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Publication# Identification of a Predator-Prey System from Simulation Data of a Convection Model

Abstract

The use of low-dimensional dynamical systems as reduced models for plasma dynamics is useful as solving an initial value problem requires much less computational resources than fluid simulations. We utilize a data-driven modeling approach to identify a reduced model from simulation data of a convection problem. A convection model with a pressure source centered at the inner boundary models the edge dynamics of a magnetically confined plasma. The convection problem undergoes a sequence of bifurcations as the strength of the pressure source increases. The time evolution of the energies of the pressure profile, the turbulent flow, and the zonal flow capture the fundamental dynamic behavior of the full system. By applying the SINDy method we identify a predator-prey type dynamical system that approximates the underlying dynamics of the three energy state variables. A bifurcation analysis of the system reveals consistency between the bifurcation structures, observed for the simulation data, and the identified underlying system.

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Related concepts (13)

Related publications (2)

Related MOOCs (19)

Simulation

A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Often, computers are used to execute the simulation. Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games.

Computational resource

In computational complexity theory, a computational resource is a resource used by some computational models in the solution of computational problems. The simplest computational resources are computation time, the number of steps necessary to solve a problem, and memory space, the amount of storage needed while solving the problem, but many more complicated resources have been defined. A computational problem is generally defined in terms of its action on any valid input.

Plasma (physics)

Plasma () is one of four fundamental states of matter, characterized by the presence of a significant portion of charged particles in any combination of ions or electrons. It is the most abundant form of ordinary matter in the universe, being mostly associated with stars, including the Sun. Extending to the rarefied intracluster medium and possibly to intergalactic regions, plasma can be artificially generated by heating a neutral gas or subjecting it to a strong electromagnetic field.

Plasma Physics and Applications [retired]

The first MOOC to teach the basics of plasma physics and its main applications: fusion energy, astrophysical and space plasmas, societal and industrial applications

Plasma Physics and Applications

The first MOOC to teach the basics of plasma physics and its main applications: fusion energy, astrophysical and space plasmas, societal and industrial applications

Plasma Physics: Introduction

Learn the basics of plasma, one of the fundamental states of matter, and the different types of models used to describe it, including fluid and kinetic.

Software engineering always cares to provide solutions for building applications as close as possible to what they should be, according to the requirements and the final users needs. Systems behavior simulation is a very common application to virtually reproduce and often predict the real-world behavior. Simulation is one of the most operational research tool in a large variety of engineering and scientific domains: Transport, telecommunication, medicine, chemical processes, physics, etc. The complexity of such application is relative to the increasing complexity of the systems. In this context, it is relevant to bring together different tools and formalisms such as markovian chain, Petri nets, etc., to improve the existent approaches and so to answer the simulations performances needs. The principle objective of this thesis is to bring together techniques from software engineering and safety engineering in order to improve the state of the art of modeling and simulation of dynamic systems in the industrial context. In addressing this objective, this work initially involves defining the essential limitations of the used formalisms, methods and tools regarding from one hand the software engineering modeling and simulation techniques and from the other hand the existent risk analysis methodologies. This work is conducted with respect to the problem of danger identification, considering the context of the complex systems behavior and their interaction with the human operator. In software engineering, it is well known that Petri/high-level nets have attractive characteristics to be used in systems simulation and behavior prediction such as the natural graphical representation, and their well-defined semantic. They are well-suited for the description of complex situations with concurrency (interleaving and true concurrency depending on the underlying semantics), conflict and confusion. However, the absence of structuring capabilities has been one of the main criticisms raised against Petri nets/high-level nets. Thus, there have been many attempts to introduce structuring principles in nets of this kind [BCM88] [Kie89] [JR91]. The attractive characteristics of Petri/high-level nets have prompted researchers to enrich these formalisms with object-oriented features. CO-OPN (Concurrent Object-Oriented Petri Net) approach, brings together the power of both Petri/high-level nets and object-orientation techniques, it has been devised so as to offer an adequate framework for the specification and design of large scale concurrent system [BG91]. CO-OPN, as a powerful modeling tool, has been used in a limited way to simulate systems. This work aims to provide a CO-OPN extension to allow a more realistic systems' simulation. Actually, its simulator semantic uses to be a suitable approach for modeling near closed systems and software components, because they need to loose coupling with external world. But, when we model more realistic problems like industrial processes, where human interaction is a relevant event, this approach is not sufficient to catch all system activity attributes. Moreover, the CO-OPN interpretation process does not allow interaction with the object internal states. This work provides a new solution to overcome CO-OPN simulation limitations and a set of prototypes to assist dynamic systems simulations. Furthermore, this work has been conducted in a Risk Analysis (RA) context, a domain where computer-based simulations research are of utmost interest. Actually, classical approaches used to address complex workplace hazard in a limited way, using checklists or sequence models. Moreover, the use of single oriented methods, such as AEA (man-oriented), FMEA (machine oriented) or HAZOP (process oriented), is not satisfactory to overcome the increasing sophistication of industrial processes. The automation of a part of the analysis process as well as the multiple-oriented approach allowed by dynamic modeling may indeed enhance significantly the analysis completeness and reduce the time analyzing time. This work, based on Object Oriented Petri net formalism (CO-OPN), propose an alternative multi-oriented approach where existent methods limitations have been criticized to develop a dynamic model, MORM (Man-machine Occupational Risk Modeling). A real industrial system (metal wire making process) has been specified to implement the different approach steps (system identification, model application, system simulation, system analysis).

Jean-Michel Sallese, Chiara Rossi

Modeling of optoelectronic devices involves long and complex numerical simulations, usually performed with TCAD tools. Numerical simulations provide accurate results for a single device but are not feasible when dealing with a full circuit comprising several nodes. To solve this issue, we developed a novel approach to simulate optoelectronic devices in standard SPICE circuit simulators, thus avoiding using TCAD tools. The concept is based on a coarse meshing of the semiconductor whose nodes are interconnected with the so-called Generalized Lumped Devices. The Generalized Lumped Devices are four ports devices: two ports simulate real currents and voltages in the semiconductor while two additional ports simulate excess carrier density and gradient through the definition of equivalent currents and voltages. The model behind the Generalized Devices is physics based and can correctly simulate optical generation of excess carriers, drift-diffusion transport, bulk and surface recombination as well as capacitive effects, without the need to introduce fitting or empirical parameters. Moreover, since all inputs and outputs are electrical quantities, the model is fully SPICE-compatible and can be merged with SPICE netlists of circuits. In this work, we use the Generalized Devices approach to simulate a bipolar phototransistor and prove that we can predict the photocurrent versus the collector voltage, for different illumination intensities. The model accurately takes into account the optically-triggered current amplification in the phototransistor. Sentaurus TCAD numerical simulations are in agreement with the Generalized Devices approach. Finally, since the model is physics based, we could assess the impact of different semiconductor parameters, such as doping concentrations, lifetime, surface recombination velocity, on the output characteristics of the phototransistors, directly with SPICE circuit simulators.