[et_pb_section fb_built=”1″ _builder_version=”4.17.6″ custom_margin=”||0px||false|false” custom_padding=”0px||0px|||” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_row column_structure=”2_3,1_3″ module_class=”reverse-columns-mobile” _builder_version=”4.17.6″ min_height=”100px” custom_padding=”0px|||||” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_column type=”2_3″ _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.27.4″ global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n
[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.27.4″ text_font=”roboto-regular||||||||” text_text_color=”#003a7c” custom_margin=”||0px||false|false” custom_margin_tablet=”||15px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|tablet” global_colors_info=”{}” theme_builder_area=”post_content”]Only precise water analyses can reliably predict the corrosion behaviour of sheet pile walls.<\/p>\n
Credits: P. Pollmeier\/HSBI[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.6″ custom_margin=”0px||0px||false|false” custom_padding=”0px||0px|||” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_row column_structure=”2_3,1_3″ _builder_version=”4.16″ custom_padding=”0px|||||” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_column type=”2_3″ _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.27.4″ global_colors_info=”{}” theme_builder_area=”post_content”]Steel, water and movement\u00a0\u2013 the infrastructure of quay walls must withstand constant stress. Indeed, sheet pile walls often lose their load-bearing capacity gradually, with no visible damage. This means waterway and port authorities have had to rely on divers who use transducers to measure the remaining thickness of the walls at various points every five years or so to detect corrosion damage. Bremen has eleven of these measuring points and Bremerhaven has 17.<\/p>\n
\u201cThis task can\u2019t be performed by diving robots yet,\u201d reported Grit Behrens, an applied computer science expert at the Minden Campus of Bielefeld University of Applied Sciences (HSBI). There are many reasons for this. For instance, mussels and plants grow on them, and abrasion from constant contact with silt, flotsam or ships is commonplace. This makes designing suitable robots challenging, and so far no one has succeeded.<\/p>\n
For the ports, diving involves considerable effort and a lot of personnel. What is known as \u201cthick water\u201d, i.e. heavily silted areas with currents and tides, makes the work in Bremen and Bremerhaven particularly difficult. Moreover, these visual inspections and fixed maintenance intervals are not always sufficient for detecting corrosion in good time, for example when it develops unevenly at different points.<\/p>\n
The divers usually transmit their findings by radio from under the water to their colleagues on board the ship, where the information is often still recorded by hand. \u201cThe data is then transferred to Excel sheets or Word files, which are subsequently saved as PDFs,\u201d the software specialist continued. Furthermore, each administration decides how to collect this data for itself, making it difficult to perform statistical rusting analyses for cross-location forecasts. <\/p>\n
\u201cWe\u2019re not only developing an application for uniform data collection in Excel and an input mask for web applications, we\u2019re also integrating AI methods,\u201d Behrens stated. \u201cThis will allow us to record the complex, variable environmental parameters as well as, for the first time, making informed predictions about expected sheet pile wall corrosion and optimise maintenance cycles.\u201d
[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ module_class=”dtb-sticky” _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_image src=”https:\/\/www.logistics-pilot.com\/wp-content\/uploads\/2023\/02\/Grit-Behrens_500px.png” alt=”Portrait of Grit Behrens” title_text=”Grit-Behrens_500px” align=”center” _builder_version=”4.27.4″ custom_margin_tablet=”” custom_margin_phone=”25px||||false|false” custom_margin_last_edited=”on|phone” global_colors_info=”{}” theme_builder_area=”post_content”][\/et_pb_image][et_pb_text _builder_version=”4.27.4″ header_3_text_color=”#002e5b” text_orientation=”center” custom_margin_tablet=”” custom_margin_phone=”||40px||false|false” custom_margin_last_edited=”on|phone” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n
Grit Behrens, Professor of Computer Science, is on the \u201cIron\u201d research project management team.[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.6″ custom_margin=”30px||||false|false” custom_padding=”0px||0px|||” bottom_divider_style=”waves2″ bottom_divider_color=”#DFE6EE” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_row column_structure=”2_3,1_3″ _builder_version=”4.16″ custom_padding=”0px|||||” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_column type=”2_3″ _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_image src=”https:\/\/www.logistics-pilot.com\/wp-content\/uploads\/2023\/02\/LP-August-2025-Logistics-Story-newsimage404199-\u00a9-P.-Pollmeier-HSBI_4C_800.jpg” alt=”Three people looking into a flow channel in a hydraulic engineering laboratory.” title_text=”LP-August-2025-Logistics-Story-newsimage404199-\u00a9 P.-Pollmeier-HSBI_4C_800″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”][\/et_pb_image][et_pb_text _builder_version=”4.27.4″ text_font=”roboto-regular||||||||” text_text_color=”#003a7c” custom_margin=”||||false|false” custom_margin_tablet=”||15px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|tablet” global_colors_info=”{}” theme_builder_area=”post_content”]The effects of water on sheet piles can be reproduced accurately in the flow channel in the Minden Campus\u2019 hydraulic engineering lab.[\/et_pb_text][et_pb_text _builder_version=”4.27.4″ custom_margin=”||50px||false|false” hover_enabled=”0″ global_colors_info=”{}” theme_builder_area=”post_content” sticky_enabled=”0″]This led to the \u201cIron\u201d (Intelligent prediction of corrosion on sheet pile walls) interdisciplinary research project. The German Federal Ministry of Education and Research was impressed and approved four years of funding, as were the port operators in Bremen (bremenports), Hamburg (Hamburg Port Authority, HPA) and Rostock (Rostock Port), as well as sheet pile manufacturer Arcelor Mittal, all of which are partners in this project.<\/p>\n
Michael Str\u00f6h, Managing Director of the Port Technology Association (HTG), is also positive about the use of AI and the \u201cIron\u201d project. \u201cAI is well on the way to developing maintenance from reactive repair to predictive added value,\u201d he claimed. \u201cAI recognises things before humans can even guess. And \u2018Iron\u2019 is a major milestone on this path, which will open new doors for maintenance that previously remained closed.\u201d<\/p>\n
\u201cHowever, we needed a large amount of data for machine learning, which we had to find first,\u201d recalled Behrens, thinking back to the initial hurdles. After all, the surveys on rusting available in ports vary in terms of quantity and quality. \u201cFortunately, we had some data for fresh and salt water,\u201d she added, \u201cand we were able to use extensive material on corrosion from Minden to pre-train the neural networks.\u201d <\/p>\n
However, for Behrens, the biggest challenge is the environmental conditions. Factors such as salinity, pH value, temperature, water depth, currents and waves, not to mention shipping traffic, all influence corrosion on sheet pile walls in different and dynamic ways, meaning that standardised maintenance plans reach their limits.
bremenports is also supporting the \u201cIron\u201d project with existing data sets on corrosion processes on steel sheet pile walls and embankments. <\/p>\n
\u201cThe aim of the project is to create improved and expanded options for evaluating this data as a basis for more efficient and informed structural upkeep,\u201d stated Christian Pabst, Head of Construction at bremenports. \u201cMoreover, we\u2019re following the development and refinement across locations and generally applicable methods that describe rusting processes on sheet pile walls in port and hydraulic engineering with great interest.\u201d<\/p>\n
AI is the technological heart of the \u201cIron\u201d project. The machine learning methods used analyse large amounts of data \u2013 from historical corrosion patterns to current environmental parameters such as salinity, flow and temperature. This information is used to create models that not only assess existing damage but can also predict future corrosion risks. This should enable port operators to make informed decisions about maintenance and repair, for example with virtual twins of the structures that digitally map their structural condition and indicate changes early on.<\/p>\n
In the future, generating reliable data could become much easier. \u201cArcelor Mittal is developing sheet piles with integrated sensors,\u201d reported Behrens. \u201cThese are currently being tested on the Moselle.\u201d The next step could be to incorporate weather data from satellites into the corrosion analysis. All of this would significantly improve the quality of corrosion forecasts for sheet piles. (cb)<\/em>[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ module_class=”dtb-sticky” _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_blurb title=”Facts” _builder_version=”4.16″ header_font=”|||on|||||” header_text_color=”#ffffff” header_font_size=”16px” text_orientation=”center” custom_margin=”||20px||false|false” custom_margin_tablet=”” custom_margin_phone=”25px||||false|false” custom_margin_last_edited=”on|phone” custom_css_blurb_title=”display: inline-block!important;||background: #002754!important;||padding: 5px 13px 3px 13px!important;||position: relative!important;” border_width_bottom=”1px” border_color_bottom=”#002754″ global_colors_info=”{}” header_text_color__hover_enabled=”on|desktop” header_text_color__hover=”rgba(255,255,255,0.71)” theme_builder_area=”post_content”][\/et_pb_blurb][et_pb_text _builder_version=”4.27.4″ hover_enabled=”0″ global_colors_info=”{}” theme_builder_area=”post_content” sticky_enabled=”0″]<\/p>\n\u201cIron\u201d project<\/h2>\n