Programa de Pós-graduação em Computação

Tópicos Especiais em Computação – Introduction to Nonlinear Simulators

Código: CMP 579

Responsáveis: Anthony J. Park e Mara Abel
Carga Horária: 15 hs
Créditos: 1 crédito
Semestres Oferecidos: 2015/2 (sob demanda apenas)
Matrícula de Graduandos: Permitida
Idioma:  aulas serão ministradas em inglês
Público alvo:  estudantes e pesquisadores em Computação, Matemática, Física, Engenharia, Geologia, Hidrogeologia.
Pre-requisito:   Conhecimento em um destes tópicos:
– Desenvolvimento de software
– Física, Química ou Cálculo avançado
– Métodos numéricos ou métodos computacionais.

Matrícula
Alunos de pós-graduação de outras unidades e Universidades podem se inscrever como alunos especiais. Inscrição em http://ppgc.inf.ufrgs.br/  Opção Aluno Especial, solicitando a disciplina de código CMP579.

Local, datas e horário:
Programa de Pós-Graduação em Computação
Instituto de Informática da UFRGS
Campus do Vale Setor 4 – Predio 67 sala 106 (Confirme a sala mais próximo ao curso)
As aulas serão ministradas das 15:30 as 18:00  hs nos dias:
Outubro, Ter 13, Qua 14, Qui 15, Ter 20 , Qua 21, Qui 22.

 

Professor convidado e ministrante:

Anthony Park has a doctorate in theoretical geochemistry. Field of Study: Theoretical geochemistry, applied computational geochemistry.  Development and application of computational simulators employing fundamental basic sciences; nonlinear dynamics; use of information technology to maximize effectiveness and efficiency of simulations; applications to environmental, petroleum exploration/production, and other geotechnical problems. Although he is an Associate professor of San Diego State University (CA, US), Tony has develop his carrier in the petroleum industry of US and Europe and he is a highly recognized consultant in reservoir and basin simulation for many of the larger petroleum companies in the world.

Súmula:

1. Introduction to Nonlinear Dynamics
2. Evolving systems and steady-state systems
3. Self-organization (self-ordering) and Patterns (Geology and Chemistry)
4. Computational Simulator Design
5. Flow-reaction Interaction (Geological) Simulator Example

Objetivos:

In a nonlinear system, two or more variables are linked through two or more processes: they are inter-dependent on each other, such that any change imposed on a process or a variable also affects the other processes and variables. They are also called coupled systems, and include chaotic, periodic, and oscilliatory systems. Real-world examples include fluid flow (laminar vs. turbulent), weather prediction (storms), chemical reactions (oscillators), and even financial systems (stock market).

Nonlinear dynamics simulators typically model how these systems evolve in time. A unique properties of these models is that the end results are not predictable at the beginning, and they also depend on the initial (starting) system configurations. These simulators are highly specialized and they require close collaborations between the disciplinary specialists and software developers. However, they are also characterized by a set of common principles on design and methods.

This couse will focus on the principles of simulator development, and will not address the mathematics governing the physical and chemical processes. Instead, the focus will be on how to evaluate the physical and chemical systems to be modeled, and to design a simulator for the problem provided.

Examples from chemical, engineering, and in particular geological disciplines will be reviewed. In particular, geological sciences provides us with a large variety of nonlinear processes that require the considerations of heat and fluid flow, stresses, and chemical reactions. One of these systems, of modeling what happens to buried sediments, will be used to demonstrate the design of a simulator.

Conteúdos

 

1. Introduction: definition of a nonlinear system
2. Difference between evolutionary and steady-state equations
3. Computational approach: numerical methods
4. Space and time: discretization
5. Self-consistent systems
6. Simulator: evaluating the problem
7. Information: flow of data and priority of processes
8. Simulator design: loops and iterations
9. Visualization: working with multidimensional data

Procedimentos:
Expositive classes and exercises in class

Critérios de Avaliação:
Class attendance
Exercise: a simulator design

 

Bibliografia básica:

Gleick, James (2008), Chaos: Making a New Science (2008), New York, Penguin Books (Introduction and highlights of concepts)

Casos e exemplos

Szymkiewica, Adam (2013), Modelling Water Flow in Unsaturated Porous Media: Accounting for Nonlinear Permeability and Material Heterogeneity, Berlin, Springer Berlin Heidelberg

Chaos Theory (general description): https://en.wikipedia.org/wiki/Chaos_theory

Chemical clock (oscillators): https://en.wikipedia.org/wiki/Chemical_clock

Patterns in Nature (see Pattern formation): https://en.wikipedia.org/wiki/Patterns_in_nature

Climate model: https://en.wikipedia.org/wiki/Climate_model

Online game, predator-prey simulation (wolves and foxes): http://www.sims.scienceinstruction.org/predprey/index.html

 

 

Outras informações
Profa Mara Abel
marabel@inf.ufrgs.br
Fone 3308-6825