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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Molecular beam mass spectrometry measurements of vibrationally excited N 2 in the effluent of an atmospheric plasma jet: a comparison with a state-to-state kinetic model

Vibrationally excited N 2 molecules are suggested to be one of the possible key species responsible for the observed synergistic effects in plasma catalysis for NH 3 synthesis. To assess the impact of vibrationally excited species in plasma-catalysis, quantitative measurements near interfaces are required, which remains challenging. In this letter, we report spatially resolved measurements of vibrationally excited N 2 in the effluent of an atmospheric pressure plasma jet by molecular beam mass spectrometry (MBMS). The mass spectrometry signals as a function of electron energy of the ionizer were fitted with the effective electron-impact ionization cross section of N 2 (v) considering the vibrational distribution function as determined by a detailed vibrational level resolved plasma kinetic calculation. Here, the reported method presented in this letter shows the capability of MBMS to measure vibrationally excited species of N 2 near interfaces when the vibrational distribution function is known or assumed and shows excellent agreement with state-to-state kinetic models of N 2 (v).

42 ENGINEERING↗
DOE OSTI2024

Energy-dependent implementation of secondary electron emission models in continuum kinetic sheath simulations

The plasma-material interactions present in multiple fusion and propulsion concepts between the flow of plasma through a channel and a material wall drive the emission of secondary electrons. This emission is capable of altering the fundamental structure of the sheath region, significantly changing the expected particle fluxes to the wall. The emission spectrum is separated into two major energy regimes, a peak of elastically backscattered primary electrons at the incoming energy, and cold secondary electrons inelastically emitted directly from the material. The ability of continuum kinetic simulations to accurately represent the secondary electron emission is limited by relevant models being formulated in terms of monoenergetic particle interactions which cannot be applied directly to the discrete distribution function. As a result, rigorous implementation of energy-dependent physics is often neglected in favor of simplified, constant models. We present here a novel implementation of semi-empirical models in the boundary of continuum kinetic simulations which allows the full range of this emission to be accurately captured in physically-relevant regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Global gyrokinetic simulation with kinetic electron for collisionless damping of zonal flow in stellarators

Global gyrokinetic simulations with kinetic electrons for collisionless damping of zonal flows in LHD and W7-X stellarators show that the helical components of the equilibrium magnetic field responsible for helically trapped particles have significant impacts on zonal flow. Kinetic electrons reduce zonal flow residue and increase the frequency of low frequency oscillation (LFO). Here, the LFO is induced by dominant helical harmonics of magnetic field strength. Furthermore, linear toroidal coupling of multiple toroidal n-harmonics barely affects the zonal flows, but can generate long wavelength toroidal harmonics with the same toroidal number as the helical magnetic field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Nonlinear saturation of reverse shear Alfvén eigenmodes induced by kinetic electrons

A strong nonlinear saturation mechanism of the reverse shear Alfvén eigenmode (RSAE) induced by thermal electrons is observed in gyrokinetic $\delta$$f$ particle-in-cell simulation. This nonlinear effect occurs at moderate mode amplitude, $\delta$$B$ ⟂ /$B$ < 10 -3 , and is associated with the electron parallel streaming along the perturbed magnetic field lines, the term v $\|$ $\frac{δΒ_{⟂}}{B}$ ∙ ∇$\delta$$f$, in the electron drift-kinetic equation. In the case of an n = 4 RSAE, where n is the toroidal mode number, this magnetic fluttering nonlinearity leads to strong mode coupling and broadening of the saturation spectrum. The nonlinear components, which are highly damped through the interaction between thermal electrons and the parallel electric field, modifies the RSAE mode structure and suppresses energetic particle drive significantly. The split-weight scheme (Chen and Parker 2007 J. Comput. Phys. 220 839–55) is used to simulate kinetic electrons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Machine learning-based real-time kinetic profile reconstruction in DIII-D

Abstract Kinetic equilibrium reconstruction plays a vital role in the physical analysis of plasma stability and control in fusion tokamaks. However, the traditional approach is subjective and prone to human biases. To address this, the consistent automatic kinetic equilibrium reconstruction (CAKE) method was introduced, providing objective results. Nonetheless, its offline nature limits its application in real-time plasma control systems (PCSs). To address this limitation, we present RTCAKENN, a machine learning model that approximates 7 CAKE-level output profiles, namely pressure, inverse q , toroidal current density, electron temperature and density, carbon ion impurity temperature and rotation profiles, using real-time available inputs. The deep neural network consists of an encoder layer, where the scalars and interdependent inputs such as plasma boundary coordinates and motional Stark effect data are encoded using multi-layer perceptrons (MLPs), while profile inputs are encoded by 1D convolutional layers. The encoded data is passed through a MLP for latent feature extraction, before being decoded in the decoding layers, which consist of upsampling and convolutional layers. RTCAKENN has been implemented in the DIII-D PCS and our model achieves accuracy comparable to CAKE and surpasses existing real-time alternatives. Through clever dropout training, RTCAKENN exhibits robustness and can operate even in the absence of Thomson scattering data or charge exchange recombination data. It executes in under 8 ms in the real-time environment, enabling future application in real-time control and analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Linking stem rehydration kinetics to hydraulic traits using a novel method and mechanistic model

Background: Despite the recognized importance of hydraulic capacitance as a mechanism used by plants to maintain hydraulic functioning during high transpiration, characterizing the dynamics of capacitance remains a challenge. Methods: For this work, we used a novel ‘two-balance method’ to investigate relationships between stem rehydration kinetics and other hydraulic traits in multiple tree species, and we developed a model to explore stem rehydration kinetics further. Key Results: We found that: (1) rehydration time constants and the amount of water uptake occurring during rehydration differed significantly across species; (2) time constants did not change with declining water potential (Ψ), while water uptake increased at lower Ψ in some species; (3) longer time constants were associated with lower wood density, higher capacitance and less negative stem pressures causing 50 % loss of hydraulic conductivity (P 50 ); (4) greater water uptake occurred in stems with lower wood density and less negative P 50 values; and (5) the model could estimate the total hydraulic resistance of the rehydration path, which cannot be measured directly. Conclusions: Overall, the two-balance method can be used to examine rehydration dynamics quickly and thoroughly in detached woody stems. This method has the potential to improve our understanding of how capacitance functions across tree species, which is an often-overlooked component of whole-plant hydraulics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗
DOE OSTI2024

Ignition Delay Times and Chemical Kinetic Model Validation for Hydrogen and Ammonia Blending With Natural Gas at Gas Turbine Relevant Conditions

Ignition delay times from undiluted mixtures of natural gas (NG)/H 2 /Air and NG/NH 3 /Air were measured using a high-pressure shock tube at the University of Central Florida. The combustion temperatures were experimentally tested between 1000 and 1500 K near a constant pressure of 25 bar. As mentioned, mixtures were kept undiluted to replicate the same chemistry pathways seen in gas turbine combustion chambers. Recorded combustion pressures exceeded 200 bar due to the large energy release, hence why these were performed at the high-pressure shock tube facility. The data are compared to the predictions of the NUIGMech 1.1 mechanism for chemical kinetic model validation and refinement. An exceptional agreement was shown for stoichiometric conditions in all cases but strayed at lean and rich equivalence ratios, especially in the lower temperature regime of H 2 addition and all temperature ranges of the baseline NG mixture. Hydrogen addition also decreased ignition delay times by nearly 90%, while NH 3 fuel addition made no noticeable difference in ignition time. NG/NH 3 exhibited similar chemistry to pure NG under the same conditions, which is shown in a sensitivity analysis. Here, the reaction CH 3 + O 2 = CH 3 O + O is identified and suggested as a possible modification target to improve model performance. Increasing the robustness of chemical kinetic models via experimental validation will directly aid in designing next-generation combustion chambers for use in gas turbines, which in turn will greatly lower global emissions and reduce greenhouse effects.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Methods—Design Guidelines for Tubular Flow-through Electrodes for Use in Electroanalytical Studies of Redox Reaction Kinetics

The tubular flow-through electrode (FTE) is a facile electroanalytical tool for investigating electrochemical reaction kinetics; however, its suitability for this purpose requires careful design and operation under conditions that guarantee uniform current distribution. In this perspective article, we provide a scaling analysis of the transport and reaction processes within a tubular FTE leading to quantitative guidelines for the FTE design and operation. Two dimensionless parameters (classical Wagner number Wa I and modified Wagner number incorporating the effect of mass transport Wa II ) are utilized to compare the magnitudes of the ohmic, activation and transport resistances of the tubular FTE, and to quantify its current distribution uniformity. With the aid of analytical modeling of the current distribution, optimal ranges for these two dimensionless parameters are defined so as to ascertain uniform current distribution. Application of these guidelines to a graphite tubular FTE is shown to enable the precise determination of the charge-transfer kinetics of the ferri/ferrocyanide redox reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Development of a kinetic-thermodynamic model for lime-stabilization of Na-bentonite

This study presents the first kinetic model to predict the solid and pore solution composition of Na-bentonite clay reacting with slaked lime over a period of 720 days. The model successfully accounts for most experimental data using a single kinetic rate constant. The following sequence of reactions was predicted by the model: initial rapid dissolution of portlandite within the first 7 days, leading to a decrease in pH and dissolved calcium, and concurrent formation of calcium silicate hydrates (C-S-H: jennite), calcium aluminate hydrate (C-A-H: C₄AH₁₃), calcium aluminosilicate hydrates (stratlingite) and hydrotalcite. After 7 days, jennite and stratlingite are predicted to transform into tobermorite-II, contributing to strength development up to 28 days. From 28 to 90 days, continued montmorillonite dissolution is predicted, along with minor formation of ettringite, partial tobermorite-II dissolution, and precipitation of secondary phases such as albite and talc. Experimentally, portlandite dissolution was confirmed by TGA and XRD and found to be complete within 7 days, in agreement with model predictions. However, other predicted solid-phase transformations (e.g., tobermorite-II formation and dissolution, ettringite, albite, and talc formation) could not be conclusively verified through experimental techniques. Aqueous phase measurements confirmed that the pH and Ca trends in solution, and that equilibrium was reached by 90 days.

Chemical kinetics↗
DOE OSTI2021

Demonstrate Capability of NEAMS Tools to Generate Reactor Kinetics Parameters for Pebble-Bed HTGRs Transient Modeling

The system analysis of anticipated operating occurrences and design basis accident for pebblebed reactor systems requires knowledge of the neutron kinetic parameters. These parameters take into account various types of feedback from the pebble-bed core and are typically integrated into system analysis tools such as the System Analysis Module (SAM) in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) tool package. These parameters are typically generated by a higher fidelity full-core coupled neutronics/thermal fluids analysis, such as using Griffin and Pronghorn, in 2D or 3D. The delayed neutron fractions (beta) and the neutron lifetimes (lambda) are typically generated by applying the adjoint solution of the neutron flux. Temperature reactivity coefficients are the most important feedback for all anticipated operating occurrences and design basis accident, then depending on the transient other effects might be important as rector control system worth, s-curves, and Xenon generation. This work package will establish a methodology and process for calculating the reactor kinetics parameters for high-temperature gas-cooled reactor and provide them in a suitable form for system level analyses of typical anticipated operating occurrences and design basis accident.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Hydro-Code Implementation and Testing of a Kinetic Phase Transition Framework

In this report we describe the Kinetic Phase Transition (KPT) framework that has been worked out over the last 10 years (from around 2014) and the implementation of it into three different codes, the one-dimensional hydro- LASLO and the three-dimensional magneto-hydro- ALEGRA, Sandia codes, via subroutines in the LAMBDA Equations of State and constitutive models package, and Flag, an arbitrary Lagrangian-Eulerian multiphysics code developed within the Lagrangian Applications project (LAP) at LANL. We discuss the introduction of phase mass (and/or volume) fractions that are needed in a code for it to be ‘phase aware’, that is, not only the thermodynamic state is known in each point but also the mixture of the materials’ phases in that point. Further we point to the need of a full Equations of State for each phase in a material to achieve phase awareness and we review the equilibrium phase model, where a phase mixture is at its lowest Gibbs free energy state, to make this point clear. Contrasting the kinetic phase transition to this equilibrium model seamlessly introduce us to the KPT framework that is subsequently thoroughly discussed. While the determination of the total state and the states and mass fractions of phases in each point is a problem that can borrow many of its numerical details from Eulerian codes and mixture of materials (not phases), the update of mass fractions with time in a KPT framework needs a new set of considerations. General for any update model is that we need to prevent mass fractions from becoming unphysical (negative or their sum to be larger than one). We have solved this problem by implementing a subdivision of the hydro time step that prevents the phase from being fully present to not present at all in one subdivided time step by limiting the size of the subdivided time step. This scheme also corrects numerical problems from abrupt changes in parameter values, the so called Gibbs phenomena, that gives rise to slushing between phases in the KPT framework. Interspersed throughout the report are discussions on different thermodynamics considerations. EOS validity windows, limitations on the EOS phase space, are needed for the KPT framework and are discussed separately and exemplified. The KPT framework described in this report has been verified by code comparison, but validation is still an active area of research. There is room for improvement in the update model, both in the model for determination of rates and in how to prevent the mass fractions from becoming unphysical. In addition, the parameters in the KPT update model and the placement of the phase boundary in the EOS phase space, and interactions with other constitutive models, are closely related and interfering with each other. One possible way forward is to simultaneously develop KPT parameters, EOS, and constitutive models for each material.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A Semi-Detailed Pyrolytic Gas-Phase Kinetic Model for the Volatiles of Polyethylene Thermal Degradation

This work presents a semi-detailed kinetic model to address the pyrolytic gas-phase reactivity of volatiles formed during thermal degradation of polyethylene (PE). The model builds on a validated multi-step condensed-phase model and employs validated lumping approaches. Short-chain compounds are modelled with high detail, while long-chain ones are described by surrogate species representative of diesel-cuts (NC16H32) and waxes (NC30H60). The reactivity of short chains is described through the comprehensive CRECK kinetic model, updated to align C5-C7 olefins based on recent literature experimental data. Due to the lack of experimental data for longer olefins, their reactivity is modeled by analogy to the shorter ones, ensuring an asymptotic behavior with increasing carbon numbers. The semi-detailed model is validated through experimental data on PE pyrolysis, assuming an instantaneous mixing of the inert inlet flow with released volatiles, followed by a segregated plug-flow behavior. Validation across different reactor setups confirms the model’s capability to predict detailed product distributions. Despite minor discrepancies, the proposed model effectively captures experimental trends. Further work will address modelling the reactivity in oxygen-containing environments.

kinetics↗
DOE OSTI2024

A framework of computer vision-enhanced microfluidic approach for automated assessment of the transient sickling kinetics in sickle red blood cells

The occurrence of vaso-occlusive crisis greatly depends on the competition between the sickling delay time and the transit time of individual sickle cells, i.e., red blood cells from sickle cell disease (SCD) patients, while they are traversing the circulatory system. Many drugs for treating SCD work by inhibiting the polymerization of sickle hemoglobin (HbS), effectively delaying the sickling process in sickle cells (SS RBCs). Most previous studies on screening anti-sickling drugs, such as voxelotor, rely on in vitro testing of sickling characteristics, often conducted under prolonged deoxygenation for up to 1 hour. However, since the microcirculation of RBCs typically takes less than 1 minute, the results of these studies may be less accurate and less relevant for in vitro-in vivo correlation. In our current study, we introduce a computer vision-enhanced microfluidic framework designed to automatically capture the transient sickling kinetics of SS RBCs within a 1-min timeframe. Our study has successfully detected differences in the transient sickling kinetics between vehicle control and voxelotor-treated SS RBCs. This approach has the potential for broader applications in screening anti-sickling therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evaluation of an Image-Derived Input Function for Kinetic Modeling of Nicotinic Acetylcholine Receptor-Binding PET Ligands in Mice

Positron emission tomography (PET) radioligands that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allow for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. Here, we investigate the use of an image-derived arterial input function and the cerebellum for kinetic analysis of radioligand binding in mice. Two radioligands were explored: 2-[ 18 F]FA85380 (2-FA), displaying similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [ 18 F]Nifene, displaying similar pKa and binding affinity to nicotine. Time–activity curves of the left ventricle of the heart displayed similar distribution across wild type mice, mice lacking the β2-subunit for ligand binding, and acute nicotine-treated mice, whereas reference tissue binding displayed high variation between groups. Binding potential estimated from a two-tissue compartment model fit of the data with the image-derived input function were higher than estimates from reference tissue-based estimations. Rate constants of radioligand dissociation were very slow for 2-FA and very fast for Nifene. We conclude that using an image-derived input function for kinetic modeling of nicotinic PET ligands provides suitable results compared to reference tissue-based methods and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

2-FA85380↗
DOE OSTI2024

Kinetics of HCP-BCC Phase Transition Boundary in Magnesium at High Pressure

Under high pressures, many crystalline metals undergo solid–solid phase transformations. In order to accurately model the behavior of materials under extreme loading conditions, it is essential to understand the kinetics of phase transition. Using molecular dynamics simulations, this work demonstrates the feasibility of characterizing the speeds of a moving phase boundary using atomistic simulations employing a suitable empirical potential for single-crystal magnesium. The model can provide temperature- and tensorial stress-dependent velocity of a moving phase boundary as a rate-limiting contribution to the kinetics of phase transformation in continuum codes. Results demonstrate that a nonlinear interaction exists between plasticity and phase transition, facilitating a jump in the velocity of a moving phase boundary, facilitated by activated plastic deformation mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predicting Asteroid Material Properties from a DART-like Kinetic Impact

Abstract NASA’s Double Asteroid Redirection Test (DART) mission is the first full-scale test of the kinetic impactor method for asteroid deflection, in which a spacecraft intentionally impacts an asteroid to change its trajectory. DART represents an important first step for planetary defense technology demonstration, providing a realistic assessment of the effectiveness of the kinetic impact approach on a near-Earth asteroid. The momentum imparted to the asteroid is transferred from the impacting spacecraft and enhanced by the momentum of material ejected from the impact site. However, the magnitude of the ejecta contribution is dependent on the material properties of the target. These properties, such as strength and shear modulus, are unknown for the DART target asteroid, Dimorphos, as well as most asteroids since such properties are difficult to characterize remotely. This study examines how hydrocode simulations can be used to estimate material properties from information available post-impact, specifically the asteroid size and shape, the velocity and properties of the impacting spacecraft, and the final velocity change imparted to the asteroid. Across >300 three-dimensional simulations varying seven material parameters describing the asteroid, we found many combinations of properties could reproduce a particular asteroid velocity. Additional observations, such as asteroid mass or crater size, are required to further constrain properties like asteroid strength or outcomes like the momentum enhancement provided by impact ejecta. Our results demonstrate the vital importance of having as much knowledge as possible prior to an impact mission, with key material parameters being the asteroid’s mass, porosity, strength, and elastic properties.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

Kinetics of antigen binding to arrays of antibodies in different sized spots

A fluorescence-based array biosensor has been developed which can measure the binding kinetics of an antigen to an immobilized antibody in real time. A patterned array of antibodies immobilized on the surface of a planar waveguide was used to capture a Cy5-labeled antigen present in a solution that was continuously flowed over the surface. The CCD image of the waveguide was monitored continuously for 25 min. The resulting exponential rise in fluorescence signal was determined by image analysis software and fitted to a reaction-limited kinetics model, giving a kf of 3.6 x 10(5) M(-1) s(-1). Different spot sizes were then patterned on the surface of the waveguide using either a PDMS flow cell or laser exposure, producing width sizes ranging from 80 to 1145 microm. It was demonstrated that under flow conditions, the reduction of spot size did not alter the association rate of the antigen with immobilized antibody; however, as the spot width decreased to < 200 nm, the signal intensity also decreased.

Non-NASA Center↗