Detail publikace

Solving inverse problems using machine learning-aided optimization method

ŠPLÍCHAL, B. LEHKÝ, D. ŠIMONOVÁ, H. KUCHARCZYKOVÁ, B. LAMPEROVÁ, K.

Originální název

Solving inverse problems using machine learning-aided optimization method

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Inverse problems play an important role in engineering practice such as characterizing materials, detecting structural damage, and optimizing designs. This paper introduces an inverse analysis meth-od using a finite element model as a digital twin of the real structure, which is updated with an Artifi-cial Neural Network-Aided Aimed Multilevel Sampling (ANN-AMS) optimization method. This method employs Latin hypercube sampling for efficient sample generation, AMS for sequential parameter targeting, and ANN for design space mapping. The proposed method is applied to solve two different inverse problems – the detection of truss bridge damage and the identification of me-chanical fracture parameters of alkali-activated fine-grained brittle matrix composites from fracture test records. The results confirmed the versatility, effectiveness and good accuracy of the method for both applied inverse problems.

Klíčová slova

Inverse analysis; Model updating; Damage detection; Parameter identification

Autoři

ŠPLÍCHAL, B.; LEHKÝ, D.; ŠIMONOVÁ, H.; KUCHARCZYKOVÁ, B.; LAMPEROVÁ, K.

Vydáno

28. 8. 2024

Nakladatel

International Federation for Structural Concrete

Místo

Budapest

ISBN

978-2-940643-24-0

Kniha

15th fib International PhD Symposium in Civil Engineering

Strany od

533

Strany do

540

Strany počet

8

URL

BibTex

@inproceedings{BUT191245,
  author="Bohumil {Šplíchal} and David {Lehký} and Hana {Šimonová} and Barbara {Kucharczyková} and Katarína {Lamperová}",
  title="Solving inverse problems using machine learning-aided optimization method",
  booktitle="15th fib International PhD Symposium in Civil Engineering",
  year="2024",
  pages="533--540",
  publisher="International Federation for Structural Concrete",
  address="Budapest",
  isbn="978-2-940643-24-0",
  url="https://fib-international.org/publications/fib-proceedings/15th-phd-symposium-in-budapest-hungary-2024-proceedings-em-pdf-em-detail.html"
}