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

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Developing an effective 2-D urban flood inundation model for city emergency management based on cellular automata

Flash floods have occurred frequently in the urban areas of southern China. An effective process-oriented urban flood inundation model is urgently needed for urban storm-water and emergency management. This study develops an efficient and flexible cellular automaton (CA) model to simulate storm-water runoff and the flood inundation process during extreme storm events. The process of infiltration, inlets discharge and flow dynamics can be simulated with little preprocessing on commonly available basic urban geographic data. In this model, a set of gravitational diverging rules are implemented to govern the water flow in a rectangular template of three cells by three cells of a raster layer. The model is calibrated by one storm event and validated by another in a small urban catchment in Guangzhou of southern China. The depth of accumulated water at the catchment outlet is interpreted from street-monitoring closed-circuit television (CCTV) videos and verified by on-site survey. A good level of agreement between the simulated process and the reality is reached for both storm events. The model reproduces the changing extent and depth of flooded areas at the catchment outlet with an accuracy of 4 cm in water depth. Comparisons with a physically based 2-D model (FloodMap) show that the model is capable of effectively simulating flow dynamics. The high computational efficiency of the CA model can meet the needs of city emergency management

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

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

A multi-scale network with percolation model to describe the spreading of forest fires

Forest fires have been a major threat to forest ecosystems and its biodiversity, as well as the environment in general, particularly in the Mediterranean regions. To mitigate fire spreading, this study aims at finding a fire-break solution for territories prone to fire occurrence. To the effect, here follows a model to map and predict phase transitions in fire regimes (spanning fires vs. penetrating fires) based on terrain morphology. The structure consists of a 2-scale network using site percolation and SIR epidemiology rules in a cellular automata to model local fire Dynamics. The target area for the application is the region of Serra de Ossa in Portugal, due to its wildfire incidence. The study considers the cases for a Moore neighbourhood of warm cells of radius 1 and 2 and also considers a heterogeneous terrain with 3 classes of vegetation. Phase transitions are found for different combinations of fire risk for each of these classes and use these values to parametrize the resulting landscape network.info:eu-repo/semantics/publishedVersio

Reliable and Resilient Surface Water Management through Rapid Scenario Screening

Surface water flooding causes significant damage, disruption and loss of life in cities, both in the UK and globally. These impacts have historically been managed through application of conventional urban drainage systems designed to meet specified design standards. Conventional strategies have performed well in the past, but are becoming increasingly unfit for purpose due to intensifying hazards caused by several emerging challenges, including climate change, urban growth and aging drainage infrastructure. In response, an extensive range of alternative novel interventions has been developed. These have been successfully applied across many case studies and their performance to meet design standards on specific sites is now well understood. However, application is still limited and challenges exist regarding how to maximise performance at the urban catchment scale and incorporate resilience to extreme rainfall events within design. This thesis addresses these challenges through evaluating intervention performance using a rapid scenario screening framework. This framework delivers insight into the complex permutations of intervention strategies at a catchment scale through evaluating alternatives, scales, spatial interactions and responses to a range of rainfall events. The study achieves novelty through developing a new modelling methodology which applies cell parameterisation to represent urban drainage systems and interventions using an existing cellular automata model. The framework is applied at a high level to screen intervention performance using easily accessible data and simplified intervention strategies, it is envisaged that this style of analysis is appropriate for initial catchment assessment to evidence and direct future flood management actions. The research finds intervention scale, distribution and placement to be important factors in determining performance within the context of initial catchment screening using theoretical modelling parameters. Although localised interventions provide benefit at a smaller scale, catchment based strategies are required to substantially reduce estimated annual damage costs across urban areas. The most effective intervention was consistently found to be extensive application of decentralised rainfall capture, which reduced expected annual damage in a UK case study by up to 76%. Intervention distribution and placement are also demonstrated to significantly influence cost effectiveness of strategies, with a wide range of ratios predicted, ranging from £0.10 to £26.0 saved per £1 spent. The most cost effective interventions across the case studies investigated were found to be high volume local drainage interventions targeted in areas of intense flooding. Results demonstrate significant variation in strategy performance depending on rainfall intensity and duration. Analysis across events ranging from 2 to 1000 year return periods found many interventions which performed well during design standard events demonstrate substantial decreases in effectiveness during higher magnitude rainfall. Of particular note are interventions with finite storage capacities, which exhibit considerable decreases in performance at certain threshold levels. The implications of this finding are that designing interventions with resilient performance requires simulation of many rainfall scenarios, and that interventions with resilient properties, such as green infrastructure, do not necessarily achieve resilient performance. The research also identifies that rapid screening frameworks contribute an adaptable and useful tool for stakeholder engagement, intervention design and scenario exploration. Case study application of the framework alongside catchment stakeholders in Melbourne, Australia, facilitated an efficient and collaborative design screening process which benefitted from enhanced communication across a wide range of expertise. The simplified development of intervention strategies provided a clear communication tool which supported the multi-disciplinary investigations required for urban planning in a complex environment. Analysis of many strategy permutations highlighted the advantage of multiple smaller intervention strategies accumulating towards catchment scale benefits, a possibility which is advantaged through stakeholder communication tools, such as this framework. Overall, this thesis demonstrates that reliable and resilient surface water management can be achieved through decentralised catchment scale implementation of interventions, complemented by targeted and cost effective high volume measures. Complexity and variation of outcomes across a range of scenarios indicates the importance of encapsulating the complex permutations of options when evaluating interventions and provides justification for future application of rapid scenario screening frameworks.Engineering and Physical Sciences Research Council (EPSRC

Understanding morphogenesis in myxobacteria from a theoretical and experimental perspective

Several species of bacteria exhibit multicellular behaviour, with individuals cells cooperatively working together within a colony. Often this has communal benefit since multiple cells acting in unison can accomplish far more than an individual cell can and the rewards can be shared by many cells. Myxobacteria are one of the most complex of the multicellular bacteria, exhibiting a number of different spatial phenotypes. Colonies engage in multiple emergent behaviours in response to starvation culminating in the formation of massive, multicellular fruiting bodies. In this thesis, experimental work and theoretical modelling are used to investigate emergent behaviour in myxobacteria. Computational models were created using FABCell, an open source software modelling tool developed as part of the research to facilitate modelling large biological systems. The research described here provides novel insights into emergent behaviour and suggests potential mechanisms for allowing myxobacterial cells to go from a vegetative state into a fruiting body. A differential equation model of the Frz signalling pathway, a key component in the regulation of cell motility, is developed. This is combined with a three-dimensional model describing the physical characteristics of cells using Monte Carlo methods, which allows thousands of cells to be simulated. The unified model explains how cells can ripple, stream, aggregate and form fruiting bodies. Importantly, the model copes with the transition between stages showing it is possible for the important myxobacteria control systems to adapt and display multiple behaviours