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Proceedings Papers

Mooring Optimization Using ML Techniques

Pau Trubat, Adrián Herrera, Climent Molins

Proc. ASME. IOWTC2022, ASME 2022 4th International Offshore Wind Technical Conference, V001T01A013, December 7–8, 2022

Paper No: IOWTC2022-98217

DOI: https://doi.org/10.1115/IOWTC2022-98217

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Topics: Mooring, Optimization, Design, Simulation, Yaw, Tension, Dynamic response, Surges, Wind velocity, Algorithms

Proceedings Papers

Characterisation of Ship-Induced Long-Period Primary Waves Using Nonlinear Fourier Transform (KdV-NFT)

Markus Brühl, Sander Wahls

Proc. ASME. OMAE2022, Volume 5B: Ocean Engineering; Honoring Symposium for Professor Günther F. Clauss on Hydrodynamics and Ocean Engineering, V05BT06A055, June 5–10, 2022

Paper No: OMAE2022-78098

DOI: https://doi.org/10.1115/OMAE2022-78098

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Topics: Fourier transforms, Ships, Waves, Solitons, Time series, Dynamics (Mechanics), Geometry, Korteweg-de Vries equation, Nonlinear waves, Spectra (Spectroscopy)

Proceedings Papers

Operational Planning and Power Management System for Offshore Platform With Wind Energy Supply – Impacts on CO 2 Reduction and Power Quality

Harald G. Svendsen, Andrzej Holdyk, Til Kristian Vrana, Idun Runde Mosgren, Jan Wiik

Proc. ASME. OMAE2022, Volume 10: Petroleum Technology, V010T11A046, June 5–10, 2022

Paper No: OMAE2022-78802

DOI: https://doi.org/10.1115/OMAE2022-78802

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Topics: Carbon dioxide, Offshore platforms, Wind energy, Emissions, Gas turbines, Pumps, Simulation, Compressors, Energy / power systems, Fuels

Proceedings Papers

Assessment of Situation Awareness for Seafarers Using Eye-Tracking Data

S. S. Virdi, Yong Thiang Ng, Yisi Liu, Kelvin Tan, Daniel Zhang

Proc. ASME. OMAE2022, Volume 1: Offshore Technology, V001T01A011, June 5–10, 2022

Paper No: OMAE2022-80754

DOI: https://doi.org/10.1115/OMAE2022-80754

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Topics: Algorithms, Bridges (Structures), Career development, Computers, Data collection, Echoes, Errors, Glass, Human factors, Navigation

Proceedings Papers

Study on Hydrodynamic Performance of a Conceptional Sea-Train

Yan Qin, Chaobang Yao, Yi Zheng, Jianghao Huang

Proc. ASME. OMAE2022, Volume 7: CFD and FSI, V007T08A049, June 5–10, 2022

Paper No: OMAE2022-79779

DOI: https://doi.org/10.1115/OMAE2022-79779

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Topics: Computer simulation, Drag reduction, Seas, Trains

Proceedings Papers

A Different Way to Execute Project Using a Product-Based Approach

Cathy Farina

Proc. ASME. OPTC2021, ASME 2021 Onshore Petroleum Technology Conference, V001T03A002, September 27–29, 2021

Paper No: OPTC2021-66752

DOI: https://doi.org/10.1115/OPTC2021-66752

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Topics: Construction industry, Delays, Design, Economics , Failure, Life cycle costing, Liquefied natural gas, Manufacturing, Modular construction, Pandemics

Proceedings Papers

Efficient Modelling of Harsh Environment Disturbances for DP and Autonomous Ships Simulations

Hasanat Zaman, Mohammed Islam, Osama Alagili, Mohammad Khan, Syed Imtiaz, Salim Ahmed

Proc. ASME. OMAE2021, Volume 6: Ocean Engineering, V006T06A067, June 21–30, 2021

Paper No: OMAE2021-63954

DOI: https://doi.org/10.1115/OMAE2021-63954

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Topics: Dynamic positioning systems, Ice, Modeling, Ships, Simulation, Waves, Wind, Stress, Design, Arctic Ocean

Proceedings Papers

Case Study ROP Modeling Using Random Forest Regression and Gradient Boosting in the Hanover Region in Germany

Patrick Höhn, Felix Odebrett, Carlos Paz, Joachim Oppelt

Proc. ASME. OMAE2020, Volume 11: Petroleum Technology, V011T11A023, August 3–7, 2020

Paper No: OMAE2020-18677

DOI: https://doi.org/10.1115/OMAE2020-18677

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Topics: Modeling, Drilling, Geothermal engineering, Geothermal power, Machine learning, Optimization, Petroleum industry, Trains

Proceedings Papers

Autonomous Surface Vessel Obstacle Avoidance Based on Hierarchical Reinforcement Learning

Chang Zhou, Lei Wang, Shangyu Yu, Huacheng He

Proc. ASME. OMAE2020, Volume 1: Offshore Technology, V001T01A005, August 3–7, 2020

Paper No: OMAE2020-18454

DOI: https://doi.org/10.1115/OMAE2020-18454

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Topics: Unmanned surface vehicles, Algorithms, Computation, Decision making, Design, Feedback, Path planning, Safety, Simulation results, Trains

Proceedings Papers

Risk Perception Oriented Autonomous Ship Navigation in AIS Environment

Ruolan Zhang, Masao Furusho

Proc. ASME. OMAE2020, Volume 1: Offshore Technology, V001T01A001, August 3–7, 2020

Paper No: OMAE2020-18003

DOI: https://doi.org/10.1115/OMAE2020-18003

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Topics: Collisions (Physics), Navigation, Risk perception, Ships, Decision making, Seas, Artificial neural networks, Algorithms, Errors, Expert systems

Proceedings Papers

Development of a Simulation Environment for Hybrid Propulsion Drive Trains: Utilization of a Holistic Approach to Predict the Dynamic Behavior in the Early Design Stage

Leif-Erik Jannsen

Proc. ASME. OMAE2020, Volume 1: Offshore Technology, V001T01A027, August 3–7, 2020

Paper No: OMAE2020-18817

DOI: https://doi.org/10.1115/OMAE2020-18817

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Topics: Design, Dimensions, Propulsion, Simulation, Trains

Proceedings Papers

Ship As a Wave Buoy: Estimating Full Directional Wave Spectra From In-Service Ship Motion Measurements Using Deep Learning

T. P. Scholcz, B. Mak

Proc. ASME. OMAE2020, Volume 1: Offshore Technology, V001T01A006, August 3–7, 2020

Paper No: OMAE2020-18783

DOI: https://doi.org/10.1115/OMAE2020-18783

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Topics: Buoys, Motion measurement, Ships, Spectra (Spectroscopy), Waves, Artificial neural networks, Encryption, Marine safety, Navigation, Ocean waves

Proceedings Papers

The Study on Flow Past a Static Hydrofoil Using Deep Neural Network

Xia Wu, Xinliang Tian, Yufeng Kou, Xin Li, Wenyue Lu

Proc. ASME. OMAE2020, Volume 8: CFD and FSI, V008T08A010, August 3–7, 2020

Paper No: OMAE2020-19256

DOI: https://doi.org/10.1115/OMAE2020-19256

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Topics: Artificial neural networks, Flow (Dynamics), Hydrofoil, Errors, Computational fluid dynamics, Drag (Fluid dynamics), Interpolation, Physics, Pressure, Trains

Proceedings Papers

Neural Network-Based Method for Structural Damage and Scour Estimation Using Modal Parameters and Dynamic Responses

Shuqing Wang, Yufeng Jiang

Proc. ASME. OMAE2020, Volume 6B: Ocean Engineering, V06BT06A013, August 3–7, 2020

Paper No: OMAE2020-18461

DOI: https://doi.org/10.1115/OMAE2020-18461

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Topics: Damage, Dynamic response, Wind turbines, Artificial neural networks, Blades, Energy industry, Fast Fourier transforms, Frequency response, Ocean engineering, Robustness

Proceedings Papers

Analysis of Bore Characteristics Using KdV-Based Nonlinear Fourier Transform

Markus Bruehl, Sander Wahls, Ignacio Barranco Granged, Philipp L.-F. Liu

Proc. ASME. OMAE2020, Volume 6B: Ocean Engineering, V06BT06A072, August 3–7, 2020

Paper No: OMAE2020-19074

DOI: https://doi.org/10.1115/OMAE2020-19074

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Topics: Fourier transforms, Solitons, Trains, Water, Waves, Computer simulation, Korteweg-de Vries equation

Proceedings Papers

Machine Learning Approach for Estimating Residual Stresses in Girth Welds of Topside Piping

Sachin Bhardwaj, R. M. Chandima Ratnayake, Arvind Keprate, Xavier Ficquet

Proc. ASME. OMAE2020, Volume 3: Materials Technology, V003T03A023, August 3–7, 2020

Paper No: OMAE2020-18703

DOI: https://doi.org/10.1115/OMAE2020-18703

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Topics: Machine learning, Pipes, Residual stresses, Welded joints, Stress, Algorithms, Errors, Fitness-for-service, Databases, Failure

Proceedings Papers

Ship As a Wave Buoy: Using Simulated Data to Train Neural Networks for Real Time Estimation of Relative Wave Direction

Bart Mak, Bülent Düz

Proc. ASME. OMAE2019, Volume 9: Rodney Eatock Taylor Honoring Symposium on Marine and Offshore Hydrodynamics; Takeshi Kinoshita Honoring Symposium on Offshore Technology, V009T13A044, June 9–14, 2019

Paper No: OMAE2019-96225

DOI: https://doi.org/10.1115/OMAE2019-96225

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Topics: Artificial neural networks, Buoys, Ships, Trains, Waves, Seas, Simulation, Doors, Geometry, Motion measurement

Proceedings Papers

Progress on the Development of a Holistic Coupled Model of Dynamics for Offshore Wind Farms: Phase II — Study on a Data-Driven Based Reduced-Order Model for a Single Wind Turbine

Z. Lin, A. Stetco, J. Carmona-Sanchez, D. Cevasco, M. Collu, G. Nenadic, O. Marjanovic, M. Barnes

Proc. ASME. OMAE2019, Volume 10: Ocean Renewable Energy, V010T09A048, June 9–14, 2019

Paper No: OMAE2019-95542

DOI: https://doi.org/10.1115/OMAE2019-95542

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Topics: Dynamics (Mechanics), Ocean engineering, Wind farms, Wind turbines, Degrees of freedom, Offshore wind turbines, Couplings, Dynamic models, Failure mechanisms, Generators

Proceedings Papers

A PDE Model for Estimating the Life Time of a Riser

Halvor Snersrud Gustad, Per Thomas Moe, Elena Celledoni

Proc. ASME. OMAE2019, Volume 5B: Pipelines, Risers, and Subsea Systems, V05BT04A055, June 9–14, 2019

Paper No: OMAE2019-96185

DOI: https://doi.org/10.1115/OMAE2019-96185

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Topics: Pipeline risers, Risers (Casting), Stress, Algorithms, Boundary-value problems, Computer simulation, Design, Errors, Fatigue, Finite element analysis

Proceedings Papers

Port Channel Navigation Subjected to Environmental Conditions Using Reinforcement Learning

José Amendola, Eduardo A. Tannuri, Fabio G. Cozman, Anna H. Reali Costa

Proc. ASME. OMAE2019, Volume 7A: Ocean Engineering, V07AT06A042, June 9–14, 2019

Paper No: OMAE2019-96120

DOI: https://doi.org/10.1115/OMAE2019-96120

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Topics: Navigation, Vessels, Engineering simulation, Simulation, Algorithms, Dynamic models, Fluctuations (Physics), Gates (Closures), Machine learning, Rotation

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NARROW

Mooring Optimization Using ML Techniques

Characterisation of Ship-Induced Long-Period Primary Waves Using Nonlinear Fourier Transform (KdV-NFT)

Operational Planning and Power Management System for Offshore Platform With Wind Energy Supply – Impacts on CO 2 Reduction and Power Quality

Assessment of Situation Awareness for Seafarers Using Eye-Tracking Data

Study on Hydrodynamic Performance of a Conceptional Sea-Train

A Different Way to Execute Project Using a Product-Based Approach

Efficient Modelling of Harsh Environment Disturbances for DP and Autonomous Ships Simulations

Case Study ROP Modeling Using Random Forest Regression and Gradient Boosting in the Hanover Region in Germany

Autonomous Surface Vessel Obstacle Avoidance Based on Hierarchical Reinforcement Learning

Risk Perception Oriented Autonomous Ship Navigation in AIS Environment

Development of a Simulation Environment for Hybrid Propulsion Drive Trains: Utilization of a Holistic Approach to Predict the Dynamic Behavior in the Early Design Stage

Ship As a Wave Buoy: Estimating Full Directional Wave Spectra From In-Service Ship Motion Measurements Using Deep Learning

The Study on Flow Past a Static Hydrofoil Using Deep Neural Network

Neural Network-Based Method for Structural Damage and Scour Estimation Using Modal Parameters and Dynamic Responses

Analysis of Bore Characteristics Using KdV-Based Nonlinear Fourier Transform

Machine Learning Approach for Estimating Residual Stresses in Girth Welds of Topside Piping

Ship As a Wave Buoy: Using Simulated Data to Train Neural Networks for Real Time Estimation of Relative Wave Direction

Progress on the Development of a Holistic Coupled Model of Dynamics for Offshore Wind Farms: Phase II — Study on a Data-Driven Based Reduced-Order Model for a Single Wind Turbine

A PDE Model for Estimating the Life Time of a Riser

Port Channel Navigation Subjected to Environmental Conditions Using Reinforcement Learning

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