Introducing a data-driven approach to  predict site-specific leading-edge erosion  from mesoscale weather simulations

Visbech, Jens; Göçmen, Tuhfe; Hasager, Charlotte Bay; Shkalov, Hristo; Handberg, Morten; Nielsen, Kristian Pagh

doi:https://doi.org/10.5194/wes-8-173-2023

Articles | Volume 8, issue 2

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Articles | Volume 8, issue 2

https://doi.org/10.5194/wes-8-173-2023

Articles | Volume 8, issue 2

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Research article

15 Feb 2023

Research article |

| 15 Feb 2023

Introducing a data-driven approach to predict site-specific leading-edge erosion from mesoscale weather simulations

Jens Visbech, Tuhfe Göçmen, Charlotte Bay Hasager, Hristo Shkalov, Morten Handberg, and Kristian Pagh Nielsen

Jens Visbech

CORRESPONDING AUTHOR

jvima@dtu.dk

https://orcid.org/0000-0002-5080-6892

Department of Wind and Energy Systems, Technical University of Denmark (DTU), 4000 Roskilde, Denmark

Tuhfe Göçmen

https://orcid.org/0000-0002-2510-0388

Department of Wind and Energy Systems, Technical University of Denmark (DTU), 4000 Roskilde, Denmark

Charlotte Bay Hasager

https://orcid.org/0000-0002-2124-5651

Department of Wind and Energy Systems, Technical University of Denmark (DTU), 4000 Roskilde, Denmark

Hristo Shkalov

Wind Power LAB, 1150 Copenhagen, Denmark

Morten Handberg

Wind Power LAB, 1150 Copenhagen, Denmark

Kristian Pagh Nielsen

Danish Meteorological Institute (DMI), 2100 Copenhagen, Denmark

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Total article views: 2,593 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
1,810	728	55	2,593	51	49

HTML: 1,810
PDF: 728
XML: 55
Total: 2,593
BibTeX: 51
EndNote: 49

Views and downloads (calculated since 20 Jun 2022)

Cumulative views and downloads (calculated since 20 Jun 2022)

Total article views: 1,871 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
1,472	360	39	1,871	41	41

HTML: 1,472
PDF: 360
XML: 39
Total: 1,871
BibTeX: 41
EndNote: 41

Views and downloads (calculated since 15 Feb 2023)

Month	HTML	PDF	XML	Total
Feb 2023	120	33	2	155
Mar 2023	72	35	3	110
Apr 2023	340	8	2	350
May 2023	205	12	2	219
Jun 2023	22	11	0	33
Jul 2023	23	17	1	41
Aug 2023	19	17	2	38
Sep 2023	30	15	1	46
Oct 2023	18	9	0	27
Nov 2023	14	9	3	26
Dec 2023	27	13	1	41
Jan 2024	21	9	0	30
Feb 2024	15	11	1	27
Mar 2024	21	25	1	47
Apr 2024	38	8	1	47
May 2024	25	11	2	38
Jun 2024	96	18	3	117
Jul 2024	129	9	2	140
Aug 2024	38	12	5	55
Sep 2024	16	3	1	20
Oct 2024	28	5	1	34
Nov 2024	15	7	0	22
Dec 2024	16	5	0	21
Jan 2025	29	17	1	47
Feb 2025	39	12	3	54
Mar 2025	33	12	1	46
Apr 2025	20	16	0	36
May 2025	3	1	0	4

Cumulative views and downloads (calculated since 15 Feb 2023)

Month	HTML	PDF	XML	Total
Feb 2023	120	33	2	155
Mar 2023	72	35	3	110
Apr 2023	340	8	2	350
May 2023	205	12	2	219
Jun 2023	22	11	0	33
Jul 2023	23	17	1	41
Aug 2023	19	17	2	38
Sep 2023	30	15	1	46
Oct 2023	18	9	0	27
Nov 2023	14	9	3	26
Dec 2023	27	13	1	41
Jan 2024	21	9	0	30
Feb 2024	15	11	1	27
Mar 2024	21	25	1	47
Apr 2024	38	8	1	47
May 2024	25	11	2	38
Jun 2024	96	18	3	117
Jul 2024	129	9	2	140
Aug 2024	38	12	5	55
Sep 2024	16	3	1	20
Oct 2024	28	5	1	34
Nov 2024	15	7	0	22
Dec 2024	16	5	0	21
Jan 2025	29	17	1	47
Feb 2025	39	12	3	54
Mar 2025	33	12	1	46
Apr 2025	20	16	0	36
May 2025	3	1	0	4

Total article views: 722 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
338	368	16	722	10	8

HTML: 338
PDF: 368
XML: 16
Total: 722
BibTeX: 10
EndNote: 8

Views and downloads (calculated since 20 Jun 2022)

Month	HTML	PDF	XML	Total
Feb 2023	120	33	2	155
Mar 2023	72	35	3	110
Apr 2023	340	8	2	350
May 2023	205	12	2	219
Jun 2023	22	11	0	33
Jul 2023	23	17	1	41
Aug 2023	19	17	2	38
Sep 2023	30	15	1	46
Oct 2023	18	9	0	27
Nov 2023	14	9	3	26
Dec 2023	27	13	1	41
Jan 2024	21	9	0	30
Feb 2024	15	11	1	27
Mar 2024	21	25	1	47
Apr 2024	38	8	1	47
May 2024	25	11	2	38
Jun 2024	96	18	3	117
Jul 2024	129	9	2	140
Aug 2024	38	12	5	55
Sep 2024	16	3	1	20
Oct 2024	28	5	1	34
Nov 2024	15	7	0	22
Dec 2024	16	5	0	21
Jan 2025	29	17	1	47
Feb 2025	39	12	3	54
Mar 2025	33	12	1	46
Apr 2025	20	16	0	36
May 2025	3	1	0	4

Cumulative views and downloads (calculated since 20 Jun 2022)

Month	HTML	PDF	XML	Total
Feb 2023	120	33	2	155
Mar 2023	72	35	3	110
Apr 2023	340	8	2	350
May 2023	205	12	2	219
Jun 2023	22	11	0	33
Jul 2023	23	17	1	41
Aug 2023	19	17	2	38
Sep 2023	30	15	1	46
Oct 2023	18	9	0	27
Nov 2023	14	9	3	26
Dec 2023	27	13	1	41
Jan 2024	21	9	0	30
Feb 2024	15	11	1	27
Mar 2024	21	25	1	47
Apr 2024	38	8	1	47
May 2024	25	11	2	38
Jun 2024	96	18	3	117
Jul 2024	129	9	2	140
Aug 2024	38	12	5	55
Sep 2024	16	3	1	20
Oct 2024	28	5	1	34
Nov 2024	15	7	0	22
Dec 2024	16	5	0	21
Jan 2025	29	17	1	47
Feb 2025	39	12	3	54
Mar 2025	33	12	1	46
Apr 2025	20	16	0	36
May 2025	3	1	0	4

Viewed (geographical distribution)

Show all Final revised paper only Preprint only

Total article views: 2,593 (including HTML, PDF, and XML) Thereof 2,518 with geography defined and 75 with unknown origin.

Total article views: 1,871 (including HTML, PDF, and XML) Thereof 1,803 with geography defined and 68 with unknown origin.

Total article views: 722 (including HTML, PDF, and XML) Thereof 715 with geography defined and 7 with unknown origin.

Country	#	Views	%
United States of America	1	668	25
China	2	615	23
Denmark	3	196	7
Germany	4	173	6
United Kingdom	5	84	3

Country	#	Views	%
China	1	567	30
United States of America	2	476	25
Germany	3	99	5
Denmark	4	97	5
United Kingdom	5	71	3

Country	#	Views	%
United States of America	1	192	26
Denmark	2	99	13
Germany	3	74	10
China	4	48	6
Spain	5	32	4


Total:	0
HTML:	0
PDF:	0
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668


Total:	0
HTML:	0
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567


Total:	0
HTML:	0
PDF:	0
XML:	0

192

Cited

Show all Final revised paper only Preprint only

12 citations as recorded by crossref.

Erosion-safe operation using double deep Q-learning J. Visbech et al. 10.1088/1742-6596/2767/3/032047
Coating material loss and surface roughening due to leading edge erosion of wind turbine blades: Probabilistic analysis A. Tempelis & L. Mishnaevsky 10.1016/j.wear.2025.205755
Rain erosion atlas for wind turbine blades based on ERA5 and NORA3 for Scandinavia Á. Hannesdóttir et al. 10.1016/j.rineng.2024.102010
Aerodynamic effects of leading-edge erosion in wind farm flow modeling J. Visbech et al. 10.5194/wes-9-1811-2024
Review on Erosion Wear Subjected to Different Coating Materials on Leading Edge Protection for Cooling Towers and Wind Turbines U. Nirmal et al. 10.1007/s40735-025-00943-8
Drop-size-dependent effects in leading-edge rain erosion and their impact on erosion-safe mode operation N. Barfknecht & D. von Terzi 10.5194/wes-10-315-2025
Impact of meteorological data factors and material characterization method on the predictions of leading edge erosion of wind turbine blades A. Castorrini et al. 10.1016/j.renene.2024.120549
Prioritizing Research for Enhancing the Technology Readiness Level of Wind Turbine Blade Leading-Edge Erosion Solutions S. Pryor et al. 10.3390/en17246285
Data-driven wind farm flow control and challenges towards field implementation: A review T. Göçmen et al. 10.1016/j.rser.2025.115605
Aerodynamic interaction of rain and wind turbine blades: the significance of droplet slowdown and deformation for leading-edge erosion N. Barfknecht & D. von Terzi 10.5194/wes-9-2333-2024
Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research S. Pryor et al. 10.3390/en15228553
Lifetime prediction of turbine blades using global precipitation products from satellites M. Badger et al. 10.5194/wes-7-2497-2022

10 citations as recorded by crossref.

Erosion-safe operation using double deep Q-learning J. Visbech et al. 10.1088/1742-6596/2767/3/032047
Coating material loss and surface roughening due to leading edge erosion of wind turbine blades: Probabilistic analysis A. Tempelis & L. Mishnaevsky 10.1016/j.wear.2025.205755
Rain erosion atlas for wind turbine blades based on ERA5 and NORA3 for Scandinavia Á. Hannesdóttir et al. 10.1016/j.rineng.2024.102010
Aerodynamic effects of leading-edge erosion in wind farm flow modeling J. Visbech et al. 10.5194/wes-9-1811-2024
Review on Erosion Wear Subjected to Different Coating Materials on Leading Edge Protection for Cooling Towers and Wind Turbines U. Nirmal et al. 10.1007/s40735-025-00943-8
Drop-size-dependent effects in leading-edge rain erosion and their impact on erosion-safe mode operation N. Barfknecht & D. von Terzi 10.5194/wes-10-315-2025
Impact of meteorological data factors and material characterization method on the predictions of leading edge erosion of wind turbine blades A. Castorrini et al. 10.1016/j.renene.2024.120549
Prioritizing Research for Enhancing the Technology Readiness Level of Wind Turbine Blade Leading-Edge Erosion Solutions S. Pryor et al. 10.3390/en17246285
Data-driven wind farm flow control and challenges towards field implementation: A review T. Göçmen et al. 10.1016/j.rser.2025.115605
Aerodynamic interaction of rain and wind turbine blades: the significance of droplet slowdown and deformation for leading-edge erosion N. Barfknecht & D. von Terzi 10.5194/wes-9-2333-2024

2 citations as recorded by crossref.

Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research S. Pryor et al. 10.3390/en15228553
Lifetime prediction of turbine blades using global precipitation products from satellites M. Badger et al. 10.5194/wes-7-2497-2022

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This paper presents a data-driven framework for modeling erosion damage based on real blade inspections and mesoscale weather data. The outcome of the framework is a machine-learning-based model that can predict and/or forecast leading-edge erosion damage based on weather data and user-specified wind turbine characteristics. The model output fits directly into the damage terminology used by the industry and can therefore support site-specific maintenance planning and scheduling of repairs.

This paper presents a data-driven framework for modeling erosion damage based on real blade...

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