Blar i forfatter Artikler, rapporter og annet (teknologi og sikkerhet) "Perera, Lokukaluge Prasad Channa"

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    • Advanced data cluster analyses in digital twin development for marine engines towards ship performance quantification 

      Taghavi, Mahmood; Perera, Lokukaluge Prasad Channa (Journal article; Tidsskriftartikkel; Peer reviewed, 2024-02-24)
      Due to the growing rate of energy consumption, it is necessary to develop frameworks for enhancing ship energy efficiency. This paper proposes a solution for this issue by introducing a digital twin framework for quantifying ship performance. For this purpose, extensive low-level clustering is performed using Gaussian Mixture Models (GMM) with the Expectation Maximization algorithm on a dataset ...

    • Coordinate Conversion and Switching Correction to Reduce Vessel Heading-Related Errors in High-Latitude Navigation 

      Wang, Yufei; Perera, Lokukaluge Prasad Channa; Batalden, Bjørn-Morten Erdal (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-11-22)
      Considering the distortion errors of projected coordinates and the switching property of vessel heading, coordinate conversion and switching correction methods are proposed to modify a kinematic motion model and the Unscented Kalman Filter (UKF). The coordinate conversion method utilizes the grid convergence from a Universal Transverse Mercator (UTM) projection to correct the vessel heading. The ...

    • Data driven control based on Deep Q-Network algorithm for heading control and path following of a ship in calm water and waves 

      Sivaraj, Sivaraman; Rajendran, Suresh; Perera, Lokukaluge Prasad Channa (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-06)
      A reinforcement learning algorithm based on Deep Q-Networks (DQN) is used for the path following and heading control of a ship in calm water and waves. The rudder action of the ship is selected based on the developed DQN model. The spatial positions, linear velocities, yaw rate, Heading Error (HE) and Cross Track Error (CTE) represent the state-space, and a set of rudder angles represents the action ...

    • Data-driven modeling of energy-exergy in marine engines by supervised ANNs based on fuel type and injection angle classification 

      Taghavifar, Hadi; Perera, Lokukaluge Prasad Channa (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-02-16)
      The application of artificial neural networks with the involvement of a modified homogeneity factor to predict exergetic terms from combustive and/or mixing dynamics in a marine engine is considered in this study. This is a significant step since the mathematical formulation of exergy in combustion is complicated and even unconvincing due to the turbulent and highly nonlinear nature of the combustion ...

    • The Effect of LNG and Diesel Fuel Emissions of Marine Engines on GHG-Reduction Revenue Policies Under Life-Cycle Costing Analysis in Shipping 

      Taghavifar, Hadi; Perera, Lokukaluge Prasad Channa (Chapter; Bokkapittel, 2023)
      The fuel life cycle involves different phases of extraction/refinery (well to tank: WtT), transport (tank to propeller: TtP), and storage where each of these processes can add a specific amount of emissions to the overall LCCA inventory. During the extraction or operation of machinery on the raw material, the released amount of GHG components is undergoing a change in the generated emissions per ...

    • Energy-Efficient Marine Engine and Dynamic Wing Evaluation Under Laboratory Conditions to Achieve Emission Reduction Targets in Shipping 

      Perera, Lokukaluge Prasad Channa; Belibassakis, Kostas (Chapter; Bokkapittel, 2023-09-22)
      There is a requirement to comply with the forthcoming IMO & EU requirements to reduce ship emissions by at least 40% in 2030 compared to the 2008 levels. Such medium-term emission reduction targets can only be achieved by introducing novel technologies into the shipping industry. The SeaTech H2020 project (seatech2020.eu) introduces two main innovations that can support the same emission reduction ...

    • Kinematic motion models based vessel state estimation to support advanced ship predictors 

      Wang, Yufei; Perera, Lokukaluge Prasad Channa; Batalden, Bjørn-Morten (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-14)
      Advanced ship predictors can generally be considered as a vital part of the decision-making process of autonomous ships in the future, where the information on vessel maneuvering behavior can be used as the source of information to estimate current vessel motions and predict future behavior precisely. As a result, the navigation safety of autonomous vessels can be improved. In this paper, vessel ...

    • Life cycle emission and cost assessment for LNG-retrofitted vessels: the risk and sensitivity analyses under fuel property and load variations 

      Taghavifar, Hadi; Perera, Lokukaluge Prasad Channa (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-13)
      There are various energy efficiency and emission reduction regulations enforced by the national and international maritime authorities for the shipping industry to adopt greener technologies. In this light, LNG-fueled vessels can be a promising alternative for ocean going diesel operated ships. It will be more beneficial if the price of LNG is lower than diesel to make that an economically viable ...

    • Life-cycle cost analysis of an innovative marine dual-fuel engine under uncertainties 

      Bui, Khanh Quang; Perera, Lokukaluge Prasad Channa; Emblemsvåg, Jan (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-10-27)
      As innovative technologies are being deployed to accelerate shipping decarbonization in response to air emission regulations, there is considerable concern about the cost effectiveness of such technologies from a life-cycle perspective. This study conducts a life-cycle cost analysis (LCCA) on an innovative marine dual-fuel engine under uncertainties, comparing the total life-cycle cost performance ...

    • Multiple Model Adaptive Estimation Coupled With Nonlinear Function Approximation and Gaussian Mixture Models for Predicting Fuel Consumption in Marine Engines 

      Taghavi, Mahmood; Perera, Lokukaluge Prasad Channa (Chapter; Bokkapittel, 2023)
      Digital twin type models can be developed for physical systems that are complex nonlinear a system of systems (SoS). However, such models are usually difficult to represent by linear equations. Therefore, an adequate linearization technique should be introduced. Therefore, linear models as digital twins can be interpreted easily and need much less computational power when applied to various industrial ...

    • Safety challenges related to autonomous ships in mixed navigational environments 

      Kim, Tae-Eun; Perera, Lokukaluge Prasad Channa; Sollid, Magne-Petter; Batalden, Bjørn-Morten; Sydnes, Are Kristoffer (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-05-30)
      Digitalization and technological advancements have accelerated the development and emergence of autonomous and remotely controlled ships in the maritime transport sector. This type of vessels consists of highly intelligent and adaptive functionalities, equipped with a variety of external sensors and actuators to gain situation awareness, automated control and adaptive maneuvering for achieving more ...

    • Trustworthiness Evaluation Framework for Digital Ship Navigators in Bridge Simulator Environments 

      Namazi Rabati, Hosna; Perera, Lokukaluge Prasad Channa (Chapter; Bokkapittel, 2023)
      The maritime industry is going towards implementing digital navigators, i.e., AI created by machine learning algorithms, on autonomous vessels in the future. Digital navigators can be developed by utilizing machine learning algorithms, e.g., deep learning type neural networks trained by data sets from human navigators. Even though there is significant importance in studying the trustworthiness of ...