Coarse-grained atomistic simulation of dislocations

This paper presents a new methodology for coarse-grained atomistic simulation of dislocation dynamics. The methodology combines an atomistic formulation of balance equations and a modified finite element method employing rhombohedral-shaped 3D solid elements suitable for fcc crystals. With significantly less degrees of freedom than that of a fully atomistic model and without additional constitutive rules to govern dislocation activities, this new coarse-graining (CG) method is shown to be able to reproduce key phenomena of dislocation dynamics for fcc crystals, including dislocation nucleation and migration, formation of stacking faults and Lomer-Cottrell locks, and splitting of stacking faults, all comparable with fully resolved molecular dynamics simulations. Using a uniform coarse mesh, the CG method is then applied to simulate an initially dislocation-free submicron-sized thin Cu sheet. The results show that the CG simulation has captured the nucleation and migration of large number of dislocations, formation of multiple stacking fault ribbons, and the occurrence of complex dislocation phenomena such as dislocation annihilation, cutting, and passing through the stacking faults. The distinctions of this method from existing coarse-graining or multiscale methods and its potential applications and limitations are also discussed.     

Effects of atrial fibrillation on the arterial fluid dynamics: a modelling perspective

Atrial fibrillation (AF) is the most common form of arrhythmia with accelerated and irregular heart rate (HR), leading to both heart failure and stroke and being responsible for an increase in cardiovascular morbidity and mortality. In spite of its importance, the direct effects of AF on the arterial hemodynamic patterns are not completely known to date. Based on a multiscale modelling approach, the proposed work investigates the effects of AF on the local arterial fluid dynamics. AF and normal sinus rhythm (NSR) conditions are simulated extracting 2000 \({\mathrm {RR}}\) heartbeats and comparing the most relevant cardiac and vascular parameters at the same HR (75 bpm). Present outcomes evidence that the arterial system is not able to completely absorb the AF-induced variability, which can be even amplified towards the peripheral circulation. AF is also able to locally alter the wave dynamics, by modifying the interplay between forward and backward signals. The sole heart rhythm variation (i.e., from NSR to AF) promotes an alteration of the regular dynamics at the arterial level which, in terms of pressure and peripheral perfusion, suggests a modification of the physiological phenomena ruled by periodicity (e.g., regular organ perfusion) and a possible vascular dysfunction due to the prolonged exposure to irregular and extreme values. The present study represents a first modeling approach to characterize the variability of arterial hemodynamics in presence of AF, which surely deserves further clinical investigation.     

关于功率谱密度与风速谱的注记

探讨了随机过程中双边功率谱密度负频率引入的原因,实际的频谱函数应将负频率项与相应正频率项成对合并起来而直流分量保持不变,此即单边功率谱所表达的含义.对目前文献中给出的单边功率谱的表达式和单边功率谱与双边功率谱的关系式进行了修正,并对维纳-辛钦公式的变换形式也做了相应的修正,指出其修正前后在不同风速谱实际应用中的区别.算例证明了本文所给公式的正确性.     

Dynamics of firing patterns, synchronization and resonances in neuronal electrical activities： experiments and analysis

Recent advances in the experimental and theoretical study of dynamics of neuronal electrical firing activities are reviewed. Firstly, some experimental phenomena of neuronal irregular firing patterns, especially chaotic and stochastic firing patterns, are presented, and practical nonlinear time analysis methods are introduced to distinguish deterministic and stochastic mechanism in time series. Secondly, the dynamics of electrical firing activities in a single neuron is concerned, namely, fast-slow dynamics analysis for classification and mechanism of various bursting patterns, one- or two-parameter bifurcation analysis for transitions of firing patterns, and stochastic dynamics of firing activities （stochastic and coherence resonances, integer multiple and other firing patterns induced by noise, etc.）. Thirdly, different types of synchronization of coupled neurons with electrical and chemical synapses are discussed. As noise and time delay are inevitable in nervous systems, it is found that noise and time delay may induce or enhance synchronization and change firing patterns of coupled neurons. Noise-induced resonance and spatiotemporal patterns in coupled neuronal networks are also demonstrated. Finally, some prospects are presented for future research. In consequence, the idea and methods of nonlinear dynamics are of great significance in exploration of dynamic processes and physiological functions of nervous systems.     

Dynamics of mechanical systems involving impact and friction using an efficient contact detection algorithm

In this work, some new results are presented on the dynamics of a class of multibody mechanical systems, involving contact and friction. The main contribution refers to the development of a systematic, accurate and efficient method for detecting contact among the components of a system of solid bodies. For some simple geometries, this task is achieved by employing analytical means. For systems possessing components with complex geometric shapes a more involved numerical methodology is developed. In both cases, once a potential contact point is detected, the common tangent plane and normal vector are located and the penetration depth is calculated, leading to determination of the force arising between the contacting bodies. This information is then passed to a solver, providing the full dynamic response of the system. The validity and numerical efficiency of the methodology developed is first demonstrated by considering a number of examples with relatively small geometric complexity but large traditional value and interesting dynamic response. Some new results are obtained and presented on the dynamics of these systems. Finally, the same methodology is also tested in a more complicated and demanding mechanical application.     

Parametric characteristic of the random vibration response of nonlinear systems

Volterra series is a powerful mathematical tool for nonlinear system analysis,and there is a wide range of nonlinear engineering systems and structures that can be represented by a Volterra series model.In the present study,the random vibration of nonlinear systems is investigated using Volterra series.Analytical expressions were derived for the calculation of the output power spectral density(PSD) and input-output cross-PSD for nonlinear systems subjected to Gaussian excitation.Based on these expressions,it was revealed that both the output PSD and the input-output crossPSD can be expressed as polynomial functions of the nonlinear characteristic parameters or the input intensity.Numerical studies were carried out to verify the theoretical analysis result and to demonstrate the effectiveness of the derived relationship.The results reached in this study are of significance to the analysis and design of the nonlinear engineering systems and structures which can be represented by a Volterra series model.     

Theoretical Approach of Bubble Entrapment Through Interconnected Pores: Supplying Principle

Fiber-reinforced composite materials are often composed of fibers collected in bundles that are stitched together. During the impregnation of a fibrous preform by a liquid resin, the multiscale porous medium leads to an heterogenous flow front, and therefore bubbles may be created and entrapped. Indeed, for a wetting system, capillary pressure is higher inside bundle, due to the microspace between fibers, than outside the bundles that represent the macrospace, thus, inducing an overflow between both pore scales. Motivated by the prediction of bubble formation during fiber fabric infiltration for composite materials, we attempt to determine the bubble rate in imbibition through a simple model network with two connected capillaries, called ??Pore Doublet Model?? (PDM). Our system is composed of two parts: a first part, continuously interconnected, in which the suppling mass to the microchannel from the macrochannel occurs, and a second part connected only by nodes. To quantify the leading flow front, a theoretical model based on the supplying principle and arranged Washburn equation is proposed. This approach has been conducted for wetting liquids, Newtonian flows, incompressible fluids and pores, no inertial and gravitational forces and no dynamic contact angle. The geometrical variability (channel radius and length) and the different configuration of connections (continuous and discrete) influence the entrapped bubble rate, leading to either microbubble in the microchannel or macrobubble in the macrochannel. The outcomes can contribute to the knowledge of void formation especially during the filling of fibrous preforms and may extend the previous works on the PDM in general.     

Particle size distribution in CPFD modeling of gas-solid flows in a CFB riser

A computational particle fluid dynamics(CPFD) numerical method to model gas-solid flows in a circulating fluidized bed(CFB) riser was used to assess the effects of particle size distribution(PSD) on solids distribution and flow.We investigated a binary PSD and a polydisperse PSD case.Our simulations were compared with measured solids concentrations and velocity profiles from experiments,as well as with a published Eulerian-Eulerian simulation.Overall flow patterns were similar for both simulation cases,as confirmed by experimental measurements.However,our fine-mesh CPFD simulations failed to predict a dense bottom region in the riser,as seen in other numerical studies.Above this bottom region,distributions of particle volume fraction and particle vertical velocity were consistent with our experiments,and the simulated average particle diameter decreased as a power function with riser height.Interactions between particles and walls also were successfully modeled,with accurate predictions for the lateral profiles of particle vertical velocity.It was easy to implement PSD into the CPFD numerical model,and it required fewer computational resources compared with other models,especially when particles with a polydisperse PSD were present in the heterogeneous flow.     

A methodology for coupling DNS and discretised population balance for modelling turbulent precipitation

In this paper, we present a methodology for simulating nanoparticle formation in a turbulent flow by coupling Direct Numerical Simulation (DNS) and population balance modelling. The population balance equation (PBE) is solved via a discretisation method employing a composite grid that provides sufficient detail over the wide range of particle sizes reached during the precipitation process. The coupled DNS/PBE approach captures accurately the strong interaction between the dynamics of turbulent mixing and particle formation processes. It also allows the calculation of the particle size distribution (PSD) of the product and enables an investigation on how it is controlled by turbulent mixing. Finally, it provides the statistics of kinetic processes and their timescales so that further analysis can be performed. The methodology is applied to the simulation of experiments of hydrodynamics and nanoparticle precipitation in a T-mixer (Schwertfirm et al., Int. J. of Heat and Fluid Flow 28, pp. 1429–1442; Schwarzer et al., Chem. Eng. Sci. 61, pp. 167–181), and the agreement with the experimental results is very good.     

一类非线性系统的随机振动频率响应分析研究

Volterra级数是研究非线性系统的一种重要数学工具, 它可看作线性系统理论中的卷积运算在非线性系统分析中的推广. 基于Volterra级数, 给出了受高斯白噪声激励下的非线性系统输出功率谱的计算公式. 公式表明, 该系统输出功率谱可用激励强度的多项式函数来表示, 其结果为研究激励强度对非线性系统输出功率谱的影响提供了有效途径.      

Particle size distribution in CPFD modeling of gas–solid flows in a CFB riser

A computational particle fluid dynamics (CPFD) numerical method to model gas–solid flows in a circulating fluidized bed (CFB) riser was used to assess the effects of particle size distribution (PSD) on solids distribution and flow. We investigated a binary PSD and a polydisperse PSD case. Our simulations were compared with measured solids concentrations and velocity profiles from experiments, as well as with a published Eulerian-Eulerian simulation. Overall flow patterns were similar for both simulation cases, as confirmed by experimental measurements. However, our fine-mesh CPFD simulations failed to predict a dense bottom region in the riser, as seen in other numerical studies. Above this bottom region, distributions of particle volume fraction and particle vertical velocity were consistent with our experiments, and the simulated average particle diameter decreased as a power function with riser height. Interactions between particles and walls also were successfully modeled, with accurate predictions for the lateral profiles of particle vertical velocity. It was easy to implement PSD into the CPFD numerical model, and it required fewer computational resources compared with other models, especially when particles with a polydisperse PSD were present in the heterogeneous flow.     

Spatiotemporal complexity of the aortic sinus vortex

The aortic sinus vortex is a classical flow structure of significant importance to aortic valve dynamics and the initiation and progression of calcific aortic valve disease. We characterize the spatiotemporal characteristics of aortic sinus vortex dynamics in relation to the viscosity of blood analog solution as well as heart rate. High-resolution time-resolved (2 kHz) particle image velocimetry was conducted to capture 2D particle streak videos and 2D instantaneous velocity and streamlines along the sinus midplane using a physiological but rigid aorta model fitted with a porcine bioprosthetic heart valve. Blood analog fluids used include a water–glycerin mixture and saline to elucidate the sensitivity of vortex dynamics to viscosity. Experiments were conducted to record 10 heart beats for each combination of blood analog and heart rate condition. Results show that the topological characteristics of the velocity field vary in timescales as revealed using time bin-averaged vectors and corresponding instantaneous streamlines. There exist small timescale vortices and a large timescale main vortex. A key flow structure observed is the counter vortex at the upstream end of the sinus adjacent to the base (lower half) of the leaflet. The spatiotemporal complexity of vortex dynamics is shown to be profoundly influenced by strong leaflet flutter during systole with a peak frequency of 200 Hz and peak amplitude of 4 mm observed in the saline case. While fluid viscosity influences the length and timescales as well as the introduction of leaflet flutter, heart rate influences the formation of counter vortex at the upstream end of the sinus. Higher heart rates are shown to reduce the strength of the counter vortex that can greatly influence the directionality and strength of shear stresses along the base of the leaflet. This study demonstrates the impact of heart rate and blood analog viscosity on aortic sinus hemodynamics.     

The collective bursting dynamics in a modular neuronal network with synaptic plasticity

In this study, how the synaptic plasticity influences the collective bursting dynamics in a modular neuronal network is numerically investigated. The synaptic plasticity is described by a modified Oja’s learning rule. The modular network is composed of some sub-networks, each of them having small-world characteristic. The result indicates that bursting synchronization can be induced by large coupling strength between different neurons, which is robust to the local dynamical parameter of individual neurons. With the emergence of synaptic plasticity, the bursting dynamics in the modular neuronal network, particularly the excitability and synchronizability of bursting neurons, is detected to be changed significantly. In detail, upon increasing synaptic learning rate, the excitability of bursting neurons is greatly enhanced; on the contrary, bursting synchronization between interacted neurons is a little suppressed by the increase in synaptic learning rate. The presented findings could be helpful to understand the important role of synaptic plasticity on neural coding in realistic neuronal network.     

神经系统疾病与认知动力学(II): 神经振荡与认知动力学

大脑神经系统具有从慢到快多种不同的振荡节律, 这些节律振荡被认为参与了大脑多种功能的实现, 其中高频的伽马同步振荡被认为与大脑的认知功能最为相关. 本文阐述了生物学实验方面关于伽马振荡及其功能的研究进展, 并针对实验中伽马振荡的频率敏感依赖于外部刺激特征的现象, 综述了基于神经网络模型进行变频伽马振荡及其认知功能的动力学建模研究工作, 解释了视觉刺激调控的变频率伽马振荡动力学产生机理, 提出了基于同步抑制增强全局放电率对比度的神经认知机制. 研究成果有助于理解神经系统同步振荡的产生机理及其认知作用, 为大脑认知原理以及类脑智能的研究奠定基础.      

Multiscale dislocation dynamics analyses of laser shock peening in silicon single crystals

Although laser shock peening (LSP) has been applied in metals for property enhancement for a long time, its application on brittle materials has not been investigated so far. The present work is the first computational attempt to show that strong dislocation activity can be generated in silicon crystal by a modified LSP process. Multiscale dislocation dynamics plasticity (MDDP) simulations are conducted to predict the dislocation structure and stress/strain distribution in silicon crystal during LSP. In the modified LSP process, dislocation mobility of silicon and shock pressure is sufficiently high to generate and transport dislocation. The relationships between dislocation activities, the laser processing conditions and ablative coating material are systematically investigated. It is found that dislocation density, dislocation multiplication rate, and dislocation microstructure strongly depend on LSP processing conditions. This LSP process can also be applied in other brittle materials.     

Nonlinear pedagogy: a constraints-led framework for understanding emergence of game play and movement skills

Team sport competition can be characterized as a complex adaptive system in which concepts from nonlinear dynamics can provide a sound theoretical framework to understand emergent behavior such as movement coordination and decision making in game play. Nonlinear Pedagogy is presented as a methodology for games teaching, capturing how phenomena such as movement variability, self-organization, emergent decision making, and symmetry-breaking occur as a consequence of interactions between agent-agent and agent-environment constraints. Empirical data from studies of basketball free-throw shooting and dribbling are used as task vehicles to exemplify how nonlinear phenomena characterize game play in sport. In this paper we survey the implications of these data for Nonlinear Pedagogy, focusing particularly on the manipulation of constraints in team game settings. The data and theoretical modeling presented in this paper provide a rationale in nonlinear dynamics for the efficacy of a prominent model of game play teaching, Teaching Games for Understanding approach.     

On translational and rotational relative velocities of fibers and fluid in a turbulent channel flow with a backward-facing step

A dilute fiber suspension in a turbulent channel with a backward-facing step is investigated by means of Feature Tracking. Its combination with a phase-discrimination methodology, which is described in detail, allows simultaneous and separate measurement of carrier and dispersed phases velocity fields, the orientation and rotation rate of fibers as well as the fiber–fluid translational and rotational slip velocities. The patterns of fibers concentration, angular velocity and the probability distribution of fibers velocity appear to be dominated by the mechanical interactions with the wall and the local high shear rather than by near-wall turbulent structures. The translational slip velocity obtained from instantaneous data shows that fibers move faster than the surrounding fluid inside the buffer layer, the velocity gap reducing gradually when approaching the channel centerline. On the other hand, the rotational slip profile suggests a gradual decoupling of the translational and rotational dynamics. Downstream of the step, the excess of streamwise velocity displayed by fibers is still observed and extends in the free-shear region, whereas the rotation rate slip decreases at a relatively short distance from the step, as the effect of the wall presence fades away.     

Model determination for nonlinear state-based system identification

A complete methodology for robust nonlinear system identification is derived and illustrated through example. A proven state estimation algorithm is utilized in conjunction with a modified version of a stepwise regression approach to successfully determine the nonlinear dynamics in a “known” truth simulation without a priori knowledge of the system model. First, Minimum Model Error (MME) estimation is derived and illustrated through example. MME is a robust state estimation routine that provides, in addition to smooth states, an estimate of the unmodeled system dynamics is determined from noisy measurement data of known variance. Next, an Analysis of Variance (ANOVA) model correlation routine where a modified version of a forward stepwise procedure is derived and implemented. The ANOVA approach to model acceptance is well documented primarily in social science literature, but has been sparsely written about for engineering applications. This paper shows a significant improvement in nonlinear model identification when used in conjunction with MME estimation.     

A reversible problem in non-equilibrium thermodynamics: Hamiltonian evolution equations for non-equilibrium molecular dynamics simulations

The reversible contribution to contemporary theories of non-equilibrium thermodynamics is reviewed as a methodology for attacking difficult, conservative problems in complex fluid dynamics. Several examples of past successes are discussed, and a new application is addressed: non-equilibrium molecular dynamics (NEMD) simulations. NEMD simulations of fluids are generally based on either a DOLLS or SLLOD tensor algorithm. The former is always considered to be a Hamiltonian system, but not particularly useful in high strain rate flow simulations, while the latter is considered not to be a Hamiltonian system, but much more practical and accurate in flow simulations. We demonstrate herein using non-canonical transformations of the particle momenta of the system that the SLLOD equations, when written in terms of appropriate non-canonical variables, are completely Hamiltonian, whereas the DOLLS equations are not so. A modified set of DOLLS equations in terms of the non-canonical variables which again is completely Hamiltonian is also derived. Both algorithms then lead to a phase space distribution function which is canonical in both the coordinates and momenta.     

A Simple Closed-Loop Active Control of Electrodynamic Shakers by Acceleration Power Spectral Density for Environmental Vibration Tests

This work presents the main results of a simple closed-loop active control for an electrodynamic shaker in order to generate acceleration Power Spectral Densities (PSD) according to prescribed Standards used in environmental vibration tests. The main idea is to start generating acceleration pseudo-signals obeying the prescribed Power Spectral Density and then to acquire acceleration data from the electrodynamic shaker’s table behaviour. So the Power Spectral Density of the acquired acceleration is computed and compared with the required PSD and then the time-varying pseudo-acceleration is updated to reflect this corrected PSD. It was noticed that for piecewise narrow bands frequencies, the electrodynamic shaker acceleration behaves near linearly, both in frequency and voltage, for the input signals. A code in AgilentVee 7.5 software to acquire, send and process signals for the active control in a closed-loop scheme was developed. The used A/D D/A hardware was a single PC sound card with specific characteristics. The control could be accomplished sending and acquiring at the same time with a range of input/output of ±1.5 V with 16 bits of resolution, at 48 kHz and assistance of an external sound amplifier.