Parallel computation of biochemical processes for soil remediation through cellular automata simulation

We present a generalization of a biochemical model of bacterial degradation of organic compounds in soils, based on genetic networks of cellular automata, and discuss the relevant parallel computation approach. The parallel implementation of the genetic model has been performed on a homogeneous cluster of personal computers in an MPI (Message Passing Interface) environment with high specific performances. By this way, it is possible to perform realistic threedimensional simulations and derive useful information for in situ technological applications

Macroscopic cellular automata for groundwater modelling: A first approach

n/

Assessment of future urban growth impact on landscape pattern using cellular automata model: a case study of xuzhou city, china

Understanding and predicting of the urban growth process and its impact have become increasingly important for decision making toward sustainable development. In this paper, we presented a cellular automata model to assess the consequence of future urban growth. The hybrid calibration method combining logistic regression with trial-and-error was applied to estimate the parameters. The study proposed the integration method of Multi-Criteria Evaluation and Analytic Hierarchy Process that can be utilized to effectively translate the qualitative descriptions of scenarios into quantitative spatial analysis. Finally, the comparison of the different scenarios provided an insight into the impacts of different urban development strategies on landscape patterns. The result indicates that CA model can be effectively connected with the urban decision making processes. The moderate development scenario could be considered as the best one in achieving the objectives of compact urban form, good residential environment, as well as environmentally and economically efficient development.

A cellular automaton model of laser-plasma interactions

This paper deals with the realization of a CA model of the physical interactions occurring when high-power laser pulses are focused on plasma targets. The low-level and microscopic physical laws of interactions among the plasma and the photons in the pulse are described. In particular, electron–electron interaction via the Coulomb force and photon–electron interaction due to ponderomotive forces are considered. Moreover, the dependence on time and space of the index of refraction is taken into account, as a consequence of electron motion in the plasma. Ions are considered as a fixed background. Simulations of these interactions are provided in different conditions and the macroscopic dynamics of the system, in agreement with the experimental behavior, are evidenced

Geophysical modeling for groundwater and soil contamination risk assessment

This PhD thesis is focused on the study of environmental problems linked to contaminant detection and transport in soil and groundwater. The research has two main objectives: development, testing and application of geophysical data inversion methods for identifying and characterizing possible anomaly sources of contamination and development and application of numerical models for simulating contaminant propagation in saturated and unsaturated conditions. Initially, three different approaches for self-potential (SP) data inversion, based on spectral, tomographical and global optimization methods, respectively, are proposed to characterize the SP anomalous sources and to study their time evolution. The developed approaches are first tested on synthetic SP data generated by simple polarized structures, (like sphere, vertical cylinder, horizontal cylinder and inclined sheet) and, then, applied to SP field data taken from literature. In particular, the comparison of the results with those coming from other numerical approaches strengthens their usefulness. As it concerns the modelling of groundwater flow and contaminant transport, two cellular automata (CA) models have been developed to simulate diffusion-dispersion processes in unsaturated and saturated conditions, respectively, and to delineate the most dangerous scenarios in terms of maximum distances travelled by the contaminant. The developed CA models have been applied to two study areas affected by a different phenomenon of contamination. The first area is located in the western basin of the Crete island (Greece), which is affected by organic contaminant due to olive oil mills wastes (OOMWs). The numerical simulations provided by the CA model predict contaminant infiltration in the saturated zone and such results are in very good agreement with the high phenol concentrations provided by geochemical analyses on soil samples collected in the survey area at different depths and times. The second case study refers to an area located in the western basin of Solofrana river valley (southern Italy), which is often affected by heavy flooding and contamination from agricultural and industrial activities in the surroundings. The application of a multidisciplinary approach, which integrates geophysical data with hydrogeological and geochemical studies, and the development of a CA model for contaminant propagation in saturated conditions, have permitted to identify a possible phenomenon of contamination and the delineation of the most dangerous scenarios in terms of infiltration rates are currently in progress

Modelling fungal competition for space:Towards prediction of community dynamics

Filamentous fungi contribute to ecosystem and human-induced processes such as primary production, bioremediation, biogeochemical cycling and biocontrol. Predicting the dynamics of fungal communities can hence improve our forecasts of ecological processes which depend on fungal community structure. In this work, simple theoretical models of fungal interactions with ordinary and partial differential equations are established, and to validate model predictions against community dynamics of a three species empirical system. We found that space is an important factor for the prediction of community dynamics, since the performance was poor for models of ordinary differential equations assuming well-mixed nutrient substrate. The models of partial differential equations could satisfactorily predict the dynamics of a single species, but exhibited limitations which prevented the prediction of empirical community dynamics. One such limitation is the arbitrary choice of a threshold local density above which a fungal mycelium is considered present in the model. In conclusion, spatially explicit simulation models, able to incorporate different factors influencing interaction outcomes and hence dynamics, appear as a more promising direction towards prediction of fungal community dynamics

Lattice Boltzmann based multicomponent reactive transport model coupled with geochemical solver for pore scale simulations

A Lattice Boltzmann (LB) based reactive transport model intended to capture reactions and solid phase changes occurring at the pore scale is presented. The proposed approach uses LB method to compute multi component mass transport. The LB multicomponent transport model is then coupled with the well-established geochemical reaction code PHREEQC which solves for thermodynamic equilibrium in mixed aqueous-solid phase system with homogenous and heterogeneous reactions. This coupling enables us to update solid phases volumes based on dissolution or precipitation using static update rules which, on pore scale, affects the change of potentially pore network geometry. Unlike conventional approach, heterogeneous reactions are conceptualized as volumetric reactions by introducing additional source term in the fluid node next to solid node, and not as flux boundaries. To demonstrate the validity of this approach several examples are presented in this paper

A hybrid mathematical model of fungal mycelia : tropisms, polarised growth and application to colony competition

Fungi are a crucial component of most ecosystems and are responsible for decomposing organic matter, distributing nutrients through the environment and supporting plants and animal life through symbiotic relationships. Certain species of fungi are common pathogens causing disease and infection in plants and animals. The highly integrated nature of fungi in relation to the environment and all life emphasises the importance of developing a greater understanding of the growth and morphology of such organisms. Mathematical modelling has provided a means through which key processes can be isolated to analyse and simulate a target system to allow observations and form predictions regarding unknown phenomena. Numerous models of fungal colonies have been produced and are generally categorised into two main groups; continuous and discrete. The following study combines the approaches so that the constructed hybrid model comprises a discrete network that represents the fungal mycelia and a continuous component to account for the continuous substrates and other compounds crucial to fungal growth and development. Key processes such as uptake, translocation and anastomosis are included in addition to the implementation of a flexible hyphal orientation scheme that facilitates a variety of tropisms to different influential factors. The hybrid model is used to investigate several scenarios such as the polarisation of growth in response to isolated nutrient resources, competition between multiple colonies and fungal development and persistence in polluted environments. These investigations demonstrate the versatility of the hybrid model and highlight the potential for further applications