arXiv subjects

Shiyi Chen

Publications and source records attributed to Shiyi Chen.

At least 55 records · Page 3Linked to original sources

arXiv2021

High-order gas-kinetic scheme in general curvilinear coordinate for iLES of compressible wall-bounded turbulent flows

In this paper, a high-order gas-kinetic scheme in general curvilinear coordinate (HGKS-cur) is developed for the numerical simulation of compressible turbulence. Based on the coordinate transformation, the Bhatnagar-Gross-Krook (BGK) equation is transformed from physical space to computational space. To deal with the general mesh given by discretized points, the geometrical metrics need to be constructed by the dimension-by-dimension Lagrangian interpolation. The multidimensional weighted essentially non-oscillatory (WENO) reconstruction is adopted in the computational domain for spatial accuracy, where the reconstructed variables are the cell averaged Jacobian and the Jacobian-weighted conservative variables. The two-stage fourth-order method, which was developed for spatial-temporal coupled flow solvers, is used for temporal discretization. The numerical examples for inviscid and laminar flows validate the accuracy and geometrical conservation law of HGKS-cur. As a direct application, HGKS-cur is implemented for the implicit large eddy simulation (iLES) in compressible wall-bounded turbulent flows, including the compressible turbulent channel flow and compressible turbulent flow over periodic hills. The iLES results with HGKS-cur are in good agreement with the refereed spectral methods and high-order finite volume methods. The performance of HGKS-cur demonstrates its capability as a powerful tool for the numerical simulation of compressible wall-bounded turbulent flows and massively separated flows.

physics.flu-dyn↗

arXiv2021

Probing Negative Sampling Strategies to Learn GraphRepresentations via Unsupervised Contrastive Learning

Graph representation learning has long been an important yet challenging task for various real-world applications. However, their downstream tasks are mainly performed in the settings of supervised or semi-supervised learning. Inspired by recent advances in unsupervised contrastive learning, this paper is thus motivated to investigate how the node-wise contrastive learning could be performed. Particularly, we respectively resolve the class collision issue and the imbalanced negative data distribution issue. Extensive experiments are performed on three real-world datasets and the proposed approach achieves the SOTA model performance.

cs.LG↗

arXiv2020

Perturbation analysis of baroclinic torque in low-Mach-number flows

In this paper, we propse a series expansion of the baroclinic torque in low-Mach-number flows, so that the accuracy and universality of any buoyancy term could be examined analytically, and new types of buoyancy terms could be constructed and validated. We first demonstrate that the purpose of introducing a buoyancy term is to approximate the baroclinic torque, and straightforwardly the accuracy of any buoyancy term could be measured by the deviation of its curl from the baroclinic torque. Then a regular perturbation method is introduced for the elliptic equation of the hydrodynamic pressure in low-Mach-number flows, resulting in a sequence of Poisson equations, whose solutions lead to the series representation of the baroclinic torque and the new types of buoyancy terms. With the error definition of buoyancy terms and the series representation of the baroclinic torque, the classical gravitational and centrifugal buoyancy term, as well as some other previously proposed buoyancy terms are revisited. Finally, numerical simulations confirm that, with a decreasing density variation or an increasing order of our newly proposed buoyancy term, the simplified equations with one of the new types of buoyancy terms can converge to the original low-Mach-number equations.

physics.flu-dyn↗

arXiv2020

Obtaining the mean fields with known Reynolds stresses at steady state

With the rising of modern data science, data--driven turbulence modeling with the aid of machine learning algorithms is becoming a new promising field. Many approaches are able to achieve better Reynolds stress prediction, with much lower modeling error ($ε_M$), than traditional RANS models but they still suffer from numerical error and stability issues when the mean velocity fields are estimated using RANS equations with the predicted Reynolds stresses, illustrating that the error of solving the RANS equations ($ε_P$) is also very important. In the present work, the error $ε_P$ is studied separately by using the Reynolds stresses obtained from direct numerical simulation and we derive the sources of $ε_P$. For the implementations with known Reynolds stresses solely, we suggest to run an adjoint RANS simulation to make first guess on $ν_t^*$ and $S_{ij}^0$. With around 10 iterations, the error could be reduced by about one-order of magnitude in flow over periodic hills. The present work not only provides one robust approach to minimize $ε_P$, which may be very useful for the data-driven turbulence models, but also shows the importance of the nonlinear part of the Reynolds stresses in flow problems with flow separations.

physics.flu-dyn↗

arXiv2020

Heterogeneous-Temporal Graph Convolutional Networks: Make the Community Detection Much Better

Community detection has long been an important yet challenging task to analyze complex networks with a focus on detecting topological structures of graph data. Essentially, real-world graph data contains various features, node and edge types which dynamically vary over time, and this invalidates most existing community detection approaches. To cope with these issues, this paper proposes the heterogeneous-temporal graph convolutional networks (HTGCN) to detect communities from hetergeneous and temporal graphs. Particularly, we first design a heterogeneous GCN component to acquire feature representations for each heterogeneous graph at each time step. Then, a residual compressed aggregation component is proposed to represent "dynamic" features for "varying" communities, which are then aggregated with "static" features extracted from current graph. Extensive experiments are evaluated on two real-world datasets, i.e., DBLP and IMDB. The promising results demonstrate that the proposed HTGCN is superior to both benchmark and the state-of-the-art approaches, e.g., GCN, GAT, GNN, LGNN, HAN and STAR, with respect to a number of evaluation criteria.

cs.LG↗

arXiv2019

Dual channels of helicity cascade in turbulent flows

Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulence. From the traditional viewpoint, there exists only one channel of helicity cascade similar to that of kinetic energy cascade. Through theoretical analysis, we find that there are two channels in helicity cascade process. The first channel mainly originates from vortex twisting process, and the second channel mainly originates from vortex stretching process. By analysing the data of direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other type of turbulent flows. The second channel is more intermittent and acts more like a scalar, especially on small scales. Besides, we find a novel mechanism of hindered even inverse energy cascade, which could be attributed to the second-channel helicity flux with large amplitude.

physics.flu-dyn↗

arXiv2019

Role of magnetic field curvature in magnetohydrodynamic turbulence

Magnetic field are transported and tangled by turbulence, even as they lose identity due to nonideal or resistive effects. On balance field lines undergo stretch-twist-fold processes. The curvature field, a scalar that measures the tangling of the magnetic field lines, is studied in detail here, in the context of magnetohydrodynamic turbulence. A central finding is that the magnitudes of the curvature and the magnetic field are anti-correlated. High curvature co-locates with low magnetic field, which gives rise to power-law tails of the probability density function of the curvature field. The curvature drift term that converts magnetic energy into flow and thermal energy, largely depends on the curvature field behavior, a relationship that helps to explain particle acceleration due to curvature drift. This adds as well to evidence that turbulent effects most likely play an essential role in particle energization since turbulence drives stronger tangled field configurations, and therefore curvature.

physics.space-ph↗

arXiv2018

Scale dependence of energy transfer in turbulent plasma

In the context of space and astrophysical plasma turbulence and particle heating, several vocabularies emerge for estimating turbulent energy dissipation rate, including Kolmogorov-Yaglom third-order law and, in its various forms, $\boldsymbol{j}\cdot\boldsymbol{E}$ (work done by the electromagnetic field on particles), and $-\left( \boldsymbol{P} \cdot \nabla \right) \cdot \boldsymbol{u}$ (pressure-strain interaction), to name a couple. It is now understood that these energy transfer channels, to some extent, are correlated with coherent structures. In particular, we find that different energy dissipation proxies, although not point-wise correlated, are concentrated in proximity to each other, for which they decorrelate in a few $d_i$(s). However, the energy dissipation proxies dominate at different scales. For example, there is an inertial range over which the third-order law is meaningful. Contributions from scale bands stemming from scale-dependent spatial filtering show that, the energy exchange through $\boldsymbol{j}\cdot\boldsymbol{E}$ mainly results from large scales, while the energy conversion from fluid flow to internal through $-\left( \boldsymbol{P} \cdot \nabla \right) \cdot \boldsymbol{u}$ dominates at small scales.

physics.space-ph↗

arXiv2016

Aerodynamic Heating in Hypersonic Boundary Layers:\ Role of Dilatational Waves

The evolution of multi-mode instabilities in a hypersonic boundary layer and their effects on aerodynamic heating are investigated. Experiments are conducted in a Mach 6 wind tunnel using Rayleigh-scattering flow visualization, fast-response pressure sensors, fluorescent temperature-sensitive paint (TSP), and particle image velocimetry (PIV). Calculations are also performed based on both parabolized stability equations (PSE) and direct numerical simulations (DNS). It is found that second-mode dilatational waves, accompanied by high-frequency alternating fluid compression and expansion, produce intense aerodynamic heating in a small region that rapidly heats the fluid passing through it. As a result, the surface temperature rapidly increases and results in an overshoot over the nominal transitional value. When the dilatation waves decay downstream, the surface temperature decreases gradually until transition is completed. A theoretical analysis is provided to interpret the temperature distribution affected by the aerodynamic heating.

physics.flu-dyn↗

arXiv2016

Evolution of material surfaces in the temporal transition in channel flow

We report a Lagrangian study on the evolution of material surfaces in the K-type temporal transitional channel flow. Based on the Eulerian velocity field from the DNS, a backward-particle-tracking method is applied to solve the transport equation of the Lagrangian scalar field, and then the iso-surfaces of the Lagrangian field can be extracted as material surfaces in the evolution. Three critical issues for Lagrangian investigations on the evolution of coherent structures using material surfaces are addressed. First, the initial scalar field is uniquely determined based on proposed criteria, so that the initial material surfaces can be approximated as vortex surfaces, and keep invariant in the initial laminar state. Second, the evolution of typical material surfaces initially from different wall distances is presented, and then the influential material surface with the maximum deformation is identified. Large vorticity variations with the maximum curvature growth of vortex lines are also observed on this surface. Moreover, crucial events in the transition can be characterized in a Lagrangian approach by conditional statistics on the material surfaces. Finally, the influential material surface, which is initially a vortex surface, is demonstrated as a surrogate of the vortex surface before significant topological changes of vortical structures. Therefore, this material surface can be used to elucidate the continuous evolution of vortical structures in transitional wall-bounded flows in a Lagrangian perspective. The evolution of the influential material surface is divided into three stages: the formation of a triangular bulge from an initially disturbed streamwise-spanwise sheet, rolling up of the vortex sheet near the bulge ridges with the vorticity intensification, and the generation and evolution of signature hairpin-like structures with self-induced dynamics of vortex filaments.

physics.flu-dyn↗

arXiv2015

Effects of shock topology on temperature field in compressible turbulence

Effects of two types of shock topology, namely, small-scale shocklet and large-scale shock wave, on the statistics of temperature in compressible turbulence were investigated by simulations. The shocklet and shock wave are caused by the solenoidal and compressive modes of driven forces, respectively. Hereafter, the related two flows are called as SFT and CFT, respectively. It shows that in SFT the temperature spectrum follows the k^-5/3 power law, and the temperature field has "ramp-cliff" structures. By contrast, in CFT the temperature spectrum obeys the k^-2 power law, and the temperature field is dominated by large-scale rarefaction and compression. The power-law exponents for the p.d.f. of large negative dilatation are -2.5 in SFT and -3.5 in CFT, close to theoretical values. For the isentropic assumption of thermodynamic variables, the derivation in SFT grows with the turbulent Mach number (Mt), and for same Mt, the variables in CFT are more anisentropic. The angle statistics shows that the temperature gradient in CFT is preferentially perpendicular to the anisotropic strain rate tensor. It tends to be parallel with the first eigenvector and be orthogonal with the other two eigenvectors. For the cascade of temperature, the temperature variance is increased by the viscous dissipation and the pressure-dilatation, but is decreased by the SGS temperature flux. The statistics of pressure-dilatation proves that the negligible contribution of pressure-dilatation at small scales is due to the cancelations of high values between rarefaction and compression regions. The strongly positive skewness of the p.d.f.s of pressure-dilatation implies that the conversion from kinetic to internal energy through compression is more intense than the opposite process through rarefaction. Furthermore, in SFT the fluctuations of pressure-dilatation approximately follow the Zeman model.

physics.flu-dyn↗

arXiv2015

A numerical investigation on active and passive scalars in isotropic compressible turbulence

In this paper, we investigated the statistical differences between active and passive scalars in isotropic compressible turbulence. In the inertial range, the kinetic energy and scalar have the Kolmogorov spectra, and the Kolmogorov and Obukhov-Corrsin constants are 2.06 and 0.87, respectively. The local scaling exponents computed from the second-order structure functions exist plateaus for velocity and active scalar, while that for passive scalar takes first a minimum of 0.61 then a maximum of 0.73. The mixed third-order structure function of velocity and passive scalar satisfies the 4/3-law. For the scaling exponent, the one of velocity and passive scalar mixing is between those of velocity and passive scalar, while the one of velocity and active scalar mixing is below those of velocity and active scalar. At large amplitudes, the p.d.f. of active scalar fluctuations is super-Gaussian, whereas that of passive scalar fluctuations is sub-Gaussian. Moreover, the p.d.f.s of the two scalar increments are concave and convex shapes, respectively, which exhibit strong intermittency at small scales, and approach Gaussian as scale increases. The active scalar has "ramp-cliff" structures, while the passive scalar seems to be dominated by rarefaction and compression. By employing a "coarse-graining" approach, we study scalar cascades. Unlike passive scalar, the cascade of active scalar is mainly determined by the viscous dissipation at small scales and the pressure-dilatation at large scales, where the latter is substantial in the vicinity of small-scale shocklets but is negligible after space averages, because of the cancelations between rarefaction and compression regions. Finally, in the inertial range, the p.d.f.s for the subgrid-scale fluxes of scalars can collapse to the same distribution, revealing the scale-invariant feature for the statistics of active and passive scalars.

physics.flu-dyn↗

arXiv2015

Transition in Hypersonic Boundary Layers: Role of Dilatational Waves

Transition and turbulence production in a hypersonic boundary layer is investigated in a Mach 6 quiet wind tunnel using Rayleigh-scattering visualization, fast-response pressure measurements, and particle image velocimetry. It is found that the second instability acoustic mode is the key modulator of the transition process. The second mode experiences a rapid growth and a very fast annihilation due to the effect of bulk viscosity. The second mode interacts strongly with the first vorticity mode to directly promote a fast growth of the latter and leads to immediate transition to turbulence.

physics.flu-dyn↗

arXiv2008

A public turbulence database cluster and applications to study Lagrangian evolution of velocity increments in turbulence

A public database system archiving a direct numerical simulation (DNS) data set of isotropic, forced turbulence is described in this paper. The data set consists of the DNS output on $1024^3$ spatial points and 1024 time-samples spanning about one large-scale turn-over timescale. This complete $1024^4$ space-time history of turbulence is accessible to users remotely through an interface that is based on the Web-services model. Users may write and execute analysis programs on their host computers, while the programs make subroutine-like calls that request desired parts of the data over the network. The users are thus able to perform numerical experiments by accessing the 27 Terabytes of DNS data using regular platforms such as laptops. The architecture of the database is explained, as are some of the locally defined functions, such as differentiation and interpolation. Test calculations are performed to illustrate the usage of the system and to verify the accuracy of the methods. The database is then used to analyze a dynamical model for small-scale intermittency in turbulence. Specifically, the dynamical effects of pressure and viscous terms on the Lagrangian evolution of velocity increments are evaluated using conditional averages calculated from the DNS data in the database. It is shown that these effects differ considerably among themselves and thus require different modeling strategies in Lagrangian models of velocity increments and intermittency.

physics.flu-dyn↗

arXiv2006

What governs the fluidic behavior of water near single DNA molecules at the micro/nano scale

The fluidic behavior of water at the micro/nano scale is studied by using of single DNA molecules as a model system. Stable curved DNA patterns with spans about one micron were generated by using of water flows, and observed by Atomic Force Microscopy. By rigorously comparing the numerical simulation results with these patterns, it is suggested that the form of the macroscopic hydrodynamic equation still works quantitatively well on the fluid flows at the nanoscale. The molecular effects, however, are still apparent that the effective viscosity of the adjacent water is considerably larger than its bulk value. Our observation is also helpful to understand of the dynamics of biomolecules in solutions from nanoscale to microscale.

physics.bio-ph↗

arXiv2006

Is the Kelvin Theorem Valid for High-Reynolds-Number Turbulence?

The Kelvin-Helmholtz theorem on conservation of circulations is supposed to hold for ideal inviscid fluids and is believed to be play a crucial role in turbulent phenomena, such as production of dissipation by vortex line-stretching. However, this expectation does not take into account singularities in turbulent velocity fields at infinite Reynolds number. We present evidence from numerical simulations for the breakdown of the classical Kelvin theorem in the three-dimensional turbulent energy cascade. Although violated in individual realizations, we find that circulations are still conserved in some average sense. For comparison, we show that Kelvin's theorem holds for individual realizations in the two-dimensional enstrophy cascade, in agreement with theory. The turbulent ``cascade of circulations'' is shown to be a classical analogue of phase-slip due to quantized vortices in superfluids and various applications in geophysics and astrophysics are outlined.

physics.flu-dyn↗

arXiv2005

Resolving singular forces in cavity flow: Multiscale modeling from atoms to millimeters

A multiscale approach for fluid flow is developed that retains an atomistic description in key regions. The method is applied to a classic problem where all scales contribute: The force on a moving wall bounding a fluid-filled cavity. Continuum equations predict an infinite force due to stress singularities. Following the stress over more than six decades in length in systems with characteristic scales of millimeters and milliseconds allows us to resolve the singularities and determine the force for the first time. The speedup over pure atomistic calculations is more than fourteen orders of magnitude. We find a universal dependence on the macroscopic Reynolds number, and large atomistic effects that depend on wall velocity and interactions.

cond-mat.mtrl-sci↗

arXiv2002

Dynamics of Freely Cooling Granular Gases

We study dynamics of freely cooling granular gases in two-dimensions using large-scale molecular dynamics simulations. We find that for dilute systems the typical kinetic energy decays algebraically with time, E(t) ~ t^{-1}, in the long time limit. Asymptotically, velocity statistics are characterized by a universal Gaussian distribution, in contrast with the exponential high-energy tails characterizing the early homogeneous regime. We show that in the late clustering regime particles move coherently as typical local velocity fluctuations, Delta v, are small compared with the typical velocity, Delta v/v ~ t^{-1/4}. Furthermore, locally averaged shear modes dominate over acoustic modes. The small thermal velocity fluctuations suggest that the system can be heuristically described by Burgers-like equations.

cond-mat.stat-mech↗