Projects per year
Description
py-Fatigue toolbox for Fatigue assessment
Abstract
It provides:
- a powerful cycle-counting implementation based on the ASTM E1049-85 rainflow method that retrieves the main class of the package: CycleCount
- capability of storing the CycleCount results in a sparse format for storage and memory efficiency
- easy applicability of multiple mean stress effect correction models
- implementation of low-frequency fatigue recovery when "summing" multiple CycleCount instances
- fatigue analysis through the combination of SN curves and multiple damage accumulation models
- crack propagation analysis through the combination of the Paris' law and multiple crack geometries
- and more...
- a powerful cycle-counting implementation based on the ASTM E1049-85 rainflow method that retrieves the main class of the package: CycleCount
- capability of storing the CycleCount results in a sparse format for storage and memory efficiency
- easy applicability of multiple mean stress effect correction models
- implementation of low-frequency fatigue recovery when "summing" multiple CycleCount instances
- fatigue analysis through the combination of SN curves and multiple damage accumulation models
- crack propagation analysis through the combination of the Paris' law and multiple crack geometries
- and more...
| Date made available | 2023 |
|---|---|
| Publisher | Zenodo |
Keywords
- Python
- Fatigue
- Signal Processing
- Rainflow
Format
- Format
- .py
Projects
- 2 Finished
-
FOD95: MAXWIND (MAintenance, Inspection and EXploitation Optimization of Offshore Wind Farms subjected to Cor-rosion-Fatigue
1/03/20 → 31/08/24
Project: Fundamental
-
Farm-wide virtual load monitoring for offshore wind structures via Bayesian neural networks
Hlaing, N., Morato, P. G., De Nolasco Santos, F., Weijtjens, W., Devriendt, C. & Rigo, P., May 2024, In: Structural Health Monitoring. 23, 3, p. 1-23 23 p., 0.Research output: Contribution to journal › Article › peer-review
Open AccessFile5 Citations (Scopus)164 Downloads (Pure) -
Enhancing Offshore Wind Turbine Fatigue and Lifetime Assessment
Sadeghi, N., Robbelein, K., Noppe, N., D'Antuono, P., Morato, P. G., Devriendt, C. & Weijtjens, W., 2023. 1 p.Research output: Unpublished contribution to conference › Poster
File -
Quantifying the effect of low-frequency fatigue dynamics on offshore wind turbine foundations: a comparative study
Sadeghi, N., D'Antuono, P., Noppe, N., Robbelein, K., Weijtjens, W. & Devriendt, C., 2023, (Submitted) Copernicus Publications, 20 p. (Wind Energy Science Discussions).Research output: Working paper › Discussion paper
File