11 resultados para patógeno de planta

em Universidade Federal do Rio Grande do Norte(UFRN)


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In the last decades, the oil, gas and petrochemical industries have registered a series of huge accidents. Influenced by this context, companies have felt the necessity of engaging themselves in processes to protect the external environment, which can be understood as an ecological concern. In the particular case of the nuclear industry, sustainable education and training, which depend too much on the quality and applicability of the knowledge base, have been considered key points on the safely application of this energy source. As a consequence, this research was motivated by the use of the ontology concept as a tool to improve the knowledge management in a refinery, through the representation of a fuel gas sweetening plant, mixing many pieces of information associated with its normal operation mode. In terms of methodology, this research can be classified as an applied and descriptive research, where many pieces of information were analysed, classified and interpreted to create the ontology of a real plant. The DEA plant modeling was performed according to its process flow diagram, piping and instrumentation diagrams, descriptive documents of its normal operation mode, and the list of all the alarms associated to the instruments, which were complemented by a non-structured interview with a specialist in that plant operation. The ontology was verified by comparing its descriptive diagrams with the original plant documents and discussing with other members of the researchers group. All the concepts applied in this research can be expanded to represent other plants in the same refinery or even in other kind of industry. An ontology can be considered a knowledge base that, because of its formal representation nature, can be applied as one of the elements to develop tools to navigate through the plant, simulate its behavior, diagnose faults, among other possibilities

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The traditional processes for treatment of hazardous waste are questionable for it generates other wastes that adversely affect people s health. As an attempt to minimize these problems, it was developed a system for treatment of hazardous waste by thermal plasma, a more appropriate technology since it produces high temperatures, preventing the formation of toxic pollutants to human beings. The present work brings out a solution of automation for this plant. The system has local and remote monitoring resources to ensure the operators security as well as the process itself. A special attention was given to the control of the main reactor temperature of the plant as it is the place where the main processing occurs and because it presents a complex mathematical model. To this, it was employed cascaded controls based on Fuzzy logic. A process computer, with a particular man-machine interface (MMI), provides information and controls of the plant to the operator, including by Internet. A compact PLC module is in charge of the central element of management automation and plant control which receives information from sensors, and sends it to the MMI

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The present work describes the use of a mathematical tool to solve problems arising from control theory, including the identification, analysis of the phase portrait and stability, as well as the temporal evolution of the plant s current induction motor. The system identification is an area of mathematical modeling that has as its objective the study of techniques which can determine a dynamic model in representing a real system. The tool used in the identification and analysis of nonlinear dynamical system is the Radial Basis Function (RBF). The process or plant that is used has a mathematical model unknown, but belongs to a particular class that contains an internal dynamics that can be modeled.Will be presented as contributions to the analysis of asymptotic stability of the RBF. The identification using radial basis function is demonstrated through computer simulations from a real data set obtained from the plant

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This document proposes to describe a pilot plant for oil wells equipped with plunger lift. In addition to a small size (21,5 meters) and be on the surface, the plant s well has part of its structure in transparent acrylic, allowing easy visualization of phenomena inherent to the method. The rock formation where the well draws its pilot plant fluids (water and air) is simulated by a machine room where they are located the compressor and water pump for the production of air and water. To keep the flow of air and water with known and controlled values the lines that connect the machine room to the wellhole are equipped with flow sensors and valves. It s developed a supervisory system that allows the user a real-time monitoring of pressures and flow rates involved. From the supervisor is still allowed the user can choose how they will be controlled cycles of the process, whether by time, pressure or manually, and set the values of air flow to the water used in cycles. These values can be defined from a set point or from the percentage of valve opening. Results from tests performed on the plant using the most common forms of control by time and pressure in the coating are showed. Finally, they are confronted with results generated by a simulator configured with the the pilot plant s feature

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This work presents an analysis of the control law based on an indirect hybrid scheme using neural network, initially proposed for O. Adetona, S. Sathanathan and L. H. Keel. Implementations of this control law, for a level plant of second order, was resulted an oscillatory behavior, even if the neural identifier has converged. Such results had motivated the investigation of the applicability of that law. Starting from that, had been made stability mathematical analysis and several implementations, with simulated plants and with real plants, for analyze the problem. The analysis has been showed the law was designed being despised some components of dynamic of the plant to be controlled. Thus, for plants that these components have a significant influence in its dynamic, the law tends to fail

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The control, automation and optimization areas help to improve the processes used by industry. They contribute to a fast production line, improving the products quality and reducing the manufacturing costs. Didatic plants are good tools for research in these areas, providing a direct contact with some industrial equipaments. Given these capabilities, the main goal of this work is to model and control a didactic plant, which is a level and flow process control system with an industrial instrumentation. With a model it is possible to build a simulator for the plant that allows studies about its behaviour, without any of the real processes operational costs, like experiments with controllers. They can be tested several times before its application in a real process. Among the several types of controllers, it was used adaptive controllers, mainly the Direct Self-Tuning Regulators (DSTR) with Integral Action and the Gain Scheduling (GS). The DSTR was based on Pole-Placement design and use the Recursive Least Square to calculate the controller parameters. The characteristics of an adaptive system was very worth to guarantee a good performance when the controller was applied to the plant

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This work discusses the design of a transformer used in a plant plasma. This plant, which is being developed in UFRN, will be used in the treatment of waste. It consists basically of a radio frequency power supply and a inductive plasma torch. The transformer operates at the nominal frequency of 400 kHz, with 50 kW, allowing the adaptation of impedance between the power supply and torch. To develop the project, a study was done on the fabrication technologies and physical effects on the frequency of operation. This was followed by the modeling of this transformer. Finally, simulations and tests were conducted to validate the design

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This research was conducted with the aim to study the genetic and pathogenic structure of Ramularia areola isolates collected in Brazil and to characterize the resistance response in cotton plants to ramularia spot. The genetic variability of 28 isolates of R. areola was studied using RAPD markers. The pathogenicity evaluation was realized by the inoculation of 6 isolates on cotton varieties Guazuncho-2 (Gossypium hirsutum) and VH8-4602 (Gossypium barbadense). The inheritance of disease resistance was studied using an artificially inoculated population of F2 individuals derived from the intercross of Guazuncho-2 (susceptible variety) end VH8-4602 (resistant variety), and also the parents and F1 individuals. Molecular polymorphism between the G. hisutum varieties DeltaOpal (suscetible) and CNPA CO-11612 (resistant) was estimated by 118 SSR and 24 AFLP markers. The parental genotypes Guazuncho-2 and VH8-4602 were selected for mapping, and then Recombinant Inbred Lines (RIL´s) derived from this crossing were evaluated with SSR 12 markers. The analysis of population structure of R. areola revealed that the three subpopulations were genetically simillar (Gst=0.18), and the isolates from Goiás and Minas Gerais were more similar to each other (0,92). This probability can be related to the relatively high gene flow among the three subpopulations (Nm=2.20). The isolates R. areola 9.1, from Minas Gerais State and 8.1 and 8.3 from Goiás State were the most aggressive ones to the susceptible variety Guazuncho-2. The variety VH8-4602 presented high level of resistance to ramularia spot. No differential interaction was observed between the pathogens and the analyzed varieties, and the resistance was classified as horizontal. The quantification of disease by number of necrotic lesions and number of spores in individual plants of F1 and F2 generations from the crossing between the varieties Guazuncho-2 and VH8-4602 presented continuous distribution, suggesting polygenic resistance. The resistance is probabilly recessive, since necrotic lesions and sporulation were observed on F1 plants. The molecular polymorphism between DeltaOpal e CNPA CO-11612 lineages was low (6%), then would be difficult to accomplish molecular mapping of disease resistance using this intercross. With the genotyping of the RIL s it was verified that 25% of the markers segregated in the proportions proposed by Mendel s Law and 75% of the studied markers presented segregation distortion in favor to the parental G. hirsutum. Both the low genetic variability of the pathogen and the number of resistance genes suggest that durable genetic resitance may be achieved

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A major and growing problems faced by modern society is the high production of waste and related effects they produce, such as environmental degradation and pollution of various ecosystems, with direct effects on quality of life. The thermal treatment technologies have been widely used in the treatment of these wastes and thermal plasma is gaining importance in processing blanketing. This work is focused on developing an optimized system of supervision and control applied to a processing plant and petrochemical waste effluents using thermal plasma. The system is basically composed of a inductive plasma torch reactors washing system / exhaust gases and RF power used to generate plasma. The process of supervision and control of the plant is of paramount importance in the development of the ultimate goal. For this reason, various subsidies were created in the search for greater efficiency in the process, generating events, graphics / distribution and storage of data for each subsystem of the plant, process execution, control and 3D visualization of each subsystem of the plant between others. A communication platform between the virtual 3D plant architecture and a real control structure (hardware) was created. The goal is to use the concepts of mixed reality and develop strategies for different types of controls that allow manipulating 3D plant without restrictions and schedules, optimize the actual process. Studies have shown that one of the best ways to implement the control of generation inductively coupled plasma techniques is to use intelligent control, both for their efficiency in the results is low for its implementation, without requiring a specific model. The control strategy using Fuzzy Logic (Fuzzy-PI) was developed and implemented, and the results showed satisfactory condition on response time and viability

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This study focused object a steam generation system, steam distribution and condensate return a textile plant located in Rio Grande do Norte. The work was based on the following objectives: Knowing the use of saturated water vapor in the dyeing and finishing processes in a textile plant; To study the various aspects of a steam distribution system to identify the ways in which energy losses occur; Obtain quantitative information of the main loss in steam generation system and steam distribution and to measure the losses, water and steam system; Using the flash steam as a means of cost reduction. For it was made use of the calculation of financial gains made in their respective improvements. As a database for the development of working registers are used in industrial processes, data from utility systems, laboratory data analysis and on-line analyzers, covering the period 2013. Using the principles set conservation laws mass and energy, those data showed that the loss of water and energy in the steam system are significant and that the environmental and economic gains to be obtained with improvement actions are quite significant. Based on the data and results suggest that future studies deem the continuity approach to steam generation systems, distribution and mainly condensate return.

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In the last decades, the oil, gas and petrochemical industries have registered a series of huge accidents. Influenced by this context, companies have felt the necessity of engaging themselves in processes to protect the external environment, which can be understood as an ecological concern. In the particular case of the nuclear industry, sustainable education and training, which depend too much on the quality and applicability of the knowledge base, have been considered key points on the safely application of this energy source. As a consequence, this research was motivated by the use of the ontology concept as a tool to improve the knowledge management in a refinery, through the representation of a fuel gas sweetening plant, mixing many pieces of information associated with its normal operation mode. In terms of methodology, this research can be classified as an applied and descriptive research, where many pieces of information were analysed, classified and interpreted to create the ontology of a real plant. The DEA plant modeling was performed according to its process flow diagram, piping and instrumentation diagrams, descriptive documents of its normal operation mode, and the list of all the alarms associated to the instruments, which were complemented by a non-structured interview with a specialist in that plant operation. The ontology was verified by comparing its descriptive diagrams with the original plant documents and discussing with other members of the researchers group. All the concepts applied in this research can be expanded to represent other plants in the same refinery or even in other kind of industry. An ontology can be considered a knowledge base that, because of its formal representation nature, can be applied as one of the elements to develop tools to navigate through the plant, simulate its behavior, diagnose faults, among other possibilities