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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Physical Science Informatics: Providing Open Science Access to Microheater Array Boiling Experiment Data

The Physical Science Informatics (PSI) system is the next step in this an effort to make NASA sponsored flight data available to the scientific and engineering community, along with the general public. The experimental data, from six overall disciplines, Combustion Science, Fluid Physics, Complex Fluids, Fundamental Physics, and Materials Science, will present some unique challenges. Besides data in textual or numerical format, large portions of both the raw and analyzed data for many of these experiments are digital images and video, requiring large data storage requirements. In addition, the accessible data will include experiment design and engineering data (including applicable drawings), any analytical or numerical models, publications, reports, and patents, and any commercial products developed as a result of the research. This objective of paper includes the following: Present the preliminary layout (Figure 2) of MABE data within the PSI database. Obtain feedback on the layout. Present the procedure to obtain access to this database.

nucleate boiling↗
DOE OSTI2019

Building Reconfigurable Devices Using Complex Liquid–Fluid Interfaces

Liquid-fluid interfaces provide a platform both for structuring liquids into complex shapes and assembling dimensionally confined, functional nanomaterials. Historically, attention in this area has focused on simple emulsions and foams, in which surface-active materials such as surfactants or colloids stabilize structures against coalescence and alter the mechanical properties of the interface. In recent decades, however, a growing body of work has begun to demonstrate the full potential of the assembly of nanomaterials at liquid-fluid interfaces to generate functionally advanced, biomimetic systems. In this work, a broad overview is given, from fundamentals to applications, of the use of liquid-fluid interfaces to generate complex, all-liquid devices with a myriad of potential applications.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Novel Biomedical Device Utilizing Light-Emitting Nanostructures Developed

Sketches and chemical diagrams of state-of-the-art device and novel proposed device are presented. Current device uses a diode laser that emits into a fluorescent fluid only one wavelength and a photodetector diode that detects only one wavelength. Only one type of bacteria can be detected. The proposed device uses a quantum dot array that emits into a fluorescent fluid multiple wavelengths and an NIR 512 spectrometer that scans 0.8- to 1.7-mm wavelengths. Hundreds of different bacteria and viruses can be detected. A novel biomedical device is being developed at the NASA Glenn Research Center in cooperation with the University of Michigan. This device uses nano-structured quantum dots that emit light in the near-infrared (IR) region. The nanostructured quantum dots are used as a source and excite fluorochrome polymers coupled with antibodies that seek out and attach to specific bacteria and viruses. The fluorochrome polymers/antibodies fluoresce at specific wavelengths in the near-IR spectrum, but these wavelengths are offset from the excitation wavelength and can be detected with a tunable spectrometer. The device will be used to detect the presence of viruses and bacteria in simple fluids and eventually in more complex fluids, such as blood. Current state-of-the-art devices are limited to single bacteria or virus detection and a considerable amount of time and effort is required to prepare samples for analysis. Most importantly, the devices are quite large and cumbersome, which prohibits them from being used on the International Space Station and the space shuttles. This novel device uses nanostructured quantum dots which, through molecular beam epitaxy and highly selective annealing processes, can be developed into an illumination source that could potentially generate hundreds of specific wavelengths. As a result, this device will be able to excite hundreds of antibody/fluorochrome polymer combinations, which in turn could be used to detect hundreds of bacteria and viruses in fluids. A novel sample preparation technique that exploits micromembrane filtration and centrifugation methods has been developed for this device. The technique greatly reduces the time required to prepare the sample and the amount of sample needed to perform an accurate and comprehensive analysis. Last, and probably most important, because of the nano-light-emitting source and the novel sample preparation technique, the overall size of the device could be reduced dramatically. This device will serve as a nanoscale lab-on-a-chip for in situ microorganism detection and will enable tests to be performed on a time scale of minutes rather than days. Thus, it is ideally suited for monitoring the environmental conditions onboard the International Space Station and the space shuttles, thereby enhancing the safety of the astronauts. In addition, the device has important commercial applications, such as detecting the presence of bacteria and viruses in water at food- and beverage-processing centers, water treatment plants, and restaurants. Also, this technology has the potential to be used to detect bacteria and viruses in more complex fluids, such as blood--which in all likelihood would revolutionize blood analysis as it is performed today. This project was made possible through the Director's Discretionary Fund and is ongoing. In addition, this project provides funding to Dr. Rachel Goldman of the University of Michigan for the research and development of nanostructured quantum dots.

Scardelletti, Maximilian C.↗
NASA NTRS2015

Rheological Properties of Quasi-2D Fluids in Microgravity

In recent years, research on complex fluids and fluids in restricted geometries has attracted much attention in the scientific community. This can be attributed not only to the development of novel materials based on complex fluids but also to a variety of important physical phenomena which have barely been explored. One example is the behavior of membranes and thin fluid films, which can be described by two-dimensional (2D) rheology behavior that is quite different from 3D fluids. In this study, we have investigated the rheological properties of freely suspended films of a thermotropic liquid crystal in microgravity experiments. This model system mimics isotropic and anisotropic quasi 2D fluids [46]. We use inkjet printing technology to dispense small droplets (inclusions) onto the film surface. The motion of these inclusions provides information on the rheological properties of the films and allows the study of a variety of flow instabilities. Flat films have been investigated on a sub-orbital rocket flight and curved films (bubbles) have been studied in the ISS project OASIS. Microgravity is essential when the films are curved in order to avoid sedimentation. The experiments yield the mobility of the droplets in the films as well as the mutual mobility of pairs of particles. Experimental results will be presented for 2D-isotropic (smectic-A) and 2D-nematic (smectic-C) phases.

microgravity↗
DOE OSTI2015

Scaling soft matter physics to thousands of graphics processing units in parallel

We describe a multi-graphics processing unit (GPU) implementation of the Ludwig application, which specialises in simulating a variety of complex fluids via lattice Boltzmann fluid dynamics coupled to additional physics describing complex fluid constituents. We describe our methodology in augmenting the original central processing unit (CPU) version with GPU functionality in a maintainable fashion. We present several optimisations that maximise performance on the GPU architecture through tuning for the GPU memory hierarchy. We describe how we implement particles within the fluid in such a way to avoid a major diversion of the CPU and GPU codebases, whilst minimising data transfer at each time step. We detail our halo-exchange communication phase for the code, which exploits overlapping to allow efficient parallel scaling to many GPUs. We present results showing that the application demonstrates excellent scaling to at least 8192 GPUs in parallel, the largest system tested at the time of writing. The GPU version (on NVIDIA K20X GPUs) is around 3.5–5 times faster that the CPU version (on fully utilised AMD Opteron 6274 16-core CPUs), comparing equal numbers of CPUs and GPUs.

Computer Science↗
DOE OSTI2017

Modeling electrokinetic flows by consistent implicit incompressible smoothed particle hydrodynamics

We present an efficient implicit incompressible smoothed particle hydrodynamics (I2SPH) discretization of Navier-Stokes, Poisson-Boltzmann, and advection-diffusion equations subject to Dirichlet or Robin boundary conditions. It is applied to model various two and three dimensional electrokinetic flows in simple or complex geometries. The I2SPH's accuracy and convergence are examined via comparison with analytical solutions, grid-based numerical solutions, or empirical models. The new method provides a framework to explore broader applications of SPH in microfluidics and complex fluids with charged objects, such as colloids and biomolecules, in arbitrary complex geometries.

Pan, Wenxiao↗
DOE OSTI2024

Lie–Poisson Neural Networks (LPNets): Data-based computing of Hamiltonian systems with symmetries

An accurate data-based prediction of the long-term evolution of Hamiltonian systems requires a network that preserves the appropriate structure under each time step. Every Hamiltonian system contains two essential ingredients: the Poisson bracket and the Hamiltonian. Hamiltonian systems with symmetries, whose paradigm examples are the Lie–Poisson systems, have been shown to describe a broad category of physical phenomena, from satellite motion to underwater vehicles, fluids, geophysical applications, complex fluids, and plasma physics. The Poisson bracket in these systems comes from the symmetries, while the Hamiltonian comes from the underlying physics. We view the symmetry of the system as primary, hence the Lie–Poisson bracket is known exactly, whereas the Hamiltonian is regarded as coming from physics and is considered not known, or known approximately. Using this approach, we develop a network based on transformations that exactly preserve the Poisson bracket and the special functions of the Lie–Poisson systems (Casimirs) to machine precision. We present two flavors of such systems: one, where the parameters of transformations are computed from data using a dense neural network (LPNets), and another, where the composition of transformations is used as building blocks (G-LPNets). We also show how to adapt these methods to a larger class of Poisson brackets. We apply the resulting methods to several examples, such as rigid body (satellite) motion, underwater vehicles, a particle in a magnetic field, and others. The methods developed in this paper are important for the construction of accurate data-based methods for simulating the long-term dynamics of physical systems.

Data-based modeling↗
NASA NTRS2002

The NASA Microgravity Fluid Physics Program: Knowledge for Use on Earth and Future Space Missions

Building on over four decades of research and technology development related to the behavior of fluids in low gravity environments, the current NASA Microgravity Fluid Physics Program continues the quest for knowledge to further understand and design better fluids systems for use on earth and in space. The purpose of the Fluid Physics Program is to support the goals of NASA's Biological and Physical Research Enterprise which seeks to exploit the space environment to conduct research and to develop commercial opportunities, while building the vital knowledge base needed to enable efficient and effective systems for protecting and sustaining humans during extended space flights. There are currently five major research areas in the Microgravity Fluid Physics Program: complex fluids, multiphase flows and phase change, interfacial phenomena, biofluid mechanics, and dynamics and instabilities. Numerous investigations into these areas are being conducted in both ground-based laboratories and facilities and in the flight experiments program. Most of the future NASA-sponsored fluid physics and transport phenomena studies will be carried out on the International Space Station in the Fluids Integrated Rack, in the Microgravity Science Glovebox, in EXPRESS racks, and in other facilities provided by international partners. This paper will present an overview of the near- and long-term visions for NASA's Microgravity Fluid Physics Research Program and brief descriptions of hardware systems planned to achieve this research.

Kohl, Fred J.↗
NASA NTRS2003

The NASA Microgravity Fluid Physics Program: Research Plans for the ISS

Building on over four decades of research and technology development related to the behavior of fluids in low gravity environments, the current NASA Microgravity Fluid Physics Program continues the quest for knowledge to further understand and design better fluids systems for use on earth and in space. NASA's Biological and Physical Research Enterprise seeks to exploit the space environment to conduct research supporting human exploration of space (strategic research), research of intrinsic scientific importance and impact (fundamental research), and commercial research. The strategic research thrust will build the vital knowledge base needed to enable NASA's mission to explore the Universe and search for life. There are currently five major research areas in the Microgravity Fluid Physics Program: complex fluids, niultiphase flows and phase change, interfacial phenomena, biofluid mechanics, and dynamics and instabilities. Numerous investigations into these areas are being conducted in both ground-based laboratories and facilities and in the flight experiments program. Most of the future NASA- sponsored flight experiments in microgravity fluid physics and transport phenomena will be carried out on the International Space Station (ISS) in the Fluids Integrated Rack (FIR), in the Microgravity Science Glovebox (MSG), in EXPRESS racks, and in other facilities provided by international partners. This paper presents an overview of the near- and long-term visions for NASA's Microgravity Fluid Physics Research Program and brief descriptions of hardware systems planned to enable this research.

Kohl, Fred J.↗
DOE OSTI2020

Phase behavior of continuous-space systems: A supervised machine learning approach

The phase behavior of complex fluids is a challenging problem for molecular simulations. Supervised machine learning (ML) methods have shown potential for identifying the phase boundaries of lattice models. In this work, we extend these ML methods to continuous-space systems. We propose a convolutional neural network model that utilizes grid-interpolated coordinates of molecules as input data of ML and optimizes the search for phase transitions with different filter sizes. We test the method for the phase diagram of two off-lattice models, namely, the Widom–Rowlinson model and a symmetric freely jointed polymer blend, for which results are available from standard molecular simulations techniques. The ML results show good agreement with results of previous simulation studies with the added advantage that there is no critical slowing down. We find that understanding intermediate structures near a phase transition and including them in the training set is important to obtain the phase boundary near the critical point. The method is quite general and easy to implement and could find wide application to study the phase behavior of complex fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

New techniques for diffusing-wave spectroscopy

We present two new types of measurements that can be made with diffusing-wave spectroscopy (DWS), a form of dynamic light scattering that applies in limit of strong multiple scattering. The first application is to measure the frequency-dependent linear viscoelastic moduli of complex fluids using light scattering. This is accomplished by measuring the mean square displacement of probe particles using DWS. Their response to thermal fluctuations is determined by the fluctuation-dissipation relation, and is controlled by the response of the surrounding complex fluid. This response can be described in terms of a memory function, which is directly related to the complex elastic modulus of the system. Thus by measuring the mean square displacement, we are able to determine the frequency dependent modulus. The second application is the measurement of shape fluctuations of scattering particles. This is achieved by generalizing the theory for DWS to incorporate the effects if amplitude fluctuations in the scattering intensity of the particles. We apply this new method to study the thermally induced fluctuations in the shape of spherical emulsion droplets whose geometry is controlled by surface tension.

Mason, T. G.↗
DOE OSTI2023

Anticipating gelation and vitrification with medium amplitude parallel superposition (MAPS) rheology and artificial neural networks

Abstract Anticipating qualitative changes in the rheological response of complex fluids (e.g., a gelation or vitrification transition) is an important capability for processing operations that utilize such materials in real-world environments. One class of complex fluids that exhibits distinct rheological states are soft glassy materials such as colloidal gels and clay dispersions, which can be well characterized by the soft glassy rheology (SGR) model. We first solve the model equations for the time-dependent, weakly nonlinear response of the SGR model. With this analytical solution, we show that the weak nonlinearities measured via medium amplitude parallel superposition (MAPS) rheology can be used to anticipate the rheological aging transitions in the linear response of soft glassy materials. This is a rheological version of a technique called structural health monitoring used widely in civil and aerospace engineering. We design and train artificial neural networks (ANNs) that are capable of quickly inferring the parameters of the SGR model from the results of sequential MAPS experiments. The combination of these data-rich experiments and machine learning tools to provide a surrogate for computationally expensive viscoelastic constitutive equations allows for rapid experimental characterization of the rheological state of soft glassy materials. We apply this technique to an aging dispersion of Laponite ® clay particles approaching the gel point and demonstrate that a trained ANN can provide real-time detection of transitions in the nonlinear response well in advance of incipient changes in the linear viscoelastic response of the system.

Lennon, Kyle R. (ORCID:0000000212515461)↗
DOE OSTI2018

Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the bulk rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number RE = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the polymer dynamics, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.

Computer Science↗
DOE OSTI2015

A model for complex flows of soft glassy materials with application to flows through fixed fiber beds

The soft glassy rheology (SGR) model has successfully described the time dependent simple shear rheology of a broad class of complex fluids including foams, concentrated emulsions, colloidal glasses, and solvent-free nanoparticle-organic hybrid materials (NOHMs). The model considers a distribution of mesoscopic fluid elements that hop from trap to trap at a rate which is enhanced by the work done to strain the fluid element. While an SGR fluid has a broad exponential distribution of trap energies, the rheology of NOHMs is better described by a narrower energy distribution and we consider both types of trap energy distributions in this study. We introduce a tensorial version of these models with a hopping rate that depends on the orientation of the element relative to the mean stress field, allowing a range of relative strengths of the extensional and simple shear responses of the fluid. As an application of these models we consider the flow of a soft glassy material through a dilute fixed bed of fibers. The dilute fixed bed exhibits a range of local linear flows which alternate in a chaotic manner with time in a Lagrangian reference frame. It is amenable to an analytical treatment and has been used to characterize the strong flow response of many complex fluids including fiber suspensions, dilute polymer solutions and emulsions. We show that the accumulated strain in the fluid elements has an abrupt nonlinear growth at a Deborah number of order one in a manner similar to that observed for polymer solutions. The exponential dependence of the hopping rate on strain leads to a fluid element deformation that grows logarithmically with Deborah number at high Deborah numbers. SGR fluids having a broad range of trap energies flowing through fixed beds can exhibit a range of rheological behaviors at small Deborah numbers ranging from a yield stress, to a power law response and finally to Newtonian behavior.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Robotic pendant drop: containerless liquid for μs-resolved, AI-executable XPCS

Abstract The dynamics and structure of mixed phases in a complex fluid can significantly impact its material properties, such as viscoelasticity. Small-angle X-ray Photon Correlation Spectroscopy (SA-XPCS) can probe the spontaneous spatial fluctuations of the mixed phases under various in situ environments over wide spatiotemporal ranges (10 −6 –10 3 s /10 −10 –10 −6 m). Tailored material design, however, requires searching through a massive number of sample compositions and experimental parameters, which is beyond the bandwidth of the current coherent X-ray beamline. Using 3.7-μs-resolved XPCS synchronized with the clock frequency at the Advanced Photon Source, we demonstrated the consistency between the Brownian dynamics of ~100 nm diameter colloidal silica nanoparticles measured from an enclosed pendant drop and a sealed capillary. The electronic pipette can also be mounted on a robotic arm to access different stock solutions and create complex fluids with highly-repeatable and precisely controlled composition profiles. This closed-loop, AI-executable protocol is applicable to light scattering techniques regardless of the light wavelength and optical coherence, and is a first step towards high-throughput, autonomous material discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A liquid jet setup for x-ray scattering experiments on complex liquids at free-electron laser sources

In this paper we describe a setup for x-ray scattering experiments on complex fluids using a liquid jet. The setup supports Small and Wide Angle X-ray Scattering (SAXS/WAXS) geometries. The jet is formed by a gas-dynamic virtual nozzle (GDVN) allowing for diameters ranging between 1 μm and 20 μm at a jet length of several hundred μm. To control jet properties such as jet length, diameter, or flow rate, the instrument is equipped with several diagnostic tools. Three microscopes are installed to quantify jet dimensions and stability in situ. The setup has been used at several beamlines performing both SAXS and WAXS experiments. As a typical example we show an experiment on a colloidal dispersion in a liquid jet at the X-ray Correlation Spectroscopy instrument at the Linac Coherent Light Source free-electron laser.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1980

Numerical analysis of complex fluid-flow systems

Very flexible computer-assisted numerical analysis is used to solve dynamic fluid-flow equations characterizing computer-controlled heat dissipation system developed for Space lab. Losses caused by bends, ties, fittings, valves, and like are easily included, and analysis can solve both steady-state and transient cases. It can also interact with parallel thermal analysis.

Holland, R. L.↗
NASA NTRS1984

A practical adaptive-grid method for complex fluid-flow problems

A practical solution, adaptive-grid method utilizing a tension and torsion spring analogy is proposed for multidimensional fluid flow problems. The tension spring, which connects adjacent grid points to each other, controls grid spacings. The torsion spring, which is attached to each grid node, controls inclinations of coordinate lines and grid skewness. A marching procedure was used that results in a simple tridiagonal system of equations at each coordinate line to determine grid-point distribution. Multidirectional adaptation is achieved by successive applications of one-dimensional adaptation. Examples of applications for axisymmetric afterbody flow fields and two dimensional transonic airfoil flow fields are shown.

Nakahashi, K.↗