Donato D’Ambrosio

A New Algorithm for Simulating Wildfire Spread through Cellular Automata

Cell-based methods for simulating wildfires can be computationally more efficient than techniques based on the fire perimeter expansion. In spite of this, their success has been limited by the distortions that plague the simulated shapes. This article presents a novel algorithm for wildfire simulation through Cellular Automata (CA), which is able to effectively mitigate the problem of distorted fire shapes. Such a result is obtained allowing spread directions that are not constrained to the few angles imposed by the lattice of cells and the neighborhood size. The characteristics of the proposed algorithm are empirically investigated under homogeneous conditions through some comparisons with the outcomes of a typical CA-based simulator. Also, using two significant heterogeneous landscapes, a comparison with the vector-based simulator FARSITE is discussed. According to the results of this study, the proposed approach performs significantly better, in terms of accuracy, than the CA taken as reference. In addition, at a far less computational cost, it provides burned regions that are equivalent, for practical purposes, to those given by FARSITE.

Pyroclastic flows modelling using cellular automata

Cellular automata (CA) and derived computational paradigms represent an alternative approach to differential equations to model and simulating complex fluid dynamical systems, whose evolution depends on the local interactions of their constituent parts. A new notion of CA was developed according to an empirical method for modelling macroscopic phenomena; its application to PYR, a CA model for simulating pyroclastic flows, generated PYR2, which permitted an improvement of the model and a more efficient implementation. PYR2 was utilised for the 1991 eruption of Mt. Pinatubo in the Philippines islands and for the 1996 eruption of the Soufriere Hills in the Montserrat Island. Results of the simulations are satisfactory if the comparison between real and simulated event is performed, considering the area involved by the event and the variations of thickness of the deposit, as generated by collapsing volcanic columns.

OpenMP parallelization of the SCIARA Cellular Automata lava flow model: performance analysis on shared-memory computers

Parallel Computing represents a valid solution for reducing execution times in simulations of complex geological processes, such as lava flows, debris flows and, in general, of fluid-dynamic processes. In these cases, Cellular Automata (CA) models have proved to be effective when the behavior of the system to be modeled can be described in terms of local interactions among its constituent parts. Cellular Automata are parallel computing models, discrete in space and time; space is generally subdivided into cells of uniform size and the overall dynamics of the system emerges as the result of the simultaneous application, at discrete time steps, of proper local rules of evolution to each one of them. Due to their intrinsic parallelism, CA models are attractive since they are suitable to be effectively and naturally implemented on parallel computers achieving also high performance. In the recent past, CA models were efficiently executed on distributed memory architectures, such as Beowulf clusters and many-node Supercomputers, while fewer implementations are found regarding shared-memory computers, such as in multi-core machines. This paper shows performance results of the parallelization of a well-known CA model for simulating lava flows – the SCIARA model – in a shared memory environment, by means of OpenMP, an Application Programming Interface which supports multi-platform shared-memory parallel programming.

Simulating the Curti–Sarno debris flow through cellular automata: the model SCIDDICA (release S2)

Cellular automata (CA) are based on a regular division of the space in cells. Each cell embeds an identical finite automaton, whose input is given by the states of neighbouring cells. The transition function r of the CA is made of a set of rules, simultaneously applied, step by step, to each cell of the cellular space. Rules are derived by subdividing, in computational terms, the physical phenomenon into a set of independent, elementary processes. By properly combining each elementary result, the behaviour of the phenomenon can be simulated. Debris flows are dense mixtures of sediment and water, which surge down the slopes and along the drainage system, characterised by severe destructive potential. They can be described in terms of local interactions among their elementary portions, and can thus be efficiently modelled through CA. Debris-flows rheologic equations cannot be easily solved without making substantial simplifications. By applying CA, a phenomenological description––able to overcome resource computational limits––can be obtained. On May 1998, hundreds of soil slip-debris flows were triggered by exceptional rains in Campania (Italy), mostly on the slopes of Pizzo dAlvano. Aiming at modelling purposes, the Curti debris flow was selected as a case study, among the whole population of landslides triggered by the event. The general frame of SCIDDICAS2 is inherited from previous releases, recently applied for the simulation of the 1992 Tessina (Italy) earth flow and of the 1984 Mt. Ontake (Japan) debris avalanche. Since its S1 release, the model satisfactorily simulated the Curti–Sarno debris flow. Latest improvements to the transition function led to the S2 release, and to better simulations (presented here). SCIDDICA exhibits a notable flexibility in modelling and simulating flow-like landslides. It could be usefully applied in hazard mapping (also through a statistical approach), and in evaluating the effects of either human works or ‘‘accidents’’ along the path of the flow. � 2002 Elsevier Science Ltd. All rights reserved.

Morphological Coevolution for Fluid Dynamical-Related Risk Mitigation

In the lava flow mitigation context, the determination of areas exposed to volcanic risk is crucial for diminishing consequences in terms of human causalities and damages of material properties. In order to mitigate the destructive effects of lava flows along volcanic slopes, the building and positioning of artificial barriers is fundamental for controlling and slowing down the lava flow advance. In this article, an evolutionary computation-based decision support system for defining and optimizing volcanic hazard mitigation interventions is proposed. In particular, the SCIARA-fv2 Cellular Automata numerical model has been applied for simulating lava flows at Mt. Etna (Italy) volcano and Parallel Genetic Algorithms (PGA) adopted for optimizing protective measures construction by morphological evolution. The PGA application regarded the optimization of the position, orientation, and extension of earth barriers built to protect Rifugio Sapienza, a touristic facility located near the summit of the volcano. A preliminary release of the algorithm, called single barrier (SBA) approach, was initially considered. Subsequently, a second GA strategy, called Evolutionary Greedy Strategy (EGS), was implemented by introducing multibarrier protection measures in order to improve the efficiency of the final solution. Finally, a Coevolutionary Cooperative Strategy (CCS), has been introduced where all barriers are encoded in the genotype and, because all the constituents parts of the solution interact with the GA environment, a mechanism of cooperation between individuals has been favored. The study has produced extremely positive results and represents, to our knowledge, the first application of morphological evolution for lava flow mitigation.

A Multi-GPU Approach to Fast Wildfire Hazard Mapping

Burn probability maps (BPMs) are among the most effective tools to support strategic wildfire and fuels management. In such maps, an estimate of the probability to be burned by a wildfire is assigned to each point of a raster landscape. A typical approach to build BPMs is based on the explicit propagation of thousands of fires using accurate simulation models. However, given the high number of required simulations, for a large area such a processing usually requires high performance computing. In this paper, we propose a multi-GPU approach for accelerating the process of BPM building. The paper illustrates some alternative implementation strategies and discusses the achieved speedups on a real landscape.

High Detailed Lava Flows Hazard Maps by a Cellular Automata Approach

The determination of areas exposed to be interested by new eruptive events in volcanic regions is crucial for diminishing consequences in terms of human causalities and damages of material properties. In this paper, we illustrate a methodology for defining flexible high-detailed lava invasion hazard maps. Specific scenarios can be extracted at any time from the simulation database, for land-use and civil defence planning in the long-term, to quantify, in real-time, the impact of an imminent eruption, and to assess the efficiency of protective measures. Practical applications referred to some inhabited areas of Mt Etna (South Italy), Europe’s most active volcano, show the methodology’s appropriateness in this field.

Swii2, a HTML5/WebGL Application for Cellular Automata Debris Flows Simulation

We here present the preliminary release of Swii2, a web application for debris flows simulation. The core of the system is Sciddica-k0, the latest release of the Sciddica debris flow Cellular Automata family, already successfully applied to the 1997 Albano lake (Italy) debris flow. In Swii2, the Sciddica-k0 model runs server-side, while a Web 2.0 application controls the simulation. The graphical user interface is based on HTML5 and JavaScript, which permits to have a fully portable application. The client is able to control the basic Sciddica-k0 simulation functionalities thanks to asynchronous callbacks to the server. Simulation results are visualized in real time by means of a 3D interactive visualization system based on WebGL, a cross-platform application program interface used to create 3D graphics in Web browsers. Eventually, user-oriented cooperative services, which desktop applications in general do not offer, are conjectured and discussed.

The Open Computing Abstraction Layer for Parallel Complex Systems Modeling on Many-Core Systems

Abstract This article introduces OpenCAL, a new open source computing abstraction layer for multi- and many-core computing based on the Extended Cellular Automata general formalism. OpenCAL greatly simplifies the implementation of structured grid applications, contextually making parallelism transparent to the user. Different OpenMP- and OpenCL-based implementations have been developed, together with a preliminary MPI-based distributed memory version, which is currently under development. The system software architecture is presented and underlying data structures and algorithms described. Numerical correctness and efficiency have been assessed by considering the S c i d d i c a T Computational Fluid Dynamics landslide simulation model as reference example. Eventually, a comprehensive study has been performed to devise the best platform for execution as a function of numerical complexity and computational domain extent. Results obtained have highlighted the OpenCAL’s potential for numerical models development and their execution on the most suitable high-performance parallel computational device.

Evolving Protection Measures for Lava Risk Management Decision Making

Many volcanic areas around the World are densely populated and urbanized. For instance , Mount Etna (Italy) is home to approximately one million people, despite being the most active volcano in Europe. Mapping both the physical threat and the exposure and vulnerability of people and material properties to volcanic hazards can help local authorities to guide decisions about where to locate a priori critical infrastructures (e.g. hospitals, power plants, railroads, etc.) and human settlements and to devise for existing locations and facilities appropriate mitigation measures. We here present the application of Parallel Genetic Algorithms for optimizing earth barriers construction by morphological evolution, to divert a case study lava flow that is simulated by the numerical Cellular Automata model Sciara-fv2 at Mt Etna volcano (Sicily, Italy). The devised area regards Rifugio Sapienza, a touristic facility located near the summit of the volcano, where the methodology was applied for the optimization of the position, orientation and extension of an earth barrier built to protect the zone. The study has produced extremely positive results, providing insights and scenarios for the area representing, to our knowledge, the first application of morphological evolution for lava flow mitigation.