A mechanical model of swimming and flying in an incompressible viscous fluid in the absence of gravity is studied on the basis of assumed equations of motion. The system is modeled as an assembly of rigid spheres subject to elastic direct interactions and to periodic actuating forces which sum to zero. Hydrodynamic interactions are taken into account in the virtual mass matrix and in the friction matrix of the assembly. An equation of motion is derived for the velocity of the geometric center of the assembly. The mean power is calculated as the mean rate of dissipation. The full range of viscosity is covered, so that the theory can be applied to the flying of birds, as well as to the swimming of fish or bacteria. As an example a system of three equal spheres moving along a common axis is studied.

We present a collision model for particle-particle and particle-wall interactions in interface-resolved simulations of particle-laden flows. Three types of interparticle interactions are taken into account: (1) long- and (2) short-range hydrodynamic interactions, and (3) solid-solid contact. Long-range interactions are incorporated through an efficient and second-order-accurate immersed boundary method (IBM). Short-range interactions are also partly reproduced by the IBM. However, since the IBM uses a fixed grid, a lubrication model is needed for an interparticle gap width smaller than the grid spacing. The lubrication model is based on asymptotic expansions of analytical solutions for canonical lubrication interactions between spheres in the Stokes regime. Roughness effects are incorporated by making the lubrication correction independent of the gap width for gap widths smaller than $\sim 1\%$ of the particle radius. This correction is applied until the particles reach solid-solid contact. To model solid-solid contact we use a variant of a linear soft-sphere collision model capable of stretching the collision time. This choice is computationally attractive because it allows us to reduce the number of time steps required for integrating the collision force accurately and is physically realistic, provided that the prescribed collision time is much smaller than the characteristic time scale of particle motion. We verified the numerical implementation of our collision model and validated it against several benchmark cases for immersed head-on particle-wall and particle-particle collisions, and oblique particle-wall collisions. The results show good agreement with experimental data.

The neutron population in a nuclear reactor is subject to fluctuations in time and in space due to the competition of diffusion by scattering, births by fission events, and deaths by absorptions. As such, fission chains provide a prototype model for the study of spatial clustering phenomena. In order for the reactor to be operated in stationary conditions at the critical point, the population of prompt neutrons instantaneously emitted at fission must be in equilibrium with the much smaller population of delayed neutrons, emitted after a Poissonian time by nuclear decay of the fissioned nuclei. In this work, we will show that the delayed neutrons, although representing a tiny fraction of the total number of neutrons in the reactor, actually have a key impact on the fluctuations, and their contribution is very effective in quenching the spatial clustering.

We analyze a one-dimensional model of hard particles, within ensembles of trajectories that are conditioned (or biased) to atypical values of the time-averaged dynamical activity. We analyze two phenomena that are associated with these large deviations of the activity: phase separation (at low activity) and the formation of hyperuniform states (at high activity). We consider a version of the model which operates at constant volume, and a version at constant pressure. In these nonequilibrium systems, differences arise between the two ensembles, because of the extra freedom available to the constant-pressure system, which can change its total density. We discuss the relationships between different ensembles, mechanical equilibrium, and the probability cost of rare density fluctuations.

The revival of oscillation and maintaining rhythmicity in a network of coupled oscillators offer an open challenge to researchers as the cessation of oscillation often leads to a fatal system degradation and an irrecoverable malfunctioning in many physical, biological, and physiological systems. Recently a general technique of restoration of rhythmicity in diffusively coupled networks of nonlinear oscillators has been proposed in Zou et al. [Nat. Commun. 6, 7709 (2015)], where it is shown that a proper feedback parameter that controls the rate of diffusion can effectively revive oscillation from an oscillation suppressed state. In this paper we show that the mean-field diffusive coupling, which can suppress oscillation even in a network of identical oscillators, can be modified in order to revoke the cessation of oscillation induced by it. Using a rigorous bifurcation analysis we show that, unlike other diffusive coupling schemes, here one has two control parameters, namely the density of the mean-field and the feedback parameter that can be controlled to revive oscillation from a death state. We demonstrate that an appropriate choice of density of the mean field is capable of inducing rhythmicity even in the presence of complete diffusion, which is a unique feature of this mean-field coupling that is not available in other coupling schemes. Finally, we report the experimental observation of revival of oscillation from the mean-field-induced oscillation suppression state that supports our theoretical results.

We study, by renormalization group methods, $\mathrm{O}\left(N\right)$ models with interactions decaying as power law with exponent $d+\sigma$. When only the long-range momentum term $p^{\sigma }$ is considered in the propagator, the critical exponents can be computed from those of the corresponding short-range $\mathrm{O}\left(N\right)$ models at an effective fractional dimension $D_{\mathrm{eff}}$. Neglecting wave function renormalization effects the result for the effective dimension is $D_{\mathrm{eff}}=\frac{2d}{\sigma }$, which turns to be exact in the spherical model limit $(N\to \infty )$. Introducing a running wave function renormalization term the effective dimension becomes instead $D_{\mathrm{eff}}=\frac{(2-{\eta }_{\mathrm{SR}})d}{\sigma }$. The latter result coincides with the one found using standard scaling arguments. Explicit results in two and three dimensions are given for the exponent $\nu$. We propose an improved method to describe the full theory space of the models where both short- and long-range propagator terms are present and no a priori choice among the two in the renormalization group flow is done. The eigenvalue spectrum of the full theory for all possible fixed points is drawn and a full description of the fixed-point structure is given, including multicritical long-range universality classes. The effective dimension is shown to be only approximate, and the resulting error is estimated.

We propose an elastic theory of epithelial monolayers based on a two-dimensional discrete model of dropletlike cells characterized by differential surface tensions of their apical, basal, and lateral sides. We show that the effective tissue bending modulus depends on the apicobasal differential tension and changes sign at the transition from the flat to the fold morphology. We discuss three mechanisms that stabilize the finite-wavelength fold structures: Physical constraint on cell geometry, hard-core interaction between non-neighboring cells, and bending elasticity of the basement membrane. We show that the thickness of the monolayer changes along the waveform and thus needs to be considered as a variable rather than a parameter. Next we show that the coupling between the curvature and the thickness is governed by the apicobasal polarity and that the amplitude of thickness modulation along the waveform is proportional to the apicobasal differential tension. This suggests that intracellular stresses can be measured indirectly by observing easily measurable morphometric parameters. We also study the mechanics of three-dimensional structures with cylindrical symmetry.

In this paper, we present an approach for predicting nanoscale capillary imbibitions using the Lucas-Washburn (LW) theory. Molecular dynamics (MD) simulations were employed to investigate the effects of surface forces on the viscosity of liquid water. This provides an update to the modified LW equation that considered only a nanoscale slip length. An initial water nanodroplet study was performed to properly elucidate the wetting behavior of copper and gold surfaces. Intermolecular interaction strengths between water and corresponding solid surfaces were determined by matching the contact angle values obtained by experimental measurements. The migration of liquid water into copper and gold capillaries was measured by MD simulations and was found to differ from the modified LW equation. We found that the liquid layering in the vicinity of the solid surface induces a higher density and viscosity, leading to a slower MD uptake of fluid into the capillaries than was theoretically predicted. The near-surface viscosity for the nanoscale-confined water was defined and calculated for the thin film of water that was sheared between the two solid surfaces, as the ratio of water shear stress to the applied shear rate. Considering the effects of both the interface viscosity and slip length of the fluid, we successfully predicted the MD-measured fluid rise in the nanotubes.

A methodology for turbulence constitutive modeling is discussed on the basis of the square-root tensor of the Reynolds stress. The present methodology can satisfy the realizability condition for the Reynolds stress proposed by Schumann [Phys. Fluids 20, 721 (1977)] in a more general manner than the conventional methodologies. The definition and uniqueness of the square-root tensor have been discussed, and its boundary condition has been properly obtained consistently with that of the Reynolds stress. Examples of possible constitutive models of both tensor-expansion and transport-equation types have been proposed.

Disordered hyperuniform (DH) media have been recognized as a new state of disordered matter that broadens our vision of material engineering. Here, long-range correlated disordered two-dimensional patterns are fabricated by self-assembling of spherical diblock-copolymer (BCP) micelles. Control of the self-assembling parameters leads to the formation of DH patterns of micelles that can host nanoscale material inclusions, therefore providing an effective strategy for fabricating multimaterial DH structures at molecular scale. Centroidal patterns are accurately determined by virtue of BCP micelles loaded with metal nanoparticles. Our analysis reveals the signature of nearly ideal DH BCP assemblies in the local density fluctuation and a dominant linear scaling in the local number fluctuation.

Using the Cayley-Dickson construction we rephrase and review the non-Hermitian diagrammatic formalism [R. A. Janik, M. A. Nowak, G. Papp, and I. Zahed, Nucl. Phys. B 501, 603 (1997)], that generalizes the free probability calculus to asymptotically large non-Hermitian random matrices. The main object in this generalization is a quaternionic extension of the $R$ transform which is a generating function for planar (noncrossing) cumulants. We demonstrate that the quaternionic $R$ transform generates all connected averages of all distinct powers of $X$ and its Hermitian conjugate $X^{†}$: $\langle \langle \frac{1}{N}\text{Tr}{X}^a{X}^{†b}{X}^c...\rangle \rangle$ for $N\to \infty$. We show that the $R$ transform for Gaussian elliptic laws is given by a simple linear quaternionic map $\mathcal{R}(z+wj)=x+{\sigma }^2\left(\mu e^{2i\varphi }z+wj\right)$ where $(z,w)$ is the Cayley-Dickson pair of complex numbers forming a quaternion $q=(z,w)\equiv z+wj$. This map has five real parameters $\text{Re}x,\text{Im}x,\varphi ,\sigma$, and $\mu$. We use the $R$ transform to calculate the limiting eigenvalue densities of several products of Gaussian random matrices.

We describe a universality class for the transitions of a generalized Pólya urn by studying the asymptotic behavior of the normalized correlation function $C\left(t\right)$ using finite-size scaling analysis. $X\left(1\right),X\left(2\right),...$ are the successive additions of a red (blue) ball $\left[X\right(t)=1(0\left)\right]$ at stage $t$ and $C\left(t\right)\equiv \text{Cov}\left[X\right(1),X(t+1\left)\right]/\text{Var}\left[X\right(1\left)\right]$. Furthermore, $z\left(t\right)={\sum }_{s=1}^{t}X\left(s\right)/t$ represents the successive proportions of red balls in an urn to which, at the $\left(t+1\right)\mathrm{th}$ stage, a red ball is added $\left[X\right(t+1)=1]$ with probability $q\left[z\right(t\left)\right]=(tanh\{J\left[2z\right(t)-1]+h\}+1)/2,J\ge 0$, and a blue ball is added $\left[X\right(t+1)=0]$ with probability $1-q\left[z\right(t\left)\right]$. A boundary $[J_c\left(h\right),h]$ exists in the $(J,h)$ plane between a region with one stable fixed point and another region with two stable fixed points for $q\left(z\right)$. $C\left(t\right)\sim c+c^{\prime }·t^{l-1}$ with $c=0(>0)$ for $J<J_c(J>J_c)$, and $l$ is the (larger) value of the slope(s) of $q\left(z\right)$ at the stable fixed point(s). On the boundary $J=J_c\left(h\right),C\left(t\right)\simeq c+c^{\prime }·{(lnt)}^{-{\alpha }^{\prime }}$ and $c=0(c>0),{\alpha }^{\prime }=1/2\left(1\right)$ for $h=0(h\ne 0)$. The system shows a continuous phase transition for $h=0$ and $C\left(t\right)$ behaves as $C\left(t\right)\simeq {(lnt)}^{-{\alpha }^{\prime }}g[(1-l)lnt]$ with a universal function $g\left(x\right)$ and a length scale $1/(1-l)$ with respect to $lnt$. $\beta ={\nu }_{\left|\right|}·{\alpha }^{\prime }$ holds with $\beta =1/2$ and ${\nu }_{\left|\right|}=1$.

The process of destroying a complex network through node removal has been the subject of extensive interest and research. Node loss typically leaves the network disintegrated into many small and isolated clusters. Here we show that these clusters typically remain close to each other and we suggest a simple algorithm that is able to reverse the inflicted damage by restoring the network's functionality. After damage, each node decides independently whether to create a new link depending on the fraction of neighbors it has lost. In addition to relying only on local information, where nodes do not need knowledge of the global network status, we impose the additional constraint that new links should be as short as possible (i.e., that the new edge completes a shortest possible new cycle). We demonstrate that this self-healing method operates very efficiently, both in model and real networks. For example, after removing the most connected airports in the USA, the self-healing algorithm rejoined almost 90% of the surviving airports.

In the present work we study the motion of microorganisms swimming by an axisymmetric distribution of surface tangential velocity in a weakly viscoelastic fluid. The second-order fluid constitutive equation is used to model the suspending fluid, while the well-known “squirmer model” [M. J. Lighthill, Comm. Pure Appl. Math. 5, 109 (1952); J. R. Blake, J. Fluid Mech. 46, 199 (1971)] is employed to describe the organism propulsion mechanism. A regular perturbation expansion up to first order in the Deborah number is performed, and the generalized reciprocity theorem from Stokes flow theory is then used, to derive analytical formulas for the squirmer velocity. Results show that “neutral” squirmers are unaffected by viscoelasticity, whereas “pullers” and “pushers” are slowed down and hastened, respectively. The power dissipated by the swimming microorganism and the “swimming efficiency” are also analytically quantified.

It is well known that the Korteweg–de Vries (KdV) equation has an infinite set of conserved quantities. The first three are often considered to represent mass, momentum, and energy. Here we try to answer the question of how this comes about and also how these KdV quantities relate to those of the Euler shallow-water equations. Here Luke's Lagrangian is helpful. We also consider higher-order extensions of KdV. Though in general not integrable, in some sense they are almost so within the accuracy of the expansion.

We first study fluctuating hydrodynamics (FH) at equilibrium in periodic domains by use of the smoothed dissipative particle dynamics (SDPD) method. We examine the performance of SDPD by comparing it with the theory of FH. We find that the spatial correlation of particle velocity is always the Dirac $\delta$ function, irrespective of numerical resolution, in agreement with the theory. However, the spatial correlation of particle density has a finite range of $r_c$, which is due to the kernel smoothing procedure for the density. Nevertheless, this finite range of correlation can be reduced to an arbitrarily small value by increasing the resolution, that is, reducing $r_c$, similarly to how the smoothing kernel converges to the Dirac $\delta$ function. Moreover, we consider temporal correlation functions (CFs) of random field variables in Fourier space. For sufficient resolution, the CFs of SDPD simulations agree very well with analytical solutions of the linearized FH equations. This confirms that both the shear and sound modes are modeled accurately and that fluctuations are generated, transported, and dissipated in both thermodynamically and hydrodynamically consistent ways in SDPD. We also show that the CFs of the classical dissipative particle dynamics (DPD) method with proper parameters can recover very well the linearized solutions. As a reverse implication, the measurement of CFs provides an effective means of extracting viscosities and sound speed of a DPD system with a new set of input parameters. Subsequently, we study the FH in truncated domains in the context of multiscale coupling via the domain decomposition method, where a SDPD simulation in one subdomain is coupled with a Navier-Stokes (NS) solver in an adjacent subdomain with an overlapping region. At equilibrium, the mean values of the NS solution are known a priori and do not need to be extracted from actual simulations. To this end, we model a buffer region as an equilibrium boundary condition (EBC) at the truncated side of the SDPD simulation. In the EBC buffer, the velocity of particles is drawn from a known Gaussian distribution, that is, the Maxwell-Boltzmann distribution. Due to the finite range of spatial correlation, the density of particles in the EBC buffer must be drawn from a conditional Gaussian distribution, which takes into account the available density distribution of neighboring interior particles. We introduce a Kriging method to provide such a conditional distribution and hence preserve the spatial correlation of density. Spatial and temporal correlations of SDPD simulations in the truncated domain are compared to that in a single complete domain. We find that a gap region between the buffer and interior is important to reduce the extra dissipation generated by the artificial buffer at equilibrium, rendering more investigations necessary for thermal fluctuations in the multiscale coupling of nonequilibrium flows.

The phase behavior of stabilized dispersions of macromolecules is most easily described in terms of the effective interaction between the centers of mass of solute particles. For molecules such as polymer chains, dendrimers, etc., the effective pair potential is finite at the origin, allowing “particles” to freely interpenetrate each other. Using a double-Gaussian model (DGM) for demonstration, we study the behavior of the system as a function of the attraction strength $\eta$. Above a critical strength ${\eta }_{\mathrm{c}}$, the infinite-size system is Ruelle unstable, in that it collapses to a cluster of finite volume. As ${\eta }_{\mathrm{c}}$ is approached from below, the liquid-vapor region exhibits an anomalous widening at low temperature, and the liquid density apparently diverges at the stability threshold. Above ${\eta }_{\mathrm{c}}$, the thermodynamic plane is divided in two regions, differing in the value of the average waiting time for collapse, being finite and small on one side of the boundary line, while large or even infinite in the other region. Upon adding a small hard core to the DGM potential, stability is fully recovered and the boundary line is converted to the spinodal line of a transition between fluid phases. We argue that the destabilization of a colloidal dispersion, as induced by the addition of salt or other flocculant, finds a suggestive analogy in the process by which a strengthening of the attraction pushes a stabilized-DGM system inside the fluid-fluid spinodal region.

The well-known Kerr effect in isotropic fluids consists in the appearance of uniaxial orientational order and birefringence that grows as the square of the applied electric field. We predict and observe that at a high electric field, the Kerr effect displays features caused by the nonlinear dependence of dielectric permittivity on the field-induced orientational order parameter. Namely, the field-induced birefringence grows faster than the square of the electric field and the dynamics of birefringence growth slows down as the field increases. As a function of temperature, the field-induced birefringence is inversely proportional to the departure from an asymptotic critical temperature, but this temperature is no longer a constant (corresponding to the lower limit of the supercooled isotropic phase) and increases proportionally to the square of the electric field.

The assembly of monomeric constituents into molecular superstructures through sequential-arrival processes has been simulated and theoretically characterized. When the energetic interactions allow for complete overlap of the particles, the model is equivalent to that of the sequential absorption of soft particles on a surface. In the present work, we consider more general cases by including arbitrary aggregating geometries and varying prescriptions of the connectivity network. The resulting theory accounts for the evolution and final-state configurations through a system of equations governing structural generation. We find that particle geometries differ significantly from those in equilibrium. In particular, variations of structural rigidity and morphology tune particle energetics and result in significant variation in the nonequilibrium distributions of the assembly in comparison to the corresponding equilibrium case.

Recovering a stochastic process from noisy ensembles of single-particle trajectories is resolved here using the coarse-grained Langevin equation as a model. The massive redundancy contained in single-particle tracking data allows recovering local parameters of the underlying physical model. We use several parametric and nonparametric estimators to compute the first and second moments of the process, to recover the local drift, its derivative, and the diffusion tensor, and to deconvolve the instrumental from the physical noise. We use numerical simulations to also explore the range of validity for these estimators. The present analysis allows defining what can exactly be recovered from statistics of super-resolution microscopy trajectories used for characterizing molecular trafficking underlying cellular functions.