Digital Twin Concept Utilizing Electrical Resistivity Tomography for Monitoring Seawater Intrusion-Reference-Cited by-同舟云学术

Digital Twin Concept Utilizing Electrical Resistivity Tomography for Monitoring Seawater Intrusion

Published:2023-01-20 Issue:1 Volume:27 Page:12-18
ISSN:1883-8014
Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
language:en
Short-container-title:JACIII

Author:

Leon Joseph Aristotle R. De¹,Concepcion II Ronnie S.¹²^ORCID,Billones Robert Kerwin C.¹²,Baun Jonah Jahara G.³^ORCID,Custodio Jose Miguel F.¹,Vicerra Ryan Rhay P.¹²^ORCID,Bandala Argel A.³²^ORCID,Dadios Elmer P.¹²^ORCID

Affiliation:

1. Department of Manufacturing Engineering and Management, De La Salle University (DLSU), 2401 Taft Avenue, Malate, Manila 1004, Philippines

2. Center for Engineering and Sustainable Development Research, De La Salle University (DLSU), 2401 Taft Avenue, Malate, Manila 1004, Philippines

3. Department of Electronics and Computer Engineering, De La Salle University (DLSU), 2401 Taft Avenue, Malate, Manila 1004, Philippines

Abstract

Electrical resistivity tomography (ERT) has been seen as an appropriate instrument in several works to monitor and aid in the control of seawater intrusion (SWI) in coastal groundwater systems. This study seeks to discuss the synthesis of a digital twin that couples information between the physical space through ERT as a monitoring sensor and the digital space using SWI simulations to accurately model the behavior of SWI in the present and future settings. To showcase the concept, a Python-based simulation was presented that shows (a) the joint forward modeling-simulation scheme for calculating expected ERT apparent resistivity values from simulated SWI and (b) the calibration of the digital coastal aquifer system through genetic algorithm to accurately match the outputs of the SWI simulations with the ERT measurements.

Funder

DOST-ERDT

DLSU-OVPRI

Philippine Council for Industry, Energy, and Emerging Technology Research and Development

DLSU-ISL

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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