The Master's program of the PPGMC started in the second half of 2006. It was originally characterized as an interdisciplinary program due to the distinct training of its professors, which included doctors in Engineering, Mathematics, Physics, Computing and Oceanography.
Area of Concentration: Scientific Computing, originally with two main fields: physical and mathematical modeling and numerical simulation and computational methods.
Objectives: Computational Modeling seeks to create, evaluate, modify, compose, manage and explore models for complex systems associated with different domains and applications. Such resolution involves the development of statistical and mathematical models, algorithms and techniques of simulation, data manipulation, and data mining, among others. So, the model is one of the products of the research itself, being interpreted as a process that filters, transforms, aggregates and generates data and information. In addition, the different ways of incorporating uncertainties in the models should also be considered, what leads to the adoption of robust methodologies for the treatment of these uncertainties.
Curriculum Structure: the Master's student must attend 3 mandatory subjects and supplement their hours with elective subjects. The Doctorate student must attend 6 mandatory subjects and supplement his hours with elective subjects.
Student and graduate profile: the PPGMC seeks the training of human resources at the Master's and Doctorate level with an interdisciplinary profile, so they are able to act efficiently at the intersection of one or more of the following areas: Computing, Engineering, Physics and Mathematics. Besides that, this professional must have solid knowledge about the most diverse computational techniques, which allow him or her to formulate, in an appropriate and optimized way, the solution to problems involving phenomena (physical, engineering, social, etc.) of scientific and/or technological interest.
Prof. Emanuel Estrada
Adriano De Cezaro
Computational Mechanics, Geophysical Fluid Modeling, Scientific Computing and Physical Modeling, Mathematics and Statistics.
Institutional and Regional Context
The Computational Modeling fits into this context, as a research and development tenológico field that encompasses various methods of representing objects of study from natural processes, or artificial. Thus, the complexity of the interrelationships present in the coastal ecosystem, is in Computational Modeling a paradigm that has proved suitable, able to capture all the fundamental aspects of the problem, at a level of detail that it deems appropriate. We consider that the Computational Modeling should be able to enhance the transformation of scientific knowledge in technology and development, which arises also in accordance with the needs required by the regional environment, currently driven by the installation of a naval pole in Rio Grande, and institutional.
The Master's course PPGMC began operating from the second half of 2006. The same was originally characterized as a distinct interdisciplinary course due to the formation of their teachers, which included doctors in engineering, mathematics, physics, computer science and oceanography and audience seeking answers, supplying a demand for a master's degree graduates who could have as tickets coming from the mechanical engineering courses, civil and computing, mathematics and physics FURG as well as related areas of courses in other universities in the region.
Despite the diversity of the faculty, the course of action that united all researchers is scientific computation, which was the focus of studies of teachers, especially computing group, and a key tool in the research of others, thus justifying the creation of a post interdisciplinary graduate program of as an area of concentration computational modeling.
Originally, the program was designed with two lines of research:
physical and mathematical modeling: systems study with non-linear behavior, with applications to science and engineering, such as in the study of gravitational systems, inverse problems, transport phenomena, etc.
numerical methods and computational simulation: development of computational models in various fields of science and engineering and application of high performance and simulation processing techniques.
These two search lines were maintained in this configuration until 2009 when, due to the growth of the faculty, the program has been redesigned with three new lines of research are:
scientific computing and physics and mathematical modeling: study of physical and mathematical models able to describe complex systems with non-linear behavior, with applications to science and engineering. It is also performed in this research studies on the development of modern techniques of high performance computing and scientific visualization.
Geophysical modeling and fluid transport phenomena: study of evolution and adaptation phenomena associated with fluids Modeling and Transport Phenomena with emphasis on ocean and air circulation problems, dispersion of pollutants, thermodynamic and transport in porous media resin.
Modeling of robotic and autonomous systems: perception systems study, decision making, control and drive, study treatment techniques, filtering and prediction signals in dynamic systems, robust and stochastic control, embedded computing, vision and machine intelligence.
Recently, with the inclusion of financial resources and the significant increase in the number of teachers FURG, MEETING reflexes began to emerge at the university several other graduate programs in areas that were originally served only by PPGMC. The effect of this growth, there was again a major change of PPGMC faculty board that is providing the program to a further restructuring of its research. Currently the program is being reorganized on the basis of three new lines of research:
Computational Mechanics: this line of research is mainly focused on the numerical approach to engineering problems related to fluid mechanics, heat transfer and solid mechanics. Among the objectives, seeks recommendations for engineering problems such as the design of devices used for renewable energy conversion into electrical energy, manufacturing processes, structural analysis, simulation of complex arrangements of artifacts such as fins, heat exchangers, among others. The geometric optimization of various engineering systems mentioned and the study of complex phenomenology are also studied numerically.
Modeling geophysical phenomena: study of evolutionary related phenomena and adaptive modeling and Fluid Transport Phenomena with emphasis on problems of atmospheric and ocean circulation and dispersion of pollutants.
Computer Science and Modeling Physics, Mathematics and Statistics: study and development of numerical methods and analytics related to Computational Modeling, working on the development of approaches to physical and mathematical models capable of promoting the description and analysis of complex systems, with applications in science and engineering : optimization, inverse problems, stochastic models, modeling, processing and analysis of scientific data. Aims to promote the synergistic interaction of different fields of knowledge, providing tools to investigate complex phenomena which, until recently, could not be treated within the strict domain of established disciplines.
Study and development of numerical methods and analytics related to Computational Modeling, working on the development of approaches to physical and mathematical models capable of promoting the description and analysis of complex systems, with applications in science and engineering: optimization, inverse problems, stochastic models, modeling , processing and analysis of scientific data. Aims to promote the synergistic interaction of different fields of knowledge, providing tools to investigate complex phenomena which, until recently, could not be treated within the strict domain of established disciplines.