Hybrid Kinetic Model Research Articles

Hybrid Kinetic Modeling of the Magnetosheath Impulsive Plasma Cloud Penetration Through the Magnetopause and Comparison With MMS and Other Spacecraft Observations

AbstractThis research examines the plasma processes under penetration of the plasma clouds (plasmoids) across the magnetopause which is modeled as a tangential discontinuity (TD). Cases with the parallel magnetic field in both sides out of the TD are under investigation. Plasma parameters and magnetic field were chosen from the MMS mission and other spacecraft observations. The results are important for understanding the following basic space plasma physics problems: (a) plasma cloud deformation and strong phase mixing with magnetospheric plasma; (b) the transfer of mass, momentum and energy of magnetosheath and magnetic cloud plasma into magnetospheric plasmas; (c) necessary conditions for plasma cloud penetration via the magnetopause; (d) wave generation by plasma clouds inside the magnetopause.

Creating a new paradigm by modeling the interaction of the solar wind with the interstellar medium using a hybrid-kinetic model

Creating a new paradigm by modeling the interaction of the solar wind with the interstellar medium using a hybrid-kinetic model

A combined immersed finite element and conservative semi-Lagrangian scheme for plasma-material interactions

In this paper, the immersed finite element (IFE) coupled with the conservative semi-Lagrangian (CSL) kinetic scheme is developed for plasma-material interactions. The proposed method (IFE-CSL) enjoys respective advantages of the IFE and CSL, i.e., the flexibility and efficiency for treating complex boundary conditions, mass conservation and being free from the Courant-Friedrichs-Lewy (CFL) condition. In the current IFE-CSL, the IFE method based on structured interface-independent meshes is developed for the spatial discretization of the field equation, which provides an accurate approach with convenient implementations to solve the field problems with irregular interface. The CSL scheme combined with an immersed method termed half-way ghost-cell is proposed for the spatial discretization of the Vlasov equation, which enables the proposed method to exactly conserve mass and conveniently handle curved boundaries. Then the IFE and CSL method are coupled via the charge density depending on full kinetic or hybrid kinetic model, where the appropriate IFE solver is developed for the linear or nonlinear Poisson equation, respectively. In the current IFE-CSL, different geometries can be treated automatically for both IFE and CSL through the specific geometric information. As a result, the proposed CSL-IFE can be conveniently and efficiently applied to simulate the plasma-material interactions with structured interface-independent meshes. Finally, several numerical experiments are performed to demonstrate the capabilities of the proposed method.

Medical education system (re)building in a fragile setting: Northwest Syria as a case study.

Syria has witnessed more than a decade of armed conflict through which healthcare workers and facilities have not only been affected, but targeted. Amidst this targeting of healthcare workers, subsequent displacement, and 'weaponization' of healthcare, the medical education and health professional training (MEHPT) of those that remain has split into at least two distinctive contexts: government controlled, and non-government controlled. Efforts to rebuild MEHPT in light of this polarisation and fragmentation have led to a new MEHPT system in non-government controlled northwest Syria, that functions through what we describe as a 'hybrid kinetic model'. This mixed-methods study provides an in-depth analysis of this MEHPT system as a case study to inform future policy planning and interventions in the context of future post-conflict health workforce development. We used mixed methods to investigate the state of MEHPT in northwest Syria during September 2021 and May 2022. This included a) Stakeholder analysis, b) 15 preparatory experts consultations c) 8 Focus group discussions d) 13 Semi-structured interviews e) 2 Questionnaires and f) Validation workshops. We identified three main categories of key stakeholders working on MEHPT in northwest Syria: 12 newly established academic institutions, 7 local governance authorities involved in MEHPT, and 12 non-governmental organisations (NGOs). The MEHPT system operated through these stakeholders in a three-layer system to provide undergraduate and postgraduate MEHPT. In the first, top, layer, external NGOs and donors hold the strongest capacity at the expense of relatively under resourced internal governance in the second, middle, level. In the third, bottom, level, local academic bodies operate. We uncovered several levels of challenges facing these stakeholders including governance challenges, institutional challenges, individual challenges, and political challenges. Despite these challenges, participants in our study highlighted significant opportunities within the MEHPT system and that MEHPT can be a peace building pillar for the community. To our knowledge, this is the first paper that provides an in-depth situational analysis of the MEHPT system in a conflict setting while engaging the voice of local key stakeholders. We found that local actors in MEHPT in non-government controlled northwest Syria have made efforts towards (re)building a new, hybrid and kinetic MEHPT system, through a bottom-up approach. Despite these efforts, the MEHPT system remains fragile and polarised, suffering from several levels of challenges with limited involvement of internal governance. Building on our findings, to improve this approach and build bridges of trust among stakeholders and the MEHPT community, further studies are needed to determine feasible approaches to increasing the role of internal governance structures in the MEHPT system through: 1-Formalisation of efforts through establishing a MEPHT technical coordination unit. 2-Further shifting of power from external supporting NGOs and funders to internal governance structures. 3- Working towards achieving sustainable long-term partnerships.

Arecoline and arecaidine lixiviation in areca nut blanching: Liquid chromatography‐ion trap‐time of flight hybrid mass spectrometry determination and kinetic modeling

The characteristic alkaloids of areca (arecoline, guvacoline, arecaidine, and guvacine) are the primary toxic compounds that cause multiple health problems. Hence, estimating variations in areca alkaloids levels during areca processing is important, and the results may contribute to the reduction of the potential toxicity of chewing areca nut. In this study, a robust and accurate liquid chromatography-ion trap-time of flight mass spectrometry method was established for the simultaneous determination of four areca-specific alkaloids and analysis of the two main toxic areca alkaloids (arecoline and arecaidine) during areca nut blanching. After the experimental data were fitted to an empirical model, high related coefficients indicated arecoline and arecaidine lixiviation during areca nut blanching followed second-order kinetics. Then the kinetics parameters obtained were applied to a model for the prediction of the amounts of arecoline and arecaidine lixiviated during areca nut blanching in wide ranges of temperature and time. Novelty impact statement A novel method was established for the simultaneous determination of four areca alkaloids. The leaching rates of arecoline and arecaidine during blanching followed second-order kinetics. The results provide a prediction model for arecoline and arecaidine during areca nut blanching.

Hybrid Kinetic Model of the Interaction Between the Dense Plasma Clouds and Magnetospheric Plasma on Large Time and Spatial Scales, and Comparison With MMS Observations

AbstractWe present a new simulation results of the cloud dynamics in the ambient magnetospheric plasma on the large time and spatial scales. It was assumed that these impulsive structures observed by the MMS spacecraft originally were created because of the reconnection at the magnetopause. Our new 3‐D hybrid kinetic modeling on the large time and spatial scales captures several of these processes: an excitation of the electromagnetic waves (whistler and shear‐Alfvén waves) and plasma instabilities (mirror and flute); a formation of shock waves, and collapsing diamagnetic cavity; particle acceleration. A strong overshoot in plasma density profile was observed in the modeling and MMS observation at the interface between the cloud and magnetospheric plasma. The cloud expansion into ambient magnetospheric plasma causes the flute waves connected with excitation of the Rayleigh‐Taylor instability observed at the overshoot in plasma density profile across the external magnetic field. The modeling demonstrates a formation of the whistler waves at the initial stage which propagate in the external magnetic field direction. At the later stage, a formation of shear‐Alfvén waves was observed.

SGD-based optimization in modeling combustion kinetics: Case studies in tuning mechanistic and hybrid kinetic models

Chemical kinetic modeling is an integral part of combustion simulation, and extensive efforts have been devoted to developing high-fidelity yet computationally affordable models. Despite these efforts, modeling combustion kinetics is still challenging due to the demand for expert knowledge and high dimensional optimization against experiments. Therefore, data-driven approaches that enable efficient discovery and calibration of kinetic models have received much attention in recent years, the core of which is the high-dimensional optimization based on big data. Evolutionary algorithms are usually adopted for optimizing chemical kinetic models, although they usually suffer from high computational costs and are limited to a small number of parameters. Meanwhile, gradient-based optimizations, especially the stochastic gradient descent (SGD) methods, have shown success in developing complex models by training large-scale deep learning models. Therefore, this work explores the applications of SGD-based optimizations in tuning mechanistic kinetic models and learning hybrid kinetic models. We first showed that SGD-based optimizations could substantially save computational cost compared to evolutionary algorithms when the number of kinetic parameters in mechanistic models reached about one hundred. We then demonstrated that the SGD-based optimization enabled us to use a neural network model to represent the pyrolysis of the Hybrid Chemistry and optimize the associated hundreds of weights in the neural network. These proof-of-concept studies showed that the SGD-based optimization is more efficient than evolutionary algorithms, is a promising approach for developing chemical kinetic models with high dimensional parameters, and is capable of developing hybrid mechanistic-machine learning kinetic models.

Importance of accurate consideration of the electron inertia in hybrid-kinetic simulations of collisionless plasma turbulence: The 2D limit

The dissipation mechanism of the magnetic energy in turbulent collisionless space and astrophysical plasmas is still not well understood. Its investigation requires efficient kinetic simulations of the energy transfer in collisionless plasma turbulence. In this respect, hybrid-kinetic simulations, in which ions are treated as particles and electrons as an inertial fluid, have begun to attract a significant interest recently. Hybrid-kinetic models describe both ion- and electron scale processes by ignoring electron kinetic effects so that they are computationally much less demanding compared to fully kinetic plasma models. Hybrid-kinetic codes solve either the Vlasov equation for the ions (Eulerian Vlasov-hybrid codes) or the equations of motion of the ions as macro-particles [Lagrangian particle-in-cell (PIC)-hybrid codes]. They consider the inertia of the electron fluid using different approximations. We check the validity of these approximations by employing our recently massively parallelized three-dimensional PIC-hybrid code Code Hybrid with Inertial Electron Fluid (CHIEF), which considers the electron inertia without any of the common approximations. In particular, we report the results of simulations of two-dimensional collisionless plasma turbulence. We conclude that the simulation results obtained using hybrid-kinetic codes, which use approximations to describe the electron inertia, need to be interpreted with caution. We also discuss the parallel scalability of CHIEF, to the best of our knowledge, the first PIC-hybrid code, which without approximations describes the inertial electron fluid.

Kinetics of the Direct DME Synthesis: State of the Art and Comprehensive Comparison of Semi-Mechanistic, Data-Based and Hybrid Modeling Approaches

Hybrid kinetic models represent a promising alternative to describe and evaluate the effect of multiple variables in the performance of complex chemical processes, since they combine system knowledge and extrapolability of the (semi-)mechanistic models in a wide range of reaction conditions with the adaptability and fast convergence of data-based approaches (e.g., artificial neural networks—ANNs). For the first time, a hybrid kinetic model for the direct DME synthesis was developed consisting of a reactor model, i.e., balance equations, and an ANN for the reaction kinetics. The accuracy, computational time, interpolation and extrapolation ability of the new hybrid model were compared to those of a lumped and a data-based model with the same validity range, using both simulations and experiments. The convergence of parameter estimation and simulations with the hybrid model is much faster than with the lumped model, and the predictions show a greater degree of accuracy within the models’ validity range. A satisfactory dimension and range extrapolation was reached when the extrapolated variable was included in the knowledge module of the model. This feature is particularly dependent on the network architecture and phenomena covered by the underlying model, and less on the experimental conditions evaluated during model development.

Application of (Bio-) Chemical Engineering Concepts and Rules in Bioinformatics. Review of a CCM-Based Modular and Hybrid Kinetic Model Used to Simulate and Optimize a Bioreactor with Genetically Modified Cells

This work briefly reviews the main concepts and principles used to solve difficult biochemical engineering, or bioengineering problems, by using extended structured cell kinetic models (including nano-scale state variables) linked in hybrid models to the biological reactor dynamic models (including macro-scale state variables). Exemplification is made for the case of the numerical methodology used by [Maria, 2021] to derive a structured hybrid modular kinetic model able to simulate the dynamics of a Fed-batch bioreactor (FBR), at both cell and bulk-phase species levels. The approached FBR includes a genetically modified E. coli culture used for the tryptophan (TRP) production. Eventually this complex hybrid dynamic model was used by [Maria and Renea, 2021] to derived the FBR optimal operating policy leading to the TRP production maximization.

Tryptophan Production Maximization in a Fed-Batch Bioreactor with Modified E. coli Cells, by Optimizing Its Operating Policy Based on an Extended Structured Cell Kinetic Model.

Hybrid kinetic models, linking structured cell metabolic processes to the dynamics of macroscopic variables of the bioreactor, are more and more used in engineering evaluations to derive more precise predictions of the process dynamics under variable operating conditions. Depending on the cell model complexity, such a math tool can be used to evaluate the metabolic fluxes in relation to the bioreactor operating conditions, thus suggesting ways to genetically modify the microorganism for certain purposes. Even if development of such an extended dynamic model requires more experimental and computational efforts, its use is advantageous. The approached probative example refers to a model simulating the dynamics of nanoscale variables from several pathways of the central carbon metabolism (CCM) of Escherichia coli cells, linked to the macroscopic state variables of a fed-batch bioreactor (FBR) used for the tryptophan (TRP) production. The used E. coli strain was modified to replace the PTS system for glucose (GLC) uptake with a more efficient one. The study presents multiple elements of novelty: (i) the experimentally validated modular model itself, and (ii) its efficiency in computationally deriving an optimal operation policy of the FBR.

A CCM-based modular and hybrid kinetic model to simulate the tryptophan synthesis in a fed-batch bioreactor using modified E. coli cells

This paper presents a novel methodology to develop complex structured bi-level (hybrid) kinetic models of some important cell bioprocesses. The approached case study refers to the tryptophan (TRP) synthesis in E. coli cells. The required experimental data were collected from a fed-batch bioreactor (FBR). The developed structured kinetic model includes several inter-connected reaction pathway (modules) able to simulate the kinetics of glycolysis, TRP-operon expression, ATP-recovery system, all belonging to the central carbon metabolism (CCM). Experiments were carried out by using an E. coli strain modified to replace the PTS-system with a more efficient one to uptake the glucose (GLC) from the environment. By linking the FBR macroscopic state variables with the nano-scale variables describing the cell metabolic processes of interest, the resulted structured hybrid dynamic model presents a large number of advantages, such as: allows further in-silico (model-based) more accurate engineering developments; it can be used for bioinformatics purposes.

Concerning the interaction of a transmitted interplanetary impulse with a plasmaspheric drainage plume: First results from 3-D hybrid kinetic modeling

We present a new hybrid kinetic model to simulate the response of plasmaspheric drainage plumes to impulsive interplanetary pressure pulses. Since particle distributions attending the interplanetary pulses and in the drainage plume are non-Maxwellian, wave-particle interactions play a crucial role in energy transport within and outside the plumes. Finite gyroradius effects become important in mass loading of the transmitted impulse with the drainage plume ions. A forward-reverse shock structure develops from the initial step-like transmitted shock. First results show that the impulse causes strong deformations in the global structure of the plume. The anisotropic ion velocity distribution functions at the impulse front and inside the plume help us determine energy transport via wave-particle interactions throughout the Earth’s inner magnetosphere.

Space-filter techniques for quasi-neutral hybrid-kinetic models

The space-filter approach has been proved as a fundamental tool in studying turbulence in neutral fluids, providing the ability to analyze scale-to-scale energy transfer in configuration space. It is well known that turbulence in plasma presents challenges different from neutral fluids, especially when the scale of interest includes kinetic effects. The space-filter approach is still largely unexplored for kinetic plasma. Here, we derive the space-filtered (or equivalently “coarse-grained”) equations in configuration space for a quasi-neutral hybrid-kinetic plasma model, in which ions are fully kinetic and electrons are a neutralizing fluid. Different models and closures for the electron fluid are considered, including finite electron-inertia effects and full electrons' pressure-tensor dynamics. Implications for the cascade of turbulent fluctuations in real space depending on different approximations are discussed.

Personalized cardiovascular intervention simulation system

BackgroundThis study proposes a series of geometry and physics modeling methods for personalized cardiovascular intervention procedures, which can be applied to a virtual endovascular simulator. MethodsBased on personalized clinical computed tomography angiography (CTA) data, mesh models of the cardiovascular system were constructed semi-automatically. By coupling 4D magnetic resonance imaging (MRI) sequences corresponding to a complete cardiac cycle with related physics models, a hybrid kinetic model of the cardiovascular system was built to drive kinematics and dynamics simulation. On that basis, the surgical procedures related to intervention instruments were simulated using specially-designed physics models. These models can be solved in real-time; therefore, the complex interactions between blood vessels and instruments can be well simulated. Additionally, X-ray imaging simulation algorithms and realistic rendering algorithms for virtual intervention scenes are also proposed. In particular, instrument tracking hardware with haptic feedback was developed to serve as the interaction interface of real instruments and the virtual intervention system. Finally, a personalized cardiovascular intervention simulation system was developed by integrating the techniques mentioned above. ResultsThis system supported instant modeling and simulation of personalized clinical data and significantly improved the visual and haptic immersions of vascular intervention simulation. ConclusionsIt can be used in teaching basic cardiology and effectively satisfying the demands of intervention training, personalized intervention planning, and rehearsing.

Gradient- and flux-driven global gyrokinetic simulations of ITG and TEM turbulence with an improved hybrid kinetic electron model

ORB5 is a global gyrokinetic code being developed by many scientists over the last 20 years. It allows performing so-called gradient-driven simulations, in which initial profiles such as density and temperature are specified and an adaptative source is used to relax the zonal component of the perturbed distribution function so that the total flux-surface-averaged distribution function does not deviate too much from the initial one, . Thus, f0 can be used as a control variate to reduce the sampling noise.Even though the gradient-driven model is useful due to its relatively low numerical cost (there is no need to perform simulations over transport time scales) it does not reflect the experimental reality where fluxes are prescribed by the actual heat sources. Furthermore, comparison between experimental and gradient-driven numerical predictions of the heat fluxes is a challenging task because of the profile stiffness: a small change, within experimental error bars, in the imposed temperature gradients leads to a large variation of the computed heat fluxes.To address the stiffness problem, the ORB5 code has been adapted to be able to run flux-driven simulations. In this model, fluxes are prescribed by a radially localized heat source and sink and the background profiles slowly evolve toward a quasi-steady state. As a first step toward complete flux-driven simulations, a mixed approach is used, in which the run is started in the gradient-driven mode providing estimates for the heat sources/sinks, which are then used for pursuing the simulation in flux-driven mode. This allows us to keep the numerical cost relatively low as a quasi-steady state is more quickly reached.In this work, we present the heat source implemented in ORB5 to perform the flux-driven simulations as well as the numerical technique used to ensure that no other moment is injected by the source up to machine precision. Furthermore, simulation results illustrating the mode switching between gradient- and flux-driven will be shown as well as preliminary results of TEM dominated cases done using an upgraded hybrid electron model.

Fed-batch ethanol fermentation at low temperature as a way to obtain highly concentrated alcoholic wines: Modeling and optimization

The effect of product inhibition on yeast hinders the production of wine with ethanol concentration above 80.0 g L−1 (∼10°GL) in the industrial ethanol production process commonly performed at 34 °C. Lowering the fermentation temperature is a way to produce wines with higher ethanol contents. In this work, batch fermentations were carried out at temperatures of 28, 30, 32, and 34 °C, with initial substrate concentration of 180.0 g L−1, using industrial yeast under conditions reproducing those found in industry. The Andrews-Levenspiel hybrid kinetic model, considering viable cells, showed an excellent fit to the experimental data. Kinetic parameters were determined for the different temperatures. The model was used to simulate fed-batch fermentations at different temperatures, with the same total substrate concentration, resulting in satisfactory descriptions of the process behaviors. A new optimization strategy to obtain the maximum possible ethanol production, based on the CEmax parameter of the Andrews-Levenspiel kinetic model, provided ethanol production of up to 134.7 g L-1 (17.1°GL) at 28 °C and 305.4 g L−1 substrate. A modification was made to the Andrews-Levenspiel kinetic model, relating the n parameter to the final ethanol concentration (CEf), in order to enable the model to describe the behavior of fed-batch fermentations performed with high substrate concentration and at temperatures from 28 to 34 °C.

Effects of multiscale phase-mixing and interior conductance in the lunar-like pickup ion plasma wake. First results from 3-D hybrid kinetic modeling

The study of multiscale pickup ion phase-mixing in the lunar plasma wake with a hybrid model is the main subject of our investigation in this paper. Photoionization and charge exchange of protons with the lunar exosphere are the ionization processes included in our model. The computational model includes the self-consistent dynamics of the light (H+ or H2+ and He+), and heavy (Na+) pickup ions. The electrons are considered as a fluid. The lunar interior is considered as a weakly conducting body. In this paper we considered for the first time the cumulative effect of heavy neutrals in the lunar exosphere (e.g., Al, Ar), an effect which was simulated with one species of Na+ but with a tenfold increase in total production rates. We find that various species produce various types of plasma tail in the lunar plasma wake. Specifically, Na+ and He+ pickup ions form a cycloid-like tail, whereas the H+ or H2+ pickup ions form a tail with a high density core and saw-like periodic structures in the flank region. The length of these structures varies from 1.5RM to 3.3RM depending on the value of gyroradius for H+ or H2+ pickup ions. The light pickup ions produce more symmetrical jump in the density and magnetic field at the Mach cone which is mainly controlled by the conductivity of the interior, an effect previously unappreciated. Although other pickup ion species had little effect on the nature of the interaction of the Moon with the solar wind, the global structure of the lunar tail in these simulations appeared quite different when the H2+ production rate was high.

Fully Kinetic versus Reduced-kinetic Modeling of Collisionless Plasma Turbulence

Abstract We report the results of a direct comparison between different kinetic models of collisionless plasma turbulence in two spatial dimensions. The models considered include a first-principles fully kinetic (FK) description, two widely used reduced models (gyrokinetic (GK) and hybrid-kinetic (HK) with fluid electrons), and a novel reduced gyrokinetic approach (KREHM). Two different ion beta ( ) regimes are considered: 0.1 and 0.5. For , good agreement between the GK and FK models is found at scales ranging from the ion to the electron gyroradius, thus providing firm evidence for a kinetic Alfvén cascade scenario. In the same range, the HK model produces shallower spectral slopes, presumably due to the lack of electron Landau damping. For , a detailed analysis of spectral ratios reveals a slight disagreement between the GK and FK descriptions at kinetic scales, even though kinetic Alfvén fluctuations likely still play a significant role. The discrepancy can be traced back to scales above the ion gyroradius, where the FK and HK results seem to suggest the presence of fast magnetosonic and ion Bernstein modes in both plasma beta regimes, but with a more notable deviation from GK in the low-beta case. The identified practical limits and strengths of reduced-kinetic approximations, compared here against the FK model on a case-by-case basis, may provide valuable insight into the main kinetic effects at play in turbulent collisionless plasmas, such as the solar wind.

Plasma turbulence at ion scales: a comparison between particle in cell and Eulerian hybrid-kinetic approaches

Kinetic-range turbulence in magnetized plasmas and, in particular, in the context of solar wind turbulence has been extensively investigated over the past decades via numerical simulations. Among others, one of the widely adopted reduced plasma models is the so-called hybrid-kinetic model, where the ions are fully kinetic and the electrons are treated as a neutralizing (inertial or massless) fluid. Within the same model, different numerical methods and/or approaches to turbulence development have been employed. In the present work, we present a comparison between two-dimensional hybrid-kinetic simulations of plasma turbulence obtained with two complementary approaches spanning approximately two decades in wavenumber – from the magnetohydrodynamics inertial range to scales well below the ion gyroradius – with a state-of-the-art accuracy. One approach employs hybrid particle-in-cell simulations of freely decaying Alfvénic turbulence, whereas the other consists of Eulerian hybrid Vlasov–Maxwell simulations of turbulence continuously driven with partially compressible large-scale fluctuations. Despite the completely different initialization and injection/drive at large scales, the same properties of turbulent fluctuations at $k_{\bot }\unicode[STIX]{x1D70C}_{i}\gtrsim 1$ are observed, where $k_{\bot }$ is the fluctuations’ wavenumber perpendicular to the background magnetic field and $\unicode[STIX]{x1D70C}_{i}$ is the ion Larmor radius. The system indeed self-consistently ‘reprocesses’ the turbulent fluctuations while they are cascading towards smaller and smaller scales, in a way which actually depends on the plasma beta parameter ($\unicode[STIX]{x1D6FD}$ is the ratio between the thermal and the magnetic pressures). Small-scale turbulence has been found to be mainly populated by kinetic Alfvén wave (KAW) fluctuations for $\unicode[STIX]{x1D6FD}\geqslant 1$, whereas KAW fluctuations are only sub-dominant for low-$\unicode[STIX]{x1D6FD}$.