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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
DOE OSTI2020

A multirate mass transfer model to represent the interaction of multicomponent biogeochemical processes between surface water and hyporheic zones (SWAT-MRMT-R 1.0)

Abstract. Surface water quality along river corridors can be modulated by hyporheic zones (HZs) that are ubiquitous and biogeochemically active. Watershed management practices often ignore the potentially important role of HZs as a natural reactor. To investigate the effect of hydrological exchange and biogeochemical processes on the fate of nutrients in surface water and HZs, a novel model, SWAT-MRMT-R, was developed coupling the Soil and Water Assessment Tool (SWAT) watershed model and the reaction module from a flow and reactive transport code (PFLOTRAN). SWAT-MRMT-R simulates concurrent nonlinear multicomponent biogeochemical reactions in both the channel water and its surrounding HZs, connecting the channel water and HZs through hyporheic exchanges using multirate mass transfer (MRMT) representation. Within the model, HZs are conceptualized as transient storage zones with distinguished exchange rates and residence times. The biogeochemical processes within HZs are different from those in the channel water. Hyporheic exchanges are modeled as multiple first-order mass transfers between the channel water and HZs. As a numerical example, SWAT-MRMT-R is applied to the Hanford Reach of the Columbia River, a large river in the United States, focusing on nitrate dynamics in the channel water. Major nitrate contaminants entering the Hanford Reach include those from the legacy waste, irrigation return flows (irrigation water that is not consumed by crops and runs off as point sources to the stream), and groundwater seepage resulting from irrigated agriculture. A two-step reaction sequence for denitrification and an aerobic respiration reaction is assumed to represent the biogeochemical transformations taking place within the HZs. The spatially variable hyporheic exchange rates and residence times in this example are estimated with the basin-scale Networks with EXchange and Subsurface Storage (NEXSS) model. Our simulation results show that (1), given a residence time distribution, how the exchange fluxes to HZs are approximated when using MRMT can significantly change the amount of nitrate consumption in HZs through denitrification and (2) source locations of nitrate have a different impact on surface water quality due to the spatially variable hyporheic exchanges.

58 GEOSCIENCES↗
DOE OSTI2022

Quantifying transport and electrocatalytic reaction processes in a gastight rotating cylinder electrode reactor via integration of Computational Fluid Dynamics modeling and experiments

Understanding the complexity of the multiple processes of mass, momentum, charge, and heat transport, and how these affect reaction kinetics at the electrode/electrolyte interface is one of the major challenges in the field of energy and catalysis. The rapid and rational scale-up of electrocatalytic systems to industrial scales require a detailed understanding of nonlinear transport-reaction processes, accessible only through the building of multi-physics models that capture with high fidelity the complexity of real-world devices. The gastight rotating cylinder electrode (RCE) reactor is a promising lab-scale tool that can decouple transport from intrinsic kinetics to generate data for first-principle models useful in the design of industrial, electrochemical reactors. Computational Fluid Dynamics (CFD) studies have previously been used to investigate the bulk flow in RCE reactors for simple corrosion and electroplating processes. However, the quantification of changes in local concentration within the viscous layer where catalysis takes place requires capturing the correct flow conditions inside the hydrodynamic boundary layer near the surface of the electrode. Further, this requires simulations with spatial resolution in the nm and μm scale and temporal resolutions between ms and s scales that are similar to the timescales for reactions on the electrode surface. In this study, experimental electrocatalysis is combined with CFD modeling to elucidate and parameterize the hydrodynamics in a gastight RCE reactor. CFD simulations of the electrochemical ferricyanide reduction reaction under mass transport limited conditions are used to evaluate the validity of the CFD model parameters by comparing calculated dimensionless mass transport descriptors to dimensionless correlations obtained experimentally. Justifications for assumptions and details of the simulation methods used in this study are presented to provide a detailed understanding of the effect that each model parameter has on the ability to accurately simulate electrocatalysis in RCE systems. The simulation methodology reported here is a first step towards the development of multi-scale models for the study of transport dependent electrocatalytic processes, such as the electrochemical transformation of CO 2 to fuels and chemicals.

42 ENGINEERING↗
DOE OSTI2020

Laboratory Study of Nonlinear QED in Intense Laser-Matter Interactions

The goal of the project was to investigate the interaction of powerful laser light with matter, which is of fundamental interest to electrodynamics, thermonuclear fusion plasmas, and high-energy-density physics for DOE. Experiments on highly nonlinear relativistic interactions were performed using the state-of-the-art DIOCLES laser at the Extreme Light Laboratory of the University of Nebraska–Lincoln (UNL). We have demonstrated a novel testbed for laser-plasma interactions in which laser pulses collided in plasma with femtosecond and micron-scale accuracy under extreme experiment conditions. This capability is crucial for future radiation reaction experiments and nonlinear QED studies. Moreover, this is also a milestone towards the efficient generation of GeV electron beams via travelling wave laser wakefield accelerator. We proposed a novel idea for measuring the radiation reaction process using travelling wave Thomson scattering, which was studied in numerical simulations. This method allows unambiguous measurement of radiation reaction in a single shot, therefore, surpassing the conventional methods, which suffer severely from the shot-to-shot fluctuations, due to the instability of laser wavefield acceleration.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Lasers for the observation of multiple order nuclear reactions

Nuclear reaction rates become nonlinear with respect to flux (cm −2 s −1 ) in extreme environments such as those found during stellar nucleosynthesis and terrestrial nuclear detonations. To observe these effects directly in the laboratory, extremely high particle fluences (cm −2 ) are necessary but not sufficient. Reactor-based neutron sources, such as the Institut Laue-Langevin’s high-flux neutron reactor, were previously the closest to meeting this challenge, albeit over ∼hour time scales. In ultra-high flux environments, where multiple reactions occur on picosecond time scales, nuclei are unable to return to their ground states between reactions; consequently, reactions take place on excited nuclei. To accurately model high-flux environments, data on the cross-sections of excited nuclear states are required, which differ significantly from those of ground states due to spin/parity effects. In order to replicate these effects in the laboratory, short high-fluence pulses on the order of the lifetime of a typical nuclear excited state (generally ≲1 ns) are required. Particle beams generated by high-intensity lasers are uniquely positioned to meet this need with the potential to produce fluences of 10 17 protons/cm 2 and 10 22 neutrons/cm 2 over a few pico-seconds or less. In addition to providing a quantitative analysis of the rates of multiple rapid reactions in general, the present work examines a number of laser-based experiments that could be conducted in the near future to observe multiple rapid reactions for laboratory-based astrophysics and the measurement of exotic cross-sections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Explicit physics-informed neural networks for nonlinear closure: The case of transport in tissues

In upscaling methods, closures for nonlinear problems present a well-known challenge. While a number of theoretical methods have been proposed for handling such closures, nonlinearities still remain a significant obstacle for many problems. In this work, we use a combination of formal upscaling and data-driven machine learning for explicitly closing a nonlinear transport and reaction process in multiscale tissues. The classical effectiveness factor model is used to formulate the macroscale reaction kinetics. We train a multilayer perceptron network using training data generated by direct numerical simulations over microscale examples. Once trained, the network is used in an algorithm for numerically solving the upscaled (coarse-grained) differential equation describing mass transport and reaction in two example tissues. The network is described as being explicit in the sense that the network is trained using macroscale concentrations and gradients of concentration as components of the feature space rather than incorporating them as part of a constraint in the optimization process. Network training and solutions to the macroscale transport equations were computed for two different tissues. The two tissue types (brain and liver) exhibit markedly different geometrical complexity and spatial scale (cell size and sample size). The upscaled solutions for the average concentration are compared with numerical solutions derived from the microscale concentration fields by a posteriori averaging. There are three outcomes of this work of particular note. 1) Our overall approach results in an upscaled nonlinear PDE. The PDE is closed using a neural network, and our approach results in the definition of the classical effectiveness factor for effecting closure. 2) We identify particular source terms for the closure problem that are important for representing the structure of the closure. These source terms involve macroscale concentrations and their gradients. We adopt these source terms to use as explicit features in the learning algorithm. We find the trained networks that include the macroscale source terms generate models that are able to predict the correction factor with increased fidelity over those that do not. 3) We find that the trained network exhibits good generalizability, and it is able to predict the effectiveness factor with high fidelity for realistically-structured tissues despite the significantly different scale and geometrical complexity of the two example tissue types. This latter result emphasizes our purposeful connection between conventional averaging methods with the use of machine learning for closure; this contrasts with some machine learning methods for upscaling where the exact form of the macroscale equation remains unknown.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Highly-scalable GPU-accelerated compressible reacting flow solver for modeling high-speed flows

Emerging supercomputing systems utilize a combination of central processing units (CPUs) and graphics processing units (GPUs) in an effort to reach exascale capabilities while minimizing the energy footprint of operating such systems. Such heterogeneous machines introduce new challenges for fluids solvers because the hardware architecture and operation of a GPU are fundamentally different from conventional CPUs. In this work, a general approach for efficient implementation of finite-volume based reacting flow solvers on such heterogeneous systems is presented. Three main challenges, namely, data access pattern, thread divergence, and thread safety, are addressed. Since compressible reacting flows require special methods to deal with chemical reactions, hyperbolic and nonlinear convection terms, and the presence of turbulence, specific algorithms that ensure GPU-based efficiency are developed. The approach is demonstrated on the widely available OpenFOAM open source software by modifying core algorithms for GPU accessibility. The scalability of the resulting solver, is demonstrated using practical test cases, including flow through a scramjet engine and the dynamics of a rotating detonation engine. Here, the solver provides near-ideal scaleup on a large number of GPUs (>3000), and extremely efficient use of the GPUs, with throughput nearly a constant even when processing a large number of control volumes.

42 ENGINEERING↗
DOE OSTI2021

Analyzing the 2019 Chilean social outbreak: Modelling Latin American economies

In this work, we propose a quantitative model for the 2019 Chilean protests. We utilize public data for the consumer price index, the gross domestic product, and the employee and per capita income distributions as inputs for a nonlinear diffusion-reaction equation, the solutions to which provide an in-depth analysis of the population dynamics. Specifically, the per capita income distribution stands out as a solution to the extended Fisher-Kolmogorov equation. According to our results, the concavity of employee income distribution is a decisive input parameter and, in contrast to the distributions typically observed for Chile and other countries in Latin America, should ideally be non-negative. Based on the results of our model, we advocate for the implementation of social policies designed to stimulate social mobility by broadening the distribution of higher salaries.

Curilef, Sergio (ORCID:0000000283183206)↗
NASA NTRS1975

Research study on stabilization and control. Modern sampled-date control theory. Stability analysis of the low cost large space telescope system

A mathematical model employing Fourier series is used to show quantization and reaction wheel friction nonlinearity in a telescope system for use in space. Block diagrams are used to illustrate the system. A discrete describing function of a quantizer also is given, and input and output signal waveforms, with illustrative examples, are shown.

Kuo, B. C.↗
NASA NTRS1988

Heterogeneous physicochemistry of the winter polar stratosphere

Present chemical theories of the Antarctic ozone hole assume that heterogeneous reactions involving polar stratospheric clouds (PSCs) are the precursor of springtime ozone depletions. However, none of the theories quantify the rates of proposed heterogeneous processed, and none utilize the extensive data base on PSC's. Thus, all of the theories must be considered incomplete until the heterogeneous mechanisms are properly defined. A unified treatment developed of the cloud related processes, both physical and chemical, and the importance of these processes using observation data is calibrated. The rates are compared competitive heterogeneous processes to place reasonable limits on critical mechanisms such as the denitrification and dechlorination of the polar winter stratosphere. Among the subjects addressed here are the physical/chemical properties of PSC's including their relevant microphysical, optical and compositional characteristics, mass transfer rates of gaseous constituents to cloud particles, adsorption, accommodation and sticking coefficients on cloud particles, time constants for condensation, absorption and other microphysical processes, effects of solubility and vapor pressure on cloud composition, the statistics of cloud processing of chemically active condensible species, rate limiting steps in heterogeneous chemical reactions, and the nonlinear dependence of ozone loss on physical and chemical parameters.

Turco, R. P.↗
NASA NTRS1991

Suppression of turbulent transport by a weak magnetic field

Two-dimensional numerical simulations with high spatial resolution are used to study the effects of a large-scale magnetic field on its turbulent transport. It is commonly believed that the nonlinear back-reaction of the magnetic field on the turbulence becomes important when the field strength is close to equipartition. However, turbulent diffusion is effectively reduced even when the large-scale field is much weaker than equipartition.

Cattaneo, Fausto↗
NASA NTRS1976

Time scales for molecule formation by ion-molecule reactions

Analytical solutions are obtained for nonlinear differential equations governing the time-dependence of molecular abundances in interstellar clouds. Three gas-phase reaction schemes are considered separately for the regions where each dominates. The particular case of CO, and closely related members of the Oh and CH families of molecules, is studied for given values of temperature, density, and the radiation field. Nonlinear effects and couplings with particular ions are found to be important. The time scales for CO formation range from 100,000 to a few million years, depending on the chemistry and regime. The time required for essentially complete conversion of C(+) to CO in the region where the H3(+) chemistry dominates is several million years. Because this time is longer than or comparable to dynamical time scales for dense interstellar clouds, steady-state abundances may not be observed in such clouds.

Langer, W. D.↗
NASA NTRS1977

Model for premixed turbulent flames

Flame speed and mean degree of reaction profiles are determined for an ensemble mean one-dimensional premixed turbulent flame. Elementary closure models are employed to treat turbulence closure problems arising from the nonlinear convective and chemical reaction rate terms in the time-dependent fuel conservation equation; a constant eddy diffusivity is useed to model correlation terms derived from the convective term. An expression developed for fuel consumption is solved to obtain the turbulent flame speed and the variation of mean fuel mass fraction across the flame. Comparison of the numerical analysis with experimental data indicates the importance of the quenching of the combustion reaction in high-wavenumber eddies.

Gouldin, F. C.↗
NASA NTRS1991

The study of PDF turbulence models in combustion

The accurate prediction of turbulent combustion is still beyond reach for today's computation techniques. It is the consensus of the combustion profession that the predictions of chemically reacting flow were poor if conventional turbulence models were used. The main difficulty lies in the fact that the reaction rate is highly nonlinear, and the use of averaged temperature, pressure, and density produces excessively large errors. The probability density function (PDF) method is the only alternative at the present time that uses local instant values of the temperature, density, etc. in predicting chemical reaction rate, and thus it is the only viable approach for turbulent combustion calculations.

Hsu, Andrew T.↗
NASA NTRS1991

Progress in the development of PDF turbulence models for combustion

A combined Monte Carlo-computational fluid dynamic (CFD) algorithm was developed recently at Lewis Research Center (LeRC) for turbulent reacting flows. In this algorithm, conventional CFD schemes are employed to obtain the velocity field and other velocity related turbulent quantities, and a Monte Carlo scheme is used to solve the evolution equation for the probability density function (pdf) of species mass fraction and temperature. In combustion computations, the predictions of chemical reaction rates (the source terms in the species conservation equation) are poor if conventional turbulence modles are used. The main difficulty lies in the fact that the reaction rate is highly nonlinear, and the use of averaged temperature produces excessively large errors. Moment closure models for the source terms have attained only limited success. The probability density function (pdf) method seems to be the only alternative at the present time that uses local instantaneous values of the temperature, density, etc., in predicting chemical reaction rates, and thus may be the only viable approach for more accurate turbulent combustion calculations. Assumed pdf's are useful in simple problems; however, for more general combustion problems, the solution of an evolution equation for the pdf is necessary.

Hsu, Andrew T.↗
DOE OSTI2024

Material Model Parameters Optimization in Liquid Mercury Target Dynamics Simulation With Machine Learning Surrogates

A pulsed spallation target is subjected to very short (∼0.7μs) but intense loads (23.3 kJ) from repeated proton pulses, which knock away neutrons from the mercury atoms’ nuclei for a wide range application in physics, engineering, medicine, petroleum exploration, biology, chemistry, etc. The effect of this pulsed loading on the stainless-steel target module which contains the flowing mercury target material is difficult to predict not only due to its short but intense explosive-like physical reaction, but also the nonlinear material behavior of the liquid mercury in the structure. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at high power level stage. However, prediction of the resultant loading on the target is more difficult when helium gas is intentionally injected into the mercury. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this complex multi-physics dynamics problem by including the bubble dynamics in the liquid mercury. A parameter sensitivity study was firstly employed to understand their impact on the simulation strains. The investigated parameters included E, μ, γ, σ, n, VFgas, and gas cumulative volume curve control parameters a and b. Verification and validation results from sparse polynomial expansions (SPE) method and directional Gaussian smoothing (DGS) optimization show that the surrogate model had training error of ∼7% and validation error of ∼15%, indicating that machine learning methods and surrogate models can help optimize the uncertain parameters in the complex 2-phase material model. This approach is expected to fill the knowledge gap between unknown liquid-gas mixture material model and measured vessel strain responses.

Lin, Lianshan↗
DOE OSTI2021

An In-Depth Analysis of the Transformation of Tin Foil Anodes during Electrochemical Cycling in Lithium-Ion Batteries

Tin foils have an impressive lithium-storage capacity more than triple that of graphite anodes, and their adoption could facilitate a drastic improvement in battery energy density. However, implementation of a dense foil electrode architecture represents a significant departure from the standard blade-cast geometry with a distinct electrochemical environment, and this has led to confusion with regards to the first cycle efficiency of the system. In this work, we investigate the unique behavior of a tin active material in a foil architecture to understand its performance as an anode. We find shallow cycling of the foil results in an irreversible formation (< 40%) due to diffusional trapping, but intermediate and complete utilization allows for a remarkably reversible formation reaction (> 90%). This striking nonlinearity stems from an in situ transformation from bulk metal to porous electrode that occurs during formation cycles and defines electrode-level lithium-transport on subsequent cycles. As a result, an alternative cycling procedure for assessing the stability of foils is proposed to account for this chemomechanical effect.

25 ENERGY STORAGE↗
NASA NTRS1992

Joystick With Cable Springs Offers Better Feel

Improved joystick allows motion in 6 degrees of freedom, biased toward central position and orientation by 16 segments of cable serving as springs. Improvement in feel and control results from nonlinear compliance of cable-spring assembly. Nonlinear variations accommodate natural reactions of hand and brain. Operator functions as part of feedback control loop. More comfortable, increases ability to exert control and reduces fatigue.

Kerley, James↗