IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v528y2026ics0096300326001840.html

Data-informed mathematical characterization of absorption properties in artificial and natural porous materials

Author

Listed:
  • Braun, Elishan C.
  • Bretti, Gabriella
  • Di Fazio, Melania
  • Medeghini, Laura
  • Pezzella, Mario

Abstract

In this work, we characterize the water absorption properties of selected porous materials through a combined approach that integrates laboratory experiments and mathematical modeling. Specifically, experimental data from imbibition tests on marble, travertine, wackestone and mortar mock-ups are used to inform and validate the mathematical and simulation frameworks. First, a monotonicity-preserving fitting procedure is developed to preprocess the measurements, aiming to reduce noise and mitigate instrumental errors. The imbibition process is then simulated through a partial differential equation model, with parameters calibrated against rough and smoothed data. The proposed procedure appears particularly effective to characterize absorption properties of different materials and it represents a reliable tool for the study and preservation of cultural heritage.

Suggested Citation

  • Braun, Elishan C. & Bretti, Gabriella & Di Fazio, Melania & Medeghini, Laura & Pezzella, Mario, 2026. "Data-informed mathematical characterization of absorption properties in artificial and natural porous materials," Applied Mathematics and Computation, Elsevier, vol. 528(C).
  • Handle: RePEc:eee:apmaco:v:528:y:2026:i:c:s0096300326001840
    DOI: 10.1016/j.amc.2026.130132
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300326001840
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2026.130132?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:528:y:2026:i:c:s0096300326001840. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.