advection diffusion
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Abstract In this paper, we present an open-source software library that can be used to numerically simulate the advection and diffusion of a chemical concentration or heat density in a viscous fluid where a moving, elastic boundary drives the fluid and acts as a source or sink. The fully- coupled fluid-structure interaction problem of an elastic boundary in a viscous fluid is solved using Peskin’s immersed boundary method. The addition or removal of the concentration or heat density from the boundary is solved using an immersed boundary-like approach in which the concentration is spread from the immersed boundary to the fluid using a regularized delta function. The concentration or density over time is then described by the advection-diffusion equation and numerically solved. This functionality has been added to our software library, IB2d, which provides an easy-to-use immersed boundary method in two dimensions with full implementations in MATLAB and Python. We provide four examples that illustrate the usefulness of the method. A simple rubber band that resists stretching and absorbs and releases a chemical concentration is simulated as a first example. Complete convergence results are presented for this benchmark case. Three more biological examples are presented: (1) an oscillating row of cylinders, representative of an idealized appendage used for filter-feeding or sniffing, (2) an oscillating plate in a background flow is considered to study the case of heat dissipation in a vibrating leaf, and (3) a simplified model of a pulsing soft coral where carbon dioxide is taken up and oxygen is released as a byproduct from the moving tentacles. This method is applicable to a broad range of problems in the life sciences, including chemical sensing by antennae, heat dissipation in plants and other structures, the advection-diffusion of morphogens during development, filter-feeding by marine organisms, and the release of waste products from organisms in flows.

AbstractDrug-filled implants (DFIs) have emerged as an innovative approach to control the delivery of drugs. These devices contain the drug within the structure of the implant itself and avoid the need to include additional drug carrier materials such as a polymers, which are often associated with inflammation and delayed healing/tissue regeneration at the implant site. One common feature of in vitro experiments to generate drug release profiles is stirring or agitation of the release medium. However, the influence of the resulting fluid flow on the rate of drug release from DFIs has yet to be quantified. In this paper we consider two DFIs, which although similar in shape and size, employ different strategies to control the release of drug: a porous pin with pores on the order of μm and a pin drilled with orifices of the order of mm. We develop a multiphysics mathematical model of drug release from these DFIs, subject to fluid flow induced through stirring and show that fluid flow greatly influences the drug release profile for the orifice pin, but that the porous pin drug release profile is relatively insensitive to flow. We demonstrate that drug release from the porous pin may adequately be described through a simplified radial 1D dissolution-diffusion model, while a 3D dissolution-advection-diffusion model is required to describe drug release from the orifice pin. A sensitivity analysis reveals that that the balance of reaction-advection-diffusion in terms of key nondimensional numbers governs the overall drug release. Our findings potentially have important implications in terms of devising the most relevant experimental protocol for quantifying drug release from DFIs.

Abstract Large meridional excursions of a jet stream are conducive to blocking and related midlatitude weather extremes, yet the physical mechanism of jet meandering is not well understood. This paper examines the mechanisms of jet meandering in boreal winter through the lens of a potential vorticity (PV)-like tracer advected by reanalysis winds in an advection-diffusion model. As the geometric structure of the tracer displays a compact relationship with PV in observations and permits a linear mapping from tracer to PV at each latitude, jet meandering can be understood by the geometric structure of tracer field that is only a function of prescribed advecting velocities. This one-way dependence of tracer field on advecting velocities provides a new modeling framework to quantify the effects of time mean flow versus transient eddies on the spatiotemporal variability of jet meandering. It is shown that the mapped tracer wave activity resembles the observed spatial pattern and magnitude of PV wave activity for the winter climatology, interannual variability, and blocking-like wave events. The anomalous increase in tracer wave activity for the composite over interannual variability or blocking-like wave events is attributed to weakened composite mean winds, indicating that the low-frequency winds are the leading factor for the overall distributions of wave activity. It is also found that the tracer model underestimates extreme wave activity, likely due to the lack of feedback mechanisms. The implications for the mechanisms of jet meandering in a changing climate are also discussed.

bl 'kks/k i= esa fu"izHkkoh vkSj vfLFkj fLFkfr;ksa esa ØkWliou lekdfyr lkanz.k ysus ds fy, nks fn’kkvksa esa vfHkogu folj.k lehdj.k ¼ADE½ dks gy fd;k x;k gSA ykIykl :ikarj.k rduhd dk mi;ksx rFkk m/okZ/kj Å¡pkbZ ij vk/kkfjr iou xfr vkSj Hkaoj folj.k’khyrk dh leh{kk djrs gq, ;g gy fudkyk x;k gSA blds lkFk gh Hkw&Lrj  vkSj vf/kdre lkanz.kksa dk Hkh vkdyu fd;k x;k gSA geus bl ekWMy esa iwokZuqekfur vkSj izsf{kr lkanz.k vk¡dM+ksa ds e/; rqyuk djus ds fy, dksiugsxu ¼MsuekdZ½ ls fy, x, vkuqHkfod vk¡dM+ksa dk mi;ksx fd;k gSA  The advection diffusion equation (ADE) is solved in two directions to obtain the crosswind integrated concentration in neutral and unstable conditions. The solution is solved using Laplace transformation technique and considering the wind speed and eddy diffusivity depending on the vertical height. Also the ground level and maximum concentrations are estimated. We use in this model empirical data from Copenhagen (Denmark) to compare between predicted and observed concentration data.