A new universal law for the Liesegang pattern formation

Classical regularities describing the Liesegang phenomenon have been observed and extensively studied in laboratory experiments for a long time. These have been verified in the last two decades, both theoretically and using simulations. However, they are only applicable if the observed system is driven by reaction and diffusion. We suggest here a new universal law, which is also valid in the case of various transport dynamics (purely diffusive, purely advective, and diffusion-advection cases). We state that ptot~Xc, where ptot yields the total amount of the precipitate and Xc is the center of gravity. Besides the theoretical derivation experimental and numerical evidence for the universal law is provided. In contrast to the classical regularities, the introduced quantities are continuous functions of time

Models of Liesegang pattern formation

In this article different mathematical models of the Liesegang phenomenon are exhibited. The main principles of modeling are discussed such as supersaturation theory, sol coagulation and phase separation, which describe the phenomenon using different steps and mechanism beyond the simple reaction scheme. We discuss whether the underlying numerical simulations are able to reproduce several empirical regularities and laws of the corresponding pattern structure. In all cases we highlight the meaning of the initial and boundary conditions in the corresponding mathematical formalism. Above the deterministic ones discrete stochastic approaches are also described. As a main tool for the control of pattern structure the effect of an external electric field is also discussed

Systematic front distortion and presence of consecutive fronts in a precipitation system

A new simple reaction-diffusion system is presented focusing on pattern formation phenomena as consecutive precipitation fronts and distortion of the precipitation front.The chemical system investigated here is based on the amphoteric property of aluminum hydroxide and exhibits two unique phenomena. Both the existence of consecutive precipitation fronts and distortion are reported for the first time. The precipitation patterns could be controlled by the pH field, and the distortion of the precipitation front can be practical for microtechnological applications of reaction-diffusion systems

Air pollution modelling using a graphics processing unit with CUDA

The Graphics Processing Unit (GPU) is a powerful tool for parallel computing. In the past years the performance and capabilities of GPUs have increased, and the Compute Unified Device Architecture (CUDA) - a parallel computing architecture - has been developed by NVIDIA to utilize this performance in general purpose computations. Here we show for the first time a possible application of GPU for environmental studies serving as a basement for decision making strategies. A stochastic Lagrangian particle model has been developed on CUDA to estimate the transport and the transformation of the radionuclides from a single point source during an accidental release. Our results show that parallel implementation achieves typical acceleration values in the order of 80-120 times compared to CPU using a single-threaded implementation on a 2.33 GHz desktop computer. Only very small differences have been found between the results obtained from GPU and CPU simulations, which are comparable with the effect of stochastic transport phenomena in atmosphere. The relatively high speedup with no additional costs to maintain this parallel architecture could result in a wide usage of GPU for diversified environmental applications in the near future.Comment: 5 figure

Probability of the emergence of helical precipitation patterns in the wake of reaction-diffusion fronts

Helical and helicoidal precipitation patterns emerging in the wake of reaction-diffusion fronts are studied. In our experiments, these chiral structures arise with well-defined probabilities P_H controlled by conditions such as e.g., the initial concentration of the reagents. We develop a model which describes the observed experimental trends. The results suggest that P_H is determined by a delicate interplay among the time and length scales related to the front and to the unstable precipitation modes and, furthermore, the noise amplitude also plays a quantifiable role.Comment: 7 pages, 5 composite figure

Összetett reakció-diffúzió rendszerek vizsgálata és modelljeik párhuzamosítása = Investigation of complex reaction-diffusion systems and paralellization of their models

Csapadékmintázatokat vizsgáltunk reakció-diffúzió rendszerekben: (i) Egyedüli önszerveződést figyeltünk meg csapadékrendszerekben, ahol spontán kialakuló spirálok megjelenését vettük észre a csapadékfront vékony rétegében; (ii) Egy új csapadékrendszerben egymás utáni frontokat és a frontok torzítását mutattuk meg; (iii) Egy új és univerzális törvényt javasoltunk a reguláris Liesegang mintázatok leírására, amely érvényes több transzport feltétel esetén is. Egy kémiai transzport és ülepedési modellt dolgoztunk ki és kapcsoltunk össze az ózonfluxusok jellemzésére Magyarország területére. Több kémiai alkalmazást is készítettünk (reakció-diffúzió rendszerek modellezése; passzív nyomanyagok légköri terjedésének szimulációja) a P-GRADE fejlesztői környezet és P-GRADE portál segítségével. | Pattern formation phenomena in precipitation systems were investigated: (i) A unique kind of self-organization, the spontaneous appearance of traveling waves, and spiral formation inside a precipitation front was reported; (ii) A new simple reaction-diffusion system was presented focusing on pattern formation phenomena as consecutive precipitation fronts and distortion of the precipitation front; (iii) A new universal law for the regular Liesegang phenomenon has been proposed, which is also valid in the case of various transport dynamics. A chemical transport model and a dry-deposition model have been coupled for the purpose of simulating ozone fluxes over Hungary. Some chemical applications (simulation reaction-diffusion equations; simulation passive tracer from a point source) have been developed using P-GRADE programming environment and P-GRADE portal

Simulation of reaction-diffusion processes in three dimensions using CUDA

Numerical solution of reaction-diffusion equations in three dimensions is one of the most challenging applied mathematical problems. Since these simulations are very time consuming, any ideas and strategies aiming at the reduction of CPU time are important topics of research. A general and robust idea is the parallelization of source codes/programs. Recently, the technological development of graphics hardware created a possibility to use desktop video cards to solve numerically intensive problems. We present a powerful parallel computing framework to solve reaction-diffusion equations numerically using the Graphics Processing Units (GPUs) with CUDA. Four different reaction-diffusion problems, (i) diffusion of chemically inert compound, (ii) Turing pattern formation, (iii) phase separation in the wake of a moving diffusion front and (iv) air pollution dispersion were solved, and additionally both the Shared method and the Moving Tiles method were tested. Our results show that parallel implementation achieves typical acceleration values in the order of 5-40 times compared to CPU using a single-threaded implementation on a 2.8 GHz desktop computer.Comment: 8 figures, 5 table

Dispersion of aerosol particles in the free atmosphere using ensemble forecasts

The dispersion of aerosol particle pollutants is studied using 50 members of an ensemble forecast in the example of a hypothetical free atmospheric emission above Fukushima over a period of 2.5 days. Considerable differences are found among the dispersion predictions of the different ensemble members, as well as between the ensemble mean and the deterministic result at the end of the observation period. The variance is found to decrease with the particle size. The geographical area where a threshold concentration is exceeded in at least one ensemble member expands to a 5-10 times larger region than the area from the deterministic forecast, both for air column "concentration" and in the "deposition" field. We demonstrate that the root-mean-square distance of any particle from its own clones in the ensemble members can reach values on the order of one thousand kilometers. Even the centers of mass of the particle cloud of the ensemble members deviate considerably from that obtained by the deterministic forecast. All these indicate that an investigation of the dispersion of aerosol particles in the spirit of ensemble forecast contains useful hints for the improvement of risk assessment