Andrzej Kraslawski

Similarity concept for case-based design in process engineering

The design process requires significant engineering experience, intuition and creativeness. To facilitate the preliminary design, the authors have proposed approach based on the re-use of design experience. The design problems in chemical engineering are often quite difficult to represent as a well-structured list of features of one-type data. Many problems in chemical engineering are very large and complex, the problem description is often incomplete and uncertain, and sometimes it changes dynamically. In order to cope with design cases that have different structure representation the general similarity concept has been developed. The paper surveys the existing mathematical methods for similarity measurements and extends them to cope with different data formats. The main idea of this paper is an integration of representation and retrieval of the cases into one step. The proposed concept is illustrated by the examples of the model selection for synthesis of distillation systems and formulation of a fats and oils product.

Development, calibration and evaluation of two mathematical models for pollutant transport in a small river

The present research has two main objectives (1) to build two models for concentration prediction in a stream subject to a pollutant release and (2) to investigate options for estimating the parameters of the models. The models rely on the fundamental advection-dispersion equation and were developed, calibrated and evaluated using tracer data from experiments conducted in the Murray Burn in Edinburgh, UK. During the evaluation by comparison against field data both models were able to predict the main features of the observations at the first three monitoring sites, but results at the final site were less good. These types of models rely very much on the ability to make good estimates of velocity and dispersion coefficients along the stream. Although these parameters could be estimated using tracer experiments, it would be easier if they could be estimated from other hydraulic data such as the water flow rate and the channel characteristics. For the Murray Burn such models for parameter estimation were developed in the form of non-linear relationships with flow rate. This approach could be used to calculate the parameters for other similar streams, if the coefficients in the equations were similar. Alternatively, further work would be needed to explore how these coefficients vary between streams.

Fuzzy Neural Network as Instance Generator for Case-Based Reasoning System: An Example of Selection of Heat Exchange Equipment in Mixing Tanks

The early stages of design are characterised by imprecise and incomplete information about the features and properties of targeted product or process. Equipment selection is one of the decisions to be taken in an initial phase of design. Mixing is an example of process where the selection of the equipment is practically realised ‘by hand’. An application of rule-based or object-oriented tools in the selection of mixing equipment encounters many problems. The main reasons are the lack of well-structured knowledge and the great diversity of mixing problems. Case-based reasoning constitutes a good tool to handle the problems of mixing equipment selection. An instance generator for case-based reasoning system is described in this work. A fuzzy neural network system has been used to produce the cases. The following types of the equipment for heat exchange in stirred vessels have been considered: plain jacket, plain jacket with agitation nozzles, plain jacket with spiral baffles, dimple jacket, halfpipe jacket, helical coil, vertical coil and vertical plate coil.

LUBRES: An expert system development and implementation for real-time fault diagnosis of a lubricating oil refining process

An expert system LUBRES (LUBricating oil Refining Expert System) is introduced in this paper. It helps plant operators in monitoring and diagnosing of abnormal situations in refining process of lubricating oil. The LUBRES structure, the knowledge base, and the inference machine are presented in detail. A new strategy is proposed for conflicts resolution - the sorting strategy of antecedents, and a selection strategy of knowledge rules in the memory knowledge base. Knowledge acquisition mechanism is based on an empirical knowledge table, while knowledge verification is carried out based on the directed graph approach. C++Builder and SQL Server 2000 have been used in developing the proposed system. LUBRES has been successfully implemented in Microsoft Windows Server environment. For 1 year, LUBRES has been used for monitoring and diagnosing of refining process of the lubricating oil. The industrial application of LUBRES proved its high reliability and accuracy.

Design and synthesis of multicomponent thermally coupled distillation flowsheets

Abstract The design and synthesis of thermally coupled distillation flowsheets for separations of five-component mixtures are studied. Four types of possible configurations are identified when simple and complex columns are both considered in a flowsheet. A universal design procedure is developed for design of any types of the identified configurations based on the abstraction of the three basic units in the flowsheets. Two examples demonstrated that this shortcut design method can be used in design of any types of the identified multicomponent thermally coupled distillation flowsheets, as well as give very good initializations for rigorous simulation of such configurations. Moreover, with a proposed computer representation of all the types of the feasible configurations, a synthesis algorithm is developed for synthesizing of multicomponent complex distillation flowsheets with both simple and complex columns. It is practical by the proposed methods for optimal design of multicomponent distillation systems in an extended search space to include the complex distillation flowsheets for industrial problems.

Case Based Design

The book by Professors Avramenko and Kraslawski is unique in several important ways. First, it is an impressive and in-depth treatment of the essence of the casebased reasoning strategy and case-based design dwelling upon the algorithmic facet of the paradigm. Second, the authors provided an excellent applied research framework by showing how this development can be effectively utilized in real word complicated environment of process engineering- a pursuit that is rarely reported in the literature in such a comprehensive manner as done in this book. In a highly authoritative and systematic manner, the authors guide the reader through the essential features of the CBR machinery.

The synthesis of thermally coupled distillation flowsheets for separations of five-component mixtures

Abstract The thermally coupled distillation flowsheets for separation of five-component mixtures are studied based on the total annual costs. Fourteen simple column sequences and some feasible thermally coupled configurations with side strippers and/or side rectifiers are considered. The costs of the flowsheets are calculated and compared for several real five-component mixtures with various relative volatility distributions and a wide range of feed compositions. Several heuristics are proposed for the synthesis of multicomponent thermally coupled distillation flowsheets.

Case-based reasoning system for mixing equipment selection

Abstract The use of case-based reasoning in the mixing equipment selection is promising. Its main advantage is use of high quality, verified knowledge and easiness of updating. The main functions of the system are a systematic documentation of the cases and an accumulation of experience. Case-based reasoning (CBR) is an alternative approach to rule-based and object-oriented systems. CBR is based on the retrieval and adaptation of the old solutions to the new problems. There are five steps in CBR: presentation of a new problem, retrieval of the most similar cases, adaptation of the most similar old solutions, validation of the current solution and updating of the system by adding the verified solution to the database of cases. The main advantages of CBR are the easy knowledge acquisition and simple explanatory system. Other important features are easy maintenance and learning capabilities. Determination of the most important features in mixing equipment selection and their importance is studied in this work. The main features discussed are liquid volume and rheological parameters, content of particles and/or gas bubbles as well as the type of application and the aim of the process. The retrieval search has been organized by using flat memory and serial search. The following data are given as the output values of the system: impeller and entering type, scale of agitation, mixing power, number of impellers and geometry of tank. An example of CBR applications to the mixing equipment selection in wastewater industry is given.

Selection of internals for reactive distillation column¿case-based reasoning approach

The design of reactive distillation (RD) systems is considerably more complex than design of the individual, conventional reactors and distillation columns. One of the main issues in the design of RD column is a definition of type and specification of geometric features of the internal devices. In this work, there is described a design supporting tool for pre-selection of packing type for RD column. Case-based reasoning has been applied as a basic method for decision support. The computer system for pre-design of reactive column internals has been built as an implementation of developed methodology. The acid catalysed reaction of 2-methylpropylacetate synthesis was used to test the system. The CBR system can significantly reduce the development time for design of reactive distillation column and suggests a good start points for further design activity.

Review of applications of various types of uncertainty in chemical engineering

Abstract The paper presents definitions of various types of uncertainty and examples of their applicability in chemical engineering. Special attention is given to such problems as control, modelling, process synthesis, multi-objective optimization and expert systems.