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Accurate Modeling of the Microwave Treatment of Works of Art

Author

Listed:
  • Roberto Pierdicca

    (Dipartimento di Ingegneria Civile, Edile e dell’Architettura, Universitá Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
    These authors contributed equally to this work.)

  • Marina Paolanti

    (Department of Information Engineering, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
    These authors contributed equally to this work.)

  • Roberto Bacchiani

    (Department of Information Engineering, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
    These authors contributed equally to this work.)

  • Roberto de Leo

    (Department of Information Engineering, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
    These authors contributed equally to this work.)

  • Bruno Bisceglia

    (Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano (SA), Italy
    These authors contributed equally to this work.)

  • Emanuele Frontoni

    (Department of Information Engineering, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
    These authors contributed equally to this work.)

Abstract

The microwave heating treatment is a useful methodology and the disinfestation of works of art can also benefit from this approach. However, even if the microwave treatment is able to eliminate the pests that could damage the works of arts, it may nevertheless present some unexpected effects such as the presence of highly heated areas (hot spots) or areas with poor radiation due to particular shapes. To overcome this issue, we developed a mathematical model allowing predicting and monitoring tasks about the heating process. The prediction model has been developed into a software solution able to predict the distribution of heating power in objects to be treated, even of complex shapes, in order to define the exposure conditions, the time necessary to the processing, the power to be transmitted in the chamber and any repair or protection to cover the most sensitive areas. It can also predict the behaviour of irradiation in the presence of other entities such as nails or pests. The data to be provided for performing a simulation are: the geometry of the object, the shape of the infesting agent and their dielectric characteristics. As a result, we obtain the distribution of heating power and a software tool able to model and predict activities for cultural heritage treatments.

Suggested Citation

  • Roberto Pierdicca & Marina Paolanti & Roberto Bacchiani & Roberto de Leo & Bruno Bisceglia & Emanuele Frontoni, 2019. "Accurate Modeling of the Microwave Treatment of Works of Art," Sustainability, MDPI, vol. 11(6), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1606-:d:214533
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    References listed on IDEAS

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    1. Chun-Hung Lee & Han-Shen Chen & Gwo-Bao Liou & Bi-Kun Tsai & Chi-Ming Hsieh, 2018. "Evaluating International Tourists’ Perceptions on Cultural Distance and Recreation Demand," Sustainability, MDPI, vol. 10(12), pages 1-14, November.
    2. Glenn C. Sutter & Tobias Sperlich & Douglas Worts & René Rivard & Lynne Teather, 2016. "Fostering Cultures of Sustainability through Community-Engaged Museums: The History and Re-Emergence of Ecomuseums in Canada and the USA," Sustainability, MDPI, vol. 8(12), pages 1-9, December.
    3. Cameron B. Wesson, 2013. "Rumors of Our Demise Have Been Greatly Exaggerated: Archaeological Perspectives on Culture and Sustainability," Sustainability, MDPI, vol. 5(1), pages 1-23, January.
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    Cited by:

    1. Pavel Koštial & Jozef Vlček & Zora Koštialová Jančíková & Hana Špačková & Jiří David & Robert Frischer & Ivan Ružiak, 2019. "Effective Ecological and Cheap Heating of Dwelling Spaces," Sustainability, MDPI, vol. 12(1), pages 1-15, December.

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