On coupling fluid plasma and kinetic neutral physics models
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A detailed electrochemical model of the alkali metal thermoelectric converter (AMTEC) electrode and current collector grid has been developed recently. Comparative evaluations of the resulting differences in model predictions reveal that the new detailed model predicts up to 50 percent higher electrode power densities at condenser operating temperatures above 600 K. The new model, with experimentally determined parameters, was used to recalculate the projected system performance of previously reported 1- and 100-kWe AMTEC space power systems that had incorporated earlier electrolyte/electrode models. It was found that when the detailed model was used to determine the electrode power densities, enhanced specific power and efficiencies are predicted.
Several different thermochemical models for H2/He mixtures are used to simulate a 1-D shock in a viscous CFD code at conditions relevant for hypersonic entry into the ice and gas giants. These models range from a 6-species, 1-temperature (1-T) model, to more complex 17 and 25-species state-to-state (StS) models. Corresponding radiance profiles for each of these models are then computed using a radiation code, and results are compared to experimental data from the NASA Ames Electric Arc Shock Tube (EAST) facility. Overall, the 6-species model with a quasi-steady state (QSS) solver for atomic H and modified ionization rates, along with the 17 and 25-species StS models, are found to reproduce the magnitude of the radiance seen in the EAST experiments reasonably accurately. Two additional changes to the modeling of species diffusion fluxes are also investigated: the exclusion of a ∇W term, as well as the inclusion of Soret/ Dufour effects. It is determined that these changes to the transport modeling have a negligible impact on the flowfield and therefore the radiance predictions for the H2/He shock conditions considered in this study.
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Residual stress, when superimposed with in-service loading, can significantly reduce the lifetime and performance of a component. Ceramic-metal composites are susceptible to residual stresses due to the thermal expansion mismatch of the ceramic and metallic phases. The WC-Cu composite explored in the present study provides a promising combination of thermal conductivity and strength properties, while exhibiting counterintuitive improvements in strength and ductility after thermal cycling. Further, this work quantifies the evolution of the residual elastic strains as a result of processing and cyclic thermal loading in a co-continuous WC-Cu composite through experimental high energy X-ray diffraction and kinetics-based modeling. Both analyses indicate that processing-induced residual tensile stress in the copper phase is relieved upon subsequent thermal cycling, with kinetics modeling revealing the cyclic-dependent nature of the active power-law creep mechanisms. The results indicate that, through stress relaxation, this material system maintains structural stability during thermal cycling. The illustrated kinetics of relaxation can inform general material processors and designers of ceramic-metal composites to minimize detrimental residual stress and improve performance of these material systems.
In this study, two novel functionalized silica nanocomposites were synthesized via covalent bonding with nanopolyaniline (NPANI) and crosslinked nanopolyaniline (CrossNPANI) to produce [NSi-NPANI] and [NSi-CrossNPANI], respectively. The two nanocomposites were portrayed by SEM, FT-IR, HR-TEM, BET-surface and TGA. The HR-TEM images of [NSi-NPANI] and [NSi-CrossNPANI] confirmed the particle size in the range 14.28–21.43 and 26.19–35.71 nm, respectively and these two nanocomposites were successfully applied to remove divalent cadmium and lead from solutions. As compared to nanosilica [NSi] sorbent, the maximum capacity values of the two nanocomposites for divalent cadmium and lead were identified to increase from 100–250 µmole g{sup −1} (pH 1.0) to 750–800 µmole g{sup −1} (pH 7.0) and from 400–1050 µmole g{sup −1} (pH 1.0) to 650–1350 µmole g{sup −1} (pH 6.0), at the optimum conditions. The adsorption data were compared using two and three parameter equations based on Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Redlish-Peterson and sips models. The kinetic study of [NSi-NPANI] and [NSi-CrossNPANI] revealed that the pseudo-second order kinetic was the best model to explain the kinetic data for cadmium(II) and lead(II). The free energy of sorption (ΔG{sup o}), enthalpy (ΔH{sup o}), and entropy (ΔS{sup o}) changes were calculated to portend the nature of adsorption. Adsorptive extraction of toxic lead and cadmium from tap water and wastewater was successfully accomplished with the range of percentage recovery values 98.5–100.0 and 91.9–93.0%, respectively.
Abstract Understanding plasma turbulence requires a synthesis of experiments, observations, theory, and simulations. In the case of kinetic plasmas such as the solar wind, the lack of collisions renders the fluid closures such as viscosity meaningless and one needs to resort to higher-order fluid models or kinetic models. Typically, the computational expense in such models is managed by simulating artificial values of certain parameters such as the ratio of the Alfvén speed to the speed of light ( v A / c ) or the relative mass ratio of ions and electrons ( m i / m e ). Although, typically care is taken to use values as close as possible to realistic values within the computational constraints, these artificial values could potentially introduce unphysical effects. These unphysical effects could be significant at sub-ion scales, where kinetic effects are the most important. In this paper, we use the 10-moment fluid model in the Gkeyll framework to perform controlled numerical experiments, systematically varying the ion–electron mass ratio from a small value down to the realistic proton–electron mass ratio. We show that the unphysical mass ratio has a significant effect on the kinetic range dynamics as well as the heating of both plasma species. The dissipative process for both ions and electrons becomes more compressive in nature, although the ions remain nearly incompressible in all cases. The electrons move from being dominated by incompressive viscous-like heating/dissipation to very compressive heating/dissipation dominated by compressions/rarefactions. While the heating change is significant for the electrons, a mass ratio of m i / m e ∼ 250 captures the asymptotic behavior of electron heating.
We report on development of a semi-empirical model describing the kinetics of H 2 /D 2 reaction with 1,4-bis(phenylethynyl)benzene (DEB)-based getters in pellet and powder form. The physical basis of the model is solid-state diffusion of DEB plus reaction of DEB with H atoms on the surface of nanometer-scale Pd catalyst particles. The purpose of this material model is to facilitate more accurate predictions of performance for DEB-based getter assemblies. These predictions will be accomplished by integrating the model presented here into finite element, reaction/diffusion simulations of getter assembly hydrogen uptake performance. As of Fall 2020, this integration is underway.
Biomass feedstocks can be used to produce low carbon-intensity chemicals and liquid fuels by displacing fossil-fuel sources. Pyrolysis is the thermal decomposition of biomass in the absence of oxygen and can be used to produce crude biofuels. A typical feeding mechanism for pyrolysis reactors is by lock hopper followed by a horizontal auger feeder. Particle agglomeration and plugging of the auger screw are regularly occurring phenomena that is detrimental to the process since it results in the need for periodic inspection and cleaning. The underlying mechanisms leading to agglomeration and plugging are unclear, but a working hypothesis is that heat from the reactor raises the temperature of the biomass in the feeder to the point at which preliminary decomposition reactions occur and produce "sticky" products. Using principles of heat and mass transfer, we derived one-dimensional differential equations for heat flow from the pyrolysis reactor through the auger feeder. Temperature profiles were solved from the system of one-dimensional differential equations using the shooting method. Subsequently, we used the temperature profiles as a one-way coupling to a reaction model for the biomass in the feeder. Kinetic models were adopted from the literature and used to predict the formation of intermediates, products, char, extractives, and metaplastics as well as phase changes along the auger feeder. Species were identified that correlated with softening of the biomass, causing it to become sticky and plug the feeder. We will discuss the details of this work, our findings, and the direction of future work that includes fully coupled transport and reaction-kinetics simulations.
Popular computational catalyst design strategies rely on the identification of reactivity descriptors, which can be used along with Brønsted–Evans–Polanyi (BEP) and scaling relations as input to a microkinetic model (MKM) to make predictions for activity or selectivity trends. The main benefit of this approach is related to the inherent dimensionality reduction of the large material space to just a few catalyst descriptors. Conversely, it is well documented that a small set of descriptors is insufficient to capture the intricacies and complexities of a real catalytic system. The inclusion of coverage effects through lateral adsorbate-adsorbate interactions can narrow the gap between simplified descriptor predictions and real systems, but mean-field MKMs cannot properly account for local coverage effects. This shortcoming of the mean-field approximation can be rectified by switching to a lattice-based kinetic Monte Carlo (kMC) method using cluster expansion representation of adsorbate–adsorbate lateral interactions. Using the prototypical CO oxidation reaction as an example, we critically evaluate the benefits of kMC over MKM in terms of trend predictions and computational cost when using only a small set of input parameters. After confirming that in the absence of lateral interactions the kMC and MKM approaches yield identical trends and mechanistic information, we observed substantial differences between the two kinetic models when lateral interactions were introduced. Here, the mean-field implementation applies coverage corrections directly to the descriptors, causing an artificial overprediction of the activity of strongly binding metals. In contrast, the cluster expansion in kMC implementation can differentiate among the highly active metals but it is very sensitive to the set of included interaction parameters. Considering that computational screening relies on a minimal set of descriptors, for which MKM makes reasonable trend predictions at a ca. three orders of magnitude lower computational cost than kMC, the MKM approach does provide a better entry point for computational catalyst design.
Understanding the kinetics of toxic ion reactions with ferrihydrite is crucial for predicting the dynamic behavior of contaminants in soil environments. In this study, the kinetics of As(V), Cr(VI), Cu, and Pb adsorption and desorption on ferrihydrite were investigated with a combination of laboratory macroscopic experiments, microscopic investigation and mechanistic modeling. The rates of As(V), Cr(VI), Cu, and Pb adsorption and desorption on ferrihydrite, as systematically studied using a stirred-flow method, was highly dependent on the reaction pH and metal concentrations and varied significantly among four metals. Spherical aberration-corrected scanning transmission electron microscopy (Cs-STEM) showed, at sub-nano scales, all four metals were distributed within the ferrihydrite particle aggregates homogeneously after adsorption reactions, with no evidence of surface diffusion-controlled processes. Based on experimental results, we developed a unifying kinetics model for both cation and oxyanion adsorption/desorption on ferrihydrite based on the mechanistic-based equilibrium model CD-MUSIC. Overall, the model described the kinetic results well, and we quantitatively demonstrated how the equilibrium properties of the cation and oxyanion binding to various ferrihydrite sites affected the adsorption and desorption rates. Our results provided a unifying quantitative modeling method for the kinetics of both cation and oxyanion adsorption/desorption on iron minerals.
Recent kinetic simulations sparked a debate regarding the emission mechanism responsible for pulsed GeV γ-ray emission from pulsars. Some models invoke curvature radiation, while other models assume synchrotron radiation in the current sheet. We interpret the curved spectrum of the Vela pulsar as seen by H.E.S.S. II (up to ∼100 GeV) and the Fermi Large Area Telescope to be the result of curvature radiation due to primary particles in the pulsar magnetosphere and current sheet. We present phase-resolved spectra and energy-dependent light curves using an extended slot gap and current-sheet model, invoking a step function for the accelerating electric field as motivated by kinetic simulations. We include a refined calculation of the curvature radius of particle trajectories in the lab frame, impacting the particle transport, predicted light curves, and spectra. Our model reproduces the decrease of the flux of the first peak relative to the second one, evolution of the bridge emission, near-constant phase positions of peaks, and narrowing of pulses with increasing energy. We can explain the first of these trends because we find that the curvature radii of the particle trajectories in regions where the second γ-ray light-curve peak originates are systematically larger than those associated with the first peak, implying that the spectral cutoff of the second peak is correspondingly larger. However, an unknown azimuthal dependence of the E field, as well as uncertainty in the precise spatial origin of the GeV emission, precludes a simplistic discrimination of emission mechanisms.
A detailed experimental and kinetic modeling study was dedicated to understand the reported octane hyperboosting effect of prenol, by means of the measurement of the ignition delay times of its blends with iso -octane, and measurement of the mole fraction profiles of the fuels and intermediates inside the ULille rapid compression machine. Here, these results show that prenol addition leads to a reduction of the first-stage ignition phenomena and negative temperature coefficient behavior, which is only qualitatively captured by the model and is consistent with knock resistance improvement. It is suggested that this behavior is caused by two different factors. The first originates from gas-phase reactivity of prenol, and spans from the formation of unreactive unsaturated species through resonance-stabilized radicals, thereby constituting a competitive pathway for the radical pool generated by iso -octane. The second is of catalytic nature and cannot be captured by means of gas-phase kinetic modeling, but could also play an important role in the behavior of prenol in internal combustion engines.