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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Microgravity Transport Phenomena Experiment (MTPE) Overview

The Microgravity Transport Phenomena Experiment (MTPE) is a fluids experiment supported by the Fundamentals in Biotechnology program in association with the Human Exploration and Development of Space (BEDS) initiative. The MTP Experiment will investigate fluid transport phenomena both in ground based experiments and in the microgravity environment. Many fluid transport processes are affected by gravity. Osmotic flux kinetics in planar membrane systems have been shown to be influenced by gravimetric orientation, either through convective mixing caused by unstably stratified fluid layers, or through a stable fluid boundary layer structure that forms in association with the membrane. Coupled transport phenomena also show gravity related effects. Coefficients associated with coupled transport processes are defined in terms of a steady state condition. Buoyancy (gravity) driven convection interferes with the attainment of steady state, and the measurement of coupled processes. The MTP Experiment measures the kinetics of molecular migration that occurs in fluids, in response to the application of various driving potentials. Three separate driving potentials may be applied to the MTP Experiment fluids, either singly or in combination. The driving potentials include chemical potential, thermal potential, and electrical potential. Two separate fluid arrangements are used to study membrane mediated and bulk fluid transport phenomena. Transport processes of interest in membrane mediated systems include diffusion, osmosis, and streaming potential. Bulk fluid processes of interest include coupled phenomena such as the Soret Effect, Dufour Effect, Donnan Effect, and thermal diffusion potential. MTP Experiments are performed in the Microgravity Transport Apparatus (MTA), an instrument that has been developed specifically for precision measurement of transport processes. Experiment fluids are contained within the MTA fluid cells, designed to create a one dimensional flow geometry of constant cross sectional area, and to facilitate fluid filling and draining operations in microgravity. The fluid cells may be used singly for bulk solutions, or in a Stokes diaphragm configuration to investigate membrane mediated phenomena. Thermal and electrical driving potentials are applied to the experiment fluids through boundary plates located at the ends of the fluid cells. In the ground based instrument, two constant temperature baths circulate through reservoirs adjacent to the boundary plates, and establish the thermal environment within the fluid cells. The boundary plates also serve as electrodes for measurement and application of electrical potentials. The Fluid Manipulation System associated with the MTA is a computer controlled system that enables storage and transfer of experiment fluids during on orbit operations. The system is used to automatically initiate experiments and manipulate fluids by orchestrating pump and valve operations through scripted sequences. Unique technologies are incorporated in the MTA for measurement of fluid properties. Volumetric Flow Sensors have been developed for precision measurement of total fluid volume contained within the fluid cells over time. This data is most useful for measuring the kinetics of osmosis, where fluid is transported from one fluid cell to another through a semipermeable membrane. The MicroSensor Array has been designed to perform in situ measurement of several important fluid parameters, providing simultaneous measurement of solution composition at multiple locations within the experiment fluids. Micromachined sensors and interface electronics have been developed to measure temperature, electrical conductivity, pH, cation activity, and anion activity. The Profile Refractometer uses a laser optical system to directly image the fluid Index of Refraction profile that exists along the MTA fluid cell axis. A video system acquires images of the RI profile over time, and records the transport kinetics that occur upon application of chemical, thermal, or electrical driving potentials. Image processing algorithms have been developed to analyze the refractometer images on a pixel by pixel basis, calibrating and scaling the measured Index of Refraction profile to correlated solution properties of interest such as density, concentration, and temperature. Additional software has been developed to compile the processed images into a three dimensional matrix that contains fluid composition data as a function of experiment time and position in the fluid cell. These data are combined with data from the other sensor systems, and analyzed in the context of transport coefficients associated with the various transport phenomena. Analysis protocols have been developed to measure the transient kinetics, and steady state distribution of fluid components that occur in response to the applied driving potentials. The results are expressed in terms of effective transport coefficients. Experiments have been performed using a variety of solutes, and results generated are that are in agreement with published transport coefficient values.

Mason, Larry W.↗
NASA NTRS1984

Buoyant production and consumption of turbulence kinetic energy in cloud-topped mixed layers

It is pointed out that studies of the entraining planetary boundary layer (PBL) have generally emphasized the role of buoyancy fluxes in driving entrainment. The buoyancy flux is proportional to the rate of conversion of the potential energy of the mean flow into the kinetic energy of the turbulence. It is not unusual for conversion to proceed in both directions simultaneously. This occurs, for instance, in both clear and cloudy convective mixed layers which are capped by inversions. A partitioning of the net conversion into positive parts, generating turbulence kinetic energy (TKE), and negative parts (TKE-consuming), would make it possible to include the positive part in the gross production rate, and closure would be achieved. Three different approaches to partitioning have been proposed. The present investigation is concerned with a comparison of the three partitioning theories. Particular attention is given to the cloud-topped mixed layer because in this case the differences between two partitioning approaches are most apparent.

Randall, D. A.↗
DOE OSTI2023

High-fidelity Experiments of Turbulent Buoyant Jets from Simultaneous Particle Image Velocimetry and Laser Induced Fluorescence

Accurate models of turbulent buoyant flows are essential for the design of nuclear reactors thermal hydraulics and passive safety systems. However, available models fail to fully capture the physics of turbulent mixing when buoyancy becomes predominant with respect to momentum. Therefore, high-fidelity experiments of well-controlled fundamental flows are needed to develop and validate more accurate models. We performed experiments of positive and negative turbulent buoyant jets, both in uniform and stratified environments, with the aim of understanding the thermal hydraulics of turbulent mixing with variable density and providing high-fidelity data for the development and validation of turbulence models. Non-intrusive, simultaneous Particle Image Velocimetry and Laser Induced Fluorescence measurements were carried out to acquire instantaneous velocity and concentration fields on a vertical section parallel to the axis of a jet in the self-similar region. The Refractive Index Matching method was applied to measure high-resolution buoyant jets with up to 8.6% density difference. These data are free of the typical errors that characterize optical measurements of buoyancy driven flows (e.g., natural and mixed convection) where the refractive index of the fluid is inhomogeneous throughout the measurement domain. Turbulent statistics and entrainment of buoyant jets in uniform and stratified environments are presented. These data are compared with non-buoyant jets in uniform environment, as a reference to investigate the effects of buoyancy and stratification on turbulent mixing. The results will be used for the assessment of current turbulence models and as basis for the development of a new one that captures turbulent mixing.

42 ENGINEERING↗
DOE OSTI2024

High-Fidelity Velocity and Concentration Measurements of Turbulent Buoyant Jets

Accurate models of turbulent buoyant flows are essential for the design of the cooling circuit of nuclear reactors and passive safety systems. However, available models fail to fully capture the physics of turbulent mixing when buoyancy becomes predominant with respect to momentum. Therefore, high-fidelity experiments of well-controlled fundamental flows are needed to develop and validate more accurate models. We analyze experiments of positive and negative turbulent buoyant jets, both in uniform and stratified environments, with the aim of understanding the thermal hydraulics of turbulent mixing with variable density and providing high-fidelity data for the development and validation of turbulence models. Non-intrusive, simultaneous particle image velocimetry and laser-induced fluorescence measurements were carried out to acquire instantaneous velocity and concentration fields on a vertical section parallel to the axis of a jet in the self-similar region. The refractive index matching method was applied to measure high-resolution buoyant jets with up to 8.6% density difference. These data are free of the typical errors that characterize optical measurements of buoyancy-driven flows (e.g. natural and mixed convection) where the refractive index of the fluid is inhomogeneous throughout the measurement domain. Turbulent statistics and entrainment of buoyant jets in uniform and stratified environments are presented. These data are compared with non-buoyant jets in a uniform environment, as a reference to investigate the effects of buoyancy and stratification on turbulent mixing. The results will be used for the assessment of current turbulence models and as a basis for the development of a new model that captures turbulent mixing.

laser induced fluorescence↗
NASA NTRS1996

Microstructural Development during Directional Solidification of Peritectic Alloys

A thorough understanding of the microstructures produced through solidification in peritectic systems has yet to be achieved, even though a large number of industrially and scientifically significant materials are in this class. One type of microstructure frequently observed during directional solidification consists of alternating layers of primary solid and peritectic solid oriented perpendicular to the growth direction. This layer formation is usually reported for alloy compositions within the two-phase region of the peritectic isotherm and for temperature gradient and growth rate conditions that result in a planar solid-liquid interface. Layered growth in peritectic alloys has not previously been characterized on a quantitative basis, nor has a mechanism for its formation been verified. The mechanisms that have been proposed for layer formation can be categorized as either extrinsic or intrinsic to the alloy system. The extrinsic mechanisms rely on externally induced perturbations to the system for layer formation, such as temperature oscillations, growth velocity variations, or vibrations. The intrinsic mechanisms approach layer formation as an alternative type of two phase growth that is inherent for certain peritectic systems and solidification conditions. Convective mixing of the liquid is an additional variable which can strongly influence the development and appearance of layers due to the requisite slow growth rate. The first quantitative description of layer formation is a model recently developed by Trivedi based on the intrinsic mechanism of cyclic accumulation and depiction of solute in the liquid ahead of the interface, linked to repeated nucleation events in the absence of convection. The objective of this research is to characterize the layered microstructures developed during ground-based experiments in which external influences have been minimized as much as possible and to compare these results to the current the model. Also, the differences between intrinsic and externally influenced layer formation were explored. The choice of alloy system is critical to a study of the formation of layered microstructures. The ideal system would have a well-characterized phase diagram, equal densities of both elements in the liquid state to minimize compositionally-driven convective flows, a low peritectic temperature to simplify directional solidification and the achievement of a high temperature gradient in the liquid, a broad composition range for the peritectic reaction, and a reasonable hardness at room temperature to facilitate handling and metallographic preparation. The In-Sn system was selected initially due to a very low peritectic temperature and the nearly equal densities of In and Sn in the liquid state. Since the In-rich peritectic reaction had apparently not been utilized previously for solidification research, experiments were conducted to check the phase diagram in the region of interest. The alloys in this system proved to be difficult to handle and prepare in bulk form with the equipment available, so experiments were initiated with the Sn-Cd system. Layered microstructures had been observed previously in Sn-Cd.

Lograsso, Thomas A.↗
NASA NTRS1991

An investigation of a contoured wall injector for hypervelocity mixing augmentation

An experimental and computational investigation of a contoured wall fuel injector is presented. The injector was aimed at enabling shock-enhanced mixing for the supersonic combustion ramjet engines currently envisioned for applications on hypersonic vehicles. Three-dimensional flow field surveys, and temporally-resolved planar Rayleigh scattering measurements are presented for Mach 1.7 helium injection into Mach 6 air. These experimental data are compared directly with a three-dimensional Navier-Stokes simulation of the flow about the injector array. Two dominant axial vorticity sources are identified and characterized. The axial vorticity produced strong convective mixing of the injectant with the freestream. Shock-impingement was particularly effective as it assured seeding of baroclinic vorticity directly on the helium/air interface. The vorticity coalesced into a counter-rotating vortex pair of a sense which produced migration of the helium away from the wall. The influences of spatial averaging on the representation of the flow field as well as the importance of the fluctuating component of the flow in producing molecularly-mixed fluid are addressed.

Waitz, Ian A.↗
DOE OSTI2022

Connecting the Radiative Influences of Aerosol upon the Mass Flux Profiles of Shallow Cumuli across the Southeast Atlantic Ocean Basin and its Boundaries (Final Report)

The Atlantic Ocean covers approximately 25% of Earth’s surface and the atmosphere above it is home to a complex array of clouds and aerosols that have important influences on regional and global weather and climate. These influences must be accurately depicted in short range, medium range, seasonal, and climate forecast models. Conditions over the tropical Atlantic are particularly complex due to continental scale plumes of dust from the Sahara Desert and smoke from agricultural burning in Africa that drift across the Atlantic Ocean basin toward the Americas. These plumes are often found meandering in the lower atmosphere above shallow tropical clouds that form above the ocean surface, presumably mingling with these clouds on occasion due to convective mixing processes. Elevated dust and smoke particles absorb incoming sunlight and substantially warm the marine atmosphere in the layer in which they are present. This warming may alter the thermal stability of the marine atmosphere and may throttle or enhance the development of clouds, change their internal structure and the rate at which they precipitate. Alternatively, it may isolate the lower atmosphere from drier layers above enabling water vapor to accumulate near the ocean surface potentially leading to the development of deeper convection. Our study was organized around the principal concept of determining the impact of African smoke and dust plumes upon cloud development at ASI and understanding how a popular shallow convection parameterization used in models responds to the presence of this aerosol. We analyzed observations collected during the US Department of Energy (DOE) Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign using the Atmospheric Radiation Measurement Program’s Mobile Facility #1 (AMF-1), which was deployed to Ascension Island (ASI) in Southeastern Atlantic for a one-year period. Ascension Island is immediately downwind from an African source of these plumes, but far enough removed to enable the lower atmosphere to have reacted to their presence. A main goal of our study was to compute radiative heating rate profiles over Ascension Island and along the trajectory from the biomass burning regions along coastal Africa to Ascension Island. To compute the radiative heating rate due to aerosols and clouds, we employed observed profiles of temperature, humidity, and clouds from LASIC alongside aerosol optical properties from the Modern-era Retrospective analysis for Research and Applications Version 2 (MERRA-2), as input for the Rapid Radiation Transfer Model (RRTM). Radiative heating was also assessed across the southeast Atlantic Ocean using an ensemble of back trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We were successful in this effort and the resulting publication is already being cited despite its relatively short lifetime in the literature. The second part of our study involved the process-level representation of the clouds observed over the Southeastern Atlantic in models. Our initial task, upon which the balance of this portion of the study depended, was to evaluate the representativeness of the clouds observed by AMF-1. What orographic influence did Ascension Island have on the measured cloud structure? We set out to answer this question by trying to separate observations that were clearly indicative of orographic forcing from those that were representative of open ocean. The siting of AMF-1, which was 340-m above sea-level on the slope of a steep escarpment, proved demonstrably problematic for cloud process measurements. Despite considerable effort using multiple approaches including artificial intelligence (AI), we were unable to successfully compensate for the orographic forcing present at the AMF-1 site on ASI and, hence, produce process-level summaries of the convective mass flux representative of open ocean over the Southeastern Atlantic. Even though the project has officially ended, we are making a final attempt using two new types of clustering algorithm (i.e., AI) on the recommendation of a former student, who is an expert in this area. Since we have only recently begun to test these new AI schemes, the recommendations from the second part of our project outlined below are based on our experience at the time of this report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Challenge Problem 1: Preliminary Results of the Direct Numerical Simulation of Transient Flows

This report presents the first direct numerical simulations (DNS) of transient mixed convection in an idealized downcomer-like channel (Challenge Problem 1, Phase II). Using the GPU-accelerated NekRS solver, we modeled a sudden decay in driving pressure, mimicking loss-of-flow events, and tracked the resulting evolution of Reynolds number, boundary-layer structure, turbulence statistics, and heat-transfer metrics. Key findings include the systematic thickening and eventual asymmetry of velocity and thermal boundary layers under buoyant deceleration; minimal “memory” lag in Reynolds shear stress and TKE profiles when sampled at matching Re, yet clear shifts of peak locations toward the cooled wall; overshoots in transient eddy-viscosity and eddy-diffusivity (and corresponding sub-unity turbulent Prandtl numbers) on the cooled side; and a pronounced transient Nusselt-number enhancement driven by wall-temperature inertia and residual eddy mixing. These effects combined to offer a temporary cooling margin above steady-state predictions during reactor LOF transients. Future work will extend this work to a more complex “Case II” geometry (90° turn + lower plenum) and generate multi-Re/Pr datasets for data-driven turbulence closures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A New Hybrid Mass-Flux/High-Order Turbulence Closure for Ocean Vertical Mixing

While various parameterizations of vertical turbulent fluxes at different levels of complexity have been proposed, each has its own limitations. For example, simple first-order closure schemes such as the K-Profile Parameterization (KPP) lack energetic constraints; two-equation models $k-ε$ like directly solve an equation for the turbulent kinetic energy but do not account for non-diffusive fluxes, and high-order closures that include the high-order transport terms are computationally expensive. To address these, we extend the Assumed-Distribution Higher-Order Closure (ADC) framework originally proposed for the atmospheric boundary layer and apply it to the ocean surface boundary layer. By assuming a probability distribution function relationship between the vertical velocity and tracers, all second-order and higher-order moments are exactly constructed and turbulence closure is achieved in the ADC scheme. In addition, this ADC parameterization has full energetic constraints and includes non-diffusive fluxes without the computational cost of a full higher-order closure scheme. We have tested the ADC scheme against a combination of large eddy simulation (LES), KPP, and $k-ε$ for surface buoyancy-driven convective mixing and found that the ADC scheme is robust with different vertical resolutions and compares well to the LES results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data-Driven RANS Turbulence Closures for Forced Convection Flow in Reactor Downcomer Geometry

Recent progress in data-driven turbulence modeling has shown its potential to enhance or replace traditional equation-based Reynolds-averaged Navier-Stokes (RANS) turbulence models. Here, this work utilizes invariant neural network (NN) architectures to model Reynolds stresses and turbulent heat fluxes in forced convection flows (when the models can be decoupled). As the considered flow is statistically one dimensional, the invariant NN architecture for the Reynolds stress model reduces to the linear eddy viscosity model. To develop the data-driven models, direct numerical and RANS simulations in vertical planar channel geometry mimicking a part of the reactor downcomer are performed. Different conditions and fluids relevant to advanced reactors (sodium, lead, unitary-Prandtl-number fluid, and molten salt) constitute the training database. The models enabled accurate predictions of velocity and temperature, and compared to the baseline k–τ turbulence model with the simple gradient diffusion hypothesis, do not require tuning of the turbulent Prandtl number. The data-driven framework is implemented in the open-source graphics processing unit–accelerated spectral element solver nekRS and has shown the potential for future developments and consideration of more complex mixed convection flows.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Benchmarking CO₂ storage simulations: Results from the 11 th Society of Petroleum Engineers Comparative Solution Project

The 11 th Society of Petroleum Engineers Comparative Solution Project (shortened SPE11 herein) benchmarked simulation tools for geological carbon dioxide (CO 2 ) storage. A total of 45 groups from leading research institutions and industry across the globe signed up to participate, with 18 ultimately contributing valid results that were included in the comparative study reported here. This paper summarizes the SPE11 results. A comprehensive introduction and qualitative discussion of the submitted data are provided, together with an overview of online resources for accessing the full depth of data. A global metric for analyzing the relative distance between submissions is proposed and used to conduct a quantitative analysis of the submissions. This analysis attempts to statistically resolve the key aspects influencing the variability between submissions. The study shows that the major qualitative variation between the submitted results is related to thermal effects, dissolution-driven convective mixing, and resolution of facies discontinuities. Moreover, a strong dependence on grid resolution is observed across all three versions of the SPE11. However, our quantitative analysis suggests that the observed variations are predominantly influenced by factors not documented in the technical responses provided by the participants. We therefore identify that unreported variations due to human choices within the process of setting up, conducting, and reporting on the simulations underlying each SPE11 submission are at least as impactful as the computational choices reported.

Nordbotten, Jan M. [Univ. of Bergen (Norway); Norw↗
DOE OSTI2023

A unified non-equilibrium phase change model for injection flow modeling

The homogenous relaxation model (HRM) is one of the most widely used models to describe the liquid- gas phase transition. However, in its original formulation, it is unable to handle multispecies vapor-liquid equilibrium (VLE), which limits its applicability to single-component fluids. In this work, a unified non-equilibrium phase change model that considers the VLE of multicomponent mixtures is proposed building upon the HRM's structure. A time factor is introduced to mimic the effect of different phase change timescales due to different mechanisms, e.g., cavitation, flash-boiling, and evaporation. Here to assess the model's performance, computational fluid dynamics simulations of the internal and near-nozzle injection flow of the Engine Combustion Network's Spray G injector were performed using the nine-component PACE-20 fuel with both the unified model and the original HRM. The predicted fuel density in the near-nozzle region matched well with X-ray tomography measurements. The simulation results indicated that, whereas the HRM failed to capture the vaporization due to convective mixing between the fuel and ambient gas, the unified model performed well in predicting the mixing-driven vaporization and the corresponding evaporative cooling. Further comparisons using the nine-component fuel formula and a single-component fuel surrogate demonstrated the unified model's ability to predict preferential vaporization, which affects the predictions of local mixture composition and rate of vaporization. Finally, it is shown that the unified model is capable of representing multiple phase change mechanisms, and the relaxation time factor plays an important role in determining the degree of phase change due to the different mechanisms.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Perfect Crystals: microgravity capillary counterdiffusion crystallization of human manganese superoxide dismutase for neutron crystallography

The NASA mission Perfect Crystals used the microgravity environment on the International Space Station (ISS) to grow crystals of human manganese superoxide dismutase (MnSOD)—an oxidoreductase critical for mitochondrial vitality and human health. The mission’s overarching aim is to perform neutron protein crystallography (NPC) on MnSOD to directly visualize proton positions and derive a chemical understanding of the concerted proton electron transfers performed by the enzyme. Large crystals that are perfect enough to diffract neutrons to sufficient resolution are essential for NPC. This combination, large and perfect, is hard to achieve on Earth due to gravity-induced convective mixing. Capillary counterdiffusion methods were developed that provided a gradient of conditions for crystal growth along with a built-in time delay that prevented premature crystallization before stowage on the ISS. Here, we report a highly successful and versatile crystallization system to grow a plethora of crystals for high-resolution NPC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Experiments and gyrokinetic simulations of the nonlinear interaction between spinning magnetized plasma pressure filaments

A set of experiments using controlled, skin depth-sized plasma pressure filaments in close proximity have been carried out in a large linear magnetized plasma device. Two- and three-filament configurations have been used to determine the scale of cross field nonlinear interaction. When the filaments are separated by a distance of approximately five times the size of a single filament or less, a significant transfer of charge and energy occurs, leading to the generation of inter-filament electric fields. This has the effect of rotating the filaments and influencing the merging dynamics. Nonlinear gyrokinetic simulations using seeded filaments confirm the presence of unstable drift-Alfvén modes driven by the steep electron temperature gradient. When the filaments are within a few collisionless electron skin depths (separations twice the size of a single filament), the unstable perturbations drive the convective mixing of the density and temperature and rearrange the gradients such that they maximize in the region surrounding the filament bundle.

Sydora, R. D. (ORCID:0000000192543149)↗
DOE OSTI2022

Toward full simulations for a liquid metal blanket: part 2. Computations of MHD flows with volumetric heating for a PbLi blanket prototype at Ha ~10 4 and Gr ~10 12

On the pathway toward full simulations for a liquid metal (LM) blanket, this part 2 extends a previous study of purely magnetohydrodynamic (MHD) flows in a DCLL blanket in reference Chen et al (2020 Nucl. Fusion 60 076003) to more general conditions when the MHD flow is coupled with heat transfer. The simulated prototypic blanket module includes all components of a real LM blanket system, such as supply ducts, inlet and outlet manifolds, multiple poloidal ducts and a U-turn zone. Volumetric heating generated by fusion neutrons is added to simulate thermal effects in the flowing lead–lithium (PbLi) breeder. The MHD flow equations and the energy equation are solved with a DNS-type finite-volume code ‘MHD-UCAS’ on a very fine mesh of 470 × 10 6 cells. The applied magnetic field is 5 T (Hartmann number Ha ~ 10 4 ), the PbLi velocity in the poloidal ducts is 10 cm s –1 (Reynolds number Re ~10 5 ), whereas the maximum volumetric heating is 30 MW m –3 (Grashof number Gr ~ 10 12 ). Four cases have been simulated, including forced- and mixed-convection flows, and either an electrically conducting or insulating blanket structure. Various comparisons are made between the four computed cases and also against the purely MHD flows computed earlier in reference Chen et al (2020 Nucl. Fusion 60 076003) with regards to the (1) MHD pressure drop, (2) flow balancing, (3) temperature field, (4) flows in particular blanket components, and (5) 3D and turbulent flow effects. The strongest buoyancy effects were found in the poloidal ducts. In the electrically non-conducting blanket, the buoyancy forces lead to significant modifications of the flow structure, such as formation of reverse flows, whereas their effect on the MHD pressure drop is relatively small. In the electrically conducting blanket case, the buoyancy effects on the flow and MHD pressure drop are almost negligible.

Physics↗
DOE OSTI2020

Modelling R Coronae Borealis stars: effects of He-burning shell temperature and metallicity

The R Coronae Borealis (RCB) stars are extremely hydrogen-deficient carbon stars that produce large amounts of dust, causing sudden deep declines in brightness. They are believed to be formed primarily through white dwarf mergers. In this paper, we use mesa to investigate how post-merger objects with a range of initial He-burning shell temperatures from 2.1 to 5.4 × 10 8 K with solar and subsolar metallicities evolve into RCB stars. The most successful model of these has subsolar metallicity and an initial temperature near 3 × 10 8 K. We find a strong dependence on initial He-burning shell temperature for surface abundances of elements involved in the CNO cycle, as well as differences in effective temperature and radius of RCBs. Elements involved in nucleosynthesis present around 1 dex diminished surface abundances in the 10 per cent solar metallicity models, with the exception of carbon and lithium that are discussed in detail. Models with subsolar metallicities also exhibit longer lifetimes than their solar counterparts. In addition, we find that convective mixing of the burned material occurs only in the first few years of post-merger evolution, after which the surface abundances are constant during and after the RCB phase, providing evidence for why these stars show a strong enhancement of partial He-burning products.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A spectrophotometric analysis of cool white dwarfs in the Gaia and pan-STARRS footprint

We present a spectrophotometric analysis of 2880 cool white dwarfs within 100 pc of the Sun and cooler than T eff ∼ 10 000 K, with grizy Pan-STARRS photometry and Gaia trigonometric parallaxes available. We also supplement our data sets with near-infrared JHK photometry, when available, which is shown to be essential for interpreting the coolest white dwarfs in our sample. We perform a detailed analysis of each individual object using state-of-the-art model atmospheres appropriate for each spectral type, including DA, DC, DQ, DZ, He-rich DA, and the so-called IR-faint white dwarfs. We discuss the temperature and mass distributions of each subsample, as well as revisit the spectral evolution of cool white dwarfs. We find little evidence in our sample for the transformation of a significant fraction of DA stars into He-atmosphere white dwarfs through the process of convective mixing between T eff = 10 000 and ∼6500 K, although the situation changes drastically in the range T eff = 6500–5500 K where the fraction of He-atmosphere white dwarfs reaches ∼45 per cent. However, we also provide strong evidence that at even cooler temperatures (T eff ≲ 5200 K), most DC white dwarfs have H atmospheres. We discuss a possible mechanism to account for this sudden transformation from He- to H-atmosphere white dwarfs involving the onset of crystallization and the occurrence of magnetism. Finally, we also argue that DQ, DZ, and DC white dwarfs may form a more homogeneous population than previously believed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Temporal Forecasting of Distributed Temperature Sensing in a Thermal Hydraulic System With Machine Learning and Statistical Models

We benchmark performance of long-short term memory (LSTM) network machine learning model and autoregressive integrated moving average (ARIMA) statistical model in temporal forecasting of distributed temperature sensing (DTS). Data in this study consists of fluid temperature transient measured with two co-located Rayleigh scattering fiber optic sensors (FOS) in a forced convection mixing zone of a thermal tee. We treat each gauge of a FOS as an independent temperature sensor. We first study prediction of DTS time series using Vanilla LSTM and ARIMA models trained on prior history of the same FOS that is used for testing. The results yield maximum absolute percentage error (MaxAPE) and root mean squared percentage error (RMSPE) of 1.58% and 0.06% for ARIMA, and 3.14% and 0.44% for LSTM, respectively. Next, we investigate zero-shot forecasting (ZSF) with LSTM and ARIMA trained on history of the co-located FOS only, which is advantageous when limited training data is available. The ZSF MaxAPE and RMSPE values for ARIMA are comparable to those of the Vanilla use case, while the error values for LSTM increase. We show that in ZSF, performance of LSTM network can be improved by training on most correlated gauges between the two FOS, which are identified by calculating the Pearson correlation coefficient. The improved ZSF MaxAPE and RMSPE for LSTM are 4.4% and 0.33%, respectively. Performance of ZSF LSTM can be further enhanced through transfer learning (TL), where LSTM is re-trained on a subset of the FOS that is the target of forecasting. We show that LSTM pre-trained on correlated dataset and re-trained on 30% of testing target dataset achieves MaxAPE and RMSPE values of 2.32% and 0.28%, respectively.

ARIMA↗