Flow of clays

Recent experimental and theoretical research into physical phenomena in clays is reviewed. Clays’ present place in the context of modern materials science is briefly discussed, and illustrated through the rich behavior recently displayed in this physical model system. We will show that in order to understand macroscopic flow behaviors in these systems, it is crucial to know the underlying nanostructures in detail. With the clay nanostructural basis at hand, we will review recent advances in clay systems from the geological example of quick clay flows and avalanches, to materials science and the stability, strength and flow of smart electrorheological clay structures. In the case of natural quick clay, there is now hope of establishing a protocol for avalanche preditction based on rheological sample data. In materials science, the use of electric fields together with flow in order to improve the processing of clay composite materials may open new unexplored avenues. We will finally discuss that due to the interplay of van der Waals and electrostatic forces screened by ions at the nanoscale, clays may either form a glass, or a gel and thus give fundamental insights into the elusive questions related to materials universal aging flow dynamics.     

New Feedback Control Model in the Lattice Hydrodynamic Model Considering the Historic Optimal Velocity Difference Effect

A feedback control model of lattice hydrodynamic model is proposed by taking the information of the historic optimal velocity into account for the traffic system. The modern control theory is applied for the linear stability condition with feedback control signal. The result shows that the stability of traffic flow is closely related to the information of the historic optimal velocity. Furthermore, numerical simulations conform that the new feedback control did increase the stability of traffic flow efficiently, which is in accord with theoretical analysis.     

Turbulent structures in cylindrical density currents in a rotating frame of reference

Gravity currents are flows generated by the action of gravity on fluids with different densities. In some geophysical applications, modeling such flows makes it necessary to account for rotating effects, modifying the dynamics of the flow. While previous works on rotating stratified flows focused on currents of large Coriolis number, the present work focuses on flows with small Coriolis numbers (i.e. moderate-to-large Rossby numbers). In this work, cylindrical rotating gravity currents are investigated by means of highly resolved simulations. A brief analysis of the mean flow evolution to the final state is presented to provide a complete picture of the flow dynamics. The numerical results, showing the well-known oscillatory behavior of the flow (inertial waves) and a final state lens shape (geostrophic adjustment), are in good agreement with experimental observations and theoretical models. The turbulent structures in the flow are visualized and described using, among others, a stereoscopic visualization and videos as supplementary material. In particular, the structure of the lobes and clefts at the front of the current is presented in association to local turbulent structures. In rotating gravity currents, the vortices observed at the lobes front are not of hairpin type but are rather of Kelvin-Helmholtz type.     

Global stability analysis of fluid flows using sum-of-squares

This paper introduces a new method for proving global stability of fluid flows through the construction of Lyapunov functionals. For finite dimensional approximations of fluid systems, we show how one can exploit recently developed optimization methods based on sum-of-squares decomposition to construct a polynomial Lyapunov function. We then show how these methods can be extended to infinite dimensional Navier-Stokes systems using robust optimization techniques. Crucially, this extension requires only the solution of infinite-dimensional linear eigenvalue problems and finite-dimensional sum-of-squares optimization problems.We further show that subject to minor technical constraints, a general polynomial Lyapunov function is always guaranteed to provide better results than the classical energy methods in determining a lower-bound on the maximum Reynolds number for which a flow is globally stable, if the flow does remain globally stable for Reynolds numbers at least slightly beyond the energy stability limit. Such polynomial functions can be searched for efficiently using the SOS technique we propose.     

蛋白质空间结构的实验技术和理论方法

文章主要介绍几种蛋白质空间结构的实验测定方法，在现代生物学研究中，最常用的方法包括X射线晶体学、二维核磁共振（2D-NMR）和低温冷冻电镜，近几年发展起来的单分子技术在生物大分子动态结构的研究中应用越来越多，这些方法都有它们特定的时间和空间分辨率，所测定的结构及其动力学受环境热运动涨落的影响也非常不同，文章对这些问题作了较详细的分析，在蛋白质结构的理论方法方面，介绍了一个新的折叠理论及其与现有折叠模型的关系．讨论了模拟计算在研究蛋白质构象变化和动力学方面的应用，同时强调了分子动力学和蒙特卡罗方法．指出粗粒化模型是研究的热点之一，对生物学中经常遇到的多长度多时问尺度问题提供了一个可行的解决方案。     

Brain-like large scale cognitive networks and dynamics

A new approach to the study of the brain and its functions known as Human Connectomics has been recently established. Starting from magnetic resonance images (MRI) of brain scans, it is possible to identify the fibers that link brain areas and to build an adjacency matrix that connects these areas, thus creating the brain connectome. The topology of these networks provides a lot of information about the organizational structure of the brain (both structural and functional). Nevertheless this knowledge is rarely used to investigate the possible emerging brain dynamics linked to cognitive functions. In this work, we implement finite state models on neural networks to display the outcoming brain dynamics, using different types of networks, which correspond to diverse segmentation methods and brain atlases. From the simulations, we observe that the behavior of these systems is completely different from random and/or artificially generated networks. The emergence of stable structures, which might correspond to brain cognitive circuits, has also been detected.     

Study of vortex core precession in combustion chambers

The article presents the results of experimental investigation of swirling flow of lean propane/air flame in a model combustion chamber at atmospheric pressure. To study the unsteady turbulent flow, the particle image velocimetry technique was used. It was concluded that dynamics of high swirl flows with and without combustion was determined by a global helical mode, complying with a precessing double-spiral coherent vortex structure. The studied low swirl flame had similar size and stability characteristics, but amplitude of the coherent helical structure substantially oscillated in time. The oscillations were associated with intermittently appearing central recirculation zone that was absent in the nonreacting flow. It is expected that the low swirl flow without the permanent central recirculation zone should be more sensitive to an external active control. In particular, this result may be useful for suppression of thermoacoustic resonance in combustion chambers.     

Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition

Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity “dendrophilia”, and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology.     

相对论重离子碰撞中的软探针和硬探针

简要回顾了高能核碰撞中夸克胶子等离子体的软探针和硬探针的一些最新进展,主要内容集中在相对论重离子对撞机和大型强子对撞机实验中各向异性集体流和喷注淬火的理论和唯象研究,对小系统中集体流的来源也做了简要的讨论。对于软探针,讨论了初态三维涨落和碰撞几何各向异性、相对论流体力学演化、末态各向异性集体流以及集体流的涨落、关联和纵向去关联等。通过与实验数据作系统的比较,可以探测重离子碰撞中夸克胶子等离子体的动力演化和各种输运性质。对于硬探针,集中讨论了部分子能量损失和喷注淬火对部分子味道的依赖性、重味夸克在夸克胶子等离子体中的强子化、整体喷注在核介质中的演化以及核介质对喷注的响应等。细致分析相关的观测量,可以帮助我们更全面地了解相对论核碰撞中喷注与核介质的相互作用以及重味粒子的生成。对于小系统,讨论初态和末态效应在解释小系统中轻强子和重味强子的集体流方面的贡献,这有助于我们理解大碰撞系统中集体流的起源成因。     

Density waves and the effect of wall roughness in granular Poiseuille flow: Simulationand linear stability

The formation of density waves and the effect of wall roughness on them are studied using molecular dynamics simulations of gravity-driven granular Poiseuille flow. Three basic types of structures are found in moderately dense flows: a plug, a sinuous wave and a slug; a new varicose wave mode has been identified in dense flows with channels of large widths at moderate dissipations; only clump-like structures appear in dilute flows. The simulation results are contrasted with the predictions of a linear stability analysis of the kinetic-theory continuum equations for granular Poiseuille flow. The theoretical predictions on the form of density waves are in qualitative agreement with simulations in denser flows, however, there are discrepancies between simulation and theory in dilute flows.     

基于Lattice Boltzmann方法的圆柱绕流大涡模拟

Lattice Boltzmann(LB)方法是近年来出现的一种流体计算的新方法,在流体力学及相关领域取得了很大的成功。但LB方法在模拟湍流流动时常常引起计算的不稳定。本文基于一种结合大涡模型的LB方法对圆柱绕流问题进行的模拟,并与其他文献的实验结果和计算结果进行对比。计算表明:这种混合LB方法能获得比较满意的结果。     

低频振荡电位的能量和相位稳定性与偶极子电流活动相关性的仿真

能量和相位是分析脑节律的重要物理量, 虽有许多研究, 但其与脑组织电特性和脑节律源的关系尚不完全清楚, 弄清这一问题有助于脑电测量及脑功能和疾病的分析. 为此, 借鉴脑电正问题研究方法, 大脑可看作均匀球, 脑组织电特性用导体各向同性和各向异性电导率来表示, 脑节律源用准静态偶极子电流来模拟, 其活动表达为较低频率的正弦振荡, 在改变该活动的振幅和相位时程时, 用球表面剖分网格的振荡电位仿真脑节律, 提取节律的能量和相位, 计算源和节律的窄带相位稳定性. 结果表明: 仿真节律的能量随电导率增大而减小, 受网格位置、电导率各向异性、偶极子电流幅值和偏心位置影响较大; 但仿真节律的相位稳定性只与自身的相位时程有关. 说明能量与相位稳定性电学意义无交集, 同时用来分析脑节律可提供更多神经信息; 能量的电学意义更复杂, 取决于包括测量条件在内的多种因素; 相位稳定性的优势在于它仅与脑节律相位时程直接相关, 可预测的是脑的非线性导致的相位时程越离散, 则相位稳定性越差.     

Scrape-off layer width set by non-linear streamer flows in drift wave turbulence

In this work, we discuss the physics behind the excitation of non-linear streamer flows in drift wave turbulence and how to selectively excite these flows. Streamer flows are modelled as a non-linear, radially elongated convective cell in drift wave turbulence. It is shown that density modulation is key for exciting streamer flows. We show that streamer flows have a finite frequency, albeit smaller than that of drift waves. Streamers propagate in the ion direction. These theoretical predictions are compared against experimental data, which shows reasonable agreement. Finally, the scrape-off layer width set by streamer flows is calculated, and a scaling law against macroscopic plasma parameters is obtained.     

The canonical problem of the fluid-conveying pipe and radiation of the knowledge gained to other dynamics problems across Applied Mechanics

The basic dynamics of pipes conveying fluid is reviewed, establishing why this system has become a model dynamical problem. The paper then discusses the radiation of the experience gained in studying this problem into other areas of Applied Mechanics, particularly other problems in fluid-structure interactions involving slender structures and axial flows; specifically the dynamics of (i) quasi-cylindrical bodies in axial flow or towed in quiescent fluid; (ii) cylindrical shells containing or immersed in axial flow; and (iii) plates in axial flow. Applications, some of them wholly unexpected when the work was done, are noted throughout.     

Breakup of Thin Liquid Filaments on Partially Wetting Substrates: from Micrometric to Nanometric Scales

We present theoretical and experimental results regarding the instability of a thin liquid film in the form a long filament sitted on a solid substrate. We consider this problem in two different scenarios, namely, at submillimetric and nanometric scales, and we study their free surface instability. In the first scale, we take into account the effects due to surface tension and gravity, while in the smaller scale, we add intermolecular interaction and neglect gravity. The flows are modeled within the long wave approximation, which leads to a nonlinear fourth-order differential equation for the fluid thickness. This model equation also includes the partial wetting condition between the liquid and the solid. In the theoretical models, we analyze the linear stability of the equilibrium configurations. The linear stability analyses lead to eigenvalue problems that are solved using pseudo spectral methods in the submillimetric case, and finite differences in the nanoscale. Whenever possible, the theoretical results are compared with experiments performed on a submillimetric scale (silicon oils on glass), as well as on nanometric scale (nickel films melted by laser irradiation on SiO2 substrates).     

Towards understanding the behavior of physical systems using information theory

One of the goals of complex network analysis is to identify the most influential nodes, i.e., the nodes that dictate the dynamics of other nodes. In the case of autonomous systems or transportation networks, highly connected hubs play a preeminent role in diffusing the flow of information and viruses; in contrast, in language evolution most linguistic norms come from the peripheral nodes who have only few contacts. Clearly a topological analysis of the interactions alone is not sufficient to identify the nodes that drive the state of the network. Here we show how information theory can be used to quantify how the dynamics of individual nodes propagate through a system. We interpret the state of a node as a storage of information about the state of other nodes, which is quantified in terms of Shannon information. This information is transferred through interactions and lost due to noise, and we calculate how far it can travel through a network. We apply this concept to a model of opinion formation in a complex social network to calculate the impact of each node by measuring how long its opinion is remembered by the network. Counter-intuitively we find that the dynamics of opinions are not determined by the hubs or peripheral nodes, but rather by nodes with an intermediate connectivity.     

A time-reversal lattice Boltzmann method

In this paper we address the time-reversed simulation of viscous flows by the lattice Boltzmann method (LB). The theoretical derivation of the reversed LB from the Boltzmann equation is detailed, and the method implemented for weakly compressible flows using the D2Q9 scheme. The implementation of boundary conditions is also discussed. The accuracy and stability are illustrated by four test cases, namely the propagation of an acoustic wave in a medium at rest and in an uniform mean flow, the Taylor–Green vortex decay and the vortex pair–wall collision.     

A Lattice Boltzmann Kinetic Model for Microflow and Heat Transfer

In this paper, we propose a lattice Boltzmann BGK model for simulation of micro flows with heat transfer based on kinetic theory and the thermal lattice Boltzmann method (He et al., J. Comp. Phys. 146:282, 1998). The relaxation times are redefined in terms of the Knudsen number and a diffuse scattering boundary condition (DSBC) is adopted to consider the velocity slip and temperature jump at wall boundaries. To check validity and potential of the present model in modelling the micro flows, two two-dimensional micro flows including thermal Couette flow and thermal developing channel flow are simulated and numerical results obtained compare well with previous studies of the direct simulation Monte Carlo (DSMC), molecular dynamics (MD) approaches and the Maxwell theoretical analysis