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Patrik Kovář

Ing. Patrik Kovář

patrik.kovar (at) fs.cvut.cz

room: A-302, Praha, Jugoslávských partyzánů
room: D-305b, Karlovo náměstí

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Journal papers

2023

  • Mesh suitability for CFD simulations performed on axial compressor airfoil cascades – Tater, A. - Mačák, P., - Kovář, P., Bulletin of the Polish Academy of Sciences - Technical Sciences. 2023, 71(6), ISSN 0239-7528.
  • Compressor cascade correlations modelling at design points using artificial neural networks – Kovář, P. - Fürst, J., Applied and Computational Mechanics. 2023, 17(2), 1-16. ISSN 1802-680X.
  • Prediction of Temperature Field Distribution in a Gas Turbine Using Higher Order Neural Network – Pařez, J. - Kovář, P., - Tater, A., Acta Polytechnica. 2023, 63(6), 430-438. ISSN 1805-2363.
  • Influence of geometrical design on the cooling process of double annular turbine section – Pařez, J. - Tater, A. - Kovář, P. - Mačák, P., - Vampola, T., International Journal of Engine Research. 2023, 2023 ISSN 1468-0874.

2021

  • Searching for the Most Suitable Loss Model Set for Subsonic Centrifugal Compressors Using an Improved Method for Off-Design Performance Prediction – Kovář, P. - Tater, A. - Mačák, P., - Vampola, T., Energies. 2021, 14(24), ISSN 1996-1073.
  • Influence of input parameters in radial compressor design algorithm on the efficiency and its sensitivity analysis – Kovář, P. - Kaňka, T. - Tater, A. - Mačák, P., - Vampola, T., Applied and Computational Mechanics. 2021, 15(1), 1-14. ISSN 1802-680X.

Proceeding papers

2023

  • SCALABLE ACTIVATION FUNCTION EMPLOYMENT IN PHYSICS INFORMED HIGHER ORDER NEURAL NETWORKS FOR INITIAL VALUE PROBLEM APPROXIMATION – Kovář, P. - Fürst, J., In: BOOK OF ABSTRACTS ISIM&ISWIM. Alba Iulia: 1 Decembrie 1918 University, 2023. p. 88-89. ISSN 2821-8779.
  • About the appropriate neural network size for the engineering applications – Kovář, P. - Tater, A. - Pařez, J., - Fürst, J., In: PROCEEDINGS OF COMPUTATIONAL MECHANICS 2023. Plzeň: University of West Bohemia, 2023. p. 91-94. ISBN 978-80-261-1177-1.
  • On prediction of non-uniform temperature fields in heat analysis of aero engines using machine learning approach – Pařez, J. - Kovář, P., In: PROCEEDINGS OF COMPUTATIONAL MECHANICS 2023. Plzeň: University of West Bohemia, 2023. p. 155-158. ISBN 978-80-261-1177-1.
  • Modelling of Temperature Field Distribution on Single Annular Using Higher Order Neural Network – Pařez, J. - Kovář, P., - Tater, A., In: Book of Abstracts 18th Youth Symposium on Experimental Solid Mechanics. Prague: Institute of Theoretical and Applied Mechanics, AS CR, 2023. p. 18. ISBN 978-80-86246-66-6.
  • Scalable Activation Function Employment in Higher Order Neural Networks in Tasks of Supervised Learning – Kovář, P. - Fürst, J., In: Book of Abstracts 18th Youth Symposium on Experimental Solid Mechanics. Prague: Institute of Theoretical and Applied Mechanics, AS CR, 2023. p. 37. ISBN 978-80-86246-66-6.
  • Compressor cascade positive and negative stall incidence angle correlation modelling using artificial neural networks – Kovář, P. - Fürst, J., In: Engineering Mechanics 2023: Book of full texts. Prague: Institute of Thermomechanics, AS CR, v.v.i., 2023. p. 127-130. First edition. ISSN 1805-8248. ISBN 978-80-87012-84-0.
  • Comparison of multilayer perceptron and higher order neural network's ability to solve initial value problem – Kovář, P. - Fürst, J., In: 24th International Scientific Conference APPLIED MECHANICS 2023 BOOK OF ABSTRACTS. Bratislava: Strojnícka fakulta STU v Bratislave, 2023. p. 55-58. ISBN 978-80-227-5294-7.
  • Development and Application of a 3D FEM Model for Rotor Thermal Bow Prediction – Pařez, J. - Kovář, P., In: 24th International Scientific Conference APPLIED MECHANICS 2023 BOOK OF ABSTRACTS. Bratislava: Strojnícka fakulta STU v Bratislave, 2023. p. 93-96. ISBN 978-80-227-5294-7.
  • Investigation of Temperature Fields During Turboprop Engine Cooling – Pařez, J. - Tater, A. - Kovář, P. - Polanský, J., - Vampola, T., In: 15th European Conference on Turbomachinery Fluid dynamics & Thermodynamics. The European Turbomachinery Society, 2023. p. 1-11. ISSN 2410-4833.
  • Prediction of Rotor Thermal Bow Using 3D Finite Element Model – Pařez, J. - Kovář, P., In: Engineering Mechanics 2023: Book of full texts. Prague: Institute of Thermomechanics, AS CR, v.v.i., 2023. p. 191-194. First edition. ISSN 1805-8248. ISBN 978-80-87012-84-0.

2022

  • Nozzle Shape Optimization based on Machine Learning using Higher Order Neural Networks – Kovář, P. - Fürst, J., In: Proceedings of the International Conference Experimental Fluid Mechanics 2022. Les Ulis Cedex A: EPJ Web of Conferences, 2022. p. 138-145. ISSN 2100-014X.
  • Compressor cascade total pressure loss correlation modelling at design points using artificial neural networks – Kovář, P. - Fürst, J., In: PROCEEDINGS OF COMPUTATIONAL MECHANICS 2022. Plzeň: University of West Bohemia, 2022. p. 50-53. ISBN 978-80-261-1116-0.
  • Sensitivity Analysis of Thermodynamical Parameters on the Thermal Bowed Rotor Using 2D Finite Element Mode – Pařez, J. - Kovář, P., - Vampola, T., In: PROCEEDINGS OF COMPUTATIONAL MECHANICS 2022. Plzeň: University of West Bohemia, 2022. p. 103-106. ISBN 978-80-261-1116-0.