Model-based Analysis of Waste Management Systems through a Natural Language Approach

Abstract

Abstract Waste management systems are complex interactive networks of data, knowledge and models comprising multiple parameters. In these systems the technologies and their models interact with each other in order to fully describe the problem. Inputs and outputs of the models intersect depending on the various parameters. These parameters, such as composition, pH, temperature etc., need to be computed simultaneously in order to select the appropriate processing path prior to model development. Therefore, the the selected path and the waste stream characteristics determine the context of the model. Waste management systems involve non-experts in decisions that require expertise from many disciplines. The need to synthesize the multidisciplinary domains of waste, integrate the knowledge and express them with common natural language terms is outlined by this work. The work builds on recent technology that was produced to synthesize superstructures for integrated biorefineries (Magioglou et al. 2014), which now extends to decision-making and allocation problems for waste management systems. The approach employs ontologies, Java language, OpenBabel library and suggests a natural language framework. Illustrations include an industrial wastewater treatment system of the chemical sector which evaluates the environmental impacts. The framework successfully synthesizes the network and allocates the waste, technologies, streams and auxiliaries along with their parameters.