Publication detail

Solving inverse problems using machine learning-aided optimization method

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

Original Title

Solving inverse problems using machine learning-aided optimization method

Type

conference paper

Language

English

Original Abstract

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.

Keywords

Inverse analysis; Model updating; Damage detection; Parameter identification

Authors

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

Released

28. 8. 2024

Publisher

International Federation for Structural Concrete

Location

Budapest

ISBN

978-2-940643-24-0

Book

15th fib International PhD Symposium in Civil Engineering

Pages from

533

Pages to

540

Pages count

8

URL

https://fib-international.org/publications/fib-proceedings/15th-phd-symposium-in-budapest-hungary-2024-proceedings-em-pdf-em-detail.html

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"
}