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Authors: David F. Nettleton 1 ; Cristina Fernandez-Avila 1 ; Sara Sánchez-Esteva 1 ; Steven Verstichel 2 ; Maria Beatrice Coltelli 3 ; Helena Marti-Soler 1 ; Laura Aliotta 3 and Vito Gigante 3

Affiliations: 1 IRIS Technology Solutions, Ctra. d’Esplugues, 39-41, 08940 Cornellà de Llobregat, Barcelona, Spain ; 2 OWS, Dok-Noord 5, 9000 Gent, Belgium ; 3 Dipartimento di Ingegneria Civile ed Industriale, Università di Pisa, Largo Lucio Lazzarino 56122 Pisa PI, Italy

Keyword(s): Modelling, Simulation, Interpolation, Multi-agent System, Case based Reasoning, Time-Series, Biodegradation, Bioplastics.

Abstract: In this paper we describe the functionality of a decision support modelling approach to select appropriate biomaterial blends depending on their mechanical/chemical properties on the one hand, and their biodegradation behaviour, on the other. Firstly, a Case Based Reasoning (CBR) approach is applied to predict expected biodegradation behaviour over time, based on historical examples and using a weighted distance metric on the material properties in order to calculate the trend curve of the new case. Secondly, a Multi-Agent System (MAS) is applied to dynamically simulate the biodegradation curve, in which the two main agents, bacteria and plastic, interact to reproduce the biodegradation kinetics over time. The results of the interpolation are very promising with a good approximation to the real curve time series and % biodegradation, and the Multi-Agent System successfully simulates the different trend curves over time. The system has been confirmed as useful by materials expert end- users, who participated in the project, in order to evaluate a priori new blends “in silico”, and identify and select the most promising, before conducting the long duration biodegradation experiments in the real environment. (More)

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Paper citation in several formats:
Nettleton, D.; Fernandez-Avila, C.; Sánchez-Esteva, S.; Verstichel, S.; Coltelli, M.; Marti-Soler, H.; Aliotta, L. and Gigante, V. (2022). Biodegradation Prediction and Modelling for Decision Support. In Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH, ISBN 978-989-758-578-4; ISSN 2184-2841, pages 26-35. DOI: 10.5220/0011136200003274

@conference{simultech22,
author={David F. Nettleton. and Cristina Fernandez{-}Avila. and Sara Sánchez{-}Esteva. and Steven Verstichel. and Maria Beatrice Coltelli. and Helena Marti{-}Soler. and Laura Aliotta. and Vito Gigante.},
title={Biodegradation Prediction and Modelling for Decision Support},
booktitle={Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH,},
year={2022},
pages={26-35},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011136200003274},
isbn={978-989-758-578-4},
issn={2184-2841},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH,
TI - Biodegradation Prediction and Modelling for Decision Support
SN - 978-989-758-578-4
IS - 2184-2841
AU - Nettleton, D.
AU - Fernandez-Avila, C.
AU - Sánchez-Esteva, S.
AU - Verstichel, S.
AU - Coltelli, M.
AU - Marti-Soler, H.
AU - Aliotta, L.
AU - Gigante, V.
PY - 2022
SP - 26
EP - 35
DO - 10.5220/0011136200003274