WALMIR MAXIMO TORRES
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Artigo IPEN-doc 25565 Two-phase flow void fraction estimation based on bubble image segmentation using Randomized Hough Transform with Neural Network (RHTN)2020 - SERRA, PEDRO L.S.; MASOTTI, PAULO H.F.; ROCHA, MARCELO S.; ANDRADE, DELVONEI A. de; TORRES, WALMIR M.; MESQUITA, ROBERTO N. deThe International Atomic Energy Agency (IAEA) has been encouraging the use of passive cooling systems in new designs of nuclear power plants. Next nuclear reactor generations are intended to have simpler and robust safety resources. Natural Circulation based systems hold an undoubtedly prominent position among these. The study of limiting conditions of these systems has led to instability behavior analysis where many different two-phase flow patterns are present. Void fraction is a key parameter in thermal transfer analysis of these flow instability conditions. This work presents a new method to estimate void fraction from images captured of an experimental two-phase flow circuit. The method integrates a set of Artificial Neural Networks with a modified Randomized Hough Transform to make multiple scans over acquired images, using crescent-sized masks. This method was called Randomized Hough Transform with Neural Network (RHTN). Each different mask size is chosen according with bubble sizes, which are the main ‘objects of interest’ in this image analysis. Images are segmented using fuzzy inference with different parameters adjusted based on acquisition focus. Void fraction calculation considers the volume of the imaged geometrical section of flow inside cylindrical glass tubes considering the acquisition depth-of-field used. The bubble volume is estimated based on geometrical parameters inferred for each detected bubble. The image database is obtained from experiments performed on a vertical two-phase flow circuit made of cylindrical glass where flow-patterns visualization is possible. The results have shown that the estimation method had good agreement with increasing void fraction experimental values. RHTN has been very efficient as bubble detector with very low ‘false-positive’ cases (< 0.004%) due robustness obtained through integration between Artificial Neural Networks with Randomized Hough Transforms.Artigo IPEN-doc 25071 Two-phase flow bubble detection method applied to natural circulation system using fuzzy image processing2018 - BUENO, R.C.; MASOTTI, P.H.F.; JUSTO, J.F.; ANDRADE, D.A.; ROCHA, M.S.; TORRES, W.M.; MESQUITA, R.N. deNatural circulation cooling systems are currently used in new nuclear reactors. Over the last decades, research in these systems has focused in the study of flow and heat transfer parameters. A particular area of interest is the estimation of two-phase flow parameters by image processing and pattern recognition using intelligent processing. Several methods have been proposed to identify objects of interest in bubbly two-phase images. Edge detection is an important task to estimate flow parameters, in which the bubbles are segmented to obtain several features, such as void fraction, area, and diameter. However, current methods face difficulties in determining those parameters in high bubble-density two-phase flow images. Here, a new edge detection method is proposed to segment bubbles in natural circulation instability images. The new method (Fuzzy Contrast Standard Deviation – FUZCON) uses Fuzzy Logic and image standard deviation estimates of locally measured contrast levels. Images were obtained through an experimental circuit made of glass, which enables imaging flow patterns of natural circulation cycles at ambient pressure. The results indicated important improvements on edge detection efficiency for high void fraction estimation on high-density two-phase flow bubble images, when compared to classical detectors, without the need to use smoothing algorithms or human intervention.Artigo IPEN-doc 24804 Thermal hydraulic analysis improvement for the IEA-R1 research reactor and fuel assembly design modification2018 - UMBEHAUN, PEDRO E.; TORRES, WALMIR M.; SOUZA, JOSE A.B.; YAMAGUCHI, MITSUO; SILVA, ANTONIO T. e; MESQUITA, ROBERTO N. de; SCURO, NIKOLAS L.; ANDRADE, DELVONEI A. deThis paper presents the sequence of activities to improve the thermal hydraulic analysis of the IEA-R1 research reactor to operate in safe conditions after power upgrade from 2 to 5 MW and core size reduction from 30 to 24 fuel assemblies. A realistic analysis needs the knowledge of the actual operation conditions (heat flow, flow rates) beyond the geometric data and the uncertainties associated with manufacturing and measures. A dummy fuel assembly was designed and constructed to measure the actual flow rate through the core fuel assemblies and its pressure drop. First results showed that the flow distribution over the core is nearly uniform. Nevertheless, the values are below than the calculated ones and the core bypass flow rate is greater than those estimated previously. Based on this, several activities were performed to identify and reduce the bypass flow, such as reduction of the flow rate through the sample irradiators, closing some unnecessary secondary holes on the matrix plate, improvement in the primary flow rate system and better fit of the core components on the matrix plate. A sub-aquatic visual system was used as an important tool to detect some bypass flow path. After these modifications, the fuel assemblies flow rate increased about 13%. Additional tests using the dummy fuel assembly were carried out to measure the internal flow distribution among the rectangular channels. The results showed that the flow rate through the outer channels is 10% - 15% lower than the internal ones. The flow rate in the channel formed between two adjacent fuel assemblies is an estimated parameter and it is difficult to measure because this is an open channel. A new thermal hydraulic analysis of the outermost plates of the fuel assemblies takes into account all this information. Then, a fuel design modification was proposed with the reduction of 50% in the uranium quantity in the outermost fuel plates. In order to avoid the oxidation of the outermost plates by high temperature, low flow rate, a reduction of 50% in the uranium density in the same ones was shown to be adequate to solve the problem.Artigo IPEN-doc 24758 Classification of natural circulation two-phase flow image patterns based on self-organizing maps of full frame DCT coefficients2018 - MESQUITA, ROBERTO N. de; CASTRO, LEONARDO F.; TORRES, WALMIR M.; ROCHA, MARCELO da S.; UMBEHAUN, PEDRO E.; ANDRADE, DELVONEI A.; SABUNDJIAN, GAIANE; MASOTTI, PAULO H.F.Many of the recent nuclear power plant projects use natural circulation as heat removal mechanism. The accuracy of heat transfer parameters estimation has been improved through models that require precise prediction of two-phase flow pattern transitions. Image patterns of natural circulation instabilities were used to construct an automated classification system based on Self-Organizing Maps (SOMs). The system is used to investigate the more appropriate image features to obtain classification success. An efficient automated classification system based on image features can enable better and faster experimental procedures on two-phase flow phenomena studies. A comparison with a previous fuzzy inference study was foreseen to obtain classification power improvements. In the present work, frequency domain image features were used to characterize three different natural circulation two-phase flow instability stages to serve as input to a SOM clustering algorithm. Full-Frame Discrete Cosine Transform (FFDCT) coefficients were obtained for 32 image samples for each instability stage and were organized as input database for SOM training. A systematic training/test methodology was used to verify the classification method. Image database was obtained from two-phase flow experiments performed on the Natural Circulation Facility (NCF) at Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN), Brazil. A mean right classification rate of 88.75% was obtained for SOMs trained with 50% of database. A mean right classificationrate of 93.98% was obtained for SOMs trained with 75% of data. These mean rates were obtained through 1000 different randomly sampled training data. FFDCT proved to be a very efficient and compact image feature to improve image-based classification systems. Fuzzy inference showed to be more flexible and able to adapt to simpler statistical features from only one image profile. FFDCT features resulted in more precise results when applied to a SOM neural network, though had to be applied to the full original grayscale matrix for all flow images to be classified.Artigo IPEN-doc 21073 Self-organizing maps applied to two-phase flow on natural circulation loop studies2015 - CASTRO, LEONARDO F.; CUNHA, KELLY de P.; ANDRADE, DELVONEI A. de; SABUNDJIAN, GAIANE; TORRES, WALMIR M.; MACEDO, LUIZ A.; ROCHA, MARCELO da S.; MASOTTI, PAULO H.F.; MESQUITA, ROBERTO N. deArtigo IPEN-doc 19812 The behavior of ANGRA 2 nuclear power plant core for a small break LOCA simulated with RELAP5 code2013 - SABUNDJIAN, GAIANE; ANDRADE, DELVONEI A.; BELCHIOR JUNIOR, ANTONIO; ROCHA, MARCELO da S.; CONTI, THADEU N.; TORRES, WALMIR M.; MACEDO, LUIZ A.; UMBEHAUN, PEDRO E.; MESQUITA, ROBERTO N.; MASOTTI, PAULO H.F.; LIMA, ANA C. de S.Artigo IPEN-doc 15277 Thermal hydraulic phenomenology for the heating process in a natural circulation facility2009 - TORRES, WALMIR M.; MACEDO, LUIZ A.; MESQUITA, ROBERTO N.; MASOTTI, PAULO H.F.; LIBARDI, ROSANI M.P.; SABUNDJIAN, GAIANE; ANDRADE, DELVONEI A.; UMBEHAUN, PEDRO E.; CONTI, THADEU N.; FILHO, MAURO F.S.; MELO, GABRIEL R.Artigo IPEN-doc 15276 Comparison between experimental data and numerical modeling for the natural circulation phenomenon2009 - SABUNDJIAN, GAIANE; ANDRADE, DELVONEI A.; UMBEHAUN, PEDRO E.; TORRES, WALMIR M.; MACEDO, LUIZ A.; CONTI, THADEU N.; MESQUITA, ROBERTO N.; MASOTTI, PAULO H.F.; PENHA, ROSANI M.L.; SILVA FILHO, MAURO F.; MELO, GABRIEL R.; BRAZ FILHO, FRANCISCO A.; BORGES, EDUARDO M.Artigo IPEN-doc 17037 Frequency analysis for the thermal hydraulic characterization of a natural circulation circuit2011 - TORRES, WALMIR M.; MACEDO, LUIZ A.; SABUNDJIAN, GAIANE; ANDRADE, DELVONEI A.; UMBEHAUN, PEDRO E.; CONTI, THADEU N.; MESQUITA, ROBERTO N.; MASOTTI, PAULO H.; ANGELO, GABRIELArtigo IPEN-doc 16918 A RELAP5 study to identify flow regime in natural circulation phenomenon2011 - SABUNDJIAN, GAIANE; TORRES, WALMIR M.; MACEDO, LUIZ A.; MESQUITA, ROBERTO N.; ANDRADE, DELVONEI A.; UMBEHAUN, PEDRO E.; CONTI, THADEU N.; MASOTTI, PAULO H.F.; BELCHIOR JUNIOR, ANTONIO; ANGELO, GABRIEL