Publications

Health assessment framework of marine engines enabled by digital twins

Tsitsilonis Konstantinos-Marios, Theotokatos Gerasimos, Patil Chaitanya, Coraddu Andrea

International Journal of Engine Research Vol 24, pp. 3264-3281 (2023)

https://doi.org/10.1177/14680874221146835

Effects of EGR transient operation on emissions and performance of automotive engines during RDE cycles

Patil Chaitanya

(2020)

Parametric investigation of diesel–methanol dual fuel marine engines with port and direct injection

Karvounis Panagiotis, Theotokatos Gerasimos, Patil Chaitanya, Xiang La, Ding Yu

Fuel Vol 381 (2025)

https://doi.org/10.1016/j.fuel.2024.133441

Data-driven model for marine engine fault diagnosis using in-cylinder pressure signals

Patil Chaitanya, Theotokatos Gerasimos, Tsitsilonis Konstantinos

Journal of Marine Engineering & Technology Vol 24, pp. 70-82 (2025)

https://doi.org/10.1080/20464177.2024.2432777

Investigation of logarithmic signatures for feature extraction and application to marine engine fault diagnosis

Patil Chaitanya, Theotokatos Gerasimos, Wu Yue, Lyons Terry

Engineering Applications of Artificial Intelligence Vol 138 (2024)

https://doi.org/10.1016/j.engappai.2024.109299

Comparative analysis of data-driven models for marine engines in-cylinder pressure prediction

Patil Chaitanya, Theotokatos Gerasimos

Machines Vol 11 (2023)

https://doi.org/10.3390/machines11100926

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Professional Activities

Digitalisation of Maritime Industry in India

Speaker

22/11/2024

world conference on maritime science and technology

Participant

18/10/2023

11th European Combustion Meeting

Participant

26/4/2023

8th International symposium of Ship Operations, Management and Economincs

Participant

7/3/2023

Intelligent marine engine diagnosis and prognosis

Speaker

4/10/2022

Application of AI in engineering

Organiser

22/9/2022

More professional activities

Projects

Neuromorphic Sensor Fusion for Under Water Object Detection

Patil, Chaitanya (Principal Investigator) Di Caterina, Gaetano (Co-investigator)

The project aims to develop a protocol of multimodal data collection through neuromorphic sensors for underwater object detection.
The underwater object detection is very tricky phenomenon due to variability of environmental
changes like wave motion, salinity as well as visibility under water. Various sensors with different
ranges and properties can be deployed to overcome the adverse environmental conditions for object detection. However, increasing number of sensors increases the data processing power, noise and uncertainty in the process rendering the data fusion from these sensors difficult. The proven neuromorphic methods introduce a paradigm shift in handling these sensor uncertainties through sensor fusion and increasing the autonomy of the data management and decision making within the operating envelope of all the sensors used for the object detection task.

01-Jan-2024 - 01-Jan-2025

AI powered fault detection for marine engines operating with B30 biodiesel.

Patil, Chaitanya (Principal Investigator)

The project aims to address challenges in implementing B30 biodiesel engines in
Indonesian maritime transportation due to fuel-related faults, leading to higher
maintenance costs and hindering widespread adoption. It proposes developing a
fault estimation model using machine learning techniques to predict and assess
common biodiesel engine faults, facilitating timely detection and cost-effective
maintenance. The project involves customising thermodynamic models, simulating
healthy and faulty operations, training ML models, and verifying them with real-time
data. Additionally, the project includes organising a workshop on AI in the
Indonesian maritime industry to discuss relevant challenges and solutions. The
project contributes to sustainable development by promoting eco-friendly practices,
reducing operational costs, and fostering economic growth of Indonesia. Key
performance indicators will measure success, including the development of fault
diagnosis models, skill development, dissemination of research outputs, and
awareness creation. The impacts of the project span academic, social, economic,
environmental, and cultural domains, benefiting stakeholders and promoting
research in maritime transportation across Indonesia and south-east Asia.

01-Jan-2024 - 31-Jan-2025

Marine Engine Modelling

Patil, Chaitanya (Principal Investigator) Theotokatos, Gerasimos (Principal Investigator)

18-Jan-2024 - 22-Jan-2024

Incylinder pressure prediction using log-signatures

Patil, Chaitanya (Principal Investigator) Wu, Yue (Principal Investigator)

01-Jan-2022 - 30-Jan-2022

EPSRC IAA: Neuromorphic Sensor Fusion for Under Water Object Detection (SENSE)

Patil, Chaitanya (Co-investigator)

01-Jan-2022 - 31-Jan-2026

Intelligent marine engines health assessment system based on digital twins and data driven models

Patil, Chaitanya (Co-investigator)

The i-HEATS project aims to develop an intelligent condition monitoring and
diagnostics system for marine engines based on first-principles digital twins
and data-driven models. The project has direct application to ship and land
power plants, endeavouring to provide a game-change in the condition
monitoring/diagnostics of internal combustion engines. I4.0 technologies will be
employed leading to the development of intelligent tools, including digital twins,
deep learning, sensors fusion, and cloud computing. The project key objectives
include:
1. Installation of a novel, custom made, data acquisition system for measuring the
instantaneous shaft torque, integrated with the existing monitoring systems to
acquire the required performance parameters.
2. Storage and analysis of acquired data locally and on cloud (edge/cloud
computing).
3. Development of thoroughly validated engine first-principles digital twins,
integrating thermodynamic models with crankshaft/shafting system dynamics
models.
4. Development of data-driven models based on deep learning techniques,
complementing the digital twins to offer real-time predictive capabilities.
5. Use of the developed data-driven model to identify inaccuracies of critical
sensors of the measured parameters and rectify those as needed.
6. Development of intelligent algorithms to monitor engine condition and provide
diagnostics based on the measured instantaneous torque and other critical
parameters.
7. Develop the prototype i-HEATS system by integrating the above tools with
appropriate hardware and user interfaces
8. Extensive testing and verification of the prototype i-HEATS system in lab and
full-scale conditions onboard two ships and improvement of its functionality
leading to a pre-commercial version.

01-Jan-2021 - 31-Jan-2023

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