Small-scale Structures Research Articles

An Adaptive Mesh Refinement–Rotated Lattice Boltzmann Flux Solver for Numerical Simulation of Two and Three-Dimensional Compressible Flows with Complex Shock Structures

An adaptive mesh refinement–rotated lattice Boltzmann flux solver (AMR-RLBFS) is presented to simulate two and three-dimensional compressible flows with complex shock structures. In the method, the RLBFS, which has a strong shock-capturing capability and can effectively eliminate the shock instability phenomenon, is applied to solve the flow filed by reconstructing the fluxes at each cell interface adaptively with the mesoscopic lattice Boltzmann model. To locally and dynamically improve the resolution of intricate shock structures and optimize the required computational resources, a block-structured adaptive mesh refinement (AMR) technique is introduced. The validity and effectiveness of the proposed method are confirmed through a range of two and three-dimensional numerical cases, including the shock tube problem, the four-wave Riemann problem, explosion within a rectangular box, and the vorticity induced by a shock. The results obtained using the AMR-RLBFS exhibit excellent agreement with published data and demonstrate high accuracy in capturing complex shock structures. The computational efficiency of the AMR-RLBFS can be also improved significantly compared to the RLBFS on uniform grids. Furthermore, the numerical outcomes underscore the capability of the AMR-RLBFS to eliminate shock instability effects while efficiently capturing a broader spectrum of small-scale vertical structures. These findings highlight the ability of AMR-RLBFS to improve the computational efficiency and capture intricate shock structures effectively, making it a valuable tool for studying a wide range of compressible flows from aerodynamics to astrophysics.

Small-scale layered structures at the inner core boundary

The fine-scale seismic features near the inner core boundary (ICB) provide critical insights into the thermal, chemical, and geodynamical interactions between liquid and solid cores, and may shed light on the evolution mechanism of the Earth’s core. Here, we utilize a dataset of pre-critical PKiKP waveforms to constrain the fine structure at the ICB, considering the influence of various factors such as source complexity, structural anomalies in the mantle, and properties at the ICB. Our modeling suggests a sharp ICB beneath Mongolia and most of Northeast Asia, but a locally laminated ICB structure beneath Central Asia, Siberia, and part of Northeast Asia. The complex ICB structure might be explained by either the existence of a kilometer-scale thickness of mushy zone, or the localized coexistence of bcc and hcp iron phase at the ICB. We infer that there may be considerable lateral variations in the dendrites growing process at ICB, probably due to the complicated thermochemical and geodynamical interaction between the outer and inner core.

A novel efficient method for transient heat analysis of cylindrical periodic structure based on the physical features and group theory

In this paper, a novel efficient and accurate numerical method is developed for analyzing the transient temperature responses of cylindrical periodic structures. By exploiting the structure’s circumferential cyclic periodic property and leveraging group theory, a circumferential decomposition strategy is presented to transform the temperature response analysis of the cylindrical periodic structure into the analyses of a series of one-dimensional periodic structures. Then, based on the physical nature of the transient heat conduction, an axial decomposition strategy is developed to convert the computations of the temperatures of these one-dimensional periodic structures into the calculations of the temperatures of a series of small-scale structures. The computational cost of these small-scale structures is further reduced by using the group theory. Several numerical examples demonstrate that the proposed method has higher accuracy and computational efficiency in comparison with the Crank-Nicolson method. When the Crank-Nicolson method attains the acceptable results, the proposed method is about 10 and 20 times faster than the Crank-Nicolson method with direct and preconditioning conjugate gradient solvers, respectively.

Entrainment, detrainment and enstrophy transport by small-scale vortex structures

The interaction of small-scale vortical structures with the surrounding fluid are studied using a fully resolved three-dimensional experimental data set of homogeneous turbulence measured at the centre of a von Kármán mixing flow facility and a direct numerical simulation (DNS) data set of forced isotropic turbulence. To identify the small-scale vortices and their boundaries, an objective observer-independent definition was implemented to avoid arbitrariness and is the first implementation applied to experimental measurements of small-scale turbulence. Volume-averaged and conditional statistics are presented to demonstrate consistency between the experimental and DNS data sets. To examine the interaction of the structures with the surrounding flow field, we examine the flow across the boundary of vortex structures by adopting a similar methodological approach to that used to investigate the local entrainment and detrainment across the turbulent–non-turbulent interface. The probability density function (p.d.f.) of entrainment velocity conditioned on the vortex boundary exhibited a non-Gaussian distribution that skewed slightly in favour of entrainment and is remarkably similar to the p.d.f.s of entrainment velocity observed in boundary layers and jets. We analyse the enstrophy transport equation conditioned on radial and axial coordinates of the vortices to quantify the inviscid and viscous components of the entrainment/detrainment process. A comparison with Burgers vortices is made and it is found that the Burgers vortex model captures the vortex structure average size and the mechanisms of enstrophy transport in the radial direction, but is unable to capture local statistics and describe the governing physics along the axes of the vortices.

Machine learning and cointegration for structural health monitoring of a model under environmental effects

Data-driven models have been recognized as powerful tools to support Structural Health Monitoring (SHM). This paper contributes to the literature by exploring two data-driven approaches to detect damage through changes in a set of variables that assess the condition of the structure, and accommodates the challenge that may arise due to the influence of environmental and operational variabilities. This influence is reflected in the response of the structure and can reduce the probability of detecting damage in a structure or increase the probability of signaling false positives. This paper conducts a comparative study between a machine learning detection approach (supported by linear regression, random forest, support vector machine, and neural networks) and a cointegration approach, with the aim of detecting damage as early as possible. This study also contributes to the literature by evaluating the merits of the damage detection methods using real data collected from a small-scale structure. The structure is analyzed in a reference state and a perturbed state in which damage is emulated. The results show that both approaches are able to detect damage within the first 24 h, without ever signaling false positives. The cointegration based approach can notably detect damage after 10 h and 15 minutes, while the machine learning approach takes 20 h 30 m to detect damage.

Simulations of weakly magnetized turbulent mixing layers

ABSTRACT Radiative turbulent mixing layers (TMLs) are expected to form pervasively at the phase boundaries in multiphase astrophysical systems. This inherently small-scale structure is dynamically crucial because it directly regulates the mass, momentum, and energy exchanges between adjacent phases. Previous studies on hydrodynamic TMLs have revealed the interactions between cold and hot phases in the context of the circumgalactic medium, offering important insight into the fate of cold clouds traveling through hot galactic winds. However, the role of magnetic field has only been sparsely investigated. We perform a series of 3D magnetohydrodynamics simulations of such mixing layers in the presence of weak to modest background magnetic field. We find that due to field amplification, even relatively weak background magnetic fields can significantly reduce the surface brightness and inflow velocity of the hot gas in the mixing layer. This reduction is attributed to a combination of magnetic pressure support and direct suppression of turbulent mixing, both of which alter the phase structures. Our results are largely independent of thermal conduction and converged with resolution, offering insights on the survival of cold gas in multiphase systems.

Self-similar Outflows at the Source of the Fast Solar Wind: A Smoking Gun of Multiscale Impulsive Reconnection?

We present results of a quantitative analysis of structured plasma outflows above a polar coronal hole observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) spacecraft. In a 6 hr interval of continuous high-cadence SDO/AIA images, we identified more than 2300 episodes of small-scale plasma flows in the polar corona. The mean upward flow speed measured by the surfing transform technique is estimated to be 122 ± 34 km s−1, which is comparable to the local sound speed. The typical recurrence period of the flow episodes is 10–30 minutes, and the mean duration and transverse size of each episode are about 3–5 minutes and 3–4 Mm, respectively. The largest identifiable episodes last for tens of minutes and reach widths up to 40 Mm. For the first time, we demonstrate that the polar coronal-hole outflows obey a family of power-law probability distributions characteristic of impulsive interchange magnetic reconnection. Turbulent photospheric driving may play a crucial role in releasing magnetically confined plasma onto open field. The estimated occurrence rate of the detected self-similar coronal outflows is sufficient for them to make a dominant contribution to the fast-wind mass and energy fluxes and to account for the wind’s small-scale structure.

Generation of Narrow-Band THz Radiation by Collision of Laser Wake Waves with a Small-Scale Transverse Structure in a Plasma

Generation of Narrow-Band THz Radiation by Collision of Laser Wake Waves with a Small-Scale Transverse Structure in a Plasma

Neural Adaptive Loop Filtering for Video Coding: Exploring Multi-Hypothesis Sample Refinement

Adaptive loop filtering (ALF) is extensively investigated for lossy video coding to mitigate compression noise. Numerous learning-based ALFs have emerged recently and improved the coding efficiency significantly through the use of complexity-intensive, large-scale models trained on excessive samples, making it impractical for real-life applications. By contrast, lightweight, small-scale ALF models cannot promise convincing performance and model generalization. In principle, the ALF estimates the sample distortion for restoration. Instead of directly approximating the distortion as in existing solutions, we reformulate it as a Multi-hypothesis Sample Refinement (MSR) problem. To this end, we first generate multiple distortion hypotheses through a deep neural network (DNN) model. Then, these hypotheses are linearly superimposed to approximate the final distortion through the minimization of mean square error (MMSE) between the filtered reconstruction and its original, uncompressed input. Finally, the linear superimposition coefficients are explicitly signaled in the compressed bitstream. As seen, the superimposition coefficients inherently generalize the MSR to various content. And using DNNs to generate distortion hypotheses essentially models the spatial priors of a local block and its underlying compression error distribution. As a result, the MSR using a small-scale convolutional neural network (CNN) model with only 5k parameters and 5 KMACs/pixel achieves 4.35% (Intra) and 2.49% (Inter) BD-Rate (Bjontegaard Delta Rate) gains over the AV1 anchor. Ablation studies further demonstrate that the MSR can be generalized to diverse small-scale network structures, different standards (e.g., H.265/HEVC and H.266/VVC), and diverse video content (e.g., screen videos).

Numerical investigation on the rotor-turbulence interaction noise

Noise from a turbomachinery component, such as compressors and turbines, is an important issue to be resolved in aerospace and ocean engineering applications. The rotor of a turbomachinery assembly usually could operate downstream to other flow structures (fuselages, stators, control surfaces, etc.) that produce either large-scale or small-scale turbulence structures, which are highly complex and are being distorted while they are ingested into the rotor, which generate the rotor-turbulence interaction noise. The presented work conducted numerical simulation research on a ten-bladed rotor ingesting different turbulence structures. The large eddy simulation (LES) and Ffowcs-Williams and Hawkings (FW-H) methods were used to predict the flow-induced noise from the rotor. The results show that the time-space evolution of the upstream turbulent structure when it passes towards the rotor. In addition, the differences in the turbulence ingestion noise at different inflow speeds and rotational speeds were studied. Furthermore, the sound generation mechanism of turbulent ingestion noise was explored using a newly proposed near-field sound source analysis method. In summary, this study can help to improve the understanding of the physical mechanisms of unsteady forces and noise generated by a rotor when it interacts with ingesting turbulent flows.

Investigating Spatial and Temporal Structuring of E‐Region Coherent Scattering Regions Over Northern Norway

AbstractRecently, it has been shown that the Spread Spectrum Interferometric Multistatic meteor radar Observing Network radar system located in northern Norway is capable of measuring ionospheric E‐region coherent scatter with spatial and temporal resolutions on the order of 1.5 km and 2 s, respectively. Four different events from June and July of 2022 are examined in the present study, where the coherent scatter measurements are used as a tracer for large‐scale ionospheric phenomena such as plasma density enhancements and ionospheric electric fields. By applying a two‐dimensional Fourier analysis to range‐time‐intensity data, we perform a multi‐scale spatial and temporal investigation to determine the change in range over time of large‐scale ionospheric structures (>3 km) which are compared with line‐of‐sight velocities of the small scale structures (∼5 m) determined from the Doppler shift of the coherent scatter. The spectral characteristics of the large‐scale structures are also investigated and logarithmic spectral slopes for scale sizes of 100–10 km were found to be between −3.0 and −1.5. This agrees with much of the previous work on the spatial spectra scaling for ionospheric electric fields. This analysis aids in characterizing the source of the plasma turbulence and provides crucial information about how energy is redistributed from large to small scales in the E‐region ionosphere.

FAUST

Context. Deuterium in H-bearing species is enhanced during the early stages of star formation. However, only a small number of high-spatial-resolution deuteration studies exist towards protostellar objects, leaving the small-scale structures of these objects unrevealed and understudied. Aims. We aim to constrain the deuterium fractionation ratios in a Class 0/I protostellar object in formaldehyde (H2CO), which has abundant deuterated isotopologues in this environment. Methods. We used the Atacama Large Millimeter Array (ALMA) within the context of the Large Program Fifty AU STudy of the chemistry in the disk/envelope system of Solar-like protostars (FAUST) to observe the Class 0/I protobinary system [BHB2007] 11, whose emission components are embedded in circumstellar disks that have radii of 2 to 3 au. The system is surrounded by a complex filamentary structure (the so-called streamers) connected to the larger circumbinary disk. In this work, we present the first study of formaldehyde D-fractionation towards this source with detections of H2CO 3(0,3)–2(0,2), combined with HDCO 4(2,2)–3(2,1), HDCO 4(1,4)–3(1,3) and D2CO 4(0,4)–3(0,3). These observations probe the structures of the protobinary system, enabling us to resolve multiple velocity components associated with the methanol hot spots also uncovered by FAUST data, as well as the colder external envelope. In addition, based on the kinematics seen in our observations of the H2CO emission, we propose the presence of a second large-scale outflow. Results. The results derived from our ALMA observations agree with the current literature in that we only find the deuterated species HDCO and D2CO in the central regions of the core, while undeuterated H2CO is found more ubiquitously. From our radiative transfer modelling, we the column density of H2CO to be in the range of (3-8) × 1014 cm−2 and that of HDCO to be within (0.8−2.9) × 1013 cm−2. The column density for the single detected velocity component of D2CO is within (2.6–1.3) × 1012 cm−2. This yields an average D/H ratio for formaldehyde in [BHB2007] 11 of $0.02_{ - 0.01}^{ + 0.02}$ from HDCO. The results of our kinematic model suggest that the dynamic feature is inconsistent with a streamer-like nature given the flat and outflowing velocity relation; we therefore tentatively conclude that the feature is an asymmetric molecular outflow launched by a wide-angle disk wind.

Applications of Computer Vision-Based Structural Monitoring on Long-Span Bridges in Turkey.

Structural displacement monitoring is one of the major tasks of structural health monitoring and it is a significant challenge for research and engineering practices relating to large-scale civil structures. While computer vision-based structural monitoring has gained traction, current practices largely focus on laboratory experiments, small-scale structures, or close-range applications. This paper demonstrates its applications on three landmark long-span suspension bridges in Turkey: the First Bosphorus Bridge, the Second Bosphorus Bridge, and the Osman Gazi Bridge, among the longest landmark bridges in the world, with main spans of 1074 m, 1090 m, and 1550 m, respectively. The presented studies achieved non-contact displacement monitoring from a distance of 600 m, 755 m, and 1350 m for the respective bridges. The presented concepts, analysis, and results provide an overview of long-span bridge monitoring using computer vision-based monitoring. The results are assessed with conventional monitoring approaches and finite element analysis based on observed traffic conditions. Both displacements and dynamic frequencies align well with these conventional techniques and finite element analyses. This study also highlights the challenges of computer vision-based structural monitoring of long-span bridges and presents considerations such as the encountered adverse environmental factors, target and algorithm selection, and potential directions of future studies.

A Small-scale Structure Model of a Jet Based on Observations of Microvariability

We developed a multiregion radiation model for the evolution of flux and spectral index with time. In this model, each perturbation component in the jet produces an independent flare. The model can be used to study the decomposition of microvariability, the structural scale of the perturbed components, and the physical parameters of the acceleration processes. Based on the shock acceleration model for a relativistic jet, the influence of the acceleration parameters on multiband flare parameters is calculated. We present the results of multiband optical microvariability of the blazar BL Lacertae observed during 89 nights in the period from 2009 to 2021, and use them as a sample for model fitting. The results show that both the amplitude and duration of flares decomposed from the microvariability light curves conform to a log-normal distribution. The time delays between the optical bands follow a normal distribution and amount to several minutes, which corroborate with both predictions from the theoretical model and the calculation of the discrete correlation function. Using the spectral index evolution and the simultaneous fitting of the multiband variability curves, we obtain the acceleration and radiation parameters to constrain and distinguish the origins of different flares. Based on the flare decomposition, we can effectively reproduce the time-domain evolution trends of the optical variations and energy spectrum, and explain the various redder-when-brighter and bluer-when-brighter behaviors.

Moving Between Scales

This dissertation employs the perspective of library and information science (LIS) to inform and guide methodological reflections in two interdisciplinary fields, computational social science (CSS) and digital humanities (DH). However, CSS often prioritizes recent digital trace data over archival material from earlier periods, and the large-scale methods used in DH face criticism from humanists for their incapability to capture perspectival and interpretative nuances.
 This dissertation blends humanistic and social-scientific approaches to study premodern China, emphasizing the importance of “moving between scales.” It bridges different scales of analysis by transitioning dynamically between them, examines small-scale structures to uncover how they reflect large-scale dynamics, and explores mid-range social phenomena by investigating prosopography of elite society members. Four research questions are posed: (1) What are the challenges and opportunities in investigating a social network based on biased text? (2) How can prosopographical data lead to conclusions about the shifting center of political power? (3) How can structural characteristics in multiple networks reveal changes in political culture? (4) What can bibliographic metadata reveal about the particularity of publishing history of 16th-to-19th-century Chinese books?
 By addressing these questions, this dissertation intends to leverage theories and practices of LIS to develop computational models unveiling historical trends. It seeks to contribute to CSS by enhancing social scientists’ understanding on how societies and cultural systems evolve over time, to DH by revealing the historical changes in the longue durée in premodern China, and to LIS by fulfilling its mission of providing an information perspective to traditional academic disciplines.

Energy captivation in vibration of laminate nanocomposite cylinders using nonlocal strain gradient theory and artificial neural network

Artificial intelligence has revolutionized the process of solving engineering problems by facilitating predictions and optimizations with ease. The use of artificial neural networks (ANNs) for predicting the mechanical behavior of small-scale structures, particularly in the instability field, is widely prevalent. The present study aims to use an ANN to predict the frequency response of microscale spinning cylindrical laminate shells. Our ANN design utilizes a novel modified Adam optimizer for dimensional consistency, and a genetic algorithm is used for optimizing the number of nodes in the hidden layers of the ANN. ANNs require a valid dataset for training and testing, thus, a numerical solution of the size-dependent elasticity theory is generated, and a parametric study is conducted to find the dependency of vibrational responses on different parameters of the cylindrical shell resting on an elastic foundation equipped with a piezoelectric layer. These numerical results are utilized to train and test the designed ANN. The unique feature of the current ANN is the utilization of several well-known optimizers to observe their efficacy in solving the vibrational problem. The results of the vibration study from both numerical and ANN are presented using transverse displacement of the structure. The study finds that the AdaDelta optimizer performs satisfactorily in comparison to other optimization algorithms in terms of both total error and convergence rate.

Numerical Investigation of Cavitating Jet Flow Field with Different Turbulence Models

In numerous industries such as drilling, peening, cleaning, etc., a cavitating jet is adopted. However, it is challenging to simulate the cavitating flow field numerically with accuracy. The flow field of the organ pipe cavitation nozzle is simulated in this research using the RNG k−ε, DES, and LES turbulence models. The LES model can more accurately predict the periodic shedding of a cavitating cloud, which is basically consistent with the jet morphology captured with a high−speed camera. The flow pattern, cavitating cloud evolution and shedding period of a cavitating jet are analyzed. The findings demonstrate that the LES model produces a cavitating effect inside the nozzle that is superior to those produced by the RNG k−ε and DES models. The vortex rings in the diffusion section are simulated using the LES model, which accelerates cavitation. The cavitating clouds of the organ pipe nozzle show periodic evolutions, with stages of generation, development, shedding and collapse. The periodic shedding of the cavitating clouds exhibits a similar pattern in the vorticities simulated using the LES model, and the vorticities display the small-scale structures where the cavitating bubbles collapse. This study can provide a reference for the simulation of a cavitating jet and the analysis of the cavitating mechanism.

Compressed sensing reconstruction of sparse geophysical data: an example from regional magnetics

Reconstruction of discretely sampled geophysical data is generally done via gridding or interpolant algorithms. Such approaches typically consider local gradients which, while emphasising small-scale structure, can also introduce gridding artefacts, and modify the frequency characteristics of the original data. Here, we examine the potential of compressed sensing techniques for spatially-varying geophysical data, particularly line and gridded aeromagnetic data. We show that for sub-Nyquist sampling rates, the approach is still able to reconstruct a legible signal, and demonstrate the frequency representation of the reconstructed data varies with data sampling frequency, showing a reduced frequency range for sparser sampling. In contrast, we demonstrate that many widespread gridding approaches artificially introduce high-frequency signals into the gridded maps that are not present in the original nor in the compressed sensing reconstructions. This demonstrates the limitations of conventional gridding approaches in spectral fidelity and also suggests the conditions under which compressed sensing may be a more appropriate interpolant technique – namely when authentic spectral representation of the data is of higher precedent than small-scale target identification.

Relative baryon-dark matter velocities in cosmological zoom simulations

ABSTRACT Supersonic relative motion between baryons and dark matter due to the decoupling of baryons from the primordial plasma after recombination affects the growth of the first small-scale structures. Large box sizes (greater than a few hundred Mpc) are required to sample the full range of scales pertinent to the relative velocity, while the effect of the relative velocity is strongest on small scales (less than a few hundred kpc). This separation of scales naturally lends itself to the use of ‘zoom’ simulations, and here we present our methodology to self-consistently incorporate the relative velocity in zoom simulations, including its cumulative effect from recombination through to the start time of the simulation. We apply our methodology to a large-scale cosmological zoom simulation, finding that the inclusion of relative velocities suppresses the halo baryon fraction by 46–23 per cent between z = 13.6 and 11.2, in qualitative agreement with previous works. In addition, we find that including the relative velocity delays the formation of star particles by ∼20 Myr on average (of the order of the lifetime of a ∼9 M⊙ Population III star) and suppresses the final stellar mass by as much as 79 per cent at z = 11.2.

Spectral investigation of the interstellar cloud towards a runaway star AE Aur

Abstract The goal of this study is tracking of possible changes in the spectrum of the interstellar cloud seen along the sightline towards a runaway star AE Aur. The study considers variations in the radial velocities of the interstellar molecules and atoms, dwelling in the cloud, for the period ≈17 years. The most recent results of 6 year monitoring of equivalent widths variability for the CH and CH+ absorption lines are also presented. The study was done using the CH B-X(0,0) 3886 Å, A-X (0,0) 4300 Å and the CH+ A-X (1-0) 3958 Å, A-X (0,0) 4232 Å lines as well as the interstellar potassium K i 7699 Å line. Moreover a short discussion concerning the distance to the star is included. The present study is a continuation of our previous works and works of other researchers dedicated to the problem of small-scale structure in diffuse interstellar clouds. High resolution optical spectra from different spectrographs have been used in this work. The results of the study do not demonstrate significant changes in the radial velocities of the spectral features mentioned. The intensities of the CH and CH+ lines show slight tendency to vary at 1–3% level.