A modeling language (MODEL.LA.) has been constructed for the interactive or automatic definition of models for processing systems. It is based on six modeling elements and 11 semantic relationships obeying basic axioms of transitivity, monotonicity, commutativity and merging. Its syntax can be described by an extended BNF (Backus-Naur Form). The structure of process models is depicted by specific digraphs, which are symbolically constructed by algorithmic procedures driven by the context of the modeling activity. MODEL.LA. can generate models of processing systems: (a) at various levels of abstraction; (b) capturing qualitative, semiquantitative and quantitative knowledge; (c) with complete documentation of the modeling context (assumptions, simplifications, process engineering task). Its object-oriented modularity makes it extensible and easily maintainable. Although a large part of MODEL.LA. is domain-independent, its vocabulary and syntax is specific to process engineering activities such as: process development, design, control and operations. A language for modeling processing systems, called MODEL.LA., has been presented. Realizing the limitations of the previous procedural attempts, it is based on an object-oriented, declarative approach. The language has been designed to be capable of: (i) expressing all points of interest assumed to be needed in modeling processing systems; (ii) representing processing systems at any level of detail; (iii) generating automatically the set of basic mathematical relationships that are describing the model components; and (iv) offering explicit documentation of all the assumptions that give rise to a particular model. It can be viewed as a very high-level special-purpose language, that moves the user several levels away from the inherent programming language (e.g. LISP, as in this case, Pascal or C). MODEL.LA. complies with all the requirements that were proposed for its design. Its basic strengths are its modularity and its inherent capability of controlling complexity by breaking down complex systems into smaller, less complex pieces. In fact, the specification of a model-class involves the subsequent specification and characterization of all its components. This idea is recursively applied throughout the definition process. Thus, it is very similar to what we usually do when we describe processing systems in natural languages. Another important feature of this language is its extensibility. At a very simple level, the ability to characterize a processing system can be extended by incorporating a richer terminal vocabulary. Also, its modularity makes possible the incorporation of new blocks in the definition of a class; blocks that may describe other aspects, that presently are not considered. If the incorporation of new modeling points of view requires the definition of new classes of modeling elements, it can be done in a straightforward manner.
ASJC Scopus subject areas
- Chemical Engineering(all)
- Computer Science Applications