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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Spectral variation of high power microwave pulse propagating in a self-generated plasma

A systematic study to understand the spectral variation of a high power microwave pulse propagating in a self-generated plasma is carried out. It includes the theoretical formulation, experimental demonstration, and computer simulations and computer experiments. The experiment of pulse propagation is conducted in a vacuum chamber filled with dry air (approximately 0.2 torr); the chamber is made of a 2 ft. cube of Plexiglas. A rectangular microwave pulse (1 microsec pulse width and 3.27 GHz carrier frequency) is fed into the cube through an S band microwave horn placed at one side of the chamber. A second S-band horn placed at the opposite side of the chamber is used to receive the transmitted pulse. The spectra of the incident pulse and transmitted pulse are then compared. As the power of the incident pulse is only slightly (less than 15%) above the breakdown threshold power of the background air, the peak of the spectrum of the transmitted pulse is upshifted from the carrier frequency 3.27 GHz of the incident pulse. However, as the power of the incident pulse exceeds the breakdown threshold power of the background air by 30%, a different phenomenon appears. The spectrum of the transmitted pulse begins to have two peaks. One is upshifted and the other one downshifted from the single peak location of the incident pulse. The amount of frequency downshift is comparable to that of the upshifted frequency. A theoretical model describing the experiment of pulse propagation in a self-generated plasma is developed. There are excellent agreements between the experimental results and computer simulations based on this theoretical model, which is also used to further carry out computer experiments identifying the role of plasma introduced wave loss on the result of frequency downshift phenomenon.

Ren, A.↗
DOE OSTI2019

Experiments and computations of microfluidic liquid–liquid flow patterns

We study two-phase liquid–liquid flow patterns in a 500 μm capillary microchannel for four biphasic systems: ethyl acetate/water, 2-pentanol/water, methyl isobutyl ketone/water, and heptane/water. Flow visualization experiments using laser induced fluorescence (LIF) reveal a total of 7 different flow patterns for all solvent pairs, namely slug flow, droplet flow, slug-droplet flow, parallel, annular, dispersed, and irregular flow. A map of different flow patterns was built to delineate the origin of their formation. We find conventional dimensionless groups are insufficient to uniquely identify the flow patterns. Computational fluid dynamics (CFD) modeling in OpenFOAM shows agreement with the experimental flow patterns for most of the two-phase flows. Principal component analysis reduces the dimensionality of potential descriptors of flow patterns and, unlike prior work using two dimensionless numbers, determines six important features that describe >95% of the variance of the experimental flow patterns. These include the total flow rate, the flow rate ratio between the two phases, the capillary and Ohnesorge numbers of the aqueous phase, and the Weber number and velocity of the organic phase. Lastly, we build a decision-tree model to further regress the data and identify the critical features and demonstrate an accuracy in predicting the flow patterns of up to 93%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Spatio-Temporal Data Analysis at Scale Using Models Based on Gaussian Processes

Gaussian processes are the most commonly used statistical model for spatial and spatio-temporal processes that vary continuously. They are broadly applicable in the physical sciences and engineering and are also frequently used to approximate the output of complex computer models, deterministic or stochastic. We undertook research related to theory, computation, and applications of Gaussian processes as well as some work on estimating extremes of distributions for which a Gaussian process assumption might be inappropriate. Our theoretical contributions include the development of new classes of spatial-temporal covariance functions with desirable properties and new results showing that certain covariance models lead to predictions with undesirable properties. To understand how Gaussian process models behave when applied to deterministic computer models, we derived what we believe to be the first significant results on the large sample properties of estimators of parameters of Gaussian processes when the actual process is a simple deterministic function. Finally, we investigated some theoretical issues related to maxima of observations with varying upper bounds and found that, depending on the circumstances, standard large sample results for maxima may or may not hold. Our computational innovations include methods for analyzing large spatial datasets when observations fall on a partially observed grid and methods for estimating parameters of a Gaussian process model from observations taken by a polar-orbiting satellite. In our application of Gaussian process models to deterministic computer experiments, we carried out some matrix computations that would have been infeasible using even extended precision arithmetic by focusing on special cases in which all elements of the matrices under study are rational and using exact arithmetic. The applications we studied include total column ozone as measured from a polar-orbiting satellite, sea surface temperatures over the Pacific Ocean, and annual temperature extremes at a site in New York City. In each of these applications, our theoretical and computational innovations were directly motivated by the challenges posed by analyzing these and similar types of data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Lithium oxidation and electrolyte decomposition at Li-metal/liquid electrolyte interfaces

In this work, we examine the evolution of events occurring when a Li metal surface is in contact with a 2 M solution of a Li salt in a solvent or mixture of solvents, via classical molecular dynamics simulations with a reactive force field allowing bond breaking and bond forming. The main events include Li oxidation and electrolyte reduction along with expansion of the Li surface layers forming a porous phase that is the basis for the formation of the solid-electrolyte interphase (SEI) components. Nucleation of the main SEI components (LiF, Li oxides, and some organics) is characterized. The analysis clearly reveals the details of these physical–chemical events as a function of time, during 20 nanoseconds. The effects of the chemistry of the electrolyte on Li oxidation and dissolution in the liquid electrolyte, and SEI nucleation and structure are identified by testing two salts: LiPF 6 and LiCF 3 SO 3 , and various solvents including ethers and carbonates and mixtures of them. The kinetics and thermodynamics of Li 6 F, the core nuclei in the LiF crystal, are studied by analysis of the MD trajectories, and via density functional theory calculations respectively. The SEI formed in this computational experiment is the “native” film that would form upon contact of the Li foil with the liquid electrolyte. As such, this work is the first in a series of computational experiments that will help elucidate the intricate interphase layer formed during battery cycling using metal anodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Solving Unit Commitment Problems with Demand Responsive Loads

This work focuses on using variations of the Frank-Wolfe (FW) algorithm for solving unit commitment problems with high volumes of demand responsive loads on the power grid. We present a formulation of the unit commitment problem with demand responsive loads. We then show through reformulation and relaxations of the problem that variations of the Frank-Wolfe algorithm can be used to determine the time series decisions for the demand responsive loads. We show through computational experiments on the IEEE Reliability Test System that the timeseries of demand responsive load decisions obtained through our approach are near optimal and describe how large-scale parallel implementations of our approach can be highly computationally efficient.

demand response↗
DOE OSTI2018

High-throughput cancer hypothesis testing with an integrated PhysiCell-EMEWS workflow

BackgroundCancer is a complex, multiscale dynamical system, with interactions between tumor cells and non-cancerous host systems. Therapies act on this combined cancer-host system, sometimes with unexpected results. Systematic investigation of mechanistic computational models can augment traditional laboratory and clinical studies, helping identify the factors driving a treatment's success or failure. However, given the uncertainties regarding the underlying biology, these multiscale computational models can take many potential forms, in addition to encompassing high-dimensional parameter spaces. Therefore, the exploration of these models is computationally challenging. We propose that integrating two existing technologiesone to aid the construction of multiscale agent-based models, the other developed to enhance model exploration and optimizationcan provide a computational means for high-throughput hypothesis testing, and eventually, optimization.ResultsIn this paper, we introduce a high throughput computing (HTC) framework that integrates a mechanistic 3-D multicellular simulator (PhysiCell) with an extreme-scale model exploration platform (EMEWS) to investigate high-dimensional parameter spaces. We show early results in applying PhysiCell-EMEWS to 3-D cancer immunotherapy and show insights on therapeutic failure. We describe a generalized PhysiCell-EMEWS workflow for high-throughput cancer hypothesis testing, where hundreds or thousands of mechanistic simulations are compared against data-driven error metrics to perform hypothesis optimization.ConclusionsWhile key notational and computational challenges remain, mechanistic agent-based models and high-throughput model exploration environments can be combined to systematically and rapidly explore key problems in cancer. These high-throughput computational experiments can improve our understanding of the underlying biology, drive future experiments, and ultimately inform clinical practice.

Agent-based model↗
NASA NTRS1990

Progress in hypersonic combustion technology with computation and experiment

Design of successful airbreathing engines for operation at near-orbital speeds presents significant challenges in all the disciplines involved, including propulsion. This paper presents a discussion of the important physics of hypersonic combustion and an assessment of the state of the art of ground simulations with pulse facilities and with computational techniques. Recent examples of experimental and computational simulations are presented and discussed. The need for continued application of these tools to establish the credibility and fidelity of engineering design methods for practical hypersonic combustors is emphasized along with the critical need for improved diagnostic methods for hypervelocity reacting flows.

Anderson, Griffin Y.↗
NASA NTRS2014

Comparing Experiment and Computation of Hypersonic Laminar Boundary Layers with Isolated Roughness

Streamwise velocity profile behavior in a hypersonic laminar boundary layer in the presence of an isolated roughness element is presented for an edge Mach number of 8.2. Two different roughness element types are considered: a 2-mm tall, 4-mm diameter cylinder, and a 2-mm radius hemisphere. Measurements of the streamwise velocity behavior using nitric oxide (NO) planar laser-induced fluorescence (PLIF) molecular tagging velocimetry (MTV) have been performed on a 20-degree wedge model. The top surface of this model acts as a flat-plate and is oriented at 5 degrees with respect to the freestream flow. Computations using direct numerical simulation (DNS) of these flows have been performed and are compared to the measured velocity profiles. Particular attention is given to the characteristics of velocity profiles immediately upstream and downstream of the roughness elements. In these regions, the streamwise flow can experience strong deceleration or acceleration. An analysis in which experimentally measured MTV profile displacements are compared with DNS particle displacements is performed to determine if the assumption of constant velocity over the duration of the MTV measurement is valid. This assumption is typically made when reporting MTV-measured velocity profiles, and may result in significant errors when comparing MTV measurements to computations in regions with strong deceleration or acceleration. The DNS computations with the cylindrical roughness element presented in this paper were performed with and without air injection from a rectangular slot upstream of the cylinder. This was done to determine the extent to which gas seeding in the MTV measurements perturbs the boundary layer flowfield.

Bathel, Brett F.↗
NASA NTRS2018

Space-Filling Designs for Multi-Layer Nested Factors

This articles considers computer experiments where levels for continuous factors are selected in sequential order with the level selected for one factor directly a ecting the range of possible levels for the nested factor, and so on for a nite number of factors. In addition, we assume the nested relationships between the factors have no closed form solution. In this paper, we propose an approach for constructing a multi-layer nested factor design, or multi-NFD for short. This space- lling design approach takes advan- tage of the maximin criterion and can be analyzed using a standard Gaussian process model. While the multi-NFD approach can be adapted for future computer experi- ments involving factor relationships of this type, we present results from a particular aerospace computer simulation study.

Gryder, Ryan W.↗
NASA NTRS2013

Characterization of Aerodynamic Interactions with the Mars Science Laboratory Reaction Control System Using Computation and Experiment

On August 5 , 2012, the Mars Science Laboratory (MSL) entry capsule successfully entered Mars' atmosphere and landed the Curiosity rover in Gale Crater. The capsule used a reaction control system (RCS) consisting of four pairs of hydrazine thrusters to fly a guided entry. The RCS provided bank control to fly along a flight path commanded by an onboard computer and also damped unwanted rates due to atmospheric disturbances and any dynamic instabilities of the capsule. A preliminary assessment of the MSL's flight data from entry showed that the capsule flew much as predicted. This paper will describe how the MSL aerodynamics team used engineering analyses, computational codes and wind tunnel testing in concert to develop the RCS system and certify it for flight. Over the course of MSL's development, the RCS configuration underwent a number of design iterations to accommodate mechanical constraints, aeroheating concerns and excessive aero/RCS interactions. A brief overview of the MSL RCS configuration design evolution is provided. Then, a brief description is presented of how the computational predictions of RCS jet interactions were validated. The primary work to certify that the RCS interactions were acceptable for flight was centered on validating computational predictions at hypersonic speeds. A comparison of computational fluid dynamics (CFD) predictions to wind tunnel force and moment data gathered in the NASA Langley 31-Inch Mach 10 Tunnel was the lynch pin to validating the CFD codes used to predict aero/RCS interactions. Using the CFD predictions and experimental data, an interaction model was developed for Monte Carlo analyses using 6-degree-of-freedom trajectory simulation. The interaction model used in the flight simulation is presented.

Schoenenberger, Mark↗
NASA NTRS1990

Dynamical experiments on models of colliding disk galaxies

Collisions between galaxies can induce large morphological changes in the participants and, in the case of colliding disk galaxies, bridges and tails are often formed. Observations of such systems indicate a wide variation in color (see Larson and Tinsley, 1978) and that some of the particpants are experiencing enhanced rates of star formation, especially in their central regions (Bushouse 1986, 1987; Kennicutt et al., 1987, Bushouse, Lamb, and Werner, 1988). Here the authors describe progress made in understanding some of the dynamics of interacting galaxies using N-body stellar dynamical computer experiments, with the goal of extending these models to include a hydrodynamical treatment of the gas so that a better understanding of globally enhanced star formation will eventually be forthcoming. It was concluded that close interactions between galaxies can produce large perturbations in both density and velocity fields. The authors measured, via computational experiments that represent a galaxy's stars, average radial velocity flows as large as 100 km/sec and 400 percent density increases. These can occur in rings that move outwards through the disk of a galaxy, in roughly homologous inflows toward the nucleus, and in off center, non-axisymmetric regions. Here the authors illustrate where the gas is likely to flow during the early stages of interaction and in future work they plan to investigate the fate of the gas more realistically by using an N-body/Smoothed Particle Hydrodynamics code to model both the stellar and gaseous components of a disk galaxy during a collision. Specifically, they will determine the locations of enhanced gas density and the strength and location of shock fronts that form during the interaction.

Gerber, Richard A.↗
DOE OSTI2020

Use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making

It is widely believed that one’s peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the “pattern” by which it receives these signals vary and when peer influence is directed towards choices which are not optimal. To investigate that, we manipulate social signal exposure in an online controlled experiment using a game with human participants. Each participant in the game decides among choices with differing utilities. We observe the following: (1) even in the presence of monetary risks and previously acquired knowledge of the choices, decision-makers tend to deviate from the obvious optimal decision when their peers make a similar decision which we call the influence decision, (2) when the quantity of social signals vary over time, the forwarding probability of the influence decision and therefore being responsive to social influence does not necessarily correlate proportionally to the absolute quantity of signals. To better understand how these rules of peer influence could be used in modeling applications of real world diffusion and in networked environments, we use our behavioral findings to simulate spreading dynamics in real world case studies. We specifically try to see how cumulative influence plays out in the presence of user uncertainty and measure its outcome on rumor diffusion, which we model as an example of sub-optimal choice diffusion. Together, our simulation results indicate that sequential peer effects from the influence decision overcomes individual uncertainty to guide faster rumor diffusion over time. However, when the rate of diffusion is slow in the beginning, user uncertainty can have a substantial role compared to peer influence in deciding the adoption trajectory of a piece of questionable information.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Benchmark microgravity experiments and computations for 3D dendritic-array stability in directional solidification

In this study, we present a comprehensive quantitative analysis of stability bands for dendritic arrays during directional solidification of a transparent succinonitrile-0.46 wt % camphor alloy, spanning a broad range of pulling velocities. Taking advantage of the microgravity environment aboard the International Space Station where most convection effects are suppressed, we obtain unique measurements that quantify the stable primary spacing range of spatially extended three-dimensional dendritic array structures under purely diffusive growth conditions. Through carefully designed velocity jump experiments and detailed examination of sub-grain boundary dynamics, we characterize key instabilities, including elimination and tertiary branching, shedding new light on the mechanisms governing dynamic dendritic spacing selection in extended 3D arrays. Phase field simulations are performed to characterize the stability limits of dendritic array structures for quantitative comparison with the flight experiments. Although the simulations capture general trends, significant deviations are noted at the upper stability boundary, indicating the influence of additional, unexplored factors. These findings contribute to a deeper understanding of dendritic growth dynamics and offer valuable benchmark data that could aid in refining predictive models and improving control of dendritic microstructures in metallurgical applications.

36 MATERIALS SCIENCE↗
NASA NTRS1980

The Spacelab Experiment Interface Device (SEID)

The Spacelab experiment interface device (SEID) is described which simulates the electrical, and logical connections of the Spacelab remote acquisition unit (RAU), the interface functions of the Spacelab experiment computer software, and the electrical aspects of the high rate multiplexer. Simulated RAU interfaces include PCM serial channels (up to four), user time clock (UTC), flexible inputs (up to 128) and discrete outputs (up to 64). Connectors are logically compatible with the rau. be instructed to execute sequences of input/output commands to the RAU, similar to those performed during flight. This approximation of the experiment computer software is adequate to detect interface problems and prevent these from occurring during Spacelab payload integration. The SEID hardware is a microprocessor based system, utilizing an 8085 microprocessor with 6K of PROM and 4K of static RAM. The basic unit is augmented with an LSI-11 microcomputer to provide disk storage and a more dynamic environment for generation of control data. A simulation of the general monitoring loop is provided to emulate Spacelab system timing.

Kallus, R.↗
DOE OSTI2021

Experiment and computational fluid dynamics investigation of biochar elutriation in fluidized bed

Here, in fluidized bed biomass fast pyrolysis, the biomass is converted to biochar and elutriated. The elutriation rate is a key parameter in reactor designs and operations. This research presents a video-based continuous measurement of biochar elutriation rate in a fluidized bed with sands and biomass as bed materials. The fluidized bed is simulated with the Computational Fluid Dynamics - Coarse-Grained Discrete Element Method (CFD-CGDEM) in MFiX. The fluidization behavior of non-spherical sands can be more accurately captured when a rolling friction model is used. The predicted elutriation rate is close to the experimental measurement when the particle size distributions are considered and the filtered drag with a shape correction is used. These results validated the accuracy of the MFiX based CFD framework for the prediction of biochar elutriations in the fluidized bed biomass fast pyrolysis reactor.

09 BIOMASS FUELS↗
DOE OSTI2018

Ternary Bismuthide SrPtBi 2 : Computation and Experiment in Synergism to Explore Solid-State Materials

A combination of theoretical calculation and the experimental synthesis to explore the new ternary compound is demonstrated in the Sr–Pt–Bi system. Because Pt–Bi is considered as a new critical charge-transfer pair for superconductivity, it inspired us to investigate the Sr–Pt–Bi system. With a thorough calculation of all the known stable/metastable compounds in the Sr–Pt–Bi system and crystal structure predictions, the thermodynamic stability of hypothetical stoichiometry, SrPtBi2, is determined. Following the high-temperature synthesis and crystallographic analysis, the first ternary bismuthide in Sr–Pt–Bi, SrPtBi2 was prepared, and the stoichiometry was confirmed experimentally. SrPtBi 2 crystallizes in the space group Pnma (S.G. 62, Pearson Symbol oP48), which matches well with theoretical prediction using an adaptive genetic algorithm. Using first-principles calculations, we demonstrate that the orthorhombic structure has lower formation energies than other 112 structure types, such as tetragonal BaMnBi 2 (CuSmP 2 ) and LaAuBi 2 (CuHfSi 2 ) structure types. The bonding analysis indicates that the Pt–Bi interactions play a critical role in structural stability. The physical property measurements show the metallic properties at the low temperature, which agrees with the electronic structure assessment.

36 MATERIALS SCIENCE↗