Gallina Alberto, dr hab. inż., prof. AGH

WIMiR-krm Katedra Robotyki i Mechatroniki

Wydział Inżynierii Mechanicznej i Robotyki

inżynieria mechaniczna

100

agallina@agh.edu.pl

Habilitacja: Metody analizy niepewności i ich zastosowania w inżynierii
Wydział:: AGH Wydział Inżynierii Mechanicznej i Robotyki
Dziedzina:: nauki inżynieryjno-techniczne
Data uchwały Rady Wydziału:: 24.05.2019
Stopień naukowy:: dr hab. nauk inżynieryjno-technicznych
Dyscyplina:: inżynieria mechniczna
Słowa kluczowe:: analiza niepewności
Uwagi:: Rozprawę habilitacyjną stanowi cykl 15 publikacji: [1] Gallina A., Martowicz A., Uhl T. (2011). Robustness analysis of a car windscreen using response surface techniques. Finite Elements in Analysis and Design vol. 47 iss. 1, s. 46-54 ; [2] Gallina A., Pichler L., Uhl T. (2011). Enhanced meta-modelling technique for analysis of mode crossing, mode veering and mode coalescence in structural dynamics. Mechanical Systems and Signal Processing vol. 25 iss. 7, s. 2297-2312 ; [3] Gallina A., [et al.] (2011). Model assisted probability of detection evaluation of a health monitoring system by using CUDA technology. W: Structural health monitoring 2011, proceedings of the 8th international workshop on Structural health monitoring, Stanford, September 13-15, 2011. Vol. 2, Condition-based maintenance and intelligent structures. Ed. F. Chang. Lancaster: DEStech Publications, s. 2437-2443 ; [4] Pichler L., [et al.] (2012). A meta-modeling technique for the natural frequencies based on the approximation of the characteristic polynomial. Computers & Structures vols. 102-103, s. 108-116 ; [5] Gallina A., [et al.] (2012). Analysis of natural frequency variability of a brake component. Mechanical Systems and Signal Processing vol. 32 spec. iss., s. 188-199 ; [6] Leite A. C., [et al.] (2012). Parameter identification and contact modeling for planetary wheeled rovers in soft soil. IFAC Proceedings Volumes vol. 45 iss. 16, s. 1707-1712 ; [7] Gallina A., Paćko P., Ambroziński Ł. (2013). Model assisted probability of detection in structural health monitoring. W: Advanced structural damage detection: from theory to engineering applications. Eds. T. Stepiński, T. Uhl, W. Staszewski. Chichester: John Wiley & Sons, s. 57-72 ; [8] Gallina A., [et al.] (2013). Parameter identification of a planetary rover wheel-soil contact model via a Bayesian approach. Journal of Field Robotics vol. 31 iss. 1 pt. 2, s. 161-175 ; [9] Rosiek M., [et al.] (2014). Probability of detection of damage for electromechanical impedance based SHM system. Diagnostyka vol. 15 no. 4, s. 3-8 ; [10] Gallina A., [et al.] (2015). Analysis of lamb wave dispersion curve sensitivity to material elastic contants in composites. W: Health monitoring of structural and biological systems 2015, San Diego, California, United States, March 9-12, 2015. Ed. T. Kundu. Bellingham: SPIE, s. 94380O-1-94380O-7. Proceedings of SPIE, 9438 ; [11] Gallina A., [et al.] (2015). Multibody simulation of planetary rover mobility in condition of uncertain soft terrain. Procedia IUTAM vol. 13, s. 118-126 ; [12] Gallina A., Krenn R., Schäfer B. (2016). On the treatment of soft soil parameter uncertainties in planetary rover mobility simulations. Journal of Terramechanics vol. 63, s. 33-47 ; [13] Martowicz A., [et al.] (2016). Mechatronic approach in application to solution of research and design problems. Mechatronics vol. 36, s. 1-17 ; [14] Dworakowski Z., [et al.] (2016). Vision-based algorithms for damage detection and localization in structural health monitoring. Structural Control and Health Monitoring vol. 23 iss. 1, s. 35-50 ; [15] Gallina A., [et al.] (2017). Bayesian parameter identification of orthotropic composite materials using Lamb waves dispersion curves measurement. Journal of Vibration and Control vol. 23 iss. 16, s. 2656-2671.