Thermoeconomic analysis method for optimization of combined heat and power systems. Part I

This article presents a thermoeconomic analysis of cogeneration plants, applied as a rational technique to produce electric power and saturated steam. The aim of this new methodology is the minimum Exergetic Production Cost (EPC), based on the Second Law of Thermodynamics. The variables selected for the optimization are the pressure and the temperature of the steam leaving the boiler in the case of using steam turbine, and the pressure ratio, turbine exhaust temperature and mass flow in the case of using gas turbines. The equations for calculating the capital costs of the components and products are formulated as a function of these decision variables. An application of the method using real data of a multinational chemical industry located in São Paulo state is presented. The conditions which establish the minimum cost are presented as final output. (C) 2003 Elsevier Ltd. All rights reserved.

A W-matrix methodology for solving sparse network equations on multiprocessor computers

This paper describes a methodology for solving efficiently the sparse network equations on multiprocessor computers. The methodology is based on the matrix inverse factors (W-matrix) approach to the direct solution phase of A(x) = b systems. A partitioning scheme of W-matrix , based on the leaf-nodes of the factorization path tree, is proposed. The methodology allows the performance of all the updating operations on vector b in parallel, within each partition, using a row-oriented processing. The approach takes advantage of the processing power of the individual processors. Performance results are presented and discussed.

Study of fuel cell co-generation systems applied to a dairy industry

This paper presents a methodology for the study of a molten carbonate fuel cell co-generation system. This system is applied to a dairy industry of medium size that typically demands 2100 kW of electricity, 8500 kg/h of saturated steam (P = 1.08 MPa) and 2725 kW of cold water production. Depending on the associated recuperation equipment, the co-generation system permits the recovery of waste heat, which can be used for the production of steam, hot and cold water, hot and cold air. In this study, a comparison is made between two configurations of fuel cell co-generation systems (FCCS). The plant performance has been evaluated on the basis of fuel utilisation efficiency and each system component evaluated on the basis of second law efficiency. The energy analysis presented shows a fuel utilisation efficiency of about 87% and exergy analysis shows that the irreversibilities in the combustion chamber of the plant are significant. Further, the payback period estimated for the fuel cell investment between US$ 1000 and US$ 1500/k-W is about 3 and 6 years, respectively. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Tangential-flow ultrafiltration: a versatile methodology for determination of complexation parameters in refractory organic matter from Brazilian water and soil samples

In this work the copper(II) complexation parameters of aquatic organic matter, aquatic and soil humic substances from Brazilian were determined using a new versatile approach based on a single-stage tangential-flow ultrafiltration (TF-UF) technique (cut-off 1 kDa) and sensitive atomic spectrometry methods. The results regarding the copper(II) complexation capacity and conditional stability constants obtained for humic materials were compared with those obtained using direct potentiometry with a copper-ion-selective electrode. The analytical procedure based on ultrafiltration is a good alternative to determine the complexation parameters in natural organic material from aquatic and soil systems. This approach presents additional advantages such as better sensibility, applicability for multi-element capability, and its possible to be used under natural conditions when compared with the traditional ion-selective electrode.

The characteristics of a test liquid formulation for use in evaluating the performance of handling and metering systems

Injection metering systems are an important option for the development of pesticide application equipment, with advantages relating to minimising the need for disposal of unused pesticide, improving the ease of cleaning and optimising the accuracy of chemical application. For all injection systems, characteristics such as the steady-state accuracy of delivered dose, dose stability and the time response for dose step changes are related to the ability of the system to operate with different chemical formulations. A system designed to inject liquids should be able to accommodate changes in viscosity and density. The aim of this study was to develop a methodology for testing chemical injection systems using liquids with different viscosities. The experimental arrangement simulating applications with injection metering systems used dye and salt solutions as tracers. Tests were conducted to analyse the influence of salt on the characteristics of the water and a viscous solution. Results showed that the salt interfered with the dye stability in the water solution. In tests with a viscous test liquid, the salt was introduced at different steps during the mixing process, providing four different liquids to be analysed in terms of viscosity, density and pH. Some differences in liquid characteristics were found which could influence the performance of the injection systems.

Development of intelligent systems for well drilling and petroleum production

Domains where knowledge representation is too complex to be described analytically and in a deterministic way is very common in the petroleum industry, particularly in the field of exploration and production. In these domains, applications of artificial intelligence techniques are very suitable, especially in cases where the preservation of corporate and technical knowledge is important. The Laboratory for Research on Artificial Intelligence Applied to Petroleum Engineering (LIAP) at Unicamp, has, during the last 10 years, dedicated research efforts to build intelligent systems in well drilling and petroleum production fields. In the following sections, recent advances in intelligent systems, under development in the research laboratory, are described. (C) 2001 Published by Elsevier B.V. B.V.

Combining artificial intelligence and human problem solving: Proposing a new architecture for ITS's

This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.

Decision-Making Tool for Knowledge-Based Projects in Offshore Production Systems

The development of an offshore field demands knowledge of many experts to choose the different components of an offshore production system. All the specialized parts of this knowledge are intrinsically related. The aim of this paper is to use Fuzzy Sets and knowledge-based systems to describe and formalize the phases of development of an offshore production system project, in order to share and to manage the required knowledge for carrying out a project, while at the same time proposing alternatives for the oil field configuration.

Electric power systems transient stability analysis by neural networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Towards an intelligent graphical interface for linear programming modelling

The increase of computing power of the microcomputers has stimulated the building of direct manipulation interfaces that allow graphical representation of Linear Programming (LP) models. This work discusses the components of such a graphical interface as the basis for a system to assist users in the process of formulating LP problems. In essence, this work proposes a methodology which considers the modelling task as divided into three stages which are specification of the Data Model, the Conceptual Model and the LP Model. The necessity for using Artificial Intelligence techniques in the problem conceptualisation and to help the model formulation task is illustrated.

Evaluation of cutting patterns produced with air-abrasion systems using different tip designs.

This study assessed cavity preparations produced with different air abrasion tip parameters. Twelve test groups of extracted teeth were prepared to evaluate the parameters of 80 degrees or 45 degrees nozzle angles and 0.38 or 0.48 mm inner tip diameters. All other factors were held constant. A device was made to hold the specimen and air abrasion handpiece that standardized the distance and position relative to the tooth and time of application. The cavities were evaluated by assessing the rounding of the cavosurface margins and cavity floor. Measurements of cavosurface angles and the angle of concavity were made at the deepest portion of the abraded surface using scanning electron micrographs. The cavosurface angles were compared using paired t-test, and the effects of the tip design parameters were analyzed by ANOVA and Duncan's Multiple Range test. From the cavity patterns found in this study, the authors suggest that 80 degrees angle tips are more appropriate than 45 degrees angle tips for making narrow, deep cuts for preventive resin restorations. Conversely, when shallow preparations are needed, as in the case of Class V cavity preparations, cutting patterns of 45 degrees angle tips are more suitable.

Transient stability analysis of electrical power systems using a neural network based on fuzzy ARTMAP

This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.

Tuning of fuzzy inference systems through unconstrained optimization techniques

This paper presents a new methodology for the adjustment of fuzzy inference systems. A novel approach, which uses unconstrained optimization techniques, is developed in order to adjust the free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through an estimation of time series. More specifically, the Mackey-Glass chaotic time series estimation is used for the validation of the proposed methodology.

Network reconfiguration and loss allocation for distribution systems with distributed generation

Distribution systems with distributed generation require new analysis methods since networks are not longer passive. Two of the main problems in this new scenario are the network reconfiguration and the loss allocation. This work presents a distribution systems graphic simulator, developed with reconfiguration functions and a special focus on loss allocation, both considering the presence of distributed generation. This simulator uses a fast and robust power flow algorithm based on the current summation backward-forward technique. Reconfiguration problem is solved through a heuristic methodology and the losses allocation function, based on the Zbus method, is presented as an attached result for each obtained configuration. Results are presented and discussed, remarking the easiness of analysis through the graphic simulator as an excellent tool for planning and operation engineers, and very useful for training. © 2004 IEEE.