Ship Handling & Manoeuvring
Nomoto modelling, heading response, turning behaviour, simulator development, and evaluation of vessel control characteristics.
About the Laboratory
The Ship Safety and Ship Handling Simulator Laboratory supports research and education in ship manoeuvring, marine accident analysis, navigational risk, passenger-vessel safety, and environmentally responsible maritime operations. The laboratory explores computational, simulation-based, and data-driven methods that may contribute to safer ship design and operation.
Its activities include evaluating the manoeuvring performance of student ship designs, investigating accidents and incidents of national and international interest, and studying navigable routes, bridge-passing performance, collision risk, grounding risk, and related safety questions for academic and professional applications.
Research Themes
Maritime Safety & Risk
Collision probability, grounding risk, bridge-passing performance, navigational-route assessment, and quantitative risk analysis.
Accident Investigation
Systematic examination of marine casualties, human and organizational factors, accident causation, and safety recommendations.
Passenger & Ferry Safety
Safe and affordable ferry design, evacuation, survivability, accessibility, passenger comfort, and public-health considerations.
Environmental Safety
Shipboard waste management, pollution prevention, climate adaptation, cleaner operations, and sustainable maritime transport.
Submarine & Underwater Safety
Submarine accidents, failure mechanisms, survivability, emergency response, and lessons for underwater systems.
Ship-Handling Simulation and AI-Based Collision Avoidance
Interactive Simulation Project
Google Maps-Based Ship-Handling Simulator
Figure 3. GUI of the Marine Traffic Simulator
The simulator combines the Google Maps API with Nomoto’s K–T manoeuvring model to visualize and control a ship’s planar motion in real time.
- Uses three linked JavaScript modules: trajectory, Google Maps, and control codes
- Solves the Nomoto K–T response using the fourth-order Runge–Kutta method
- Accepts ship dimensions, speed, initial heading, rudder command, and nondimensional K′ and T′
- Displays animated position, instantaneous heading, rate of turn, and live response graphs
Artificial Intelligence Research
Collision Avoidance for Autonomous Ships
The collision-avoidance work links algorithmic decision support for autonomous ships with evidence from inland-waterway collision characteristics in Bangladesh.
- Compares route-planning and collision-avoidance approaches for autonomous navigation
- Uses simulator-based scenarios to examine encounter handling and decision support
- The 2010 accident study identifies collision as a major inland-waterway safety problem
- Cargo vessels were frequently involved, and inadequate lighting, reporting, and collision-avoidance devices were key concerns
Featured Research
Simulation
Ship Handling Simulation
A marine traffic simulator on Google Maps using the Nomoto K–T model and real-time geographic visualization.
Read representative publicationCollision Avoidance
Collision Avoidance
Collision characteristics of marine vehicles in Bangladesh, providing an evidence base for collision-prevention measures.
Read representative publicationSafety Science
Marine Accident Investigation
A systems-theoretic analysis of inland passenger-ship safety and the interactions among regulatory, organizational, and operational controls.
Read representative publicationPassenger Safety
Passenger Ship Safety
A model for airborne SARS-CoV-2 transmission on the upper deck of a passenger ship and the implications for onboard prevention.
Read representative publicationEnvironment
Environmental Sustainability
A sustainable passenger-ship waste-management model incorporating biogas-composting and plastic segregation.
Read representative publicationArtificial Intelligence
AI for Maritime Engineering
AI-driven estimation of ship-repair time as a decision-support application for maritime engineering and the blue economy.
Read representative publicationInternational Recognition: WFSA Competition
Student Design for Safer Ferries
Students associated with the laboratory have achieved sustained recognition in the International Student Design Competition for a Safe and Affordable Ferry organized by the Worldwide Ferry Safety Association. These projects combine ship design, safety assessment, manoeuvring analysis, sustainable propulsion, and context-specific transport needs.
Five Recognized Entries
BUET teams received Third Place in 2021, Honourable Mention in 2023, Second Place in 2024, First Place in 2025, and Third Place in 2026.
2021
Third Place
Cisne Rosa Express, a 300-passenger Ro-Pax ferry for the Amazon River, Brazil.
2023
Honourable Mention
Green Falcon Express, a 100-passenger electric ferry for the Pasig River, Philippines.
2024
Second Place
Black Pearl, a 200-passenger Ro-Pax ferry for the Niger River route in Nigeria.
2025
First Place
Najia Spirit, a 200-passenger electric ferry for the Lagos Inland Waterway, Nigeria.
2026
Third Place
A 200-passenger ferry for the Niger River route between Lokoja and Onitsha, Nigeria.
Lab In-Charge
Dr. Zobair Ibn Awal
ডঃ জোবায়ের ইবনে আওয়াল
Exploring safer, smarter, and bio-inspired marine systems through engineering and artificial intelligence
Professor
Department of Naval Architecture & Marine Engineering (NAME)
Bangladesh University of Engineering & Technology (BUET)
Dhaka 1000, Bangladesh