Algorítmo de mapeamento usando modelagem probabilística

SOUZA, Anderson A.S. ; MEDEIROS, Adelardo A. D. ; GONÇALVES, Luiz Marcos G. . Algorítmo de mapeamento usando modelagem probabilística. In: SIMPOSIO BRASILEIRO DE AUTOMAÇÃO INTELIGENTE, 2007, Natal. Anais... Natal, 2007.

Mapeamento com Sonar Usando Grade de Ocupação baseado em Modelagem Probabilística

In this work, we propose a probabilistic mapping method with the mapped environment represented through a modified occupancy grid. The main idea of the proposed method is to allow a mobile robot to construct in a systematic and incremental way the geometry of the underlying space, obtaining at the end a complete environment map. As a consequence, the robot can move in the environment in a safe way, based on a confidence value of data obtained from its perceptive system. The map is represented in a coherent way, according to its sensory data, being these noisy or not, that comes from exterior and proprioceptive sensors of the robot. Characteristic noise incorporated in the data from these sensors are treated by probabilistic modeling in such a way that their effects can be visible in the final result of the mapping process. The results of performed experiments indicate the viability of the methodology and its applicability in the area of autonomous mobile robotics, thus being an contribution to the field

Algorítmo de mapeamento usando modelagem probabilística

SOUZA, Anderson A.S. ; MEDEIROS, Adelardo A. D. ; GONÇALVES, Luiz Marcos G. . Algorítmo de mapeamento usando modelagem probabilística. In: SIMPOSIO BRASILEIRO DE AUTOMAÇÃO INTELIGENTE, 2007, Natal. Anais... Natal, 2007.

Modelagem de dados de falhas de equipamentos de sub-superfície em poços de petróleo da Bacia Potiguar

This master´s thesis presents a reliability study conducted among onshore oil fields in the Potiguar Basin (RN/CE) of Petrobras company, Brazil. The main study objective was to build a regression model to predict the risk of failures that impede production wells to function properly using the information of explanatory variables related to wells such as the elevation method, the amount of water produced in the well (BSW), the ratio gas-oil (RGO), the depth of the production bomb, the operational unit of the oil field, among others. The study was based on a retrospective sample of 603 oil columns from all that were functioning between 2000 and 2006. Statistical hypothesis tests under a Weibull regression model fitted to the failure data allowed the selection of some significant predictors in the set considered to explain the first failure time in the wells

Mapeamento robótico 2,5-D com representação em grade de ocupação-elevação

This work introduces a new method for environment mapping with three-dimensional information from visual information for robotic accurate navigation. Many approaches of 3D mapping using occupancy grid typically requires high computacional effort to both build and store the map. We introduce an 2.5-D occupancy-elevation grid mapping, which is a discrete mapping approach, where each cell stores the occupancy probability, the height of the terrain at current place in the environment and the variance of this height. This 2.5-dimensional representation allows that a mobile robot to know whether a place in the environment is occupied by an obstacle and the height of this obstacle, thus, it can decide if is possible to traverse the obstacle. Sensorial informations necessary to construct the map is provided by a stereo vision system, which has been modeled with a robust probabilistic approach, considering the noise present in the stereo processing. The resulting maps favors the execution of tasks like decision making in the autonomous navigation, exploration, localization and path planning. Experiments carried out with a real mobile robots demonstrates that this proposed approach yields useful maps for robot autonomous navigation

Modelagem dinâmica e simulação computacional de poços de petróleo verticais e direcionais com elevação por bombeio mecânico

LINS, Filipe C. A. et al. Modelagem dinâmica e simulação computacional de poços de petróleo verticais e direcionais com elevação por bombeio mecânico. In: CONGRESSO BRASILEIRO DE PESQUISA E DESENVOLVIMENTO EM PETRÓLEO E GÁS, 5. 2009, Fortaleza, CE. Anais... Fortaleza: CBPDPetro, 2009.

Modelagem analítica e experimental da filtração em meios porosos

Deep bed filtration occurs in several industrial and environmental processes like water filtration and soil contamination. In petroleum industry, deep bed filtration occurs near to injection wells during water injection, causing injectivity reduction. It also takes place during well drilling, sand production control, produced water disposal in aquifers, etc. The particle capture in porous media can be caused by different physical mechanisms (size exclusion, electrical forces, bridging, gravity, etc). A statistical model for filtration in porous media is proposed and analytical solutions for suspended and retained particles are derived. The model, which incorporates particle retention probability, is compared with the classical deep bed filtration model allowing a physical interpretation of the filtration coefficients. Comparison of the obtained analytical solutions for the proposed model with the classical model solutions allows concluding that the larger the particle capture probability, the larger the discrepancy between the proposed and the classical models

Modelagem e previsão da perda de injetividade em poços canhoneados

Waterflooding is a technique largely applied in the oil industry. The injected water displaces oil to the producer wells and avoid reservoir pressure decline. However, suspended particles in the injected water may cause plugging of pore throats causing formation damage (permeability reduction) and injectivity decline during waterflooding. When injectivity decline occurs it is necessary to increase the injection pressure in order to maintain water flow injection. Therefore, a reliable prediction of injectivity decline is essential in waterflooding projects. In this dissertation, a simulator based on the traditional porous medium filtration model (including deep bed filtration and external filter cake formation) was developed and applied to predict injectivity decline in perforated wells (this prediction was made from history data). Experimental modeling and injectivity decline in open-hole wells is also discussed. The injectivity of modeling showed good agreement with field data, which can be used to support plan stimulation injection wells

Modelagem e simulação de um sistema de bombeio mecânico em poços direcionais utilizando parâmetros concentrados

This work aims presenting the development of a model and computer simulation of a sucker rod pumping system. This system take into account the well geometry, the flow through the tubing, the dynamic behavior of the rod string and the use of a induction motor model. The rod string were modeled using concentrated parameters, allowing the use of ordinary differential equations systems to simulate it s behavior

Análise da modelagem experimental da perda de injetividade

Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different

Modelagem do desempenho ambiental dos projetos de exploração e produção aplicando equações estruturais

A legislação ambiental e os principais agentes que se relacionam com a empresa se constituem em fatores exógenos que não podem ser negligenciados ao formular-se e avaliar-se a política ambiental corporativa. As influências exógenas e seus efeitos sobre a gestão ambiental e o gerenciamento de projetos de exploração e produção (E&P) e, por essa via, sobre o desempenho ambiental, foram objetos de estudo desta tese. Embora o desempenho ambiental seja um assunto relevante, a pesquisa sobre esse tema ainda é escassa. Tal carência desponta ainda mais acentuada quando se aborda o desempenho ambiental de projetos na indústria de petróleo e gás. O principal objetivo deste estudo foi avaliar a relação entre a legislação ambiental vigente, as ações de órgãos reguladores, fornecedores, empresas terceirizadas e comunidades locais e o desempenho ambiental dos projetos de E&P na indústria de petróleo e gás e, também, analisar os efeitos do sistema de gestão ambiental e o gerenciamento dos projetos sobre tal desempenho. Na fase abdutiva, foi conduzido um estudo de caso com abordagem qualitativa em uma grande empresa brasileira do setor de petróleo e gás, na fase dedutiva, foi realizada uma pesquisa survey explanatória de corte transversal com abordagem quantitativa, incluindo 113 projetos de E&P de cinco unidades executoras da empresa. Foi formulado um modelo conceitual, com cinco construtos e sete hipóteses de pesquisa, representativo dos efeitos de fatores externos sobre o desempenho ambiental dos projetos de E&P. Os dados foram tratados aplicando a Análise Fatorial Exploratória e a Modelagem de Equações Estruturais com aplicação dos softwares IBM® SPSS® Statistics 20.0 e IBM® SPSS® Amos 18.0. O modelo de equações estruturais foi reespecificado e estimado utilizando o método de Máxima Verossimilhança e o procedimento bootstrap com 2000 reamostragens, até alcançar adequados valores dos índices de ajustamento. O modelo mostrou boa aderência às evidências empíricas, representando uma teoria explicativa dos fatores que influenciam o desempenho ambiental dos projetos de E&P na empresa estudada. As estatísticas descritivas apontaram adequado desempenho dos projetos de E&P com relação aos efluentes descartados, volume de água reutilizada, redução de resíduos e práticas de reciclagem. Identificou-se que projetos de maior porte alcançam melhor desempenho ambiental em relação aos de menor tamanho. Não foram achadas diferenças significativas entre os desempenhos de projetos executados por unidades operacionais distintas. Os resultados da modelagem indicaram que nem a legislação ambiental, nem os agentes externos exercem influência significativa sobre a sistemática da gestão dos projetos de E&P. Os agentes externos atuam sobre a gestão ambiental da empresa exercitando capacidades colaborativas, obstrutivas e propositivas. A legislação ambiental é percebida como entrave ao desenvolvimento dos projetos ao longo de seu ciclo de vida, principalmente, pelas deficiências dos órgãos ambientais. Identificou-se que o sistema de gestão ambiental influencia diretamente o Programa de Desenvolvimento e Execução de Projetos de E&P, que, por sua vez, provoca efeitos diretos e indiretos sobre o desempenho ambiental. Finalmente, comprovou-se que o Sistema de Gestão Ambiental da empresa é determinante para o desempenho ambiental dos projetos de E&P, tanto pelos seus efeitos diretos, como pelos indiretos, estes últimos mediados pela sistemática de gestão dos projetos de E&P

Modelagem matemática para o transporte de partículas sujeitas a múltiplos mecanismos de retenção

Discrepancies between classical model predictions and experimental data for deep bed filtration have been reported by various authors. In order to understand these discrepancies, an analytic continuum model for deep bed filtration is proposed. In this model, a filter coefficient is attributed to each distinct retention mechanism (straining, diffusion, gravity interception, etc.). It was shown that these coefficients generally cannot be merged into an effective filter coefficient, as considered in the classical model. Furthermore, the derived analytic solutions for the proposed model were applied for fitting experimental data, and a very good agreement between experimental data and proposed model predictions were obtained. Comparison of the obtained results with empirical correlations allowed identifying the dominant retention mechanisms. In addition, it was shown that the larger the ratio of particle to pore sizes, the more intensive the straining mechanism and the larger the discrepancies between experimental data and classical model predictions. The classical model and proposed model were compared via statistical analysis. The obtained p values allow concluding that the proposed model should be preferred especially when straining plays an important role. In addition, deep bed filtration with finite retention capacity was studied. This work also involves the study of filtration of particles through porous media with a finite capacity of filtration. It was observed, in this case, that is necessary to consider changes in the boundary conditions through time evolution. It was obtained a solution for such a model using different functions of filtration coefficients. Besides that, it was shown how to build a solution for any filtration coefficient. It was seen that, even considering the same filtration coefficient, the classic model and the one here propposed, show different predictions for the concentration of particles retained in the porous media and for the suspended particles at the exit of the media

Biodegradação de hidrocarbonetos aromáticos policíclicos: prospecção metagenômica e modelagem computacional 3-D de proteínas

Knowledge of the native prokaryotes in hazardous locations favors the application of biotechnology for bioremediation. Independent strategies for cultivation and metagenomics contribute to further microbiological knowledge, enabling studies with non-cultivable about the "native microbiological status and its potential role in bioremediation, for example, of polycyclic aromatic hydrocarbons (HPA's). Considering the biome mangrove interface fragile and critical bordering the ocean, this study characterizes the native microbiota mangrove potential biodegradability of HPA's using a biomarker for molecular detection and assessment of bacterial diversity by PCR in areas under the influence of oil companies in the Basin Petroleum Geology Potiguar (BPP). We chose PcaF, a metabolic enzyme, to be the molecular biomarker in a PCR-DGGE detection of prokaryotes that degrade HPA s. The PCR-DGGE fingerprints obtained from Paracuru-CE, Fortim-CE and Areia Branca-RN samples revealed the occurrence of fluctuations of microbial communities according to the sampling periods and in response to the impact of oil. In the analysis of microbial communities interference of the oil industry, in Areia Branca-RN and Paracuru-CE was observed that oil is a determinant of microbial diversity. Fortim-CE probably has no direct influence with the oil activity. In order to obtain data for better understanding the transport and biodegradation of HPA's, there were conducted in silico studies with modeling and simulation from obtaining 3-D models of proteins involved in the degradation of phenanthrene in the transport of HPA's and also getting the 3-D model of the enzyme PcaF used as molecular marker in this study. Were realized docking studies with substrates and products to a better understanding about the transport mechanism and catalysis of HPA s

Modelagem molecular na caracterização eletrônica de oligopeptídeos e na descrição quântica da interação fármaco-receptor

In this dissertation, the theoretical principles governing the molecular modeling were applied for electronic characterization of oligopeptide α3 and its variants (5Q, 7Q)-α3, as well as in the quantum description of the interaction of the aminoglycoside hygromycin B and the 30S subunit of bacterial ribosome. In the first study, the linear and neutral dipeptides which make up the mentioned oligopeptides were modeled and then optimized for a structure of lower potential energy and appropriate dihedral angles. In this case, three subsequent geometric optimization processes, based on classical Newtonian theory, the semi-empirical and density functional theory (DFT), explore the energy landscape of each dipeptide during the search of ideal minimum energy structures. Finally, great conformers were described about its electrostatic potential, ionization energy (amino acids), and frontier molecular orbitals and hopping term. From the hopping terms described in this study, it was possible in subsequent studies to characterize the charge transport propertie of these peptides models. It envisioned a new biosensor technology capable of diagnosing amyloid diseases, related to an accumulation of misshapen proteins, based on the conductivity displayed by proteins of the patient. In a second step of this dissertation, a study carried out by quantum molecular modeling of the interaction energy of an antibiotic ribosomal aminoglicosídico on your receiver. It is known that the hygromycin B (hygB) is an aminoglycoside antibiotic that affects ribosomal translocation by direct interaction with the small subunit of the bacterial ribosome (30S), specifically with nucleotides in helix 44 of the 16S ribosomal RNA (16S rRNA). Due to strong electrostatic character of this connection, it was proposed an energetic investigation of the binding mechanism of this complex using different values of dielectric constants (ε = 0, 4, 10, 20 and 40), which have been widely used to study the electrostatic properties of biomolecules. For this, increasing radii centered on the hygB centroid were measured from the 30S-hygB crystal structure (1HNZ.pdb), and only the individual interaction energy of each enclosed nucleotide was determined for quantum calculations using molecular fractionation with conjugate caps (MFCC) strategy. It was noticed that the dielectric constants underestimated the energies of individual interactions, allowing the convergence state is achieved quickly. But only for ε = 40, the total binding energy of drug-receptor interaction is stabilized at r = 18A, which provided an appropriate binding pocket because it encompassed the main residues that interact more strongly with the hygB - C1403, C1404, G1405, A1493, G1494, U1495, U1498 and C1496. Thus, the dielectric constant ≈ 40 is ideal for the treatment of systems with many electrical charges. By comparing the individual binding energies of 16S rRNA nucleotides with the experimental tests that determine the minimum inhibitory concentration (MIC) of hygB, it is believed that those residues with high binding values generated bacterial resistance to the drug when mutated. With the same reasoning, since those with low interaction energy do not influence effectively the affinity of the hygB in its binding site, there is no loss of effectiveness if they were replaced.

Modelagem estocástica do índice de radiação ultravioleta na costa leste do nordeste do Brasil

The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (João Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period