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Daniel R. Pipa
Researcher at Federal University of Technology - Paraná
Publications - 65
Citations - 473
Daniel R. Pipa is an academic researcher from Federal University of Technology - Paraná. The author has contributed to research in topics: Iterative reconstruction & Two-phase flow. The author has an hindex of 11, co-authored 57 publications receiving 333 citations. Previous affiliations of Daniel R. Pipa include Petrobras & Helmholtz-Zentrum Dresden-Rossendorf.
Papers
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Journal ArticleDOI
Image processing techniques for high-speed videometry in horizontal two-phase slug flows
C. E. F. do Amaral,Rafael Fabricio Alves,M. J. da Silva,Lúcia Valéria Ramos de Arruda,Leyza Baldo Dorini,Rigoberto E. M. Morales,Daniel R. Pipa +6 more
TL;DR: In this paper, a technique that automatically estimates bubble parameters (e.g., frequency, dimension and velocity) through video analysis of high-speed camera measurements in horizontal pipes is presented.
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Improving Spatial Resolution of Raman DTS Using Total Variation Deconvolution
João Paulo Bazzo,Daniel R. Pipa,Cicero Martelli,Erlon Vagner da Silva,Jean Carlos Cardozo da Silva +4 more
TL;DR: In this paper, a deconvolution algorithm is proposed to improve the spatial resolution of a Raman DTS system, which is based on a linear DTS model and total variation regularization.
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A sparse reconstruction algorithm for ultrasonic images in nondestructive testing.
Giovanni Alfredo Guarneri,Daniel R. Pipa,Flávio Neves Junior,Lúcia Valéria Ramos de Arruda,Marcelo V. W. Zibetti +4 more
TL;DR: In this paper, an image reconstruction algorithm based on regularized least squares using a l 1 regularization norm was proposed to reconstruct an image of a point-like reflector, using both simulated and real data.
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Accelerating Overrelaxed and Monotone Fast Iterative Shrinkage-Thresholding Algorithms With Line Search for Sparse Reconstructions
TL;DR: The use of fast line search is extended to the monotone fast iterative shrinkage-threshold algorithm (MFISTA) and some of its variants and shows through numerical results that line search improves their performance for tomographic high-resolution image reconstruction.
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Thermal Imaging of Hydroelectric Generator Stator Using a DTS System
João Paulo Bazzo,Felipe Mezzadri,Erlon Vagner da Silva,Daniel R. Pipa,Cicero Martelli,Jean Carlos Cardozo da Silva +5 more
TL;DR: In this article, a new method for thermal imaging of hydroelectric generators stators is presented based on distributed temperature optical fiber sensing using Raman scattering, which can contribute for identification of fault in the structure insulation, which when early identified can reduce damage caused by short circuit in the stator windings.