Boundary layer scaling in Rayleigh-Benard convection

Accepted versio

Computational Models of Timing Mechanisms in the Cerebellar Granular Layer

A long-standing question in neuroscience is how the brain controls movement that requires precisely timed muscle activations. Studies using Pavlovian delay eyeblink conditioning provide good insight into this question. In delay eyeblink conditioning, which is believed to involve the cerebellum, a subject learns an interstimulus interval (ISI) between the onsets of a conditioned stimulus (CS) such as a tone and an unconditioned stimulus such as an airpuff to the eye. After a conditioning phase, the subject’s eyes automatically close or blink when the ISI time has passed after CS onset. This timing information is thought to be represented in some way in the cerebellum. Several computational models of the cerebellum have been proposed to explain the mechanisms of time representation, and they commonly point to the granular layer network. This article will review these computational models and discuss the possible computational power of the cerebellum

Understanding entrainment processes in the atmosphere: the role of numerical simulation

Turbulent entrainment is a process of primary importance in the atmospheric boundary layer; however despite several decades of intense study much remains to be understood. Direct Numerical Simulation (DNS) and Large-Eddy Simulation (LES) have a tremendous potential to improve the understanding of turbulent entrainment, particularly if combined with theory. We discuss a recently developed framework for turbulent jets and plumes to decompose turbulent entrainment in various physical processes, and modify it for use in a stably stratified shear driven (nocturnal) boundary layer. The decomposition shows that inner layer processes become negligible as time progresses and that the entrainment coefficient is determined by turbulence production in the outer layer only

Applying the Leray-alpha model to unbounded Rayleigh-Benard convection

Accepted versio

A graphics processing unit (GPU) approach to large eddy simulation (LES) for transport and contaminant dispersion

Recent advances in the development of large eddy simulation (LES) atmospheric models with corresponding atmospheric transport and dispersion (AT&D) modeling capabilities have made it possible to simulate short, time-averaged, single realizations of pollutant dispersion at the spatial and temporal resolution necessary for common atmospheric dispersion needs, such as designing air sampling networks, assessing pollutant sensor system performance, and characterizing the impact of airborne materials on human health. The high computational burden required to form an ensemble of single-realization dispersion solutions using an LES and coupled AT&D model has, until recently, limited its use to a few proof-of-concept studies. An example of an LES model that can meet the temporal and spatial resolution and computational requirements of these applications is the joint outdoor-indoor urban large eddy simulation (JOULES). A key enabling element within JOULES is the computationally efficient graphics processing unit (GPU)-based LES, which is on the order of 150 times faster than if the LES contaminant dispersion simulations were executed on a central processing unit (CPU) computing platform. JOULES is capable of resolving the turbulence components at a suitable scale for both open terrain and urban landscapes, e.g., owing to varying environmental conditions and a diverse building topology. In this paper, we describe the JOULES modeling system, prior efforts to validate the accuracy of its meteorological simulations, and current results from an evaluation that uses ensembles of dispersion solutions for unstable, neutral, and stable static stability conditions in an open terrain environment