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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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NASA NTRS1983

Acoustic imaging for diagnostics of chemically reacting systems

The concept of local diagnostics, in chemically reacting systems, with acoustic imaging is developed. The elements of acoustic imaging through ellipsoidal mirrors are theoretically discussed. In a general plan of the experimental program, the first system is chosen in these studies to be a simple open jet, non premixed turbulent flame. Methane is the fuel and enriched air is the oxidizer. This simple chemically reacting flow system is established at a Reynolds number (based on cold viscosity) of 50,000. A 1.5 m diameter high resolution acoustic mirror with an f-number of 0.75 is used to map the acoustic source zone along the axis of the flame. The results are presented as acoustic power spectra at various distances from the nozzle exit. It is seen that most of the reaction intensity is localized in a zone within 8 diameters from the exit. The bulk reactions (possibly around the periphery of the larger eddies) are evenly distributed along the length of the flame. Possibilities are seen for locally diagnosing single zones in a multiple cluster of reaction zones that occur frequently in practice. A brief outline is given of the future of this work which will be to apply this technique to chemically reacting flows not limited to combustion.

Ramohalli, K.↗

DOE OSTI2022

Autoencoder Neural Network for chemically reacting systems

Incorporating detailed chemical kinetic models is critical for accurate simulations of reacting flows. However, detailed models involve a large number of thermochemical (TC) state variables. Solving the governing equations to evolve these TC variables becomes impractical for real-world applications. In this work, we propose an autoencoder (AE) neural network (NN)-based reduced model to accelerate such simulations. The AE NN is first trained to find a low-dimensional latent representation of the TC states. Then, the evolving state of a chemical system can be tracked by solving the equations of the latent variables instead of the original TC equations. We demonstrate the reduced model in a syngas CO/H 2 combustion system, using training data collected from canonical perfectly stirred reactors (PSRs). It is found that the AE model can reduce the dimension of the combustion system from 12 to 2 while maintaining low reconstruction error and excellent elemental mass conservation for the test dataset. In the a posteriori test, the combustion states obtained from solving the two latent equations are compared to those from solving the 12 equations of the full model. The AE reduced method is found to be able to capture the diverse combustion states on the top two branches of the S-curve well including the extinction turning point, but with higher prediction errors for states near the ignition turning point.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2003

Seventh International Workshop on Microgravity Combustion and Chemically Reacting Systems

The Seventh International Workshop on Microgravity Combustion and Chemically Reacting Systems was planned for June 3-6, 2003, in Cleveland, Ohio, near the NASA John H. Glenn Research Center at Lewis Field. The new name for the workshop is based on the decision to broaden our scope to encompass support for future space exploration through basic and applied research in reacting systems that in some cases may not look like combustion. The workshop has been lengthened to 4 days with focus sessions on spacecraft fire safety and exploration-related research. We believe that the microgravity combustion science community is almost uniquely positioned to make substantial contributions to this new effort.

Sacksteder, Kurt↗

DOE OSTI2018

Errors in nanoparticle growth rates inferred from measurements in chemically reacting aerosol systems

In systems in which aerosols are being formed by chemical transformations,individual particles grow due to the addition of molecular species. Efforts to improve our understanding of particle growth often focus on attempts to reconcile observed growth rates with values calculated from models. However,because it is typically not possible to measure the growth rates of individual particles in chemically reacting systems, they must be inferred from measurements of aerosol properties such as size distributions, particle number concentrations, etc. Furthermore this work discusses errors in growth rates obtained using methods that are commonly employed for analyzing atmospheric data. We analyze “data” obtained by simulating the formation of aerosols in a system in which a single chemical species is formed at a constant rate, R . We show that the maximum overestimation error in measured growth rates occurs for collision-controlled nucleation in a single-component system in the absence of a preexisting aerosol, wall losses, evaporation or dilution,as this leads to the highest concentrations of nucleated particles. Those high concentrations lead to high coagulation rates that cause the nucleation mode to grow faster than would be caused by vapor condensation alone. We also show that preexisting particles, when coupled with evaporation, can significantly decrease the concentration of nucleated particles. This can lead to decreased discrepancies between measured growth rate and true growth rate by reducing coagulation among nucleated particles. However, as particle sink processes become stronger, measured growth rates can potentially be lower than true particle growth rates. We briefly discuss nucleation scenarios in which the observed growth rate approaches zero while the true growth rate does not.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Advances in imaging of chemically reacting flows

Many important chemically reacting systems are inherently multi-dimensional with spatial and temporal variations in the thermochemical state, which can be strongly coupled to interactions with transport processes. Fundamental insights into these systems require multi-dimensional measurements of the thermochemical state as well as fluid dynamics quantities. Laser-based imaging diagnostics provide spatially and temporally resolved measurements that help address this need. The state of the art in imaging diagnostics is continually progressing with the goal of attaining simultaneous multi-parameter measurements that capture transient processes, particularly those that lead to stochastic events, such as localized extinction in turbulent combustion. Development efforts in imaging diagnostics benefit from advances in laser and detector technology. This article provides a perspective on the progression of increasing dimensionality of laser-based imaging diagnostics and highlights the evolution from single-point measurements to 1D and 2D multi-parameter imaging and 3D high-speed imaging. This evolution is demonstrated using highlights of laser-based imaging techniques in combustion science research as an exemplar of a complex multi-dimensional chemically reacting system with chemistry–transport coupling. Imaging diagnostics impact basic research in other chemically reacting systems as well, such as measurements of near-surface gases in heterogeneous catalysis. The expanding dimensionality of imaging diagnostics leads to larger and more complex datasets that require increasingly demanding approaches to data analysis and provide opportunities for increased collaboration between experimental and computational researchers in tackling these challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Stable high-pressure phases in the H-S system determined by chemically reacting hydrogen and sulfur

Synchrotron x-ray diffraction and Raman spectroscopy have been used to study the chemical reactions of molecular hydrogen (H 2 ) with sulfur (S) at high pressures. We find theoretically predicted Cccm and Im3¯m H 3 S to be the reaction products at 50 and 140 GPa, respectively. Im3¯m H 3 S is a stable crystalline phase above 140 GPa and it transforms to R 3 m H 3 S on pressure release below 140 GPa. Here, the latter phase is (meta)stable down to at least 70 GPa where it transforms to Cccm H 3 S upon annealing (T < 1300 K) to overcome the kinetic hindrance. Cccm H 3 S has an extended structure with symmetric hydrogen bonds at 50 GPa, and upon decompression it experiences a transformation to a molecular mixed H 2 S – H 2 structure below 40 GPa without any apparent change in the crystal symmetry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1986

Thermodynamics and combustion modeling

Modeling fluid phase phenomena blends the conservation equations of continuum mechanics with the property equations of thermodynamics. The thermodynamic contribution becomes especially important when the phenomena involve chemical reactions as they do in combustion systems. The successful study of combustion processes requires (1) the availability of accurate thermodynamic properties for both the reactants and the products of reaction and (2) the computational capabilities to use the properties. A discussion is given of some aspects of the problem of estimating accurate thermodynamic properties both for reactants and products of reaction. Also, some examples of the use of thermodynamic properties for modeling chemically reacting systems are presented. These examples include one-dimensional flow systems and the internal combustion engine.

Zeleznik, Frank J.↗

DOE OSTI2024

CMLM (Co-Optimized Machine-Learned Manifolds) [SWR-23-41]

Co-optimized Machine-Learned Manifolds (CMLM) is a data-driven approach for developing reduced-order manifold models for high-dimensional chemically reacting systems. It involves a specially designed neural network, the training of which simultaneously optimizes linear combinations of species that define the manifold, nonlinear mapping to outputs of interest such as reaction rates, and (optionally) subfilter closure for large eddy simulation. This software package provides an implementation of the CMLM approach in Python using the PyTorch machine learning library. A few example cases are included, showing how the tool can be applied to different types of data from 0D and 1D reacting simulations performed using Cantera. The neural networks can be saved in a format that is readable by the Pele suite of combustion solvers for use in reacting computational fluid dynamics simulations. This software repository contains several python scripts to perform various tasks associated with the Co-optimized Machine Learned Manifolds (CMLM) model, which is described in Perry, Henry de Frahan, and Yellapantula, CNF, 2022 (https://doi.org/10.1016/j.combustflame.2022.112286). This includes not only the code that defines the CMLM model, but also scripts to generate suitable training data, scripts to pre-process the data, scripts to train the CMLM model, and scripts to plot the output, as well as various other helper files. The scripts depend on several commonly used python libraries for data analysis and chemical reaction computations. The trained models that result from this tool are designed to work with the an interface being implemented in the Pele suite of reacting flow solvers (https://github.com/AMReX-Combustion).

Perry, Bruce↗

DOE OSTI2014

The small-voxel tracking algorithm for simulating chemical reactions among diffusing molecules

Simulating the evolution of a chemically reacting system using the bimolecular propensity function, as is done by the stochastic simulation algorithm and its reaction-diffusion extension, entails making statistically inspired guesses as to where the reactant molecules are at any given time. Those guesses will be physically justified if the system is dilute and well-mixed in the reactant molecules. Otherwise, an accurate simulation will require the extra effort and expense of keeping track of the positions of the reactant molecules as the system evolves. One molecule-tracking algorithm that pays careful attention to the physics of molecular diffusion is the enhanced Green's function reaction dynamics (eGFRD) of Takahashi, Tănase-Nicola, and ten Wolde [Proc. Natl. Acad. Sci. U.S.A. 107, 2473 (2010)]. We introduce here a molecule-tracking algorithm that has the same theoretical underpinnings and strategic aims as eGFRD, but a different implementation procedure. Called the small-voxel tracking algorithm (SVTA), it combines the well known voxel-hopping method for simulating molecular diffusion with a novel procedure for rectifying the unphysical predictions of the diffusion equation on the small spatiotemporal scale of molecular collisions. Indications are that the SVTA might be more computationally efficient than eGFRD for the problematic class of non-dilute systems. A widely applicable, user-friendly software implementation of the SVTA has yet to be developed, but we exhibit some simple examples which show that the algorithm is computationally feasible and gives plausible results.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

The role of energy transfer and competing bimolecular reactions in characterizing the unimolecular dissociations of allylic radicals

Resonantly stabilized radicals (RSR's) such as allylic radicals typically have bond energies exceeding 45 kcal/mol and are therefore reasonably long-lived up to quite high temperatures. Consequently, kinetics of the unimolecular dissociations and bimolecular reactions of these long-lived RSR's assume significance in high temperature chemically reacting systems such as in flames. Our recent analyses (J. Cho et al., Proc. Comb. Inst., 2022) of the uncertainty propagated by the energy transfer parameters for 1-methylallyl (1MA) dissociation to the laminar flame speed, indicates an intricate coupling between the kinetics of 1MA dissociation (chain propagation) and its reaction with H-atoms (chain-termination). Here, this work extends such analyses to other C 3 – C 5 allylic radicals: allyl, 2-methylallyl, 1,1-dimethylallyl, 1,2-dimethylallyl, and 1,3-dimethylallyl. Theoretical kinetics for the C 3 – C 4 allylic radicals were taken from prior literature studies (J.A. Miller et al., J. Phys. Chem., 2008; J. Cho et al., Proc. Comb. Inst., 2022; R.S. Tranter et al., Proc. Comb. Inst., 2017). Potential energy surfaces were newly computed for the dissociations of the larger C5 allylic radicals and the reactions of these radicals with H-atoms. These PES's were then used to calculate rate constants for the relevant unimolecular and bimolecular reactions. Energy transfer has a crucial role to play in these pressure-dependent reactions and therefore the present kinetics calculations relied on a-priori predictions of collisional energy transfer parameters to best characterize the branching between chain propagating unimolecular dissociations of these allylic radicals and chain terminating bimolecular reactions of these RSR's with H-atoms. Prompt dissociations are now established to be a universal feature of free radical dissociations. Here we have also characterized the propensity for prompt dissociations in these more-stable allylic RSR's and their role in combustion simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Time dependent solution for acceleration of tau-leaping

The tau-leaping method is often effective for speeding up discrete stochastic simulation of chemically reacting systems. However, when fast reactions are involved, the speed-up for this method can be quite limited. One way to address this is to apply a stochastic quasi-steady state assumption. However we must be careful when using this assumption. If the fast subsystem cannot reach a steady distribution fast enough, the quasi-steady-state assumption will propagate error into the simulation. To avoid these errors, we propose to use the time dependent solution rather than the quasi-steady-state. Generally speaking, the time dependent solution is not easy to derive for an arbitrary network. However, for some common motifs we do have time dependent solutions. We derive the time dependent solutions for these motifs, and then show how they can be used with tau-leaping to achieve substantial speed-ups, including for a realistic model of blood coagulation. Although the method is complicated, we have automated it.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Zero-Order Reaction Kinetics

Zero-order Reaction Kinetics (Zero-RK) is a software package that simulates chemically reacting systems in a computationally efficient manner. The fundamental advance embodied in Zero-RK is the numerical approach, which results in orders-of-magnitude reduction in simulation time while maintaining the accuracy of the results.

Mcnenly, MatthewJ↗

DOE OSTI2021

Zero-Order Reaction Kinetics v3.0

Zero-RK is a software package that simulates chemically reacting systems using sparse, preconditioned, adaptive matrix methods to achieve orders-of-magnitude reduction in simulation time while maintaining accurate results.

Mcnenly, MatthewJ.↗

DOE OSTI2020

Zero-Order Reaction Kinetics

Lapointe, Simon↗

DOE OSTI2023

Zero-Order Reaction Kinetics v. 3.4.hip

Mcnenly, MatthewJ↗

DOE OSTI2025

Zero-Order Reaction Kinetics v. 3.6

McNenly, MatthewJ [Lawrence Livermore National Lab↗

DOE OSTI2024

Investigating the collective nature of cavity-modified chemical kinetics under vibrational strong coupling

Abstract In this paper, we develop quantum dynamical methods capable of treating the dynamics of chemically reacting systems in an optical cavity in the vibrationally strong-coupling (VSC) limit at finite temperatures and in the presence of a dissipative solvent in both the few and many molecule limits. In the context of two simple models, we demonstrate how reactivity in the collective VSC regime does not exhibit altered rate behavior in equilibrium but may exhibit resonant cavity modification of reactivity when the system is explicitly out of equilibrium. Our results suggest experimental protocols that may be used to modify reactivity in the collective regime and point to features not included in the models studied, which demand further scrutiny.

Lindoy, Lachlan P.↗

NASA NTRS1992

Flow effects in a vertical CVD reactor

A model is presented to simulate the non-Boussinesq flow in a vertical, two-dimensional, chemical vapor deposition reactor under atmospheric pressure. Temperature-dependent conductivity, mass diffusivity, viscosity models, and reactive species mass transfer to the substrate are incorporated. In the limits of small Mach number and small aspect ratio, asymptotic expressions for the flow, temperature, and species fields are developed. Soret diffusion effects are also investigated. Analytical solutions predict an inverse relationship between temperature field and concentration field due to Soret effects. This finding is consistent with numerical simulations, assisting in the understanding of the complex interactions amongst the flow, thermal, and species fields in a chemically reacting system.

Young, G. W.↗