Dimitrios Skaltsas — Dr.
Naval architect and marine engineer (NTUA); Ph.D. NTUA on the thermo-elasto-hydrodynamic analysis of slider and journal bearings with stochastic operational and geometric parameters, including magnetic-fluid-based hydrodynamic bearings. Senior researcher of the group.
Contact
- Machine Elements / Tribology Lab, S-NAME, NTUA.
- E-mail: d.skaltsas1@gmail.com
- Google Scholar: profile →
Education
- Ph.D., NTUA (from March 2021)
Thesis: Thermo-elasto-hydrodynamic analysis of slider and journal bearings with stochastic operational and geometric parameters. - Diploma, S-NAME NTUA (2014 – 2021)
Grade 7.64/10; thesis: A comparative study of the Reynolds equation solution for slider and journal bearings with stochastic roughness on the stator and the rotor. - Erasmus, DTU — mechanical engineering (spring 2019).
Research
- Stochastic surface roughness in slider, journal and magnetic-fluid-based hydrodynamic bearings.
- Thermo-elasto-hydrodynamic (TEHD) analysis of slider and journal bearings with stochastic operational and geometric parameters.
- Generalized Reynolds-type equations for surfaces with stochastic roughness under the effect of a symmetric electric double layer.
- Calculation of higher-order moments of the operational parameters of bearings with stochastic roughness on the stator and rotor.
Selected publications
Most recent first. Citation counts are those reported by Google Scholar in 2025.
Pervelis I., Rossopoulos G. N., Papadopoulos C. I., Applicability of Winkler and FEM models for elastohydrodynamic analysis of deformable oil and water-lubricated journal bearings.
Proc. IMechE Part J: Journal of Engineering Tribology — 2026.
Rossopoulos G. N., Pervelis I., Skaltsas D., Papadopoulos C. I., Vlachos O., Koutsoumpas G., Leontopoulos C., Experimental characterization of the tribological and acoustic performance of different stern-tube bearing materials.
Tribology International 206, 110590 — 2025.
Rossopoulos G. N., Papadopoulos C. I., AI techniques for evaluating misaligned journal bearing performance: an approach beyond the Sommerfeld number.
Proc. IMechE Part J — 2024. · doi
Rossopoulos G. N., Papadopoulos C. I., A π-theorem-based advanced scaling methodology for similarity assessment of marine shafting systems.
Journal of Marine Science and Engineering 12 (6), 894 — 2024.
Rossopoulos G. N., Papadopoulos C. I., A journal bearing performance prediction method utilizing a machine learning technique.
Proc. IMechE Part J 236 (10), 1993–2003 — 2022. doi
Moschopoulos M., Rossopoulos G. N., Papadopoulos C. I., Journal bearing performance prediction using machine learning and octave-band signal analysis of sound and vibration measurements.
Rossopoulos G. N., Papadopoulos C. I., Leontopoulos C., Tribological comparison of an optimum single and double slope design of the stern tube bearing: case study for a marine vessel.
Selected conferences
- MadeAI 2024 — surrogate-model AI for bearing state estimation and early failure detection.
- 47th Leeds–Lyon Symposium on Tribology (2023, 2024).
- SNAME Maritime Convention 2023 (two presentations; session chair, SOME 2023).
- MARSTRUCT 2023 — hull deflection estimation model for marine shaft alignment applications.
- 7th World Tribology Congress 2022 (two presentations, Lyon).
- Leeds–Lyon 2019 — a methodology to classify acceptable operating conditions for heavily misaligned marine journal bearings.