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Wyszukujesz frazę "Koris, Kálmán" wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Nonlinear modelling of a bridge: A case study-based damage evaluation and proposal of Structural Health Monitoring (SHM) system
Autorzy:
Fawad, Muhammad
Koris, Kalman
Salamak, Marek
Gerges, Michael
Bednarski, Lukasz
Sienko, Rafal
Powiązania:
https://bibliotekanauki.pl/articles/2174024.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
most żelbetowy
metoda elementów skończonych
metoda nieniszcząca
monitorowanie stanu konstrukcji
pęknięcie
czujnik
reinforced concrete bridge
finite element method
non-destructive method
structural health monitoring
crack
sensor
Opis:
Monitoring and structural health assessment are the primary requirements for performance evaluation of damaged bridges. This paper highlights the case-study of a damaged Reinforced Concrete (RC) bridge structure by considering the outcomes of destructive testing, Non-Destructive Testing (NDT) evaluations, static and 3D non-linear analysis methods. Finite element (FE) modelling of this structure is being done using the material properties extracted by the in-situ testing. Analysis is carried out to evaluate the bridge damage based on the data recorded after the static linear (AXIS VM software) and 3D non-linear analysis (ATENA 3D software). Extensive concrete cracking and high value of crack width are found to be the major problems, leading to lowering the performance of the bridge. As a solution, this paper proposes a proper Structural Health Monitoring (SHM) system, that will extend the life cycle of the bridge with minimal repair costs and reduced risk of failure. This system is based on the installation of three different types of sensors: Liquid Levelling sensors (LLS) for measurement of vertical displacement, Distributed Fiber Optic Sensors (DFOS) for crack monitoring, and Weigh in Motion (WIM) devices for monitoring of moving loads on bridge.
Źródło:
Archives of Civil Engineering; 2022, 68, 3; 569--584
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Implementation of digital twin and support vector machine in structural health monitoring of bridges
Autorzy:
Al-Hijazeen, Asseel Za'al Ode
Fawad, Muhammad
Gerges, Michael
Koris, Kálmán
Salamak, Marek
Powiązania:
https://bibliotekanauki.pl/articles/27312162.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
monitorowanie stanu konstrukcji
most
uszkodzenie
bliźniak cyfrowy
uczenie maszynowe
maszyna wektorów wsparcia
structural health monitoring
bridge
damage
digital twin
machine learning
support vector machine
Opis:
Structural health monitoring (SHM) of bridges is constantly upgraded by researchers and bridge engineers as it directly deals with bridge performance and its safety over a certain time period. This article addresses some issues in the traditional SHM systems and the reason for moving towards an automated monitoring system. In order to automate the bridge assessment and monitoring process, a mechanism for the linkage of Digital Twins (DT) and Machine Learning (ML), namely the Support Vector Machine (SVM) algorithm, is discussed in detail. The basis of this mechanism lies in the collection of data from the real bridge using sensors and is providing the basis for the establishment and calibration of the digital twin. Then, data analysis and decision-making processes are to be carried out through regression-based ML algorithms. So, in this study, both ML brain and a DT model are merged to support the decision-making of the bridge management system and predict or even prevent further damage or collapse of the bridge. In this way, the SHM system cannot only be automated but calibrated from time to time to ensure the safety of the bridge against the associated damages.
Źródło:
Archives of Civil Engineering; 2023, 69, 3; 31--47
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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