Clustering in mixing flows

We calculate the Lyapunov exponents for particles suspended in a random three-dimensional flow, concentrating on the limit where the viscous damping rate is small compared to the inverse correlation time. In this limit Lyapunov exponents are obtained as a power series in epsilon, a dimensionless measure of the particle inertia. Although the perturbation generates an asymptotic series, we obtain accurate results from a Pade-Borel summation. Our results prove that particles suspended in an incompressible random mixing flow can show pronounced clustering when the Stokes number is large and we characterise two distinct clustering effects which occur in that limit.Comment: 5 pages, 1 figur

Size-selective concentration of chondrules and other small particles in protoplanetary nebula turbulence

Size-selective concentration of particles in a weakly turbulent protoplanetary nebula may be responsible for the initial collection of chondrules and other constituents into primitive body precursors. This paper presents the main elements of this process of turbulent concentration. In the terrestrial planet region, both the characteristic size and size distribution of chondrules are explained. "Fluffier" particles would be concentrated in nebula regions which were at a lower gas density and/or more intensely turbulent. The spatial distribution of concentrated particle density obeys multifractal scaling}, suggesting a close tie to the turbulent cascade process. This scaling behavior allows predictions of the probability distributions for concentration in the protoplanetary nebula to be made. Large concentration factors (>10^5) are readily obtained, implying that numerous zones of particle density significantly exceeding the gas density could exist. If most of the available solids were actually in chondrule sized particles, the ensuing particle mass density would become so large that the feedback effects on gas turbulence due to mass loading could no longer be neglected. This paper describes the process, presenting its basic elements and some implications, without including the effects of mass loading.Comment: 34 pages, 7 figures; in press for Astrophys. J; expected Jan 01 2001 issu

Acceleration of heavy and light particles in turbulence: comparison between experiments and direct numerical simulations

We compare experimental data and numerical simulations for the dynamics of inertial particles with finite density in turbulence. In the experiment, bubbles and solid particles are optically tracked in a turbulent flow of water using an Extended Laser Doppler Velocimetry technique. The probability density functions (PDF) of particle accelerations and their auto-correlation in time are computed. Numerical results are obtained from a direct numerical simulation in which a suspension of passive pointwise particles is tracked, with the same finite density and the same response time as in the experiment. We observe a good agreement for both the variance of acceleration and the autocorrelation timescale of the dynamics; small discrepancies on the shape of the acceleration PDF are observed. We discuss the effects induced by the finite size of the particles, not taken into account in the present numerical simulations.Comment: 7 pages, 4 figure

Singular Scaling Functions in Clustering Phenomena

We study clustering in a stochastic system of particles sliding down a fluctuating surface in one and two dimensions. In steady state, the density-density correlation function is a scaling function of separation and system size.This scaling function is singular for small argument -- it exhibits a cusp singularity for particles with mutual exclusion, and a divergence for noninteracting particles. The steady state is characterized by giant fluctuations which do not damp down in the thermodynamic limit. The autocorrelation function is a singular scaling function of time and system size. The scaling properties are surprisingly similar to those for particles moving in a quenched disordered environment that results if the surface is frozen.Comment: 8 pages, 3 figures, Invited talk delivered at Statphys 23, Genova, July 200

Clustering dynamics of Lagrangian tracers in free-surface flows

We study the formation of clusters of passive Lagrangian tracers in a non-smooth turbulent flow in a flat free-slip surface as a model for particle dynamics on free surfaces. Single particle and pair dispersion show different behavior for short and large times: on short times particles cluster exponentially rapidly until patches of the size of the divergence correlation length are depleted; on larger times the pair dispersion is dominated by almost ballistic hopping between clusters. We also find that the distribution of particle density is close to algebraic and can trace this back to the exponential distribution of the divergence field of the surface flow.Comment: 5 pages, 5 Postscript figure

Development of Low Cost Sensors for Hydrogen Safety Applications

We are developing rugged and reliable hydrogen safety sensors that can be easily manufactured. Potential applications also require an inexpensive sensor that can be easily deployed. Automotive applications demand low cost, while personnel safety applications emphasize light-weight, battery-operated, and wearable sensors. Our current efforts involve developing and optimizing sensor materials for stability and compatibility with typical thick-film manufacturing processes. We are also tailoring the sensor design and size along with various packaging and communication schemes for optimal acceptance by end users

Dynamics of a small neutrally buoyant sphere in a fluid and targeting in Hamiltonian systems

We show that, even in the most favorable case, the motion of a small spherical tracer suspended in a fluid of the same density may differ from the corresponding motion of an ideal passive particle. We demonstrate furthermore how its dynamics may be applied to target trajectories in Hamiltonian systems.Comment: See home page http://lec.ugr.es/~julya

The antisense oligonucleotide nusinersen for treatment of spinal muscular atrophy

Spinal muscular atrophy (SMA) is a rare, autosomal recessive neuromuscular degenerative disease characterized by loss of spinal cord motor neurons leading to progressive muscle wasting. The most common pathology results from a homozygous disruption in the survival motor neuron 1 (SMN1) gene on chromosome 5q13 via deletion, conversion, or mutation. SMN2 is a near duplicate of SMN1 that can produce full-length SMN mRNA transcripts, but its overall production capability of these mRNA transcripts is lower than that seen in SMN1. This leads to lower levels of functional SMN protein within motor neurons. The FDA approved nusinersen in December 2016 to treat SMA associated with SMN1 gene mutation. It is administered directly to the central nervous system by intrathecal injection. An antisense oligonucleotide (ASO) drug, nusinersen, provides an upcoming and promising treatment option for SMA and represents a novel pharmacological approach with a mechanism of action relevant for other neurodegenerative disorders. Nusinersen begins with four initial loading doses that are followed by three maintenance doses per year. Three major studies (CHERISH, ENDEAR, and NURTURE) have shown to improve motor function in early and late-onset individuals and reduce the chances of ventilator requirements in pre-symptomatic infants. Studies investigating the timing of drug delivery in mouse models of SMA report the best outcomes when drugs are delivered early before any significant motor function is lost. Nusinersen is a novel therapeutic approach with consistent results in all three studies and is proof of the novel concept for treating SMA and other neurodegenerative disorders in the future