Detalhes bibliográficos
| Ano de defesa: |
2020 |
| Autor(a) principal: |
Neelakshi Joshi |
| Orientador(a): |
Reinaldo Roberto Rosa,
Stephan Stephany |
| Banca de defesa: |
Francisco Carlos Rocha Fernandes,
Juan Alejandro Valdivia |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
eng |
| Instituição de defesa: |
Instituto Nacional de Pesquisas Espaciais (INPE)
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação do INPE em Computação Aplicada
|
| Departamento: |
Não Informado pela instituição
|
| País: |
BR
|
| Link de acesso: |
http://urlib.net/sid.inpe.br/mtc-m21c/2020/04.17.16.01
|
Resumo: |
Many dynamic processes in space physics can be investigated from the study of nonlinear fluctuations observed from instruments with high temporal and spectral resolution. In this thesis, it is presented, for the first time, the characterization of inhomogeneous turbulence as a possible cause of the spectral deviations found for the variables associated with the instability of the ionospheric and solar plasma. Algorithms based on formalisms for the analysis of monofractal and multifractal detrended fluctuation (DFA-MFDFA) were implemented. To validate the results obtained from the multifractal analysis, the theoretical framework for the energy cascade, based on twoscale Cantor set, a formalism known as the p model, was also implemented, tested and used. The multiplicity of intermittent behavior of plasma irregularities in the Type I solar emissions, the ionospheric F region and the E-F valley region were characterized by the MFDFA, including the respective validations through the p model spectra. The multifractal spectra are presented for the three case studies in space physics. In all three cases, the hypothesis of a non homogeneous multiplicative cascade process for the distribution of turbulent energy is confirmed by the spectra. Also, the same analytical computational procedure has been discussed for applications in complex systems in general, considering, for example, the modelling of armed conflict time series. |
