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At least 145 records · Page 8

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NASA NTRS2008

Shear Thinning Near the Critical Point of Xenon

We measured shear thinning, a viscosity decrease ordinarily associated with complex liquids, near the critical point of xenon. The data span a wide range of reduced shear rate: 10(exp -3) < gamma-dot tau < 700, where gamma-dot tau is the shear rate scaled by the relaxation time tau of critical fluctuations. The measurements had a temperature resolution of 0.01 mK and were conducted in microgravity aboard the Space Shuttle Columbia to avoid the density stratification caused by Earth's gravity. The viscometer measured the drag on a delicate nickel screen as it oscillated in the xenon at amplitudes 3 mu,m < chi (sub 0) >430 mu, and frequencies 1 Hz < omega/2 pi < 5 Hz. To separate shear thinning from other nonlinearities, we computed the ratio of the viscous force on the screen at gamma-dot tau to the force at gamma-dot tau approximates 0: C(sub gamma) is identical with F(chi(sub 0), omega tau, gamma-dot tau )/F)(chi(sub 0, omega tau, 0). At low frequencies, (omega tau)(exp 2) < gamma-dot tau, C(sub gamma) depends only on gamma-dot tau, as predicted by dynamic critical scaling. At high frequencies, (omega tau)(exp 2) > gamma-dot tau, C(sub gamma) depends also on both x(sub 0) and omega. The data were compared with numerical calculations based on the Carreau-Yasuda relation for complex fluids: eta(gamma-dot)/eta(0)=[1+A(sub gamma)|gamma-dot tau|](exp - chi(sub eta)/3+chi(sub eta)), where chi(sub eta) =0.069 is the critical exponent for viscosity and mode-coupling theory predicts A(sub gamma) =0.121. For xenon we find A(sub gamma) =0.137 +/- 0.029, in agreement with the mode coupling value. Remarkably, the xenon data close to the critical temperature T(sub c) were independent of the cooling rate (both above and below T(sub c) and these data were symmetric about T(sub c) to within a temperature scale factor. The scale factors for the magnitude of the oscillator s response differed from those for the oscillator's phase; this suggests that the surface tension of the two-phase domains affected the drag on the screen below T(sub c).

Zimmerli, Gregory A.↗

NASA NTRS2010

International Space Station Mechanisms and Maintenance Flight Control Documentation and Training Development

International Space Station (ISS) crew and flight controller training documentation is used to aid in training operations. The Generic Simulations References SharePoint (Gen Sim) site is a database used as an aid during flight simulations. The Gen Sim site is used to make individual mission segment timelines, data, and flight information easily accessible to instructors. The Waste and Hygiene Compartment (WHC) training schematic includes simple and complex fluid schematics, as well as overall hardware locations. It is used as a teaching aid during WHC lessons for both ISS crew and flight controllers. ISS flight control documentation is used to support all aspects of ISS mission operations. The Quick Look Database and Consolidated Tool Page are imagery-based references used in real-time to help the Operations Support Officer (OSO) find data faster and improve discussions with the Flight Director and Capsule Communicator (CAPCOM). A Quick Look page was created for the Permanent Multipurpose Module (PMM) by locating photos of the module interior, labeling specific hardware, and organizing them in schematic form to match the layout of the PMM interior. A Tool Page was created for the Maintenance Work Area (MWA) by gathering images, detailed drawings, safety information, procedures, certifications, demonstration videos, and general facts of each MWA component and displaying them in an easily accessible and consistent format. Participation in ISS mechanisms and maintenance lessons, mission simulation On-the-Job Training (OJT), and real-time flight OJT was used as an opportunity to train for day-to-day operations as an OSO, as well as learn how to effectively respond to failures and emergencies during mission simulations and real-time flight operations.

Daugherty, Colin C.↗

NASA NTRS2016

Expanding NASA and Roscosmos Scientific Collaboration on the International Space Station

The International Space Station (ISS) is a world-class laboratory orbiting in space. NASA and Roscosmos have developed a strong relationship through the ISS Program Partnership, working together and with the other ISS Partners for more than twenty years. Since 2013, based on a framework agreement between the Program Managers, NASA and Roscosmos are building a joint program of collaborative research on ISS. This international collaboration is developed and implemented in phases. Initially, members of the ISS Program Science Forum from NASA and TsNIIMash (representing Roscosmos) identified the first set of NASA experiments that could be implemented in the "near term". The experiments represented the research categories of Technology Demonstration, Microbiology, and Education. Through these experiments, the teams from the "program" and "operations" communities learned to work together to identify collaboration opportunities, establish agreements, and jointly plan and execute the experiments. The first joint scientific activity on ISS occurred in January 2014, and implementation of these joint experiments continues through present ISS operations. NASA and TsNIIMash have proceeded to develop "medium term" collaborations, where scientists join together to improve already-proposed experiments. A major success is the joint One-Year Mission on ISS, with astronaut Scott Kelly and cosmonaut Mikhail Kornienko, who returned from ISS in March, 2016. The teams from the NASA Human Research Program and the RAS Institute for Biomedical Problems built on their considerable experience to design joint experiments, learn to work with each other's protocols and processes, and share medical and research data. New collaborations are being developed between American and Russian scientists in complex fluids, robotics, rodent research and space biology, and additional human research. Collaborations are also being developed in Earth Remote Sensing, where scientists will share data from imaging systems mounted on ISS as well as other orbiting spacecraft to improve our understanding of the Earth and its climate. NASA and Roscosmos continue to encourage international scientific cooperation and expanded use of the ISS Laboratory. "Long-term", larger collaborations will achieve scientific objectives that no single national science team or agency can achieve on its own. The joint accomplishments achieved so far have paved the way for a stronger international scientific community and improved results and benefits from ISS.

Hasbrook, Pete↗

NASA NTRSDate not supplied

What's New in the PSI? (Physical Sciences Informatics)

The NASA Physical Sciences Informatics (PSI) database is NASA’s archival for physical sciences research in microgravity – on ISS and also other reduced gravity platforms. The database has been making data from microgravity physical science investigations publicly available since its launch late 2014. The database was an early investment in Open Science for NASA’s Biophysics and Physical Sciences (BPS) Division of the Science Mission Directorate (SMD), who conducts fundamental and applied physical sciences yielding research data in 6 disciplines: biophysics, combustion science, complex fluids, fluid physics, fundamental physics, and materials science. PSI started initially with data from 14 microgravity investigations. Receipt of data through the years and an annual NRA to fund ground investigations extending flight datasets has increased the total to 72 investigations available with 8 new datasets in the 2020 NRA (NNH20ZDA014N). These new datasets are open for public access at the PSI website at https://www.nasa.gov/PSI.

Physical Sciences Informatics PSI database↗

DOE OSTI2021

Slippery self-lubricating polymer surfaces

The present disclosure describes a strategy to create self-healing, slippery self-lubricating polymers. Lubricating liquids with affinities to polymers can be utilized to get absorbed within the polymer and form a lubricant layer (of the lubricating liquid) on the polymer. The lubricant layer can repel a wide range of materials, including simple and complex fluids (water, hydrocarbons, crude oil and bodily fluids), restore liquid-repellency after physical damage, and resist ice, microorganisms and insects adhesion. Some exemplary applications where self-lubricating polymers will be useful include energy-efficient, friction-reduction fluid handling and transportation, medical devices, anti-icing, optical sensing, and as self-cleaning, and anti-fouling materials operating in extreme environments.

Aizenberg, Joanna↗

DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Mapping Local Dissipation and Entropy Production in Complex and Active Fluids

While global entropy production provides a measure of irreversibility, its partitioning into contributions from local regions is key to understanding the mechanisms underlying time-reversal symmetry breaking in complex systems and active matter. Here, by analyzing local heat flows and fluxes, we propose a framework that enables the mapping of local dissipation and entropy production in a nonequilibrium system. We test this approach in simulations of fluids driven through complex environments and active systems. We connect the results across the local and global scales by showing that local dissipation and entropy production satisfy a local version of the usual (global) fluctuation theorem, which accounts for the correlations between the local region and its surroundings. Interestingly, in the case of the active fluid, our analysis reveals that these correlations are of opposite signs for the active (stochastic) and passive (deterministic) contributions to local dissipation.

Entropy↗

DOE OSTI2026

Selective transport of light vs. heavy rare earth elements by sulfate/bisulfate complexes in hydrothermal fluids

Here, this study explores the transport of rare earth elements (REE) in acidic sulfate-bearing hydrothermal fluids and the implications for the fractionation of light/heavy REE in critical mineral deposits. The speciation of Nd (light REE) and Yb (heavy REE) sulfate complexes were determined via in situ Raman spectroscopy using fused SiO 2 capillary cells up to 300 ºC at saturated water vapor pressure and in a hydrothermal diamond anvil cell up to 500 ºC and 540 MPa. The REE monosulfate (REESO 4 + ) and REE disulfate (REE(SO 4 ) 2 - ) species are stable below 150 to 250 ºC but become less stable at higher temperatures, particularly the light REE, due to the decreased solubility of REE sulfate solids. At higher pressure, these REE sulfate complexes display an increased stability field up to 400 ℃. The REE bisulfate complex (REEHSO 4 2+ ) was identified with a wide stability field below 400 ºC for the HREE in acidic Yb 2 (SO 4 ) 3 -bearing solutions, whereas in Nd 2 (SO 4 ) 3 -bearing solutions, the LREE bisulfate complex is restricted to below 100 ℃. These results suggest that bisulfate is a previously unrecognized selective ligand for heavy REE transport at low temperature in acidic oxidized hydrothermal fluids. Such fluids are responsible for hydrothermal alteration in many REE deposits. Prediction of phase stabilities across pressure, temperature, and composition space (P-T- x ) is crucial for predicting the role of aqueous REE sulfate complexes in the mobilization of REE in crustal fluids.

58 GEOSCIENCES↗

DOE OSTI2021

Computationally Efficient Multiscale Neural Networks Applied to Fluid Flow in Complex 3D Porous Media

Abstract The permeability of complex porous materials is of interest to many engineering disciplines. This quantity can be obtained via direct flow simulation, which provides the most accurate results, but is very computationally expensive. In particular, the simulation convergence time scales poorly as the simulation domains become less porous or more heterogeneous. Semi-analytical models that rely on averaged structural properties (i.e., porosity and tortuosity) have been proposed, but these features only partly summarize the domain, resulting in limited applicability. On the other hand, data-driven machine learning approaches have shown great promise for building more general models by virtue of accounting for the spatial arrangement of the domains’ solid boundaries. However, prior approaches building on the convolutional neural network (ConvNet) literature concerning 2D image recognition problems do not scale well to the large 3D domains required to obtain a representative elementary volume (REV). As such, most prior work focused on homogeneous samples, where a small REV entails that the global nature of fluid flow could be mostly neglected, and accordingly, the memory bottleneck of addressing 3D domains with ConvNets was side-stepped. Therefore, important geometries such as fractures and vuggy domains could not be modeled properly. In this work, we address this limitation with a general multiscale deep learning model that is able to learn from porous media simulation data. By using a coupled set of neural networks that view the domain on different scales, we enable the evaluation of large ( $$>512^3$$ > 512 3 ) images in approximately one second on a single graphics processing unit. This model architecture opens up the possibility of modeling domain sizes that would not be feasible using traditional direct simulation tools on a desktop computer. We validate our method with a laminar fluid flow case using vuggy samples and fractures. As a result of viewing the entire domain at once, our model is able to perform accurate prediction on domains exhibiting a large degree of heterogeneity. We expect the methodology to be applicable to many other transport problems where complex geometries play a central role.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Complex subsurface hydrothermal fluid mixing at a submarine arc volcano supports distinct and highly diverse microbial communities

Hydrothermally active submarine volcanoes are mineral-rich biological oases contributing significantly to chemical fluxes in the deep sea, yet little is known about the microbial communities inhabiting these systems. Here we investigate the diversity of microbial life in hydrothermal deposits and their metagenomics-inferred physiology in light of the geological history and resulting hydrothermal fluid paths in the subsurface of Brothers submarine volcano north of New Zealand on the southern Kermadec arc. From metagenome-assembled genomes we identified over 90 putative bacterial and archaeal genomic families and nearly 300 previously unknown genera, many potentially endemic to this submarine volcanic environment. While magmatically influenced hydrothermal systems on the volcanic resurgent cones of Brothers volcano harbor communities of thermoacidophiles and diverse members of the superphylum “DPANN,” two distinct communities are associated with the caldera wall, likely shaped by two different types of hydrothermal circulation. The communities whose phylogenetic diversity primarily aligns with that of the cone sites and magmatically influenced hydrothermal systems elsewhere are characterized predominately by anaerobic metabolisms. These populations are probably maintained by fluids with greater magmatic inputs that have interacted with different (deeper) previously altered mineral assemblages. However, proximal (a few meters distant) communities with gene-inferred aerobic, microaerophilic, and anaerobic metabolisms are likely supported by shallower seawater-dominated circulation. Furthermore, mixing of fluids from these two distinct hydrothermal circulation systems may have an underlying imprint on the high microbial phylogenomic diversity. Collectively our results highlight the importance of considering geologic evolution and history of subsurface processes in studying microbial colonization and community dynamics in volcanic environments.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1985

Application of computational fluid dynamics to complex inlet ducts

A three-dimensional parabolic Navier-Stokes code, PEPSIG, was used to analyze the flow in the subsonic diffuser section of a typical modern inlet design. The effect of curvature of the diffuser centerline and transitioning cross sections was studied to determine the primary cause of flow distortion in the duct. Total pressure values at the engine compressor face are reported.

Towne, C. E.↗

NASA NTRS1985

Application of computational fluid dynamics to complex inlet ducts

Towne, C. E.↗

NASA NTRS1991

A finite element random response analysis of a complex panel with fluid-conveying pipes

A finite element approach is developed for a complex panel with fluid-conveying pipes undergoing large deflections subjected to random loadings. The influence of fluid velocity on the random response is investigated. The root-mean-square (rms) deflections and frequencies for different sound spectrum level value are studied. All four edges of the panel are considered to have the same conditions and restrictions. Either simply supported of clamped boundary condition with respect to the transverse deflection of the panel is considered. The prediction of fatigue life is then based on obtained rms stress. This analytical investigation will help to broaden the basic understanding of the role of fluid flow within structures subjected to acoustic loading.

Chiang, C. K.↗

NASA NTRS2006

Program for Analyzing Flows in a Complex Network

Generalized Fluid System Simulation Program (GFSSP) version 4 is a general-purpose computer program for analyzing steady-state and transient flows in a complex fluid network. The program is capable of modeling compressibility, fluid transients (e.g., water hammers), phase changes, mixtures of chemical species, and such externally applied body forces as gravitational and centrifugal ones. A graphical user interface enables the user to interactively develop a simulation of a fluid network consisting of nodes and branches. The user can also run the simulation and view the results in the interface. The system of equations for conservation of mass, energy, chemical species, and momentum is solved numerically by a combination of the Newton-Raphson and successive-substitution methods.

Majumdar, Alok Kumar↗

DOE OSTI2021

Rocket yeast

Not Available

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2003

Precision Clean Hardware: Maintenance of Fluid Systems Cleanliness

The ISS fluid systems are so complex that fluid system cleanliness cannot be verified at the assembly level. A "build clean / maintain clean" approach was used by all major fluid systems: Verify cleanliness at the detail and subassembly level. Maintain cleanliness during assembly.

Sharp, Sheila↗

DOE OSTI2022

Room-temperature polariton quantum fluids in halide perovskites

Abstract Quantum fluids exhibit quantum mechanical effects at the macroscopic level, which contrast strongly with classical fluids. Gain-dissipative solid-state exciton-polaritons systems are promising emulation platforms for complex quantum fluid studies at elevated temperatures. Recently, halide perovskite polariton systems have emerged as materials with distinctive advantages over other room-temperature systems for future studies of topological physics, non-Abelian gauge fields, and spin-orbit interactions. However, the demonstration of nonlinear quantum hydrodynamics, such as superfluidity and Čerenkov flow, which is a consequence of the renormalized elementary excitation spectrum, remains elusive in halide perovskites. Here, using homogenous halide perovskites single crystals, we report, in both one- and two-dimensional cases, the complete set of quantum fluid phase transitions from normal classical fluids to scatterless polariton superfluids and supersonic fluids—all at room temperature, clear consequences of the Landau criterion. Specifically, the supersonic Čerenkov wave pattern was observed at room temperature. The experimental results are also in quantitative agreement with theoretical predictions from the dissipative Gross-Pitaevskii equation. Our results set the stage for exploring the rich non-equilibrium quantum fluid many-body physics at room temperature and also pave the way for important polaritonic device applications.

42 ENGINEERING↗

DOE OSTI2021

Ring Model Development and Validation for Prismatic HTGR Core Thermal-hydraulics and Safety Analysis

Because of the complex core geometry, prismatic high temperature gas-cooled reactors (prismatic HTGRs) often exhibit complex thermal fluid behaviors during both normal operating and transient conditions. Most HTGR designs rely on passive safety system for decay heat removal, such as the reactor cavity cooling system (RCCS). During postulated accidents like Pressurized Conduction Cooldown (PCC) event, the decay heat is first radially transferred from the core region to the reactor vessel outer surface, then to the RCCS cooling panels. The peak fuel temperature is controlled by heat transfer mechanisms with two distinctive characteristic length scales, i.e., the core-wise effective heat conduction and local heat conduction in the fuel pellet scale. As both length scales are essential to determine the fuel temperature, from the modeling perspective, computer codes must be able to capture heat transfer in both scales. This is challenging for both computational fluid dynamics (CFD) tools because of extremely large amount of computation resources required, and for system analysis codes because of the challenge to model the complex core geometry. Under the support of DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, efforts have been pursued to support HTGR technology development and its modeling and simulation needs. There is a particular need for advanced modeling and simulation tools to predict thermal-fluid behavior during safety-related transients. In our previous studies, the ring model was adopted in SAM and further developed to simulate the normal operating condition and a PCC event using the MHTGR-350 design of General Atomics as the reference design. This current work represents a continuation of these previous efforts, and the focus is to critically review and examine simplifications and assumptions made to develop the ring model, and to perform code validation using experimental data from an integral-effect test facility, the High Temperature Test Facility (HTTF) at the Oregon State University. In this study, the test PG-27 from the HTTF test suite was selected for code validation purpose. The test PG-27 is a transient test designed to simulate the PCC event of the MHTGR design. Very good agreements between SAM prediction and experimental measurements were found in both coolant and solid structure temperatures during the transient.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗