All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Evaluation of Forces in Dynamically Loaded Journal Bearings Using Feedforward Neural Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43963800" target="_blank" >RIV/49777513:23520/24:43963800 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-031-56496-3_40" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-56496-3_40</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-56496-3_40" target="_blank" >10.1007/978-3-031-56496-3_40</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Evaluation of Forces in Dynamically Loaded Journal Bearings Using Feedforward Neural Networks

  • Original language description

    This paper explores the usage of artificial neural networks to evaluate forces acting in dynamically loaded finite-length journal bearings. Unlike standard numerical approaches, which require solving a hydrodynamic pressure field, the network predicts the forces directly from relative displacements and velocities of a rotating journal to a stationary bearing shell. This practice can significantly accelerate transient simulations of systems supported on such bearings without compromising their nonlinear properties. The proposed method utilises feedforward neural networks, which use a precomputed database of nondimensional forces for training. This database is generated using a finite difference method and supplemented with the corresponding relative displacements and velocities. The performance of the trained networks is also analysed.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/EF17_048%2F0007267" target="_blank" >EF17_048/0007267: Research and Development of Intelligent Components of Advanced Technologies for the Pilsen Metropolitan Area (InteCom)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Perspectives in Dynamical Systems II — Numerical and Analytical Approaches

  • ISBN

    978-3-031-56495-6

  • ISSN

    2194-1009

  • e-ISSN

    2194-1017

  • Number of pages

    16

  • Pages from-to

    617-632

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Łódź

  • Event date

    Dec 6, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001289530700040