In offshore engineering, structural steel is a very important kind, which can not only improve work efficiency and reduce cost. It also has high safety and reliability. This paper takes ships as the research object, analyzes its application and development, puts forward the application of shipbuilding profiles in the manufacturing mode and service life of sea going ships under new technology, and summarizes the relevant fields. Finally, combined with the concrete example design of structural steel, through the process of theoretical study to practical operation, it expounds how to combine high-strength steel bars with other materials. The experimental results show that the high strength structural steel has excellent yield strength, tensile strength and elongation, and can meet the quality requirements of marine engineering.

Ken Lodewyk. High Strength Structural Steel in Ship and Marine Engineering Structures. Frontiers in Ocean Engineering (2022), Vol. 3, Issue 3: 1-8. https://doi.org/10.38007/FOE.2022.030301.

[1] Slawomir Konrad Tadeja, Yupu Lu, Maciej Rydlewicz, Wojciech Rydlewicz, Tomasz Bubas, Per Ola Kristensson:Exploring gestural input for engineering surveys of real-life structures in virtual reality using photogrammetric 3D models. Multim. Tools Appl. 80(20): 31039-31058 (2021). https://doi.org/10.1007/s11042-021-10520-z

[2] Enrique García-Macías, Rafael Castro-Triguero, Erick I. Saavedra Flores, Sergio J. Yanez, Karen Hinrechsen:An interactive computational strategy for teaching the analysis of silo structures in civil engineering. Comput. Appl. Eng. Educ. 27(4): 821-835 (2019). https://doi.org/10.1002/cae.22112

[3] Feng Tao, Tijun Fan, Kin Keung Lai:Inventory Management Under Power Structures With Consignment Contract Subject to Inventory Inaccuracy. IEEE Trans. Engineering Management 66(4): 763-773 (2019). https://doi.org/10.1109/TEM.2018.2850003

[4] Yichi Zhang, Denghua Zhong, Binping Wu, Tao Guan, Pan Yue, Han Wu:3D Parametric Modeling of Complex Geological Structures for Geotechnical Engineering of Dam Foundation Based on T-Splines. Comput. Aided Civ. Infrastructure Eng. 33(7): 545-570 (2018). https://doi.org/10.1111/mice.12343

[5] Massimo Donelli, Federico Viani:Remote Inspection of the Structural Integrity of Engineering Structures and Materials With Passive MST Probes. IEEE Trans. Geosci. Remote. Sens. 55(12): 6756-6766 (2017). https://doi.org/10.1109/TGRS.2017.2734042

[6] Alan Smith, Rodrigo Sarlo:Automated extraction of structural beam lines and connections from point clouds of steel buildings. Comput. Aided Civ. Infrastructure Eng. 37(1): 110-125 (2022). https://doi.org/10.1111/mice.12699

[7] Paolo Cicconi, Vincenzo Castorani, Michele Germani, Marco Mandolini, Alessio Vita:A multi-objective sequential method for manufacturing cost and structural optimization of modular steel towers. Eng. Comput. 36(2): 475-497 (2020). https://doi.org/10.1007/s00366-019-00709-0

[8] Shahrin Mohammad, Tan Cher Siang, Sharifah Osman, Nurdiana Yasmin Jamaluddin, Nur Afiqah Mohamed Alfu, Lee Yeong Huei:A Proposed Heutagogy Framework for Structural Steel Design in Civil Engineering Curriculum. Int. J. Emerg. Technol. Learn. 14(24): 96-105 (2019). https://doi.org/10.3991/ijet.v14i24.12091

[9] P. P. Kapse, M. T. Telsang:Parametric investigation and optimisation of plasma arc cutting of structural steel St.52-3 using grey-based fuzzy algorithm. Int. J. Manuf. Res. 14(2): 179-197 (2019). https://doi.org/10.1504/IJMR.2019.100020

[10] Christopher John Steele, M. Mallar Chakravarty:Gray-matter structural variability in the human cerebellum: Lobule-specific differences across sex and hemisphere. NeuroImage 170: 164-173 (2018). https://doi.org/10.1016/j.neuroimage.2017.04.066

[11] Serdar Çarbas:Optimum structural design of spatial steel frames via biogeography-based optimization. Neural Comput. Appl. 28(6): 1525-1539 (2017). https://doi.org/10.1007/s00521-015-2167-6

[12] Vaughn R. Steele, Vikram Rao, Vince D. Calhoun, Kent A. Kiehl:Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders. NeuroImage 145: 265-273 (2017). https://doi.org/10.1016/j.neuroimage.2015.12.013

[13] Nadia Pérot, Nicolas Bousquet:Functional Weibull-based models of steel fracture toughness for structural risk analysis: estimation and selection. Reliab. Eng. Syst. Saf. 165: 355-367 (2017). https://doi.org/10.1016/j.ress.2017.04.024

[14] Burak Efe, Ömer Faruk Efe, Alessio Ishizaka:A model proposal to examine the effects of ships to marine pollution in terms of internal and external factors. Soft Comput. 26(5): 2121-2134 (2022). https://doi.org/10.1007/s00500-021-06626-z

[15] Hiroyasu Kifune, Mehdi Karbalaye Zadeh, Hidetsugu Sasaki:Efficiency Estimation of Synchronous Generators for Marine Applications and Verification With Shop Trial Data and Real Ship Operation Data. IEEE Access 8: 195541-195550 (2020). https://doi.org/10.1109/ACCESS.2020.3033404

[16] Cagatay Kandemir, Metin Celik:A human reliability assessment of marine auxiliary machinery maintenance operations under ship PMS and maintenance 4.0 concepts. Cogn. Technol. Work. 22(3): 473-487 (2020). https://doi.org/10.1007/s10111-019-00590-3

[17] Soroush Azizi, Mohammad Hassan Asemani, Navid Vafamand, Saleh Mobayen, Afef Fekih:Adaptive Neural Network Linear Parameter-Varying Control of Shipboard Direct Current Microgrids. IEEE Access 10: 75825-75834 (2022). https://doi.org/10.1109/ACCESS.2022.3191385

[18] Simon Blindheim, Tor Arne Johansen:Electronic Navigational Charts for Visualization, Simulation, and Autonomous Ship Control. IEEE Access 10: 3716-3737 (2022). https://doi.org/10.1109/ACCESS.2021.3139767