCALE Leap-In for Cores at Equilibrium (SLICE) method leverages capabilities available in the SCALE modeling and simulation suite to facilitate rapid estimation of equilibrium core inventories for flowing-pebble reactor systems in support of a variety of fuel cycle applications. New capabilities that compliment the SLICE method have been developed for the ORIGAMI interface to ORIGEN in SCALE to facilitate rapid depletion calculations for flowing-pebble systems. New features include a more generalized and flexible means of specifying interpolation dimensions, the ability to evaluate pebbles moving through user-defined “axial zones” in each of the pebble’s multiple passes through the core, and the treatment of differential velocities across radial channels (representing both pebble-to-pebble and wall-to-pebble friction effects). ORIGAMI thus provides an efficient user interface to define a pebble’s path and irradiation histories of its multiple passes through the core to calculate the pebble’s time-dependent inventories, which can be useful in various applications domains such as safeguards, criticality safety, and disposal analyses. The consistency of new ORIGAMI approach was verified against the solution obtained using the SLICE method with ORIGEN-ARP, showing excellent agreement.

Skutnik, Steven E. [Oak Ridge National Laboratory ↗

Uncertainty quantification for nuclear forensics with population analyses

Although neural networks offer cutting-edge predictive power, their deployment in high-consequence nuclear forensic applications is limited, partly because of their black-box nature. Incorporating robust uncertainty quantification methods into the predictive frameworks of neural networks is progress towards their future deployment in such scenarios. This work integrates uncertainty quantification into neural networks for nuclear reactor core-average burnup estimation from simulated environmental samples. We test two regimes (homogeneous and heterogeneous events) on DeepSets and Set Transformer architectures, we find both quantify predictive uncertainty effectively, but Set Transformer excels in partitioning latent events, offering superior predictive power and more informative uncertainty estimates.

Hatton, Conner [ORNL] (ORCID:0009000804970959)↗

Attention to quantum complexity

The imminent era of error-corrected quantum computing demands robust methods to characterize quantum state complexity from limited, noisy measurements. We introduce the Quantum Attention Network (QuAN), a classical artificial intelligence (AI) framework leveraging attention mechanisms tailored for learning quantum complexity. Inspired by large language models, QuAN treats measurement snapshots as tokens while respecting permutation invariance. Combined with our parameter-efficient miniset self-attention block, this enables QuAN to access high-order moments of bit-string distributions and preferentially attend to less noisy snapshots. We test QuAN across three quantum simulation settings: driven hard-core Bose-Hubbard model, random quantum circuits, and toric code under coherent and incoherent noise. QuAN directly learns entanglement and state complexity growth from experimental computational basis measurements, including complexity growth in random circuits from noisy data. In regimes inaccessible to existing theory, QuAN unveils the complete phase diagram for noisy toric code data as a function of both noise types, highlighting AI’s transformative potential for assisting quantum hardware.

Kim, Hyejin [Cornell Univ., Ithaca, NY (United Sta↗

Consist v0.1.0

A Python library for provenance tracking, intelligent caching, and data virtualization in scientific simulation workflows. It automatically records code, configuration, and input data to skip redundant computations and enables querying results across many runs without manual bookkeeping. Designed to support multi-model simulation workflows like the BEAM CORE toolset at LBL, but designed to be extensible to a wide range of research workflows. Combines lineage tracking features as provided by OpenLineage with deterministic hashing like SnakeMake, and adds powerful analysis tools on model outputs.

Needell, Zachary [Lawrence Berkeley National Labor↗