Steel Hydrogen-Induced Degradation Diagnostics for Turbo Aggregated Rotor Shaft Repair Technologies
Abstract
1. Introduction
2. Materials and Methods
3. Results
3.1. Structural-Phase Approaches and Reflections
- new dislocations;
- new or displaced grain boundaries;
- substructures (subgrains);
- zones of local rearrangement;
- in some cases, heterogeneous formation of new grains (structure reformation).
3.2. Effect of Structural-Phase Composition Under Conditions of Gradual Hydrogen Charging on Machining
3.3. Electrochemical Investigation
4. Discussion
4.1. Common Provisions
4.2. The Main Reasons for the Movement of Carbides to the Grain Boundaries
4.2.1. Increased Diffusion Along Grain Boundaries
4.2.2. Dissolution of Intra-Grain Carbides
4.2.3. Redeposition of Carbides at Grain Boundaries
4.2.4. Growth and Coagulation of Carbides
4.2.5. The Effect of Thermal Aging
4.3. Influence of Alloying Elements and Microstructure Parameters on Diffusion and Hydrogen Embrittlement
4.4. Application of Screening Analyses and Computer Vision Methods
5. Conclusions
- −
- Regular chip analysis should be implemented as part of turbine maintenance protocols to monitor early-stage degradation and material instability.
- −
- Computer vision integration is recommended for the automated classification and morphometric evaluation of wear particles and cutting chips, enhancing diagnostic accuracy and consistency.
- −
- Machine learning algorithms should be developed and trained for intelligent classification of wear debris, utilizing shape, texture, and fractographic features as input parameters for failure prediction models.
- −
- In situ hydrogen detection techniques, including sensor-based or spectroscopic methods, should be investigated to enable real-time tracking of hydrogen transport and accumulation in rotor steel microstructures.
- −
- Comparative studies on alternative steel grades, such as Cr-Mo or Ni-based alloys, are needed to identify materials with superior resistance to hydrogen embrittlement under similar thermal and operational loads.
- −
- Microstructural evolution studies should focus on the role of secondary phases (e.g., σ-phase, Laves phase, intermetallics like Ni3Mo, Fe2Mo) in promoting localized embrittlement, especially at grain boundaries and carbide–matrix interfaces.
- −
- Finite element simulations and microstructure-based modeling can support the prediction of stress concentration zones, trap saturation effects, and critical hydrogen levels leading to mechanical failure.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
TGV | turbogenerator with hydrogen cooling |
TA | Turbo aggregate (turbine + turbogenerator) |
TG | hydrogen-cooling turbogenerator |
ppm | parts per million |
Ecor | corrosion potential |
Icor | corrosion current density |
LCL | lubricating cooling liquid |
LCLs | lubricating cooling liquid based on sunflower oils |
LCLr | lubricating cooling liquid based on rapeseed oils |
LCLp | lubricating cooling liquid based on petroleum oil |
pH | indicator of the acidity or alkalinity of a solution |
°C | degrees Celsius—Celsius temperature |
Rz | roughness values (dry cutting) |
Rzp | roughness values (after LCLp cutting) |
Rzs | roughness values (after LCLs cutting) |
CH | hydrogen concentration |
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Environment | icor,·104 mA/cm2 | Ecor, mV | icor,·104 mA/cm2 | Ecor, mV | icor,·104 mA/cm2 | Ecor, mV | icor,·104 mA/cm2 | Ecor, mV |
---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
LCLs | 1.70 (100%) | −175 | 1.83 (8.12%) | −174 | 1.88 (10.61%) | −172 | 1.96 (15.44%) | −169 |
LCLr | 2.14 (100%) | −179 | 2.31 (8.27%) | −178 | 2.37 (10.94%) | −176 | 2.47 (15.77%) | −173 |
LCLp | 6.03 (100%) | −187 | 6.59 (9.35%) | −186 | 6.71 (11.33%) | −184 | 7.01 (16.39%) | −181 |
Water | 16.02 (100%) | −325 | 17.62 (10.0%) | −324 | 18.03 (12.57%) | −322 | 18.78 (17.28%) | −319 |
Environment | a (Slope) | b (Intercept) | R2 | p-Value | CI (a) |
---|---|---|---|---|---|
LCLs | 0.0752 | 1.8222 | 0.8886 | 0.012 | (0.03–0.12) |
LCLr | 0.0923 | 2.3 | 0.8817 | 0.015 | (0.04–0.14) |
LCLp | 0.2368 | 6.5562 | 0.8105 | 0.030 | (0.09–0.39) |
Water | 0.6654 | 17.543 | 0.8655 | 0.010 | (0.32–1.01) |
Method | Sensitivity to Early Damage | Hydrogen Detection | Spatial Resolution | Application | Remarks |
---|---|---|---|---|---|
Metallography (SEM/OM) | High | Indirect | ~1 μm | Laboratory | Reveals microcracks, carbide redistribution, inclusions |
Fractography of chips | Medium | Indirect | ~1 μm | Field and lab | Useful for real-time wear/degradation trends |
Hydrogen content in chips | High | Direct (ppm-level) | Local bulk | Lab | Requires sample prep; correlates with structural degradation |
Electrochemical testing | Medium | Indirect | Macro (~mm) | Lab | Good for coolant evaluation and general corrosion resistance |
Magnetic/eddy current tests | Medium | No | ~0.1–1 mm | Field | Detects discontinuities; limited for internal damage |
Computer vision (chip wear) | Medium–High | No | Image resolution-based | Field and lab | Promising for automation and continuous monitoring |
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Balitskii, A.I.; Kolesnikov, V.O.; Havrilyuk, M.R.; Balitska, V.O.; Ripey, I.V.; Królikowski, M.A.; Pudlo, T.K. Steel Hydrogen-Induced Degradation Diagnostics for Turbo Aggregated Rotor Shaft Repair Technologies. Energies 2025, 18, 4368. https://doi.org/10.3390/en18164368
Balitskii AI, Kolesnikov VO, Havrilyuk MR, Balitska VO, Ripey IV, Królikowski MA, Pudlo TK. Steel Hydrogen-Induced Degradation Diagnostics for Turbo Aggregated Rotor Shaft Repair Technologies. Energies. 2025; 18(16):4368. https://doi.org/10.3390/en18164368
Chicago/Turabian StyleBalitskii, Alexander I., Valerii O. Kolesnikov, Maria R. Havrilyuk, Valentina O. Balitska, Igor V. Ripey, Marcin A. Królikowski, and Tomasz K. Pudlo. 2025. "Steel Hydrogen-Induced Degradation Diagnostics for Turbo Aggregated Rotor Shaft Repair Technologies" Energies 18, no. 16: 4368. https://doi.org/10.3390/en18164368
APA StyleBalitskii, A. I., Kolesnikov, V. O., Havrilyuk, M. R., Balitska, V. O., Ripey, I. V., Królikowski, M. A., & Pudlo, T. K. (2025). Steel Hydrogen-Induced Degradation Diagnostics for Turbo Aggregated Rotor Shaft Repair Technologies. Energies, 18(16), 4368. https://doi.org/10.3390/en18164368