Fluctuation Modes Research Articles

Implicit large-eddy simulation of an over-expanded screeching rectangular jet

Implicit large-eddy simulation of an over-expanded screeching rectangular jet is performed with a seventh-order finite difference scheme. Good agreement is found between the predicted flow- and acoustic fields with the experimental observations. Fourier decomposition, phase-averaging analysis and Spectral Proper Orthogonal Decomposition (SPOD) are used to investigate the origin of the screech, the shock leakage during the shear-layer flapping, and the distinguishing fluctuating characteristics in the minor- and major-axis plane of the rectangular jet. It finds that the screech is radiated from the end of the forth shock cell, where the interaction of the shock waves with the shear layer causes periodic leakages of shock-wave tips in the minor-axis plane, resulting in the generation of intense acoustic waves in the surrounding air. An obvious flapping mode at the same frequency of the screech is captured in the minor-axis plane and dominates the dynamic motions of the rectangular jet. The SPOD modes of pressure and velocity fluctuations at the screech frequency help to reveal the relationship between the screech generation and the coherent structures.

Effect of Morphological Characteristics of Aggregates on Thermal Properties of Molten Salt Nanofluids

Molten salt-based nanofluid is a thermal storage and heat transfer medium for concentrated solar thermal power plants formed by adding nanoparticles to molten salt, which can enhance the thermal performance of molten salt. However, the nanoparticles tend to aggregate in nanofluids, causing changes in thermal properties. In this work, molecular dynamics simulations were used to study the effect of morphological characteristics of aggregates on the thermal conductivity and specific heat capacity of molten salt-based nanofluids. The results show that the aggregated nanoparticles cause a greater increase in thermal conductivity and specific heat capacity than dispersed nanoparticles. Additionally, the increase in fractal dimension leads to thermal conductivity reduction, while there is no clear correlation between the fractal dimension and specific heat capacity. New insights into the thermal properties of aggregated nanofluids are provided by analyzing the contribution of material components, heat flux fluctuation modes, and energy compositions. It is found that the thermal conductivity of aggregated nanofluids is mainly dominated by the base liquid and collision term. However, the specific heat is not related to the variation in the contribution of different energy compositions. Moreover, compared to the dispersed nanofluid, the increased specific heat capacity of aggregated nanofluids is attributed to the thicker semi-solid layer. This study provides guidance for the design and control of the thermal properties of molten salt-based nanofluids.

A Simulation-Based Bayesian Network Approach to the Joint Decision of the International Transportation Mode and Safety Inventory Policy

Uncertainty in international transportation can have a significant impact on inventory costs and customer service levels in a global supply chain network. A very limited number of studies in the literature have addressed the international transportation mode and safety inventory policy (ITM-SIP) issues simultaneously. This study formulates the problem and proposes a simulation-based Bayesian network (SBN) approach for the joint decisions on ITM-SIP, where Bayesian networks are used to dynamically estimate international replenishment lead times for railway and maritime transportation modes. We implement our approaches in an international automotive spare parts supply chain experiencing fluctuations in its shipping supply market and with dynamic demand. For this joint decision problem, we build an international supply chain network simulation model in which the time-delay uncertainties of key bottleneck nodes in maritime and railway transportation routes are considered. The simulation experiment results show the performance improvement of the SBN approach in substantially reducing total costs and achieving service levels. We also provide insights into the value of decision tactics for responding to different fluctuation modes in the shipping supply market in the global supply chain network.

Current fluctuations in a partially asymmetric simple exclusion process with a defect particle.

We study an exclusion process on a ring comprising a free defect particle in a bath of normal particles. The model is one of the few integrable cases in which the bath particles are partially asymmetric. The presence of the free defect creates localized or shock phases according to parameter values. We use a functional approach to Bethe equationsresulting from a nested Bethe ansatz to calculate exactly the mean currents and diffusion constants. The results agree very well with Monte Carlo simulations and reveal the main modes of fluctuation in the different phases of the steady state.

Entropy-driven nonequilibrium phonon-stimulated electron-phonon coupling in tin dioxide nanorods.

Nonequilibrium (NEQ) phonon fluctuation in a nanosystem has been studied through the statistical assessment of the entropy-production and -consumption events in ultrasmall tin dioxide (SnO_{2}) nanorods. Size- and shape-dependent alteration in free energy leading to modulation of the probability distribution function of the phonon dynamics has been observed from the x-ray diffraction and Raman scattering characterizations. The Gallavotti-Cohen nonequilibrium fluctuation theorem has been utilized to qualitatively describe the aforementioned behaviors under the influence of a global flux. The observation of entropy consumption and thermodynamically favorable entropy-production events indicates the presence of NEQ fluctuations in the phonon modes. The effective energy scale of fluctuation in driven phonon modes, dissipating energy faster than relaxation time, is quantified on the order of nanojoules. From optical absorption and photoluminescence studies, the observation of the electron-phonon coupled state confirms the interaction of the NEQ phonons with electrons. The strength of the coupling has been estimated from the temperature-independent Barry center shift and found to be enhanced to 5.35. Valence band x-ray photoelectron spectroscopy and Fourier transformed infrared spectroscopy analyses reconcile NEQ phonon mediated alteration of the valence band density of states, activation of silent phonon modes, and superior excitonic transitions, suitable for the new generation of ultrafast quantum device applications.

Freezing and Thawing of Enclosing Structures and Foundation Soils Taking into Account the Effects of Solar Energy: Part 1. Theoretical Foundations of Freezing Wet Soils

The temperature and humidity state of the foundations and foundations in the climatic conditions of the Russian Federation is decisive in their design,it affects the bearing capacity, operational reliability, and durability of the foundations and the entire building. When designing foundations and foundations, they solve a set of tasks that are subordinated to one idea, so that the soil (base) he carried the load from the building or structure proposed to him, and the foundation structure itself would ensure reliable operation of the building or structure for the entire life cycle, since the foundations belong to permanent structures, and their repair is associated with large material costs. Existing modern calculation methods assume that the heat transfer process is stationary and do not consider real processes – seasonal and daily fluctuations in outdoor air temperature, heating on and off modes, temperature changes in the depth of the soil, wet structures due to accidents of heating plants, the absence (or destruction) of a blind area, etc. Freezing of soils, as a rule, occurs in autumn-winter period, when the soil is saturated with moisture. Thawing of the soil occurs in the spring-summer period. These processes are non-stationary in nature, which is influenced by many factors, including solar radiation. The work is devoted to modelling and calculation of these real processes. The process of freezing and thawing of the foundation soils is influenced by many factors: the composition of the soil, water, ice, snow, solar radiation, fluctuations in outdoor temperature. The paper provides general information about some of the physical properties of water, ice, and snow, necessary for understanding the processes under consideration.

Impact of nanoparticle agglomeration on thermal conductivity of molten salt based nanofluids: Insights from molecular dynamics and lattice Boltzmann methods

The nanoparticle aggregation has significant influence on heat transfer properties. The contradictions between different researches exist and the underlying mechanisms of heat conduction remain unclear. To address these issues, the thermal conductivity of solar salt-SiO2 nanofluids in the non-aggregated and aggregated states was investigated, based on the combination of the advantages of molecular dynamics (MD) in revealing physical insights and lattice Boltzmann method (LBM) in simulating properties for complex structures. LBM models were simplified on the basic of MD results. Different heat transfer physics in nanofluids at nanoscale and mesoscale were compared. The results show that the thermal conductivity of aggregated nanofluid is higher than the non-aggregated nanofluid. By analyzing the diffusion coefficient, number density and vibrational density of states, we found that the previous hypotheses (such as Brownian motion, interfacial layer and interfacial thermal resistance) cannot explain the enhanced thermal conductivity induced by the nanoparticle agglomeration. The heat transfer mechanisms of aggregated nanofluid were further analyzed from new perspectives, i.e., the contributions of different material components and fluctuation modes to heat flux. It is found that the nanoparticle aggregation leads to the nanoparticle contribution increase, indicating the formation of low thermal resistance channels within the aggregates. The heat conduction contributed by collision decreases in the aggregated state, while that contributed by potential energy increases. Moreover, the thermal conductivity of aggregated nanofluid is negatively correlated with temperature, aggregate size and fractal dimension of agglomerates, and positively correlated with mass fraction of nanoparticles, degree of agglomeration, and backbone length of each aggregate.

Collective modes and quantum effects in two-dimensional nanofluidic channels.

Nanoscale fluid transport is typically pictured in terms of atomic-scale dynamics, as is natural in the real-space framework of molecular simulations. An alternative Fourier-space picture, that involves the collective charge fluctuation modes of both the liquid and the confining wall, has recently been successful at predicting new nanofluidic phenomena such as quantum friction and near-field heat transfer, that rely on the coupling of those fluctuations. Here, we study the charge fluctuation modes of a two-dimensional (planar) nanofluidic channel. Introducing confined response functions that generalize the notion of surface response function, we show that the channel walls exhibit coupled plasmon modes as soon as the confinement is comparable to the plasmon wavelength. Conversely, the water fluctuations remain remarkably bulk-like, with significant confinement effects arising only when the wall spacing is reduced to 7 Å. We apply the confined response formalism to predict the dependence of the solid-water quantum friction and thermal boundary conductance on channel width for model channel wall materials. Our results provide a general framework for Coulomb interactions of fluctuating matter under nanoscale confinement.

Robust Sample Information Retrieval in Dark-Field Computed Tomography with a Vibrating Talbot-Lau Interferometer.

X-ray computed tomography (CT) is a crucial tool for non-invasive medical diagnosis that uses differences in materials' attenuation coefficients to generate contrast and provide 3D information. Grating-based dark-field-contrast X-ray imaging is an innovative technique that utilizes small-angle scattering to generate additional co-registered images with additional microstructural information. While it is already possible to perform human chest dark-field radiography, it is assumed that its diagnostic value increases when performed in a tomographic setup. However, the susceptibility of Talbot-Lau interferometers to mechanical vibrations coupled with a need to minimize data acquisition times has hindered its application in clinical routines and the combination of X-ray dark-field imaging and large field-of-view (FOV) tomography in the past. In this work, we propose a processing pipeline to address this issue in a human-sized clinical dark-field CT prototype. We present the corrective measures that are applied in the employed processing and reconstruction algorithms to mitigate the effects of vibrations and deformations of the interferometer gratings. This is achieved by identifying spatially and temporally variable vibrations in air reference scans. By translating the found correlations to the sample scan, we can identify and mitigate relevant fluctuation modes for scans with arbitrary sample sizes. This approach effectively eliminates the requirement for sample-free detector area, while still distinctly separating fluctuation and sample information. As a result, samples of arbitrary dimensions can be reconstructed without being affected by vibration artifacts. To demonstrate the viability of the technique for human-scale objects, we present reconstructions of an anthropomorphic thorax phantom.

Confined bicontinuous microemulsions: nanoscale dynamics of the surfactant film.

A confined bicontinuous C10E4-D2O-n-octane microemulsion is studied using neutron spin echo spectroscopy (NSE). Controlled pore glasses serve as confining matrices with pore diameters ranging from 24 to 112 nm. Firstly, the microemulsion in bulk is investigated by NSE and dynamic light scattering, which allows the determination of the unperturbed collective dynamics as well as the observation of the undulation of the surfactant film. In confinement, it is observed that the collective modes are drastically slowed down in all investigated pore sizes. The undulations of the surfactant film in the largest pores are found to be comparable to those of the bulk and decrease with decreasing pore diameter. Fitting procedures of the intermediate scattering function revealed that the long wavelength undulations are cut off from the spectrum of fluctuation modes due to the interactions with the pore walls.

Tuning the stability of a model quasicrystal and its approximants with a periodic substrate.

Quasicrystals and their periodic approximants are complex crystalline phases. They have now been observed in many metallic alloys, soft matter systems, and particle simulations. In recent experiments of thin-film perovskites on solid substrates, the type of complex phase was found to change depending on thermodynamic conditions and the type of substrate used. Here, we investigate the effect of a substrate on the relative thermodynamic stability of a two-dimensional model quasicrystal and its approximants. Our simulation model is particles interacting via the Lennard-Jones-Gauss potential. Our numerical methods are molecular dynamics simulations and free energy calculations that take into account phason flips explicitly. For substrates interacting weakly with the particles, we observe an incommensurate-commensurate transition, in which a continuous series of quasicrystal approximants locks into a small number of approximants. Interestingly, we observe that the 3/2 approximant exhibits phason mode fluctuations in thermodynamic equilibrium. Such fluctuations are reminiscent of random tiling and a phenomenon usually associated only with quasiperiodic order. For stronger substrates, we find an enhancement of the stability of the dodecagonal quasicrystal and variants of square lattices. We explain all observed phenomena by the interplay of the model system with the substrate. Our results demonstrate that designing novel complex periodic and quasiperiodic structures by choice of suitable substrates is a promising strategy.

Entropy production in the nonreciprocal Cahn-Hilliard model.

We study the nonreciprocal Cahn-Hilliard model with thermal noise as a prototypical example of a generic class of non-Hermitian stochastic field theories, analyzed in two companion papers [Suchanek, Kroy, and Loos, Phys. Rev. Lett. 131, 258302 (2023)10.1103/PhysRevLett.131.258302; Phys. Rev. E 108, 064123 (2023)10.1103/PhysRevE.108.064123]. Due to the nonreciprocal coupling between two field components, the model is inherently out of equilibrium and can be regarded as an active field theory. Beyond the conventional homogeneous and static-demixed phases, it exhibits a traveling-wave phase, which can be entered via either an oscillatory instability or a critical exceptional point. By means of a Fourier decomposition of the entropy production rate, we quantify the associated scale-resolved time-reversal symmetry breaking, in all phases and across the transitions, in the low-noise regime. Our perturbative calculation reveals its dependence on the strength of the nonreciprocal coupling. Surging entropy production near the static-dynamic transitions can be attributed to entropy-generating fluctuations in the longest wavelength Fourier mode and heralds the emerging traveling wave. Its translational dynamics can be mapped on the dissipative ballistic motion of an active (quasi)particle.

Four-dimensional flow field near a sphere settling in Newtonian fluid

This paper presents time-resolved, three-dimensional measurements coupling particle trajectories with flow fields around settling spheres in Newtonian fluids. The experiments cover a range of particle Reynolds numbers (Re), spanning from 1.6 to 6. Our calculated drag coefficients, derived from sphere trajectories, closely align with values reported in the literature. Notably, our high spatial resolution reveals oscillations, potentially corresponding to the “streamwise oscillations” phenomenon discussed by Horowitz and Williamson [“The effect of Reynolds number on the dynamics and wakes of freely rising and falling spheres,” J. Fluid Mech. 651, 251 (2010)]. For a single sphere, we extract the three-dimensional flow field using particle tracking velocimetry. Discrete particle tracks are meticulously interpolated onto a regular grid using a fine-scale reconstruction based on the vortex-in-cell method. Leveraging the known sphere position, we introduce a sphere-centered coordinate system, enabling time-averaging of flow properties. Additionally, we interpolate and analyze the pressure field on the sphere's surface, employing proper orthogonal decomposition to unveil distinct pressure fluctuation modes.

Functional renormalisation group approach to shell models of turbulence

Shell models are simplified models of hydrodynamic turbulence, retaining only some essential features of the original equations, such as the non-linearity, symmetries and quadratic invariants. Yet, they were shown to reproduce the most salient properties of developed turbulence, in particular universal statistics and multi-scaling. We set up the functional renormalisation group (FRG) formalism to study generic shell models. In particular, we formulate an inverse RG flow, which consists in integrating out fluctuation modes from the large scales (small wavenumbers) to the small scales (large wavenumbers), which is physically grounded and has long been advocated in the context of turbulence. Focusing on the Sabra shell model, we study the effect of both a large-scale forcing, and a power-law forcing exerted at all scales. We show that these two types of forcing yield different fixed points, and thus correspond to distinct universality classes, characterised by different scaling exponents. We find that the power-law forcing leads to dimensional (K41-like) scaling, while the large-scale forcing entails anomalous scaling.

Toward Interpreting the IBEX Ribbon with Mirror Diffusion in Interstellar Turbulent Magnetic Fields

We investigate the role of the magnetohydrodynamic (MHD) turbulence measured by Voyager in the very local interstellar medium (VLISM) in modeling the Interstellar Boundary Explorer ribbon. We demonstrate that the mirroring by compressible modes of MHD turbulence dominates over that by the mean magnetic field. Based on the new mirror diffusion mechanism identified by Lazarian & Xu for particles with large pitch angles in MHD turbulence, we find that the mirror diffusion can both confine pickup ions and preserve their initial pitch angles, and thus it accounts for the enhanced intensity of energetic neutral atoms that return to the heliosphere. The ribbon width is determined by both the range of pitch angles for effective turbulent mirroring and the field line wandering induced by Alfvénic modes. It in turn provides a constraint on the amplitude of magnetic fluctuations of fast modes. The field line wandering also affects the coherence of the ribbon structure across the sky. By extrapolating the magnetic energy spectrum measured by Voyager, we find that the injection scale of the turbulence in the VLISM must be less than ∼500 au for the ribbon structure to be coherent.

How Does the Time-Varying Network Structure Evolve between the EU Carbon Futures Prices and Industrial and Energy-Related Indices? A Study Based on a Time-Varying T-Copula

Industrial and energy-related industries are major sources of carbon dioxide emissions, and their interdependence, as reflected in the financial field, has attracted the attention of scholars. For the purpose of exploring the evolutionary characteristics of the short-term dynamic correlation coefficient between the EU carbon futures price and the industrial and energy-related indices, this paper selected the settlement price of EU carbon emission quota futures, the MSCI energy I index on three dimensions, and the Dow Jones industrial index and West Texas crude oil futures price, as sample data. Using the time-varying t-copula model to measure the dynamic correlation coefficient between variables, the time-sliding window idea and coarse-grained method were combined to establish the correlation fluctuation mode, and a complex network theory and analysis methods were used to study the evolutionary traits of the time-varying network structure between the EU carbon price and the industrial and energy-related index. The results show that the transmission objects of the key correlation fluctuation modes in the network are stable and maintain their own state with a high probability. Second, the clustering effect exists in the transmission process. Some nodes with high mediating abilities are also the key correlation wave modes in the dynamic correlation evolution network. This study provides ideas for the study of the correlations between multiple variables and is also a useful reference for international investors.

Electromagnetic fluctuation and collective modes in relativistic bosonic superfluid in mixed dimensions

In Gaussian approximation, we investigate the marginal electromagnetic fluctuation in models of charged relativistic bosonic superfluids in three and two spatial dimensions at zero temperature. The electromagnetism is modeled by the ordinary Maxwell term and the non-local pseudo-electrodynamics action in these dimensions respectively. We explore the collective excitations in these systems by integrating the superfluid velocity fields. We unveil that different collectives mode dispersions are results of the competition between different characteristic scales of speed and that between short-ranged and long-ranged interactions. In (3+1) dimensions, we derive the roton mode reminiscent of what was discovered in the context of the free relativistic Bose–Einstein condensate as a generalization of the Higgs mode and determine the necessary and sufficient condition for the roton to exist. In (2+1) dimensions, besides solving the dispersion relation for the surface plasmon, we prove there cannot be roton-like excitation in this model as opposed to its (3+1) dimensional counterpart, and additionally derive the asymptotic lines of the dispersion in the limits of long wavelength and short distance. These asymptotic dispersions are supplied with alternative perspective using duality.

Gauge fixing in cosmological perturbations of Unimodular Gravity

With focus on the cosmological evolution of linear perturbations of matter and geometry, we calculate the equivalent expressions to that of the Newtonian and Synchronous gauges within the framework of Unimodular Gravity, being these two gauges commonly used and implemented in Boltzmann codes. An important aspect of our analysis is the inclusion of the energy-momentum current violation, as well as its perturbations. Moreover, for the first time we demonstrate that it is possible to fix both gauges consistently, although as it has been already noticed in previous literature, neither of them is recovered in the sense of the dynamics given in General Relativity for matter and metric fluctuations. Specifically, we show that since the unimodular constraint at the level of linear perturbations lead to only one degree of freedom of scalar modes of metric fluctuations, the dynamics in Unimodular Gravity forces to keep the anisotropic stress in the Newtonian gauge, whereas the cold dark matter comoving frame can not be set in the Synchronous gauge. The physical implications on the density contrast of cold dark matter is reviewed, and the Sachs-Wolfe effect is obtained and compared with previous results in the literature of cosmological perturbations in Unimodular Gravity.

High-order moment closure models with random batch method for efficient computation of multiscale turbulent systems.

We propose a high-order stochastic-statistical moment closure model for efficient ensemble prediction of leading-order statistical moments and probability density functions in multiscale complex turbulent systems. The statistical moment equations are closed by a precise calibration of the high-order feedbacks using ensemble solutions of the consistent stochastic equations, suitable for modeling complex phenomena including non-Gaussian statistics and extreme events. To address challenges associated with closely coupled spatiotemporal scales in turbulent states and expensive large ensemble simulation for high-dimensional systems, we introduce efficient computational strategies using the random batch method (RBM). This approach significantly reduces the required ensemble size while accurately capturing essential high-order structures. Only a small batch of small-scale fluctuation modes is used for each time update of the samples, and exact convergence to the full model statistics is ensured through frequent resampling of the batches during time evolution. Furthermore, we develop a reduced-order model to handle systems with really high dimensions by linking the large number of small-scale fluctuation modes to ensemble samples of dominant leading modes. The effectiveness of the proposed models is validated by numerical experiments on the one-layer and two-layer Lorenz '96 systems, which exhibit representative chaotic features and various statistical regimes. The full and reduced-order RBM models demonstrate uniformly high skill in capturing the time evolution of crucial leading-order statistics, non-Gaussian probability distributions, while achieving significantly lower computational cost compared to direct Monte-Carlo approaches. The models provide effective tools for a wide range of real-world applications in prediction, uncertainty quantification, and data assimilation.

Differential phase-diversity electrooptic modulator for cancellation of fiber dispersion and laser noise

Bandwidth and noise are fundamental considerations in all communication and signal processing systems. The group-velocity dispersion of optical fibers creates nulls in their frequency response, limiting the bandwidth and hence the temporal response of communication and signal processing systems. Intensity noise is often the dominant optical noise source for semiconductor lasers in data communication. In this paper, we propose and demonstrate a class of electrooptic modulators that is capable of mitigating both of these problems. The modulator, fabricated in thin-film lithium niobate, simultaneously achieves phase diversity and differential operations. The former compensates for the fiber’s dispersion penalty, while the latter overcomes intensity noise and other common mode fluctuations. Applications of the so-called four-phase electrooptic modulator in time-stretch data acquisition and in optical communication are demonstrated.