• Dagens livbåter: Fin farge – falsk trygghet? 

      Hagen, Benedicte Byholt; Haugan, Thomas; Røe, Andrine (Bachelor thesis, 2023)
      Dagens konvensjonelle livbåter følger kravene LSA-koden har satt for utforming av sitteplasser. Disse kravene ble sist oppdatert i år 1997, og med dagens demografi og økende kroppsvekt undersøker oppgaven nærmere hvordan ...
    • Data Analysis and Modeling of Ship Motion Data for Offshore Operations 

      Cheng, Xu (Doctoral theses at NTNU;2020:180, Doctoral thesis, 2020)
      Ship intelligence aims to make the marine and offshore industries more efficient, innovative, and adaptable to future operations. In fact, ship intelligence has been listed as an important part of the digital agenda, one ...
    • Data analysis and modelling for onboard support of marine operations 

      Wang, Chunlin (Doctoral theses at NTNU;2023:253, Doctoral thesis, 2023)
      The ever-increasing exploration of ocean resources has led to more frequent and intensive marine operations. However, marine operations are vulnerable to accidents due to unpredictable environmental factors and human ...
    • Data Set from Long-Term Wave, Wind, and Response Monitoring of the Bergsøysund Bridge 

      Kvåle, Knut Andreas Kirkestuen; Fenerci, Aksel; Petersen, Øyvind Wiig; Rønnquist, Nils Erik Anders; Øiseth, Ole Andre (Peer reviewed; Journal article, 2023)
      Wind, wave, displacement, and acceleration data have been collected in a measurement campaign on Norway’s Bergsøysund Bridge, an end-supported pontoon bridge, between the years 2014 and 2018. The data set is now available ...
    • Data-Based Modelling of Ships for Motion Prediction and Control Allocation 

      Skulstad, Robert (Doctoral theses at NTNU;2021:383, Doctoral thesis, 2021)
      Vessels operating on the surface of the ocean are exposed to an array of disturbances. These may come in terms of environmental disturbances, but may also come from signal loss. Modelling the behaviour of ships using ...
    • Data-Driven Approaches to Diagnostics and State of Health Monitoring of Maritime Battery Systems 

      Vanem, Erik; Liang, Qin; Ferreira, Carla; Agrell, Christian; Karandikar, Nikita; Wang, Shuai; bruch, maximilian; Bertinelli Salucci, Clara; Grindheim, Christian; Kejvalova, Anna; Alnes, Øystein Åsheim; Thorbjørnsen, Kristian; Bakdi, Azzeddine; Kandepu, Rambabu (Chapter, 2023)
      Battery systems are increasingly being used for powering ocean going ships, and the number of fully electric or hybrid ships relying on battery power for propulsion and maneuvering is growing. In order to ensure the safety ...
    • Data-driven enhancement to ship dynamic model for motion prediction 

      Kanazawa, Motoyasu (Doctoral theses at NTNU;2023:247, Doctoral thesis, 2023)
      Ensuring safety and efficiency is the most critical agenda for the maritime industry. It is essential to have a good understanding of ship dynamics and make accurate predictions of ship motion. This enables us to properly ...
    • Data-driven Methods for Decision Support in Smart Ship Operations 

      Han, Peihua (Doctoral theses at NTNU;2022:163, Doctoral thesis, 2022)
      Vessels operating on the surface of the ocean today are now increasingly equipped with sensors. This includes GPS, MRU, IMU that monitor the vessel’s motion behavior, and power, RPM, temperature sensors that monitor the ...
    • Data-driven Modeling of Ship Motion Prediction Based on Support Vector Regression 

      Kawan, Bikram; Wang, Hao; Li, Guoyuan; Chhantyal, Khim (Journal article; Peer reviewed, 2017)
      This paper presents a flexible system structure to analyze and model for the potential use of huge ship sensor data to generate efficient ship motion prediction model. The noisy raw data is cleaned using noise reduction, ...
    • Data-Driven Prediction of Ship Propulsion Power Using Spark Parallel Random Forest on Comprehensive Ship Operation Data 

      Liang, Qin; Vanem, Erik; Knutsen, Knut Erik; Zhang, Houxiang (Chapter, 2022)
      This paper aims to propose an efficient machine learning framework for maritime big data and use it to train a random forest model to estimate ships’ propulsion power based on ship operation data. The comprehensive data ...
    • A Data-Driven Prognostics and Health Management System for Autonomous and Semi- Autonomous Ships 

      Ellefsen, André Listou (Doctoral theses at NTNU;2020:178, Doctoral thesis, 2020)
      Ship autonomy has been one of the most-sought research objectives at the Norwegian University of Science and Technology in Aalesund for the last three years. Through credible research, we aim to maintain our competitive ...
    • Data-driven sea state estimation for vessels using multi-domain features from motion responses 

      Han, Peihua; Li, Guoyuan; Skjong, Stian; Wu, Baiheng; Zhang, Houxiang (Chapter, 2021)
      Situation awareness is of great importance for autonomous ships. One key aspect is to estimate the sea state in a real-time manner. Considering the ship as a large wave buoy, the sea state can be estimated from motion ...
    • Data-Driven Ship Design 

      Gaspar, Henrique Murilo (Chapter, 2018)
      This paper proposes data-driven methods thinkingto the ship design practices, enabling effective data collection, quality, access, analysis and monitoring during the vessel lifecycle.Data is here understood as the key ...
    • Data-driven Uncertainty and Sensitivity Analysis for Ship Motion Modeling in Offshore Operations 

      Cheng, Xu; Li, Guoyuan; Skulstad, Robert; Major, Pierre Yann; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang (Journal article; Peer reviewed, 2019)
      To build a compact data-driven ship motion model for offshore operations that require high control safety, it is necessary to select the most influential parameters and to analyze the uncertainty of the input parameters. ...
    • Dead Reckoning of Dynamically Positioned Ships: Using an Efficient Recurrent Neural Network 

      Skulstad, Robert; Li, Guoyuan; Fossen, Thor I.; Vik, Bjørnar; Zhang, Houxiang (Journal article; Peer reviewed, 2019)
      When a ship experiences a loss of position reference systems, its navigation system typically enters a mode known as dead reckoning (DR) to maintain an estimate of its position. Commercial systems perform this task using ...
    • Decarbonization synergies from joint planning of electricity and hydrogen production: A Texas case study 

      Bødal, Espen Flo; Mallapragada, Dharik; Botterud, Audun; Korpås, Magnus (Peer reviewed; Journal article, 2020)
      Hydrogen (H2) shows promise as an energy carrier in contributing to emissions reductions from sectors which have been difficult to decarbonize, like industry and transportation. At the same time, flexible H2 production via ...
    • Decision Transparency for enhanced human-machine collaboration for autonomous ships 

      Madsen, Andreas Solnørdal; Brandsæter, Andreas; Aarset, Magne Vollan (Chapter, 2023)
      Maritime Autonomous Surface Ships (MASS) are quickly emerging as a gamechanging technology in various parts of the world. They can be used for a wide range of applications, including cargo transportation, oceanographic ...
    • A Deep Learning Approach to Detect and Isolate Thruster Failures for Dynamically Positioned Vessels Using Motion Data 

      Han, Peihua; Li, Guoyuan; Skulstad, Robert; Skjong, Stian; Zhang, Houxiang (Peer reviewed; Journal article, 2020)
      Vessels today are being fully monitored, thanks to the advance of sensor technology. The availability of data brings ship intelligence into great attention. As part of ship intelligence, the desire of using advanced ...
    • Deep Reinforcement Learning based Energy Management in Marine Hybrid Vehicle 

      Kumar, Swapnil (Master thesis, 2021)
      Automatisering har nylig fått mye oppmerksomhet fra maritim industri. Selv om mye autonome navigasjoner har blitt lagt vekt på, er det også viktig å ta opp behovet for autonom kontroll av andre prosesser som energiledelse. ...
    • Deep-Sea Mining: Et nødvendig ledd i EUs energiomstilling? 

      Edvardsen, Fabian Vaa; Jacobsen, Runar (Bachelor thesis, 2022)
      Dette hovedprosjektet tar for hvordan dypvannsgruvedrift fungerer; om det er et globalt og nasjonalt behov for dypvannsgruvedrift; hvilke globale mineralforekomster som påvirker miljøet i størst grad samt hva det har å si ...