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Proceedings Papers

A Decision Support Framework for Cost-Effective and Energy-Efficient Shipping

Khanh Q. Bui, Lokukaluge P. Perera

Proc. ASME. OMAE2020, Volume 6A: Ocean Engineering, V06AT06A026, August 3–7, 2020

Paper No: OMAE2020-18368

DOI: https://doi.org/10.1115/OMAE2020-18368

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Topics: Artificial intelligence, Cycles, Data acquisition systems, Decision making, Emissions, Energy efficiency, Flow (Dynamics), Greenhouse gases, Innovation, Internet of things

Proceedings Papers

Unsupervised Trajectory Anomaly Detection for Situation Awareness in Maritime Navigation

Brian Murray, Lokukaluge P. Perera

Proc. ASME. OMAE2020, Volume 6A: Ocean Engineering, V06AT06A024, August 3–7, 2020

Paper No: OMAE2020-18281

DOI: https://doi.org/10.1115/OMAE2020-18281

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Topics: Navigation, Trajectories (Physics), Ships, Collisions (Physics), Traffic

Journal Articles

Deep Learning Toward Autonomous Ship Navigation and Possible COLREGs Failures

Lokukaluge P. Perera

J. Offshore Mech. Arct. Eng. June 2020, 142(3): 031102.

Paper No: OMAE-19-1027

DOI: https://doi.org/10.1115/1.4045372

Published Online: December 17, 2019

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Topics: Collisions (Physics), Navigation, Ships, Vessels, Failure

Proceedings Papers

An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels

Brian Murray, Lokukaluge P. Perera

Proc. ASME. OMAE2019, Volume 7B: Ocean Engineering, V07BT06A031, June 9–14, 2019

Paper No: OMAE2019-95963

DOI: https://doi.org/10.1115/OMAE2019-95963

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Topics: Collisions (Physics), Trajectories (Physics), Vessels, Algorithms, Modeling

Proceedings Papers

Situation Awareness of Autonomous Ship Navigation in a Mixed Environment Under Advanced Ship Predictor

Lokukaluge P. Perera, Brian Murray

Proc. ASME. OMAE2019, Volume 7B: Ocean Engineering, V07BT06A029, June 9–14, 2019

Paper No: OMAE2019-95571

DOI: https://doi.org/10.1115/OMAE2019-95571

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Topics: Navigation, Ships, Collisions (Physics), Vessels, Regulations, Seas, Failure, Risk assessment, Traffic, Water

Proceedings Papers

An Overview of Data Veracity Issues in Ship Performance and Navigation Monitoring

Lokukaluge P. Perera, Brage Mo

Proc. ASME. OMAE2018, Volume 11B: Honoring Symposium for Professor Carlos Guedes Soares on Marine Technology and Ocean Engineering, V11BT12A004, June 17–22, 2018

Paper No: OMAE2018-77669

DOI: https://doi.org/10.1115/OMAE2018-77669

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Topics: Navigation, Ships, Internet of things, Performance, Vessels, Data acquisition, Data acquisition systems, Sensors

Proceedings Papers

Autonomous Ship Navigation Under Deep Learning and the Challenges in COLREGs

Lokukaluge P. Perera

Proc. ASME. OMAE2018, Volume 11B: Honoring Symposium for Professor Carlos Guedes Soares on Marine Technology and Ocean Engineering, V11BT12A005, June 17–22, 2018

Paper No: OMAE2018-77672

DOI: https://doi.org/10.1115/OMAE2018-77672

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Topics: Navigation, Ships, Collisions (Physics), Vessels, Decision making, Oceans, Seas, Driverless cars, Failure, Liabilities

Proceedings Papers

Visualization of Relative Wind Profiles in Relation to Actual Weather Conditions of Ship Routes

Lokukaluge P. Perera, Brage Mo, Matthias P. Nowak

Proc. ASME. OMAE2017, Volume 7B: Ocean Engineering, V07BT06A033, June 25–30, 2017

Paper No: OMAE2017-61120

DOI: https://doi.org/10.1115/OMAE2017-61120

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Topics: Ships, Visualization, Wind, Navigation, Vessels, Air pollution control, Energy efficiency, Sensors, Supervisory Control and Data Acquisition systems, Wind velocity

Proceedings Papers

Digitalization of Seagoing Vessels Under High Dimensional Data Driven Models

Lokukaluge P. Perera, Brage Mo

Proc. ASME. OMAE2017, Volume 7A: Ocean Engineering, V07AT06A001, June 25–30, 2017

Paper No: OMAE2017-61011

DOI: https://doi.org/10.1115/OMAE2017-61011

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Topics: Vessels, Navigation, Ships, Internet of things

Proceedings Papers

Automated System for Fleet Benchmarking and Assessment of Technical Condition

Brage Mo, Petter Dehli, Christian Steinebach, Tow Foong Lim, Lokukaluge P. Perera

Proc. ASME. OMAE2017, Volume 7A: Ocean Engineering, V07AT06A007, June 25–30, 2017

Paper No: OMAE2017-61219

DOI: https://doi.org/10.1115/OMAE2017-61219

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Topics: Diesel engines, Energy / power systems, Energy generation, Engines, Equipment performance, Fuel efficiency, Fuels, Instrumentation, Machinery, Maintenance

Proceedings Papers

Visual Analytics in Ship Performance and Navigation Information for Sensor Specific Fault Detection

Lokukaluge P. Perera, Brage Mo

Proc. ASME. OMAE2017, Volume 7B: Ocean Engineering, V07BT06A032, June 25–30, 2017

Paper No: OMAE2017-61118

DOI: https://doi.org/10.1115/OMAE2017-61118

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Topics: Flaw detection, Navigation, Sensors, Ships, Internet of things, Vessels, Air pollution control, Energy efficiency, Oceans, Performance

Journal Articles

Marine Engine-Centered Data Analytics for Ship Performance Monitoring

Lokukaluge P. Perera, Brage Mo

J. Offshore Mech. Arct. Eng. April 2017, 139(2): 021301.

Paper No: OMAE-16-1081

DOI: https://doi.org/10.1115/1.4034923

Published Online: January 31, 2017

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Topics: Engines, Propellers, Ships, Navigation, Vessels, Algorithms

Proceedings Papers

Data Compression of Ship Performance and Navigation Information Under Deep Learning

Lokukaluge P. Perera, Brage Mo

Proc. ASME. OMAE2016, Volume 7: Ocean Engineering, V007T06A086, June 19–24, 2016

Paper No: OMAE2016-54093

DOI: https://doi.org/10.1115/OMAE2016-54093

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Topics: Compression, Navigation, Ships, Data acquisition systems, Data centers, Energy efficiency, System architecture, Vessels, Air pollution control, Data acquisition

Proceedings Papers

Data Analytics for Capturing Marine Engine Operating Regions for Ship Performance Monitoring

Lokukaluge P. Perera, Brage Mo

Proc. ASME. OMAE2016, Volume 7: Ocean Engineering, V007T06A087, June 19–24, 2016

Paper No: OMAE2016-54168

DOI: https://doi.org/10.1115/OMAE2016-54168

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Topics: Engines, Ships, Algorithms, Energy efficiency, Propellers, Vessels, Air pollution control, Navigation, Shapes

Proceedings Papers

Evaluations on Ship Performance Under Varying Operational Conditions

Lokukaluge P. Perera, Brage Mo, Leifur Arnar Kristjánsson, Petter Chr. Jønvik, Jan Øivind Svardal

Proc. ASME. OMAE2015, Volume 7: Ocean Engineering, V007T06A060, May 31–June 5, 2015

Paper No: OMAE2015-41793

DOI: https://doi.org/10.1115/OMAE2015-41793

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Topics: Ships, Energy efficiency, Vessels, Air pollution control, Engines, Navigation, Design, Energy consumption, Fuel consumption, Wind

Journal Articles

System Identification of Nonlinear Vessel Steering

Lokukaluge P. Perera, P. Oliveira, C. Guedes Soares

J. Offshore Mech. Arct. Eng. June 2015, 137(3): 031302.

Paper No: OMAE-12-1058

DOI: https://doi.org/10.1115/1.4029826

Published Online: June 1, 2015

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Topics: Vessels, Algorithms

Proceedings Papers

Collaborated and Constrained Neural-EKF Algorithm for the Vessel Traffic Monitoring and Information System

Lokukaluge P. Perera, Paulo Oliveira, C. Guedes Soares

Proc. ASME. OMAE2011, Volume 6: Ocean Engineering, 871-879, June 19–24, 2011

Paper No: OMAE2011-50248

DOI: https://doi.org/10.1115/OMAE2011-50248

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Topics: Algorithms, Traffic, Vessels, State estimation, Trajectories (Physics), Navigation, Oceans, Artificial neural networks, Computer software, Kalman filters

Proceedings Papers

Dynamic Parameter Estimation of a Nonlinear Vessel Steering Model for Ocean Navigation

Lokukaluge P. Perera, Paulo Oliveira, C. Guedes Soares

Proc. ASME. OMAE2011, Volume 6: Ocean Engineering, 881-888, June 19–24, 2011

Paper No: OMAE2011-50249

DOI: https://doi.org/10.1115/OMAE2011-50249

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Topics: Navigation, Oceans, Parameter estimation, Vessels, Kalman filters, Physics

Journal Articles

Periodic Tension Disturbance Attenuation in Web Process Lines Using Active Dancers

Prabhakar R. Pagilla, Associate Professor, Ramamurthy V. Dwivedula, Graduate Student, Yongliang Zhu, Graduate Student, Lokukaluge P. Perera, Graduate Student

J. Dyn. Sys., Meas., Control. September 2003, 125(3): 361–371.

DOI: https://doi.org/10.1115/1.1590678

Published Online: September 18, 2003

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Topics: Rollers, Tension, Arches, Control equipment, Design

Journal citation

NARROW

A Decision Support Framework for Cost-Effective and Energy-Efficient Shipping

Unsupervised Trajectory Anomaly Detection for Situation Awareness in Maritime Navigation

Deep Learning Toward Autonomous Ship Navigation and Possible COLREGs Failures

An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels

Situation Awareness of Autonomous Ship Navigation in a Mixed Environment Under Advanced Ship Predictor

An Overview of Data Veracity Issues in Ship Performance and Navigation Monitoring

Autonomous Ship Navigation Under Deep Learning and the Challenges in COLREGs

Visualization of Relative Wind Profiles in Relation to Actual Weather Conditions of Ship Routes

Digitalization of Seagoing Vessels Under High Dimensional Data Driven Models

Automated System for Fleet Benchmarking and Assessment of Technical Condition

Visual Analytics in Ship Performance and Navigation Information for Sensor Specific Fault Detection

Marine Engine-Centered Data Analytics for Ship Performance Monitoring

Data Compression of Ship Performance and Navigation Information Under Deep Learning

Data Analytics for Capturing Marine Engine Operating Regions for Ship Performance Monitoring

Evaluations on Ship Performance Under Varying Operational Conditions

System Identification of Nonlinear Vessel Steering

Collaborated and Constrained Neural-EKF Algorithm for the Vessel Traffic Monitoring and Information System

Dynamic Parameter Estimation of a Nonlinear Vessel Steering Model for Ocean Navigation

Periodic Tension Disturbance Attenuation in Web Process Lines Using Active Dancers

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