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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 NTRS2001

Three-Dimensional Stereoscopic Tracking Velocimetry and Experimental/Numerical Comparison of Directional Solidification

Measurement of three-dimensional (3-D) three-component velocity fields is of great importance in both ground and space experiments for understanding materials processing and fluid physics. The experiments in these fields most likely inhibit the application of conventional planar probes for observing 3-D phenomena. Here, we present the investigation results of stereoscopic tracking velocimetry (STV) for measuring 3-D velocity fields, which include diagnostic technology development, experimental velocity measurement, and comparison with analytical and numerical computation. STV is advantageous in system simplicity for building compact hardware and in software efficiency for continual near-real-time monitoring. It has great freedom in illuminating and observing volumetric fields from arbitrary directions. STV is based on stereoscopic observation of particles-Seeded in a flow by CCD sensors. In the approach, part of the individual particle images that provide data points is likely to be lost or cause errors when their images overlap and crisscross each other especially under a high particle density. In order to maximize the valid recovery of data points, neural networks are implemented for these two important processes. For the step of particle overlap decomposition, the back propagation neural network is utilized because of its ability in pattern recognition with pertinent particle image feature parameters. For the step of particle tracking, the Hopfield neural network is employed to find appropriate particle tracks based on global optimization. Our investigation indicates that the neural networks are very efficient and useful for stereoscopically tracking particles. As an initial assessment of the diagnostic technology performance, laminar water jets with and without pulsation are measured. The jet tip velocity profiles are in good agreement with analytical predictions. Finally, for testing in material processing applications, a simple directional solidification apparatus is built for experimenting with a metal analog of succinonitrile. Its 3-D velocity field at the liquid phase is then measured to be compared with those from numerical computation. Our theoretical, numerical, and experimental investigations have proven STV to be a viable candidate for reliably measuring 3-D flow velocities. With current activities are focused on further improving the processing efficiency, overall accuracy, and automation, the eventual efforts of broad experimental applications and concurrent numerical modeling validation will be vital to many areas in fluid flow and materials processing.

Lee, David↗
DOE OSTI2020

An in-situ crosslinking binder for binder jet additive manufacturing

Additive Manufacturing (AM) of metals is a potentially disruptive technology that could significantly change the industrial supply chain. There are a limited number of AM methods capable of creating metal parts, and one method showing significant potential is Binder Jet AM (Binder Jetting). Binder Jetting utilizes an inkjet print head to deposit a binder fluid onto a powder bed and bind together powder particles into a desired geometry. This study investigates a new binder system consisting of a difunctional monomer, triethylene glycol dimethacrylate (TEG-DMA). TEG-DMA exhibits excellent printability with an Ohnesorge’s number of .258 making the Z number 3.876. During the thermal curing process, the difunctional monomer polymerizes and crosslinks at the onset temperature of 138 °C, becoming a solid dimethacrylate network. When the binder is utilized within the stainless-steel powder bed at 200 °C, it forms a network incorporating the stainless-steel particles, binding the powder into any specified geometry. Crosslinking the monomer within the stainless-steel 420 powder bed imparts a flexural strength of 1.0–3.3 MPa to the green part depending on the volume of monomer in the part. After sintering, the final stainless-steel parts results in a void fraction close to 60 % and carbon content below 0.4 %.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modeling Nanoconfinement Effects Using Active Learning

Predicting the spatial configuration of gas in nanopores of is relevant in applications such as fluid flow forecasting and hydrocarbon reserves estimation. For example, shale reservoirs have suffered from computationally intractable multiscale problems, since fluid properties such as viscosity, density, and adsorption must be calculated by using expensive molecular dynamics (MD) simulations within each nanopore, whereas flow through these connected nanopores must be simulated at the micrometer scale. We utilize machine learning techniques to quickly and accurately model nanoscale confinement effects as an important step toward bridging the nano and micro scales. Our workflow is based on building and training physics-based deep-neural-networks models by learning from a database of MD calculations. The model accounts for the adsorption phenomenon by predicting the statistical distribution of gas inside nanopores. Because large databases of MD calculations are expensive to create, we investigate active learning (AL) as a data set construction strategy. In this workflow, new data are selected based on the model uncertainty via the query-by-committee approach. We show that our workflow obtains accurate models that generalize to real scanning electron microscopy geometries with 1/10th of the number of MD calculations required vs random data set generation. Our method enables the possibility of modeling nanoconfinement effects at the mesoscale, where complex connected sets of nanopores affect flow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Numerical Investigation of a Central Fuel Property Hypothesis Under Boosted Spark-Ignition Conditions

In the present work, a central fuel property hypothesis (CFPH), which states that fuel properties are sufficient to provide an indication of a fuel’s performance irrespective of its chemical composition, was numerically investigated. In particular, the objective of the study was to determine whether Research Octane Number (RON) and Motor Octane Number (MON), as fuel properties, are sufficient to describe a fuel’s knock-limited performance under boosted spark-ignition (SI) conditions within the framework of CFPH. To this end, four TPRF-bioblendstock surrogates having different compositions but matched RON (=98) and MON (=90), were first generated using a non-linear regression model based on artificial neural network (ANN). Additionally, three unconventional bioblendstocks were included in the analysis: di-isobutylene (DIB), isobutanol, and Anisole. Skeletal reaction mechanisms were generated for the TPRF-DIB, TPRF-isobutanol, and TPRF-anisole blends from a detailed kinetic mechanism. Thereafter, numerical simulations were performed for the fuel surrogates using the skeletal mechanisms and a virtual cooperative fuel research (CFR) engine model, under a representative boosted operating condition. In the computational fluid dynamics (CFD) model, the G-equation approach was employed to track the turbulent flame front and the well-stirred reactor model combined with the multi-zone binning strategy was used to capture auto-ignition in the end-gas. In addition, laminar flame speed (LFS) was tabulated for each blend as a function of pressure, temperature, and equivalence ratio a priori, and the lookup tables were used to prescribe laminar flame speed as an input to the G-equation model. Parametric spark timing sweeps were performed for each fuel blend to determine the corresponding knock-limited spark advance (KLSA) and 50% burn point (CA50) at the respective KLSA timing. It was observed that despite same RON, MON, and engine operating conditions, the TPRF-anisole blend exhibited markedly different knock-limited performance from the other three blends. This deviation from the octane index (OI) expectation was shown to be caused by differences in laminar flame speed. However, it was found that relatively large fuel-specific differences in LFS (>20%) would have to be present to cause any appreciable deviation from the OI framework. Otherwise, RON and MON would still be robust enough to predict a fuel’s knock-limited performance.

42 ENGINEERING↗
DOE OSTI2020

C HIMERA : A Massively Parallel Code for Core-collapse Supernova Simulations

Herein we provide a detailed description of the C HIMERA code, a code developed to model core collapse supernovae (CCSNe) in multiple spatial dimensions. The CCSN explosion mechanism remains the subject of intense research. Progress to date demonstrates that it involves a complex interplay of neutrino production, transport, and interaction in the stellar core, three-dimensional stellar core fluid dynamics and its associated instabilities, nuclear burning, and the fundamental physics of the neutrino–stellar core weak interactions and the equations of state of all stellar core constituents—particularly, the nuclear equation of state associated with core nucleons, both free and bound in nuclei. C HIMERA , by incorporating detailed neutrino transport, realistic neutrino–matter interactions, three-dimensional hydrodynamics, realistic nuclear, leptonic, and photonic equations of state, and a nuclear reaction network, along with other refinements, can be used to study the role of neutrino radiation, hydrodynamic instabilities, and a variety of input physics in the explosion mechanism itself. It can also be used to compute observables such as neutrino signatures, gravitational radiation, and the products of nucleosynthesis associated with CCSNe. The code contains modules for neutrino transport, multidimensional compressible hydrodynamics, nuclear reactions, a variety of neutrino interactions, equations of state, and modules to provide data for post-processing observables such as the products of nucleosynthesis, and gravitational radiation. C HIMERA is an evolving code, being updated periodically with improved input physics and numerical refinements. We detail here the current version of the code, from which future improvements will stem, which can in turn be described as needed in future publications.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1989

Low level remote sensing: Orographic winds

The orographic flow data set was obtained from a flight program to measure the influence of orographic features on turbulence momentum, heat, and moisture fluxes. The NASA B-57 aircraft instrumented with probes for measuring the three fluctuating wind speed components, temperature, and humidity was the primary measuring vehicle. Ancillary measurements were made with several ground-based sensors. These include the NOAA radar wind profilers, the Boulder wind network, the PROFS mesoscale surface network, the Boulder Atmospheric Observatory 300 m tower, special rawinsonde observations, and the NOAA/WPL Doppler lidar. The major objective of the flight program was to provide planetary boundary layer parameter information for new and current general circulation computer models. A numerical code, WINDER, based on a discrete element technique was run to numerically model the water tunnel simulated flow. Comparison of the analytical model with the experimental results is very good. Physical fluid dynamic principles embedded in the computational model and visual and hot wire anemometer measurements from the simulation are being rationalized to develop a physical understanding of the vortex flow. The results will be interpreted as they pertain to full scale atmospheric flows.

Frost, Walter↗
NASA NTRS1996

An Evaluation of Architectural Platforms for Parallel Navier-Stokes Computations

We study the computational, communication, and scalability characteristics of a computational fluid dynamics application, which solves the time accurate flow field of a jet using the compressible Navier-Stokes equations, on a variety of parallel architecture platforms. The platforms chosen for this study are a cluster of workstations (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), and distributed memory multiprocessors with different topologies - the IBM SP and the Cray T3D. We investigate the impact of various networks connecting the cluster of workstations on the performance of the application and the overheads induced by popular message passing libraries used for parallelization. The work also highlights the importance of matching the memory bandwidth to the processor speed for good single processor performance. By studying the performance of an application on a variety of architectures, we are able to point out the strengths and weaknesses of each of the example computing platforms.

Jayasimha, D. N.↗
NASA NTRS1997

Parallelizing Navier-Stokes Computations on a Variety of Architectural Platforms

We study the computational, communication, and scalability characteristics of a Computational Fluid Dynamics application, which solves the time accurate flow field of a jet using the compressible Navier-Stokes equations, on a variety of parallel architectural platforms. The platforms chosen for this study are a cluster of workstations (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), distributed memory multiprocessors with different topologies-the IBM SP and the Cray T3D. We investigate the impact of various networks, connecting the cluster of workstations, on the performance of the application and the overheads induced by popular message passing libraries used for parallelization. The work also highlights the importance of matching the memory bandwidth to the processor speed for good single processor performance. By studying the performance of an application on a variety of architectures, we are able to point out the strengths and weaknesses of each of the example computing platforms.

Jayasimha, D. N.↗
NASA NTRS1998

Magmatic Intrusions and a Hydrothermal Origin for Fluvial Valleys on Mars

Numerical models of Martian hydrothermal systems demonstrate that systems associated with magmatic intrusions greater than several hundred cubic kilometers can provide sufficient groundwater outflow to form the observed fluvial valleys, if subsurface permeability exceeds about 1.0 darcy. Groundwater outflow increases with increasing intrusion volume and subsurface permeability and is relatively insensitive to intrusion depth and subsurface porosity within the range considered here. Hydrothermally-derived fluids can melt through 1 to 2 km thick ice-rich permafrost layers in several thousand years. Hydrothermal systems thus provide a viable alternative to rainfall for providing surface water for valley formation. This mechanism can form fluvial valleys not only during the postulated early warm, wet climatic epoch, but also during more recent epochs when atmospheric conditions did not favor atmospheric cycling of water. The clustered distribution of the valley networks on a given geologic surface or terrain unit of Mars may also be more compatible with localized, hydrothermally-driven groundwater outflow than regional rainfall. Hydrothermal centers on Mars may have provided appropriate environments for the initiation of life or final oases for the long-term persistence of life.

Gulick, Virginia C↗
NASA NTRS2016

Numerical Modeling of Pressurization of Cryogenic Propellant Tank for Integrated Vehicle Fluid System

This paper presents a numerical model of pressurization of a cryogenic propellant tank for the Integrated Vehicle Fluid (IVF) system using the Generalized Fluid System Simulation Program (GFSSP). The IVF propulsion system, being developed by United Launch Alliance, uses boiloff propellants to drive thrusters for the reaction control system as well as to run internal combustion engines to develop power and drive compressors to pressurize propellant tanks. NASA Marshall Space Flight Center (MSFC) has been running tests to verify the functioning of the IVF system using a flight tank. GFSSP, a finite volume based flow network analysis software developed at MSFC, has been used to develop an integrated model of the tank and the pressurization system. This paper presents an iterative algorithm for converging the interface boundary conditions between different component models of a large system model. The model results have been compared with test data.

Majumdar, Alok K.↗
DOE OSTI2022

Normalizing flows for likelihood-free inference with fusion simulations

Fluid-based scrape-off layer transport codes, such as UEDGE, are heavily utilized in tokamak analysis and design, but typically require user-specified anomalous transport coefficients to match experiments. Determining the uniqueness of these parameters and the uncertainties in them to match experiments can provide valuable insights to fusion scientists. Here, we leverage recent work in the area of likelihood-free inference (‘simulation-based inference’) to train a neural network, which enables accurate statistical inference of the anomalous transport coefficients given experimental plasma profile input. UEDGE is treated as a black-box simulator and runs multiple times with anomalous transport coefficients sampled from priors, and the neural network is trained on these simulations to emulate the posterior. The neural network is trained as a normalizing flow model for density estimation, allowing it to accurately represent complicated, high-dimensional distribution functions. With a fixed simulation budget, we compare a single-round procedure to a multi-round approach that guides the training simulations toward a specific target observation. Finally, we discuss the future possibilities for use of amortized models, which train on a wide range of simulations and enable fast statistical inference for results during experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1992

Distributed Visualization for Computational Fluid Dynamics

Distributed concurrent visualization and computation in computational fluid dynamics (CFD) is not a new concept. Specialized applications such as Realtime Interactive Particle-tracer (RIP) and vendor specific tools like Distributed Graphics Language (DGL) have been in use for some time. This paper describes a current project underway at NASA Lewis Research Center to provide the CFD researcher with an easy method for incorporating distributed processing concepts into program development. Details on the FORTRAN capable interface to a set of network and visualization functions are presented along with some results from initial CFD case studies that employ these techniques.

Don J Sosoka↗
DOE OSTI2024

Application of a Geochemically Informed Leak Detection (GILD) Model to CO 2 Injection Sites on the United States Gulf Coast

The Gulf Coast region possesses great potential for CO 2 enhanced oil recovery (EOR) and CO 2 storage. A geochemically informed leak detection (GILD) model has been applied to CO 2 injection sites on the Gulf Coast with considerations of measurement variability. The Jasper aquifer in Montgomery County, Texas, was chosen to demonstrate the method. Based on background data from wells in the area, combinations of mineral and fluid compositions were used to create 23 scenarios for the geochemical model. The output from the geochemical model was used to identify sensitive monitoring species, and response functions were generated for these as a function of the CO 2 leakage concentration. The sources of measurement variability for background conditions were characterized from the Jasper aquifer background data, and then normalized using the coefficient of variation of each species across the monitoring wells. Bayesian belief network (BBN) models were constructed, and measurement variability of different levels were added to compare leak detection probabilities. Increasing measurement variability decreased the power to detect a leak of a given size. For a moderately high CO 2 concentration of 0.2 mol/kg, the probability of detecting this leakage effect using pH as the monitoring variable in an aquifer with calcite decreases from 98% (no measurement variability) to 61% (medium variability) to 33% (high variability). The loss in power of the sampling protocol with increasing measurement variability is similar in magnitude when Ca 2+ or HCO 3 - is used as the monitoring parameter, but only for aquifers with calcite.

58 GEOSCIENCES↗
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↗
NASA NTRS1985

Calculation of flow about posts and powerhead model

A three dimensional analysis of the non-uniform flow around the liquid oxygen (LOX) posts in the Space Shuttle Main Engine (SSME) powerhead was performed to determine possible factors contributing to the failure of the posts. Also performed was three dimensional numerical fluid flow analysis of the high pressure fuel turbopump (HPFTP) exhaust system, consisting of the turnaround duct (TAD), two-duct hot gas manifold (HGM), and the Version B transfer ducts. The analysis was conducted in the following manner: (1) modeling the flow around a single and small clusters (2 to 10) of posts; (2) modeling the velocity field in the cross plane; and (3) modeling the entire flow region with a three dimensional network type model. Shear stress functions which will permit viscous analysis without requiring excessive numbers of computational grid points were developed. These wall functions, laminar and turbulent, have been compared to standard Blasius solutions and are directly applicable to the cylinder in cross flow class of problems to which the LOX post problem belongs.

Anderson, P. G.↗
NASA NTRS1994

Parallel Calculation of Sensitivity Derivatives for Aircraft Design using Automatic Differentiation

Sensitivity derivative (SD) calculation via automatic differentiation (AD) typical of that required for the aerodynamic design of a transport-type aircraft is considered. Two ways of computing SD via code generated by the ADIFOR automatic differentiation tool are compared for efficiency and applicability to problems involving large numbers of design variables. A vector implementation on a Cray Y-MP computer is compared with a coarse-grained parallel implementation on an IBM SP1 computer, employing a Fortran M wrapper. The SD are computed for a swept transport wing in turbulent, transonic flow; the number of geometric design variables varies from 1 to 60 with coupling between a wing grid generation program and a state-of-the-art, 3-D computational fluid dynamics program, both augmented for derivative computation via AD. For a small number of design variables, the Cray Y-MP implementation is much faster. As the number of design variables grows, however, the IBM SP1 becomes an attractive alternative in terms of compute speed, job turnaround time, and total memory available for solutions with large numbers of design variables. The coarse-grained parallel implementation also can be moved easily to a network of workstations.

Bischof, c. H.↗
DOE OSTI2018

Effectiveness of supercritical-CO 2 and N 2 huff-and-puff methods of enhanced oil recovery in shale fracture networks using microfluidic experiments

Current oil recovery methods in hydraulically fractured shale reservoirs have a low recovery efficiency of about 10%. The objective of this work is to investigate the effectiveness of nitrogen and supercritical carbon dioxide in the huff-and-puff method for enhanced oil recovery as a means to re-energize reservoirs and improve recovery rates. Here, we conduct direct visualization experiments with a microfluidic system to reveal the mechanisms and to quantify the recovery rates of oil from fracture networks. We compared the effectiveness of water, nitrogen and supercritical carbon dioxide at reservoir conditions in a process mimicking the huff-and-puff method in both dead-end and connected fracture systems. The microfluidic chips were made of glass and placed in a confining pressure system pressurized to 10 MPa, 50 °C. The system was allowed to equilibrate, and then depressurized to simulate huff-and-puff oil recovery. Fluorescence microscope images were continuously taken to visualize and calculate residual oil saturation as a function of pressure drawdown. As the system was depressurized from 10 MPa, gas exsolution from the oil liquid phase, including bubble nucleation, growth, and coalescence, appeared to be the main driver for mobilizing oil from the fracture networks. Injection of supercritical CO 2 resulted in the highest recovery rate with an average end-point recovery of about 90% in the connected fracture network and 60% in the dead-end fracture network. N 2 has lower solubility in oil and hence showed a lower recovery rate of 40% in the connected fracture network and 25% in the dead-end fracture network. Injection of water had no effect on oil mobilization since water is insoluble, immiscible and incompressible. The main mechanism of enhanced recovery was gas exsolution from the liquid phase as pressure was decreased below the bubble point pressure. Because the gas was distributed throughout the oil phase, bubble nucleation, growth, coalescence, and elongation occurred throughout the fracture network. Expansion of the gas forced oil out of the network through piston displacement in continuous oil areas and film flow in the dispersed oil areas. Bubbles began as spheres and grew until they touched the fracture walls where they elongated along the fracture length. The bubble growth rate depended on local mass transfer from liquid to gas phase and gas volume expansion due to pressure drop. The efficiency of the huff-and-puff process is dependent on the solubility and miscibility of the injection fluid with oil. High gas solubility allows for more bubble nucleation, growth and expansion during the depressurization cycle.

58 GEOSCIENCES↗
DOE OSTI2022

Physical characterization of fault rocks within the Opalinus Clay formation

Near-surface disposal of radioactive waste in shales is a promising option to safeguard the population and environment. However, natural faults intersecting these geological formations can potentially affect the long-term isolation of the repositories. This paper characterizes the physical properties and mineralogy of the internal fault core structure intersecting the Opalinus Clay formation, a host rock under investigation for nuclear waste storage at the Mont Terri Laboratory (Switzerland). We have performed porosity, density, microstructural and mineralogical measurements in different sections of the fault, including intact clays, scaly clays and fault gouge. Mercury intrusion porosimetry analysis reveal a gouge that has a pore network dominated by nanopores of less than 10 nm, yet a high-porosity (21%) and low grain density (2.62 g/cm 3 ) when compared to the intact rock (14.2%, and 2.69 g/cm 3 ). Thus, a more permeable internal fault core structure with respect to the surrounding rock is deduced. Further, we describe the OPA fault gouge as a discrete fault structure having the potential to act as a preferential, yet narrow, and localized channel for fluid-flow if compared to the surrounding rock. Since the fault gouge is limited to a millimetres-thick structure, we expect the barrier property of the geological formation is almost not affected.

58 GEOSCIENCES↗