Moment Fluctuations Research Articles

Experimental and numerical investigation of hydrodynamic performance of a new surface piercing propeller family

Today, passenger and racing boats increasingly utilize surface-piercing propellers. This type of propeller operates in two distinct phases of water and air simultaneously. As a result, this propeller type has additional characteristics that must be investigated separately from conventional propellers. A new family of surface piercing propellers was investigated using experimental and numerical methods. The family consisted of five propeller models with varying geometric features operating at an immersion ratio of 0.7. Experiments were conducted in the Sharif University of Technology's hydrodynamic group's cavitation tunnel. Additionally, using Star-CCM + software, the numerical simulation was performed using the RANS method for implicit unsteady flow with a sliding mesh technique in free surface conditions. The results indicate that by increasing the pitch ratio from 1.074 to 1.61, the critical advance coefficient value, which is in the range of 0.4–0.6, moves to 0.8–1 interval. Also, the efficiency enhances by 14% while raising the pitch ratio. The amplitude of force and moment fluctuation components increases at higher than 0.5 values of the advance coefficient by increasing pitch ratios. The expanded area grows proportional to an increased number of blades and as a result, the thrust and torque coefficients increase, but the efficiency does not improve significantly. Furthermore, the fluctuation amplitude of forces and moments applied to the key blade increases up to the critical advance coefficient in all models and then decreases for above critical values.

Solvation of small gold clusters in supercritical water

Solvation in supercritical water features fascinating properties such as the selective dissolution or precipitation of non-polar versus polar species. This is known since long to open up astonishing possibilities in organic synthesis, catalysis, or engineering. Less known is the role that supercritical aqueous solutions play close to hydrothermal vents in the deep sea and in ore deposit formation in Earth’s crust. Within this realm, we explore here the solvation of small uncharged gold species, namely the gold dimer and tetramer, in supercritical water in terms of structural and electronic properties using ab initio molecular dynamics simulations. Our simulations reveal that a highly anisotropic first solvation shell is formed around these gold clusters which consists of less than two water molecules on average. Importantly, we find very significant charge transfer and polarization effects between these water molecules and the neutral gold particles, which cannot be captured when using non-polarizable force fields. These electronic many-body effects lead not only to enormous dipole moment fluctuations of the gold clusters themselves, but also to an unexpectedly strong increase of the average effective dipole moments in their first solvation shell. Thus, supercritical solutions of gold particles in water turn out to be surprisingly complex.

Longitudinal fluctuations of Co spin moments and their impact on the Curie temperature of the Heusler alloy Co2FeSi

The magnetism of the full Heusler alloy Co2FeSi with its high magnetic ordering temperature is studied on a first-principles basis employing the disordered local moment approximation, the magnetic force theorem and single-site spin fluctuation theory as formulated recently in the framework of the Local Spin Density Approximation. We find that the magnetic moments of Fe and Co in Co2FeSi exhibit a quite distinctive behavior at high temperatures. The Fe moments are well localized and keep their magnitude unchanged with temperature, whereas the Co moments are itinerant and show a temperature dependence. We find that the effects of magnetic disorder strongly renormalize the Fe-Co inter-atomic exchange interactions. Our results suggest a deficiency of the classical Heisenberg model with rigid localized atomic spin moments for the description of magnetism in Co2FeSi. An accurate estimation of the Curie temperature is obtained by taking into the account the thermal longitudinal fluctuations the Co moments.

Determination of the effective anisotropy of magnetite/maghemite nanoparticles from Mössbauer effect spectra

The stoichiometry and the effective anisotropy constant (K eff ) of several samples of iron-oxide nanoparticles with sizes between 12 and 51 nm, showing spheroidal and cubic shapes, were studied by means of Mössbauer spectroscopy at room temperature (RT). Mössbauer spectra were analyzed and fitted considering two magnetically split subspectra due to and ions in tetrahedral and octahedral sites of a non-stoichiometric magnetite, respectively. In order to take into account the collective fluctuations of the NPs magnetic moments, the measured Mössbauer spectra were fitted including a distribution of the hyperfine interactions associated with the NPs volume (V) distribution. To determine the K eff value, a direct comparison between the size distribution obtained from structural characterization techniques and the product obtained from Mössbauer spectra fitting was made. In this regard, the K eff value was determined as the one that maximizes the coincidence between the mean NPs sizes obtained by both methods. Finally, an overall surface anisotropy constant K s value was obtained by means of a linear relation between the mean NP size, the experimentally determined K eff and a weighted arithmetic mean magnetic anisotropy related with the bulk magnetite and maghemite anisotropy constants at RT. An evident relation between the values through the parameter and the magnetite/maghemite fraction in each sample was also observed.

Exploring dielectric spectra of polymer through molecular dynamics simulations

ABSTRACT In this work, poly(N-isopropylacrylamide) (PNIPAM) was used as a research object to explore the feasibility of molecular dynamics (MD) simulations to study the dielectric properties of polymers. A comparison of the static dielectric constants for two different calculation schemes, the applied electric field method and the dipole moment fluctuation method, has been conducted. The dielectric properties of PNIPAM aqueous solutions with different concentrations were studied as a function of temperature. The static dielectric constants derived from dipole moment fluctuation method at different temperatures can accurately describe the phase transition process. The concentration does not affect the lower critical solution temperature, but significantly affects the relaxation process of the system. According to the frequency-dependent dielectric constants, two relaxation processes are observed, namely, the dielectric relaxation process in the region of frequency less than 30 terahertz (THz) determined by the synergistic interaction of PNIPAM and water molecules, and that in the region of frequency higher than 30 THz mainly determined by water molecules beyond the solvation shell of the polymer. The calculation results suggest that the dielectric behaviour is concentration and temperature independent, similar to Debye behaviour of bulk water. This method of calculating dielectric properties using MD simulations can be used in detecting the dynamic processes of soft condensed matter and in aiding the design of materials with excellent dielectric properties.

Giant diamagnetism of a quantum charged particle after inversion of the magnetic field

We consider a quantum charged particle moving in the $xy$ plane under the action of a uniform perpendicular time-dependent magnetic field, in the presence of a parabolic binding potential. The time-dependent probability distribution of the magnetic moment is calculated analytically and numerically in the case of initial thermodynamic equilibrium state. In the high-temperature regime, the initial distribution is almost symmetric, resulting in a tiny mean diamagnetism. However, if the magnetic field eventually changes its sign, the fragile balance between the diamagnetic and paramagnetic ``wings'' of the probability distribution becomes broken, resulting in a giant mean diamagnetic moment, exceeding the initial one by several orders of magnitude. The final mean value of the magnetic moment is inversely proportional to the strength of the binding potential, and it does not depend on the Planck constant in the high-temperature regime. Strong fluctuations of the magnetic moment (described in terms of the variance) exist in all temperature regimes.

Interaction of the new inhibitor paxlovid (PF-07321332) and ivermectin with the monomer of the main protease SARS-CoV-2: A volumetric study based on molecular dynamics, elastic networks, classical thermodynamics and SPT

The COVID-19 pandemic has accelerated the study of drugs, most notably ivermectin and more recently Paxlovid (PF-07321332) which is in phase III clinical trials with experimental data showing covalent binding to the viral protease Mpro. Theoretical developments of catalytic site-directed docking support thermodynamically feasible non-covalent binding to Mpro. Here we show that Paxlovid binds non-covalently at regions other than the catalytic sites with energies stronger than reported and at the same binding site as the ivermectin B1a homologue, all through theoretical methodologies, including blind docking. We volumetrically characterize the non-covalent interaction of the ivermectin homologues (avermectins B1a and B1b) and Paxlovid with the mMpro monomer, through molecular dynamics and scaled particle theory (SPT). Using the fluctuation-dissipation theorem (FDT), we estimated the electric dipole moment fluctuations at the surface of each of complex involved in this study, with similar trends to that observed in the interaction volume. Using fluctuations of the intrinsic volume and the number of flexible fragments of proteins using anisotropic and Gaussian elastic networks (ANM+GNM) suggests the complexes with ivermectin are more dynamic and flexible than the unbound monomer. In contrast, the binding of Paxlovid to mMpro shows that the mMpro-PF complex is the least structurally dynamic of all the species measured in this investigation. The results support a differential molecular mechanism of the ivermectin and PF homologues in the mMpro monomer. Finally, the results showed that Paxlovid despite beingbound in different sites through covalent or non-covalent forms behaves similarly in terms of its structural flexibility and volumetric behaviour.

Comparative Additional Factor for Diffraction Loss On (TEM01) Mode from That of (TEM00) Mode

Comparative Additional Factor for Diffraction Loss On (TEM01) Mode from That of (TEM00) Mode

Simulation of thermodynamic properties of magnetic transition metals from an efficient tight-binding model: The case of cobalt and beyond

Atomic scale simulations at finite temperature are an ideal approach to study the thermodynamic properties of magnetic transition metals. However, the development of interatomic potentials explicitly taking into account magnetic variables is a delicate task. In this context, we present a tight-binding model for magnetic transition metals in the Stoner approximation. This potential is integrated into a Monte Carlo structural relaxations code where trials of atomic displacements as well as fluctuations of local magnetic moments are performed to determine the thermodynamic equilibrium state of the considered systems. As an example, the Curie temperature of cobalt is investigated while showing the important role of atomic relaxations. Furthermore, our model is generalized to other transition metals highlighting a local magnetic moment distribution that varies with the gradual filling of the d states. Consequently, the successful validation of the potential for different magnetic configurations indicates its great transferability makes it a good choice for atomistic simulations sampling a large configuration space.

Direct observation of a dynamical glass transition in a nanomagnetic artificial Hopfield network

Spin glasses, generally defined as disordered systems with randomized competing interactions, are a widely investigated complex system. Theoretical models describing spin glasses are broadly used in other complex systems, such as those describing brain function, error-correcting codes, or stock-market dynamics. This wide interest in spin glasses provides strong motivation to generate an artificial spin glass within the framework of artificial spin ice systems. Here, we present the experimental realization of an artificial spin glass consisting of dipolar coupled single-domain Ising-type nanomagnets arranged onto an interaction network that replicates the aspects of a Hopfield neural network. Using cryogenic x-ray photoemission electron microscopy (XPEEM), we performed temperature-dependent imaging of thermally driven moment fluctuations within these networks and observed characteristic features of a two-dimensional Ising spin glass. Specifically, the temperature dependence of the spin glass correlation function follows a power law trend predicted from theoretical models on two-dimensional spin glasses. Furthermore, we observe clear signatures of the hard to observe rugged spin glass free energy in the form of sub-aging, out of equilibrium autocorrelations and a transition from stable to unstable dynamics.

On the interplay between hillslope and drainage network flow dynamics in the catchment travel time distribution

AbstractTravel time is a robust measure of water transport dynamics in catchments. At a given control section along a drainage network, travel time distribution results from an interplay between two main processes: (i) the transport through the hillslopes and (ii) transport through the drainage network. The main scope of this work is to quantify this interplay, specifically we aim to identify the relative impact of hillslopes and channels on the travel time at the catchment scale. A theoretical framework is developed following a bottom‐up modelling approach that combines a Boussinesq model for water flow and water travel time in hillslopes, with a geomorphological model for water transport in drainage network. Simple semi‐analytical solutions are derived for the first two moments of the travel time distribution within a flow section. We provide some relevant examples based on synthetic rainfall data, exploring the relative impacts of hillslope and channel properties. As expected, the dynamics of the hillslopes control the travel time distribution at the catchment scale. The drainage network typically introduces a lag in the average travel time exiting the hillslopes and reduces the temporal fluctuations of the mean travel time and its variance. Our theoretical model provides meaningful insights on the investigation of the dominant dynamics taking place in catchments: results suggest that hillslopes and their features are the main driver of travel time in catchments. The temporal fluctuations of the travel time moments show a non‐linear dependence with the recharge time‐series and need to be considered as time‐variant. Variability of water ages collected in a single water sample can be very large, the latter feature may have a significant effect on the water quality and on the tracer data analysis, largely governed by the contact times between water and catchment material.

Effect of base blowing by a large-scale fluidic oscillator on the bistable wake behind a flat-back Ahmed body

The dynamics of the wake behind a flat-back Ahmed body are modified using a large-scale fluidic oscillator, aiming at drag reduction and the reflectional symmetry breaking (RSB) mode suppression. In the present experiment, the sweeping jet (SWJ) actuator is integrated into the base of the bluff body such that its nozzle width corresponds to about 2/3 of the bluff body base width. The jet is sweeping in the horizontal plane, which coincides with the plane of the wake flow state switching due to the RSB mode. The impact of the SWJ actuator is evaluated for three different locations along the base's height, and for a range of blowing coefficients. The base suction coefficient is recorded from four pressure measurements at the base, while the drag coefficient is obtained from direct force and moment measurements. Particle image velocimetry of the near wake reveals the modifications of the mean flow, which elucidate on the changes in the base suction and drag coefficients. Both drag reduction and RSB mode suppression are achieved, however, not for the same blowing coefficient. The symmetrized wake yields a near Gaussian distribution of the base pressure gradients around zero in both gy and gz directions. This result is corroborated by the joint probability distributions of pitching and yawing moment fluctuations from force balance measurements.

Deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm

The ferromagnetic resonance (FMR) spectra of dilute random assemblies of magnetite nanoparticles with cubic magnetic anisotropy and various aspect ratios are calculated using the stochastic Landau–Lifshitz equation at a finite temperature, T = 300 K, taking into account the thermal fluctuations of the particle magnetic moments. Particles of non-spherical shape in the first approximation are described as elongated spheroids with a given semiaxes ratio a/b, where a and b are the long and transverse semiaxes of a spheroid, respectively. A representative database of FMR spectra is created for assemblies of randomly oriented spheroidal magnetite nanoparticles with various transverse diameters D = 5–25 nm, moderate aspect ratios a/b = 1.0–1.8, and magnetic damping constants κ = 0.1, 0.2. The basic FMR spectra of assemblies with D = 25 nm at different aspect ratios can be considered as representatives of assemblies of single-domain magnetite nanoparticles with transverse diameters D > 25 nm. The database is calculated at exciting frequency f = 4.9 GHz (S-band) to clarify the details of the FMR spectrum that depend on the particle magnetic anisotropy nature. The data obtained make it possible to analyze arbitrary combined FMR spectra constructed as weighted linear combinations of FMR spectra of the base assemblies. In addition, using a genetic algorithm, the corresponding inverse problem is solved. The latter consists in determining the volume fractions of the base assemblies in some arbitrary nanoparticle assembly, which is represented by its FMR spectrum.

Sensitivity Optimisation of a Main Marine Diesel Engine Electronic Speed Governor

Electronic speed governors have become widespread on marine diesel engines. In comparison with hydromechanical ones, they have an additional setting parameter – input signal sensitivity. This parameter allows changing the response of governors to high-frequency disturbances. In camshaft diesel engines, such disturbances are generated when the cams run over fuels pump push rods, while in ME (MAN Energy Solutions) or RT-flex (Wärtsilä) engines they result from the use of inductive sensors with a serrated tape on the diesel shaft for speed measurement. If the engine is used as a main engine on vessels, the governor’s sensitivity additionally allows governors to vary the response to propeller shaft resistance moment fluctuations in sea waves conditions. In practice the value of sensitivity of electronic speed governors of main marine engines is selected intuitively. As a result, the adjustment of governors doesn’t provide satisfactory stability of speed modes at the change of sea conditions. The study aims to develop a methodology for adjusting the sensitivity of main engines electronic speed governors with considering the stochasticity of the load on the diesel engine in sea waves state. The study was carried out using the systems of automatic speed control model, which is based on the assumption of relatively small deviations of diesel engine shaft rotation speed and load parameters at sea waves conditions. Considering the character and magnitude of change of load on diesel engine at sea waves conditions depend on many variables of external conditions (waves levels, course of a vessel in relation to wind-wave conditions, wind gusts, vessel’s loading condition, given speed of a vessel), any set value of sensitivity of electronic speed governors appears to be optimum only for a particular case of vessel movement in sea waves state. The scientific novelty is defined by the fact that recommendations on the choice of governor sensitivity are determined with considering stochasticity of propeller shaft resistance moment fluctuations at sea waves conditions, that increased accuracy, and validity of recommendations. The practical significance of the research consist in the increase of stability of speed modes of the main engine with electronic speed governor at various sea waves conditions

Testing the superposition model in small CORSIKA shower simulations

The idea of superposition in the high-energy interactions of cosmic ray nuclei and the development of extensive air showers initiated by them has been known for more than half a century. It has been thoroughly and successfully tested in a number of simulations for primary energies around 1015 and above. In this work, we will investigate its applicability to lower energies. At the lowest energies, when the shower contains on average about one charged particle (or even less), deviations from the superposition model can be seen in the simulation results. Fluctuations of higher moments of the main shower parameters are systematically broader than expected. Further studies to confirm superposition in particular in the shower longitudinal profile are in progress. A correct description of the longitudinal development of the small shower, a precise description of its fluctuations on the observational level with a correct implementation of the superposition principle will enable to construct a simple and fast phenomenological algorithm generating small showers indispensable for the interpretation of measurements made using a small local shower array and determination of the flux of single, incoherent, secondary cosmic ray particles.

Monitoring electron spin fluctuations with paramagnetic relaxation enhancement

The magnetic interactions between the spin of an unpaired electron and the surrounding nuclear spins can be exploited to gain structural information, to reduce nuclear relaxation times as well as to create nuclear hyperpolarization via dynamic nuclear polarization (DNP). A central aspect that determines how these interactions manifest from the point of view of NMR is the timescale of the fluctuations of the magnetic moment of the electron spins. These fluctuations, however, are elusive, particularly when electron relaxation times are short or interactions among electronic spins are strong. Here we map the fluctuations by analyzing the ratio between longitudinal and transverse nuclear relaxation times T1/T2, a quantity which depends uniquely on the rate of the electron fluctuations and the Larmor frequency of the involved nuclei. This analysis enables rationalizing the evolution of NMR lineshapes, signal quenching as well as DNP enhancements as a function of the concentration of the paramagnetic species and the temperature, demonstrated here for LiMg1−xMnxPO4 and Fe(III) doped Li4Ti5O12, respectively. For the latter, we observe a linear dependence of the DNP enhancement and the electron relaxation time within a temperature range between 100 and 300 K.

CFD Research on the Hydrodynamic Performance of Submarine Sailing near the Free Surface with Long-Crested Waves

The simulations of submarine sailing near the free surface with long-crested waves have been conducted in this study using an in-house viscous URANS solver with an overset grid approach. First, the verification and validation procedures were performed to evaluate the reliability, with the results showing that the generation of irregular waves is adequately accurate and the results of total resistance are in good agreement with EFD. Next, three different submerged depths ranging from 1.1D to 3.3D were selected and the corresponding conditions of submarine sailing near calm water were simulated, the results of which were then compared with each other to investigate the influence of irregular waves and submerged depths. The simulations of the model near calm water at different submerged depths demonstrated that the free surface will cause increasing resistance, lift, and bow-up moments of the model, and this influence decreases dramatically with greater submerged depths. The results of the irregular wave simulations showed that irregular waves cause considerable fluctuations of hydrodynamic force and moments, and that this influence remains even at a deeper submerged depth, which can complicate the control strategies of the submarine. The response spectrum of hydrodynamic forces and moments showed slight amplitudes in the high-frequency region, and the model showed less sensitivity to high-frequency excitations.

Real-time prediction of science student learning outcomes using machine learning classification of hemodynamics during virtual reality and online learning sessions

Current data sources used for the prediction of student outcomes average about 55% accuracy and require a significant amount of input data and time for researchers and educators to produce predictive models of student outcomes. The aim of this study is to examine how neurocognitive data collected via functional near infrared spectroscopy (fNIRS) may be used to create predictive models of student outcomes with greater speed and accuracy when using a synthetic adaptive learning environment (SALEs). Specifically, this study examines the utility of using neurocognitive data to develop student response prediction on a science content test. Participants were recruited from schools located in the United States ( n = 40). Participants in the study engaged in three conditions: no content, video and virtual reality. The lesson video and virtual reality lesson provides an explanation of deoxyribonucleic acid replication. Observed neurocognitive responses were collected during each condition and used to predict the success of student responses on an assessment. On average the predicative accuracy of this approach is 85% and occur within 300 ms. Predictive error rates are less than 15%. Results of this study provides evidence to support the use of neurocognitive data for adaption of digitally presented content and how machine learning approaches and artificial intelligence may be used to classify student data in real-time as students engage with content. Results also illustrate good accuracy and capture of moment-to- moment fluctuations of cognition in real-time. These findings may help the development of artificially intelligent tutors and improve student-based learning analytics. • Classification of neurocognitive data lends itself to prediction of student outcomes. • Describes neurocognitive data sources for development of predictive learning platforms. • Hemodynamic response can help to understand levels of student attention and engagement.

Stall flutter suppression of NACA 0012 airfoil based on steady blowing

Stall flutter is a classical aeroelastic phenomenon that seriously affects the performance of flexible wings at high angle of attack. In this article, steady blowing from the leading edge is designed to suppress stall flutter of a two-dimensional airfoil model at 15° static equilibrium angle of attack. The dynamic responses are measured to analyze the nonlinear characteristics of the aeroelastic system. It is found that the leading-edge blowing changes the local bifurcation behavior from a subcritical Hopf bifurcation followed by a saddle–node bifurcation to a supercritical Hopf bifurcation, with the flutter amplitude decreasing and the flutter critical velocity increasing. Time-resolved particle image velocimetry (TR-PIV) measurements are acquired to observe the flowfield evolution during stall flutter. The unsteady aerodynamic moment and flowfield results show that the leading-edge blowing effectively controls dynamic stall during oscillations. Low-momentum injection promotes shedding of dynamic stall vortices (DSVs) and reduces aerodynamic moment fluctuation, whereas high-momentum injection further suppresses the formation of DSVs and shrinks the aerodynamic moment hysteresis loop. During pitching-down of the airfoil, leading-edge blowing induces rapid recovery of the aerodynamic moment, which promotes the decay of stall flutter. When the blowing excitation is strong enough, stall flutter can be completely suppressed within several cycles.

Magnetic properties of textured ferrocomposite consisting of immobilized superparamagnetic nanoparticles.

Wide use of magnetic nanoparticles in modern technologies and biomedical applications requires reliable theoretical models capable of predicting physical properties. Solidification of a ferroparticle suspension under the action of permanent magnetic field allows us to obtain a ferrocomposite, characterized by some orientational texture of the nanoparticle easy magnetization axes. The static magnetic response of this ferrocomposite differs from that of the parent magnetic suspension due to "freezing" of nanoparticle translational and rotational degrees of freedom. Here the superparamagnetic fluctuations of the nanoparticle magnetic moments play a key role in the formation of the ferrocomposite magnetic response depending on the degree of orientational ordering, obtained during synthesis of a ferrocomposite. With the help of statistical mechanics we calculate the magnetization and the initial magnetic susceptibility of the textured ferrocomposite for various temperatures and magnetic field strengths. The easy axis texturing leads to a significant increase of the magnetic properties, and the effect intensifies with the growth of nanoparticle magnetocrystalline anisotropy. Theoretical predictions are supported by Monte Carlo simulations. The obtained results evidence that the texturing of a ferroparticle suspension and transforming it into a textured ferrocomposite are a real way to enhance the magnetic response of these magnetic soft materials.