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At least 1,585 records · Page 88

Neural-network learning of SPOD latent dynamics

Here, we aim to reconstruct the latent space dynamics of high dimensional, quasi-stationary systems using model order reduction via the spectral proper orthogonal decomposition (SPOD). The proposed method is based on three fundamental steps: in the first, once that the mean flow field has been subtracted from the realizations (also referred to as snapshots), we compress the data from a high-dimensional representation to a lower dimensional one by constructing the SPOD latent space; in the second, we build the time-dependent coefficients by projecting the snapshots containing the fluctuations onto the SPOD basis and we learn their evolution in time with the aid of recurrent neural networks; in the third, we reconstruct the high-dimensional data from the learnt lower -dimensional representation. The proposed method is demonstrated on two different test cases, namely, a compressible jet flow, and a geophysical problem known as the Madden-Julian Oscillation. An extensive comparison between SPOD and the equivalent POD-based counterpart is provided and differences between the two approaches are highlighted. The numerical results suggest that the proposed model is able to provide low rank predictions of complex statistically stationary data and to provide insights into the evolution of phenomena characterized by specific range of frequencies. The comparison between POD and SPOD surrogate strategies highlights the need for further work on the characterization of the interplay of error between data reduction techniques and neural network forecasts.

97 MATHEMATICS AND COMPUTING↗

Beyond interpolation: Physics-inspired gating transformers for extrapolating irradiation conditions to novel nuclear fuels

The qualification of advanced nuclear fuels relies on irradiation experiments in test reactors that emulate commercial conditions. Designing these tests requires accurate prediction of key irradiation quantities, particularly heat generation rate and burnup, yet obtaining them typically involves computationally expensive multi-step simulation workflows. We propose a physics-inspired gating transformer (PIGT) that integrates an inverse-square, distance-based attenuation into the encoder representation to bias attention toward physically relevant spatial relationships while retaining data-driven flexibility. Using MiniFuel irradiation data from the High Flux Isotope Reactor at Oak Ridge National Laboratory, we benchmark against ensemble methods, feedforward and recurrent networks, convolutional models, and standard transformers. While baseline models perform well under interpolation, they exhibit a pronounced generalization gap when evaluated on fuels not included in the training set. The proposed model consistently improves extrapolative accuracy and stability, yielding the strongest performance on unseen fuel configurations. These results indicate that a lightweight physics structure embedded within attention mechanisms can substantially improve robustness, enabling more reliable surrogate predictions to accelerate the design of nuclear fuel irradiation experiments.

Fuel qualification↗

Consequences of contamination of the spacecraft environment: immunologic consequences

Long-term space voyages pose numerous known and unknown health hazards, to the human immune system. Well-studied clinical examples of secondary immunodeficiencies created on Earth, lead one to predict that the conditions of prolonged space flight would weaken the human immune responses that normally hold infection and cancer in check. From evidence gathered from humans flown for prolonged periods in space and from human models of space flight studied on Earth it is reasonable to suspect that space travelers to the planet Mars would experience a weakening of immunity. Subtle defects of immune cell structure and function have been observed in astronauts, such as weakening of specific T-lymphocyte recall of specific antigens. Ground-based models also have demonstrated alterations of immune function, such as the elevation of neuroendocrine immune system messengers, interleukin-6, and soluble tumor necrosis factor-alpha receptor in sleep deprivation. Since severe immune compromise the clinical consequences of reactivation of latent virus infections and the development of cancer, has yet to be seen in space flight or in the Earth models, it is extremely important to begin to quantify early changes in immunity to predict the development of immune system collapse with poor clinical outcomes. This approach is designed to validate a number of surrogate markers that will predict trouble ahead. Inherent in this research is the development of countermeasures to reduce the risks of infection and cancer in the first humans going to Mars.

Non-NASA Center↗

The Evolution of the Impact Evidence Library Methods – What We Learned

During fiscal years 2020-2022 NASA’s Human Research Program, Exploration Medical Capability Element has worked to source this evidence for the model. During the process several lessons learned have been identified and drive recommendations for future efforts. The ICL 1.0: Spaceflight Medical Operational expertise should be consulted regarding the addition of future conditions. A clinician experienced with the nuances of spaceflight is recommended to have a minimum of 20 hours per condition to adequately source the evidence. Condition definitions should be carefully crafted to maintain mutual exclusivity. Common side effects from medications, common and consequential incidental findings in laboratory studies, and consequential side effects of diagnostic and procedural capabilities should be considered for inclusion as unique conditions in future iterations of the ICL 1.0. Incidence: Spaceflight incidence, although based on small population sizes, is the gold standard. Terrestrial incidence should be applied cautiously. Probability of minor vs. severe cases of the condition: Data informing severity probability of the medical condition are nearly always terrestrial. Special attention should be paid to this metric as it drives outcomes in the model and terrestrial data often overestimate severity of expected cases in spaceflight. Condition duration: Three clinical phases currently exist in the model. They represent the time necessary for diagnosis, treatment/convalescence/recurrence, and the remaining duration of the mission after maximal recovery, respectively. Further subdivision of acute and convalescent treatment/recurrence is recommended. Probability of need for evacuation: Surrogates for “Return to Definitive Care” were chosen prior to data collection. In most cases these surrogates were “need for hospitalization” or “need for surgery.” For many conditions these may not be realistic drivers of “Return to Definitive Care” and should be re-examined. Probability of Crew Mortality: Terrestrial mortality data is difficult to apply to astronauts who, invariably, have less comorbidities than terrestrial subjects. It must be applied judiciously. The proportion of mission tasks impaired by the condition: “Task Impairment” was assigned to each condition prior to the condition duration data becoming available. Future efforts should assign Task Impairment as the final step in sourcing the evidence.

A.J. Kreykes↗

Recommended Methods for Monitoring Skeletal Health in Astronauts to Distinguish Specific Effects of Prolonged Spaceflight

NASA uses areal bone mineral density (aBMD) by dual-energy X-ray absorptiometry (DXA) to monitor skeletal health in astronauts after typical 180-day spaceflights. The osteoporosis field and NASA, however, recognize the insufficiency of DXA aBMD as a sole surrogate for fracture risk. This is an even greater concern for NASA as it attempts to expand fracture risk assessment in astronauts, given the complicated nature of spaceflight-induced bone changes and the fact that multiple 1-year missions are planned. In the past decade, emerging analyses for additional surrogates have been tested in clinical trials; the potential use of these technologies to monitor the biomechanical integrity of the astronaut skeleton will be presented. OVERVIEW: An advisory panel of osteoporosis policy-makers provided NASA with an evidence-based assessment of astronaut biomedical and research data. The panel concluded that spaceflight and terrestrial bone loss have significant differences and certain factors may predispose astronauts to premature fractures. Based on these concerns, a proposed surveillance program is presented which a) uses Quantitative Computed Tomography (QCT) scans of the hip to monitor the recovery of spaceflight-induced deficits in trabecular BMD by 2 years after return, b) develops Finite Element Models [FEM] of QCT data to evaluate spaceflight effect on calculated hip bone strength and c) generates Trabecular Bone Score [TBS] from serial DXA scans of the lumbar spine to evaluate the effect of age, spaceflight and countermeasures on this novel index of bone microarchitecture. SIGNIFICANCE: DXA aBMD is a widely-applied, evidence-based predictor for fractures but not applicable as a fracture surrogate for premenopausal females and males <50 years. Its inability to detect structural parameters is a limitation for assessing changes in bone integrity with and without countermeasures. Collective use of aBMD, TBS, QCT, and FEM analysis for astronaut surveillance could accommodate NASA's aggressive schedule for risk definition and inform a NASA-developed model which assesses the probability of overloading bones during mechanically-loaded mission tasks and possibly for physical activities after return to Earth.

Vasadi, Lukas J.↗

Chemical insights into ethyl acetate flames from experiment and kinetic modeling: Laminar burning velocity, speciation and NO$_x$ emission

Oxygenated fuels, such as alcohols, ethers, and esters, are promising alternatives to conventional fuels. These fuels can help reduce detrimental emissions like carbon monoxide and unburned hydrocarbons and enhance octane ratings. Among these oxygenates, ethyl acetate (EA), a small alkyl ester sourced from biomass, emerges as a clean, promising energy carrier. It serves as a surrogate fuel to facilitate investigations into the combustion behaviours of biodiesel. Despite its importance, the literature knowledge of EA combustion characteristics is limited. Therefore, this study aims to broaden the knowledge of the combustion behaviour of this type of oxygenated fuel compound. In this study, we measured the laminar burning velocities of EA by employing a heat flux burner and a closed combustion vessel over the equivalence ratios of 0.7 – 1.7, pressures of 1 – 10 bar and temperatures ranging from 353 – 423 K. Further, we also measured the NOx emissions in exhaust gas of the premixed flames fueled by EA/air for the first time over the equivalence ratio of 0.8 – 1.2. Additionally, we employed a non-premixed counterflow flame setup for extensive characterisation of species and their concentration under diverse conditions encompassing various strain rates and oxygen concentrations. Finally, we utilized these newly measured data to construct and validate a detailed kinetic model developed as part of this work. The newly developed model will help characterize the combustion properties of EA.

30 DIRECT ENERGY CONVERSION↗

Vadose Zone Flow and Transport Parameters Data Package for the Hanford Site Composite Analysis and Cumulative Impact Evaluation

This report provides a description of the basis for the development and implementation of a conceptual model for vadose zone flow and transport for the composite analysis (CA) groundwater pathway analysis and the cumulative impact evaluation (CIE). The parameterization for a numerical model is intimately linked to the conceptual model framework. The report describes the basis for the selection of hydraulic and transport parameters for the hydrostratigraphic units (HSUs) identified in the 200 East and 200 West Areas. Whenever data are sparse or unavailable, surrogate hydraulic properties are chosen based on samples collected within the 200 Areas and nearby locations that are representative of sediments characteristic of the HSUs identified elsewhere.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Long-Lag, Wide-pulse Gamma-Ray Bursts

The best available probe of the early phase of gamma-ray burst (GRB) jet attributes is the prompt gamma-ray emission, in which several intrinsic and extrinsic variables determine observed GRB pulse evolution, including at least: jet opening angle, profiles of Lorentz factor and matter/field density, distance of emission region from central source, and viewing angle. Bright, usually complex bursts have many narrow pulses that are difficult to model due to overlap. However, the relatively simple, long spectral lag, wide-pulse bursts may have simpler physics and are easier to model. We have analyzed the temporal and spectral behavior of wide pulses in 24 long-lag bursts from the BATSE sample, using a pulse model with two shape parameters - width and asymmetry - and the Band spectral model with three shape parameters. We find that pulses in long-lag bursts are distinguished both temporally and spectrally from those in bright bursts: the pulses in long spectral lag bursts are few in number, and approximately 100 times wider (10s of seconds), have systemtically lower peaks in nu*F(nu), harder low-energy spectra and softer high-energy spectra. These five pulse descriptors are essentially uncorrelated for our long-lag sample, suggesting that at least approximately 5 parameters are needed to model burst temporal and spectral behavior, roughly commensurate with the theoretical phase space. However, we do find that pulse width is strongly correlated with spectral lag; hence these two parameters may be viewed as mutual surrogates. The prevalence of long-lag bursts near the BATSE trigger threshold, their predominantly low nu*F(nu) spectral peaks, and relatively steep upper power-law spectral indices indicate that Swiift will detect many such bursts.

Norris, J. P.↗

Effect of the ..beta..-Hydroxy Group on Ester Reactivity: Combustion Kinetics of Methyl Hexanoate and Methyl 3-Hydroxyhexanoate

One of the major biofuels used today is biodiesel, composed of fatty acid methyl esters. The fats and oils feedstocks used to make biodiesel are in relatively short supply. To meet increasing global demand, engineered microorganisms have been developed to catalyze conversion of sugar to fatty acid esters that contain unique ..beta..-hydroxy-esters. This study investigated the effect of a hydroxyl group on the combustion characteristics of methyl esters by comparing the chemical behavior of methyl hexanoate (MHx) and methyl 3-hydroxyhexanoate (M3OHHx) - used as surrogates for diesel-boiling-range esters with longer fatty acid chains. The oxidation of these esters was studied experimentally in a flow reactor at 0.84 and 10 bar, 600 to 1,100 K, and stoichiometric conditions; and in a constant volume combustion chamber at 5 and 10 bar, 600 to 900 K, and equivalence ratios of 0.3 and 0.6. MHx was more reactive in the constant volume chamber at temperatures below 800 K at 10 bar and equivalence ratio of 0.6. MHx also exhibited a higher indicated cetane number (16.4) than M3OHHx (8.1). We investigated this reactivity trend using an updated MHx kinetic model and M3OHHx model developed as part of this work. The kinetic models predicted that radicals formed from MHx were consumed by low-temperature chemistry reactions, whereas the M3OHHx reactivity was significantly governed by the ..beta..-radical (on the same carbon as the OH group) chemistry which mainly terminated via the less reactive chain propagation pathway to methyl-3-oxohexanoate + HO2. This study extends our understanding of structural effects on ester reactivity, which will allow for accurate surrogate formulation and performance simulations.

AFIDA↗

On Managing the Use of Surrogates in General Nonlinear Optimization and MDO

This paper is concerned with a trust region approximation management framework (AMF) for solving the nonlinear programming problem in general and multidisciplinary optimization problems in particular The intent of the AMF methodology is to facilitate the solution of optimization problems with high-fidelity models. While such models are designed to approximate the physical phenomena they describe to a high degree of accuracy, their use in a repetitive procedure, for example, iterations of an optimization or a search algorithm, make such use prohibitively expensive. An improvement in design with lower-fidelity, cheaper models, however, does not guarantee a corresponding improvement for the higher-fidelity problem. The AMF methodology proposed here is based on a class of multilevel methods for constrained optimization and is designed to manage the use of variable-fidelity approximations or models in a systematic way that assures convergence to critical points of the original high-fidelity problem.

Alexandrov, Natalia M.↗

A non-fueled nuclear-heated rod for in-pile transient boiling studies

Separate-effects boiling experiments have recently been conducted in the Transient Reactor Test Facility at Idaho National Laboratory to investigate transient heating and irradiation effects on cladding-to-coolant heat transfer. Specifically, transient critical heat flux (CHF) remains an important area of research, and better understanding of this phenomenon has potential for improving predictive models related to operational and safety limits. Consequently, this knowledge is expected to improve efficiency of light-water reactor operations. A novel borated nuclear-heated rodlet (BNHR) was designed to enable observation of transient cladding-to-coolant heat transfer phenomena. The final BNHR design takes a surrogate approach, wherein nuclear heating is induced by 10 B(n, α) reactions rather than derived from fissions in a fueled specimen. The structure of the BNHR consists of a hollowed out borated (B nat ~ 2.05 wt %) stainless steel tube with an hourglass-shaped outer surface, capped at both ends with non-borated stainless steel. This geometry allows for inner-rodlet instrumentation and generation of the highest nuclear heating rates near the center of the rodlet to ensure onset of boiling near instrumentation for real-time observation. A novel approach to measuring the nuclear energy deposition rate in the BNHR separate and apart from the influence of the coolant, termed the n-a thermometer, is also detailed in this paper. This device has demonstrated excellent repeatability, and measurements indicate predictive modeling results for energy deposition in the BNHR rod agree within a 10% margin of the experiment measurements. In conclusion, these results give confidence that the BNHR design has successfully met experiment objectives.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Droplet burning of n-butyl acetate/n-heptane mixtures in the standard atmosphere: experiments and numerical modeling

Blending petroleum fuels with oxygenates is a common approach to stem the depletion of crude oil while also mitigating the impact of their combustion on the environment. It has recently been considered that n-butyl acetate (BA, C6H12O2 , boiling point of 399K) could be a viable oxygenate additive to diesel fuel. In this application it is important to determine the influence of the fractional amount of BA on burning of the mixture. This presentation considers this problem from an experimental and computational approach using n-heptane (C7H14 , boiling point of 372K) as an essentially single component surrogate for diesel fuel. The burning configuration considered was ostensibly spherical symmetry as promoted by burning droplets under conditions where forced and natural convection effects were minimized. In this configuration the droplet and flame are concentric spheres and soot aggregates are trapped in a shell structure between the droplet and flame. Measurements were made of the droplet, flame and soot shell diameters through video imaging of the burning process. The experimental results were used to validate a detailed numerical model of the spherically symmetric droplet burning process that incorporated a consistent combustion kinetic mechanism for BA/heptane mixtures, comprised of 402 species and 16,872 reactions inclusive of soot chemistry. A model for soot formation was also included in the simulation to predict formation of the soot shell. The simulations agreed well with measured droplet and flame diameters. It was found both experimentally and computationally that adding BA to heptane had a minimal effect on the mixture burning rate, while the flame was positioned closer to the droplet surface and the simulated soot volume fraction decreased. The implications of these results are discussed for using BA as a potential additive to diesel fuel.

09 BIOMASS FUELS↗

Final Seismic Shake Table Test Plan

The Spent Fuel Waste Disposition (SFWD) program is planning to conduct a full-scale seismic shake table test on the dry storage systems of spent nuclear fuel (SNF) to close the gap related to seismic loads on fuel assemblies in dry storage systems. This test will allow for quantifying the strains and accelerations on surrogate fuel assembly hardware and cladding during earthquakes of different magnitudes and frequency content. Full-scale testing is needed because a dry storage system is a complex and highly nonlinear system making it hard to predict (model) the responses to seismic excitations. The non-linearity arises from the multiple spatial gaps in the system – between fuel rods and the basket, between the basket and dry storage canister, between the dry storage canister and the storage cask (overpack), and ventilation gaps. The non-linearities pose significant limitations on the value of tests with scaled systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a data-driven alternative that uses local neural operators, trained on spatiotemporal microscopic/mesoscopic data, to obtain efficient short-time solution operators. These surrogates are employed within Krylov subspace methods to compute coarse steady and unsteady-states, while also providing Jacobian information in a matrix-free manner. Krylov-Arnoldi iterations then approximate the dominant eigenspectrum, yielding reduced models that capture the open-loop slow dynamics without explicit Jacobian assembly. Both discrete-time Linear Quadratic Regulator (dLQR) and pole-placement (PP) controllers are based on this reduced system and lifted back to the full nonlinear dynamics, thereby closing the feedback loop.

93B52, 93C20, 47N70, 65J15, 65M32, 68T07, 68T20, 6↗

Comparing Control Performance Between Simulation and Experiment using the Microreactor Automated Control System Testbed

In the advanced reactor domain, a flexible and scalable software/hardware infrastructure is crucial for integrating and validating various control technologies. This study used the Microreactor Automated Control System (MACS) hardware platform as a testbed. MACS was originally designed to mirror Idaho National Laboratory (INL)'s Microreactor Applications Research Validation and Evaluation (MARVEL), a 85-kW thermal fission microreactor. It features control drums for simulated reactivity control; lights that function as a surrogate reactor core, with the brightness being proportional to the reactor power; and light sensors that emulate neutron detectors. To transform MACS into a physical twin of MARVEL for evaluating control methods, the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software was employed. This software integrated the hardware with two models of the MARVEL core, based on Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The study aimed to demonstrate the gap between control theory and actual practice—a gap that often necessitates empirical adjustments such as control gain retuning, filters, time discretization, and integrator anti-windup measures. Controllers were developed based on increasingly complex simulations without hardware, starting from the base MARVEL model and then introducing actuator saturation constraints and sensor noise. The final control strategy was then tested using MACS, and a comparative performance analysis was conducted.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Simulating combustion of a seven-component surrogate for a gasoline/ethanol blend including soot formation and comparison with experiments

Combustion of a seven-component surrogate for a research grade 87 octane gasoline mixed with 10% ethanol is investigated experimentally and numerically from the perspective of an isolated droplet burning under conditions that promote one-dimensional gas transport. The numerical analysis included a kinetic mechanism comprised of 398 species and 24,814 reactions and a soot model that accounted for nucleation, surface growth, coalescence/aggregation of soot particles, and luminous flame radiation. Measurements of droplet and flame diameters were made for an initial droplet diameter (D o ) of approximately 0.63 mm. The simulations agreed well with the measurements including the location of the soot shell. Preferential vaporization was revealed by simulations of the liquid concentrations in the droplet. Predicted peak soot volume fractions coincided with temperatures between 1300 K and 1400 K as a soot inception temperature. Simulations were also carried out for D o between 0.25 mm and 5 mm to explore the effect of radiation and D o on burning. Below 0.25 mm radiation was negligible and burning rates and flame temperatures converged to a single value. Increasing D o up to 1.8 mm lowered the burning rate with luminous radiation having a strong effect. When radiation was entirely removed from the model the burning rate was nearly constant. Above D o = 2 mm droplets extinguished almost immediately after ignition. The flame temperature decreased with increasing D o while it increased when radiation was omitted. As a result, the simulations show that soot precursors including polyaromatic hydrocarbons were concentrated around the soot shell.

42 ENGINEERING↗

Low-temperature oxidation pathways are critical to thermal incineration of PFAS-laden materials

With growing desire to destroy per- and poly-fluoroalkyl substances (PFAS) now known to be detrimental to human health, a sound understanding of fluorocarbon combustion chemistry is important to efficient thermal destruction within incinerators. While most fluorocarbon combustion models and the sets of reactions contained within them were originally developed for the high temperatures encountered in flame suppression applications, they have often been used to assess PFAS destruction in incinerators, which emphasize a lower range of temperatures. We present results that demonstrate that low-temperature fluorocarbon oxidation pathways—not yet known to play a role in fluorocarbon combustion—impact key incinerator performance metrics, including: PFAS surrogate mole fractions, products of incomplete destruction, and waste destruction efficiencies. The results further point to the utility of NO as a potential additive. The present results show the influence of these pathways for CF 3 O 2 , for which some data are available, but analogous pathways would also occur for other fluoroalkylperoxy radicals, for which little is known. Furthermore, the results demonstrate the need for future work to identify and characterize low-temperature pathways more generally, consider such pathways in kinetic model development, and experimentally probe intermediate temperature conditions to better understand, design, and control thermal destruction technologies for improved PFAS management.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗