This study focuses on the stochastic nonlinear Kodama (SNLK) equation influenced by multiplicative noise interpreted in the Stratonovich sense. The equation is significant for modeling complex physical systems in fluid dynamics, plasma physics, and nonlinear optics. We employ both the Kumar–Malik method and the polynomial expansion technique to construct exact soliton solutions in various functional forms, including Jacobi elliptic, hyperbolic, exponential, and trigonometric types. The combination of these two analytical methods provides a novel framework for investigating nonlinear wave structures in stochastic environments. To complement the analytical results, numerical simulations are conducted using Maple (or Mathematica) software, which confirm the accuracy and dynamic consistency of the solutions. These simulations also offer deeper insight into the behavior and evolution of the solutions under random influences. Our results demonstrate the effectiveness and adaptability of the applied methods, making them suitable for a wider class of nonlinear partial differential equations. This work contributes to a better theoretical and computational understanding of stochastic wave phenomena and lays the groundwork for further exploration in related physical contexts.
Precise droplet manipulation is critical in material synthesis, biochemical detection, and tissue engineering. However, the droplet velocity and volume manipulated by magnetic techniques are restricted owing to the low magnetic force exerted on magnetic particles and beads. Furthermore, magnetic particles are prone to contaminate droplets owing to residues and corrosion. To address these issues, this paper proposes a hydrophilic hard-magnetic soft robot (HMSR) with strong magnetic controllability and chemical stability for precise droplet manipulation. A porous HMSR was synthesized by incorporating NdFeB particles and sacrificial sugar particles into an Ecoflex elastomer. Oxygen plasma treatment was applied to make the HMSR become hydrophilic and thus enhance the driving force exerted on droplets. Three forms of droplet manipulation were demonstrated: droplet transport, droplet splitting, and robot–magnet detachment. Theoretical analysis and experimental results revealed that the critical HMSR speed requisite for droplet transport and splitting was inversely proportional to the droplet volume. Notably, a 50 μl droplet was transported in a 20 mT magnetic field at a maximum velocity of 200 mm/s. The maximum droplet volume that the HMSR could transport reached 900 μl. Benefiting from its chemical stability, HMSR successfully manipulated chemical reactions of acidic and alkaline droplets. Additionally, the HMSR achieved targeted removal of microparticles through droplet adhesion to them. This HMSR with precise droplet manipulation capability holds broad prospects for applications in biochemical detection, material synthesis, and surgical robotics.
von Willebrand factor (vWF) is a crucial plasma glycoprotein that facilitates thrombus formation by promoting platelet recruitment in response to shear-induced conformational changes during blood flow, particularly under high-shear stress conditions. Despite its recognized thrombogenic role, the behavior of vWF chains in complex flow environments has not been fully characterized. This study utilized detailed mesoscopic simulations based on dissipative particle dynamics to investigate interactions among blood cells, blood plasma, and functionalized vessel surfaces. Significant transitions of vWF chains from a globule state to an extended conformation were revealed with increasing shear rates, elucidating their critical role in platelet recruitment and adhesion dynamics. The extent of vWF chain stretching was quantified via mean square end-to-end distance analysis, confirming its sensitivity to applied shear rates. Mechanisms of platelet adhesion on fibrinogen- and vWF-coated surfaces were examined, with fibrinogen exhibiting effectively platelet binding at low shear rates (less than 600s) while vWF displayed a strong affinity for platelets at high-shear rates exceeding 1000s. A systematic analysis of the influence of vWF chain length and density on platelet adhesion were conducted, resulting in the development of a novel phase diagram categorizing three distinct adhesion regimes. The distinctive role of vWF chains in vaso-occlusive crises at elevated shear rates was further investigated, highlighting the importance of varying blood flow velocities in both physiological and pathological contexts. Collectively, these results provide valuable insight into vWF-mediated platelet adhesion under various shear flow conditions, thereby enhancing the understanding of the early stages of thrombus formation.
Abstract The Konopelchenko–Dubrovsky–Kaup–Kupershmidt system has significant implications in various fields, including fluid mechanics, ocean dynamics, and plasma physics. This system includes various widely recognized nonlinear evolution equations as special cases. In this study, we present a systematic approach to identifying novel wave solutions to the system, examining various combinations of interactions between lumps, stripes, double stripes, and periodic waves. By strategically selecting the arbitrary free parameters, we incorporate various 2D and 3D profiles to clearly demonstrate the dynamic behaviors of the mixed localized wave structures. These graphical representations indicate that some of the identified solutions exhibit periodic wave propagation along a straight line at specific angles to the spatial axes, maintaining constant wavelengths, amplitudes, and velocities. The solutions proposed in this study provide valuable insights into the mechanisms of wave propagation across diverse physical domains. Furthermore, the approach outlined herein is versatile and can be applied to various nonlinear differential equations in mathematical physics.
The estimation of the poloidal velocity of the turbulence and the poloidal mean flow velocity are important quantities for the study of sheared flows on turbulence and transport. The estimation depends on the underlying model of the turbulence. Beside the propagation time of the turbulence, its decay with the fading time must be considered. For the description of the propagation, the elliptical approach (EA) is applied, which takes into account the propagation and fading time of the turbulence. The model has been applied successfully in experimental fluid dynamics and is confirmed by direct numerical simulations, also. In this paper, the EA is applied in the analysis of density fluctuations, measured by poloidal correlation reflectometry at two different fusion devices, TEXTOR and W7-X. For the latter, it is demonstrated that the EA is necessary for a correct description of the turbulence propagation. In addition, the velocity modulations are investigated, which in principle can be either generated by an oscillation of the propagation time of density fluctuations and/or an oscillation of the fading of the turbulence. An example for low frequency velocity oscillations in W7-X will be given in the paper, showing a relation between turbulence properties and small oscillations on the measured diamagnetic plasma energy.
The influence of control parameters was studied on silicon (Si) nanoparticle synthesis using tandem modulated induction thermal plasmas (Tandem-MITP) with time-controlled feeding of feedstock (TCFF) method to optimize the modulation conditions on the basis of machine learning technique. This novel method, developed by our group, creates a time-varying high-temperature thermofluid field that facilitates efficient nanoparticle synthesis, with numerous control parameters influencing the process. To optimize the synthesis conditions, a comprehensive numerical thermofluid model was developed to simulate thermal plasma fields, feedstock dynamics, and nanoparticle formation and transport. Using this model, we applied a machine learning-based sequential approximate optimization (SAO) method with a radial basis function (RBF) network to identify optimal modulation conditions for maximizing nanoparticle production with smaller particle sizes. The results demonstrate that higher modulation amplitudes induce greater fluctuations in the plasma temperature and gas flow fields, leading to an increased quantity of smaller Si nanoparticles. Results showed that larger modulation condition provides larger variation in temperature-gas flow field, which results in larger quantities of smaller nanoparticles.
The 13.56 MHz radio frequency ion source test bed (RFISTB) has been designed and constructed to evaluate the instruments used in fusion and plasma physics experiments at the Physics and Accelerator Research School in Tehran, Iran. This test bed enables the integration of advanced diagnostic tools for a comprehensive analysis and characterization of ion beam dynamics utilized in energy analyzers and neutral beam injectors. In this article, both theoretical and experimental details of the RFISTB system are presented. Subsequently, the operational capabilities of radio frequency (RF) ion sources have been examined. For this purpose, the effects of various system components, such as applied RF power, probe voltage and focusing voltage, are analyzed and characterized through experiment. To our knowledge, the Thonemann ion source type has only been tested in direct mode and up to 5 keV. Higher voltages cannot be attained due to arc discharge. In this study, we have investigated the pulse performance of the system in addition to the direct mode, reaching up to 12 keV. In addition, since the impedance varies with fluctuations in discharge pressure and input power, accurately calculating the equivalent impedance of plasma during discharge is challenging. To optimize the transfer of maximum output power from the RF power source to the antenna of the ion source an impedance-matching circuit has been designed.
Determination of the absolute neutron rate production in any fusion device and in particular for ITER and future power plants is essential for their operation and for the optimization of the fusion power. A common calibration approach is to use well characterized neutron sources placed inside the vacuum vessel combined with Monte Carlo simulations. This method is fraught with several difficulties both from an engineering and data modeling and interpretation point of view. This is particularly true for future fusion power plants. This work demonstrates an alternative approach to the absolute calibration of the neutron rate based on activation foil measurements combined with forward modeling of a well characterized plasma discharge and fusion device. This method has been applied to MAST Upgrade and the good agreement found between measured and modeled foil activity support this approach. The results presented suffer from some limitations but suggestions are given on how to resolve them.
In this research work, a new algorithm is proposed, which involves coupling a new integral transform, namely, the Elzaki transform, with a well‐known alternative variational iteration method called the alternative variational iteration Elzaki transform method, to solve both linear and nonlinear time‐fractional regularized long wave equations. Six examples have been examined of regularized long‐wave equations, widely used in various applied sciences and engineering fields, including space‐charge waves, ion‐acoustic swells, ocean engineering, tsunami modeling, and plasma. The existence, uniqueness, and stability analysis of the solution demonstrated the efficiency and authenticity of the method, showing that the solutions derived from the alternative variational iteration Elzaki transform method are both convergent and unique. This method generates reliable solutions to a wider class of nonlinear partial differential equations in a simple manner, without the need for discretization, linearization, or computation of Adomian polynomials. The obtained results were validated by comparing them with exact results and results from other existing literature using tables of comparison, 3D plots, and convergence analysis.
Abstract This study presents experimental results from the PACO plasma focus device. The device, powered by a 4 µ F capacitor bank charged to 31 kV (2 kJ), generates currents up to 250 kA in a deuterium-filled chamber (1.0–2.3 mbar) achieving a typical neutron yield of 3 × 10 9 per shot. Diagnostics included a Rogowski coil for current derivative measurements, a fast resistive voltage divider for anode voltage, and a NE102A scintillator-photomultiplier system to detect neutron and hard x-ray emissions. Key findings focus on the plasma current sheet dynamics, characterized through inductance derivatives and pinch voltage. Analysis revealed the moment where the current sheet travel change from axial to radial, when the beam–target mechanism is possible and when the fusion begins enabling a defined moment where start the fusion pinch zone .
Raffaele Sparago, Francisco Javier Artola, Matthias Hoelzl
An adequate modelling of the electromagnetic interaction of the plasma with the surrounding conductors is paramount for the correct reproduction of 3D plasma dynamics. Simulations of the latter provide in turn useful predictions regarding the plasma evolution, the related MHD modes leading to disruptions and the electromagnetic forces acting on the vacuum vessel's components when said disruptions occur. The latest modelling efforts with the 3D FEM non-linear JOREK code have been directed towards the eddy current coupling of a reduced magnetohydrodynamic (MHD) plasma model with thin and volumetric wall codes (STARWALL and CARIDDI). In this contribution, we present an eddy current coupling between the full MHD model of JOREK and the STARWALL code; this new coupling scheme describes the full three-dimensional interactions of the plasma with the vacuum region and external conductors, modeled by natural boundary conditions linking the magnetic vector potential $\mathbf{A}$ to the magnetic field $\mathbf{B}$. The consistency of the new coupling scheme is validated via benchmarks for axisymmetric Vertical Displacement Events and multi-harmonics simulations of MHD modes.
The interaction of plasma with liquids has led to various established industrial implementations as well as promising applications, including high-voltage switching, chemical analysis, nanomaterial synthesis, and plasma medicine. Along with these numerous accomplishments, the physics of plasma in liquid or in contact with a liquid surface has emerged as a bipartite research field, for which we introduce here the term “plasma physics of liquids.” Despite the intensive research investments during the recent decennia, this field is plagued by some controversies and gaps in knowledge, which might restrict further progress. The main difficulties in understanding revolve around the basic mechanisms of plasma initiation in the liquid phase and the electrical interactions at a plasma-liquid interface, which require an interdisciplinary approach. This review aims to provide the wide applied physics community with a general overview of the field, as well as the opportunities for interdisciplinary research on topics, such as nanobubbles and the floating water bridge, and involving the research domains of amorphous semiconductors, solid state physics, thermodynamics, material science, analytical chemistry, electrochemistry, and molecular dynamics simulations. In addition, we provoke awareness of experts in the field on yet underappreciated question marks. Accordingly, a strategy for future experimental and simulation work is proposed.
Manuel Formela, Niclas Hamann, Gudrid Moortgat-Pick
et al.
In recent years, the concept of high-gradient, symmetric focusing using active plasma lenses has regained notable attention owing to its potential benefits in terms of compactness and beam dynamics when juxtaposed with traditional focusing elements. An enticing application lies in the optical matching of extensively divergent positrons originating from the undulator-based ILC positron source, thereby enhancing the positron yield in subsequent accelerating structures. Through a collaboration between the University of Hamburg and DESY Hamburg, a scaled-down prototype for this purpose has been conceptualized and fabricated. In this presentation, we provide an overview of the ongoing progress in the development of this prototype. Furthermore, first insights into the development of a particle tracking code especially designed for plasma lenses with implemented Bayes optimization, are given.
An important problem in nuclear fusion plasmas is the prediction and control of turbulence which drives the cross-field transport, thus leading to energy loss from the system and deteriorating confinement. Turbulence, being a highly nonlinear and multiscale process, is challenging to theoretically describe and computationally model. Most advanced computational models fall into one of the two categories: fluid or gyro-kinetic. They both come at a high computational cost and cannot be applied for routine simulation of plasma discharge evolution and control. Development of reduced models based on (physics informed) artificial neural networks could potentially fulfil the need for affordable simulations of plasma turbulence. However, the training requires an extensive data base and the obtained models lack extrapolation capability to scenarios not originally encountered during training. This leads to reduced models of limited validity which may not prove adequate for predicting scenarios in future machines. In contrast, we explore a data-driven model discovery approach based on sparse regression to infer governing nonlinear partial differential equations directly from the data. Our input data are generated by simulations of drift-wave turbulence according to the Hasegawa–Wakatani and modified Hasegawa–Wakatani models. Balancing model accuracy and complexity enables the reconstruction of the systems of partial differential equations accurately describing the dynamics simulated in the input data sets. Sparse regression is not data hungry and can be extrapolated to unexplored parameter ranges. We explore and demonstrate the potential of this approach for fusion plasma turbulence modelling. The findings show that the methodology is promising for the development of reduced and computationally efficient turbulence models as well as for existing model cross-validation.
Abstract Due to the growing interest in studying the compression and disruption of the plasma filament in magnetic fusion devices and Z-pinches, this work may be important for new developments in the field of controlled thermonuclear fusion. Recently, on a coaxial plasma accelerator, we managed to obtain the relatively long-lived (∼300 μs) plasma filaments with its self-magnetic field. This was achieved after modification of the experimental setup by using high-capacitive and low-inductive energy storage capacitor banks, as well as electrical cables with low reactive impedance. Furthermore, we were able to avoid the reverse reflection of the plasma flux from the end of the plasma accelerator by installing a special plasma-absorbing target. Thus, these constructive changes of the experimental setup allowed us to investigate the physical properties of the plasma filament by using the comprehensive diagnostics including Rogowski coil, magnetic probes, and Faraday cup. As a result, such important plasma parameters as density of ions and temperature of electrons in plasma flux, time dependent plasma filament’s azimuthal magnetic field were measured in discharge gap and at a distance of 23.5 cm from the tip of the cathode. In addition, the current oscillograms and I–V characteristics of the plasma accelerator were obtained. In the experiments, we also observed the charge separation during the acceleration of plasma flow via oscillograms of electron and ion beam currents.
The research subject is the kinetic and irreversible thermodynamic behavior of gaseous plasma (GP) flow limited by a moving rigid flat plate (RFP). The effects of an unsteady nonlinear applied electric field (NLAEF) were examined on the GP. To explore gas dynamics with the electron velocity distribution function (EVDF), researchers have concentrated on the Bhatnagar-Gross-Krook (BGK)–model of the kinetic Boltzmann equation (BE). An analytical solution was found using the moment method (MM), traveling wave, and shooting method. As illustrated, mean velocity, shear stress, and electromagnetic fields all founded play essential roles. An interesting comparison between the non-equilibrium EVDF and the equilibrium EVDF is made carefully with 3-Dimensional graphics in various time values. We found that the system goes to an equilibrium state (ES) with time compatible with Le Chatelier's principles. The relations between the various macroscopic variables of the GP are studied. The irreversible non-equilibrium thermodynamics (NT) properties of the system are presented. Entropy and entropy generation are derived, and their behavior is investigated. The essence of entropy, the degree of internal chaos of a system, is gradually described with the advent of statistical physics and information theory. Cybernetics, probability theory, life science, and astrophysics are just a few of the domains where it is functional. According to our findings, NLAEF has a strong effect on GP. Compared to the effect of the nonlinear applied magnetic field (NLAMF), it causes it to vary and disturb substantially. To save the ES for a GP, we should employ NLAMF rather than NLAEF in the GP management procedure. The importance of this research stems from its wide applications in domains such as physics, electrical engineering, micro-electro-mechanical systems (MEMS), and nano-electro-mechanical systems (NEMS) technologies as industrial and commercial sectors.