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PhD Studentship - Reducing shipping emissions through accurate assessment of energy efficient technologies using statistical analysis of operational data

School of Engineering

Location:  Highfield Campus
Closing Date:  Monday 31 August 2020
Reference:  1249120DA

Supervisor:                 Prof. Dominic Hudson, Dr. Adam Sobey, Prof. Sujit Sahu, (Mathematical Sciences)

Project description

Global shipping is responsible for 3.1% of CO2 emissions (IMO, 3rd Greenhouse Gas report, 2014), yet is outside of UNFCCC commitments to reduce emissions. In 2018 IMO set out its ambitions for reducing CO2 emissions from shipping – by 40% in terms of Carbon intensity by 2030 and by 50% in terms of absolute emissions reductions by 2050. To achieve the first goal will rely on efficient use of existing knowledge in ship design, operation and energy efficient technologies. 

Central to efforts to reduce shipping’s global CO2 emissions is an ability to measure accurately the fuel consumption of a ship during its operation. This enables:

  • Accurate assessment of technology aimed at reducing emissions (e.g. propeller modifications, ducts, anti-fouling coatings, air lubrication, wind-assist devices)

  • Tackling of identified ‘split incentives’ in owner-charterer agreements for ship operation – who pays for emissions reduction techniques? who benefits from reduced fuel use?

  • Charterers to choose energy efficient vessels in a transparent manner

These rely on fuel consumption measurements, which are in practice hard to achieve due to the lack of measurements made during ship operation. Interpreting such data is difficult due to uncertainties arising from: 

  • Imprecise measurement of vessel operational speed through the water

  • Reliance on poorly resolved measurements, or models, of ocean current and wind and wave strength and direction

  • Continuous changes in vessel operating parameters such as engine revolutions, heading, draught and trim

  • Uncertainties in the condition and performance of shipboard machinery

This project aims to reduce these uncertainties through combining naval architecture understanding with statistical techniques to derive reliable estimates of fuel consumption with environmental and operational parameters, together with quantification of statistical reliability.

In order to improve accuracy and integrate uncertainty arising this project will develop rigorous hierarchical statistical models (HSMs) for measurements that ultimately calculate ship power and fuel efficiency. HSMs, postulated in a Bayesian framework, are ideally suited for this problem since they allow synthesis of information from different disparate sources, such as environmental, mechanical, meteorological, operational, into a unified model that allows the propagation and presentation of integrated uncertainty. 

HSMs provide a means to incorporate detailed component-wise spatial, and temporal information and capture the nature of the dependence between observations and processes.

Working with our industrial partner, Shell Shipping and Maritime, this project has the potential to properly target and quantify interventions leading to significantly decreased vessel emissions.

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).

Closing date: applications should be received no later than 31 August 2020 for standard admissions, but later applications may be considered depending on the funds remaining in place.

Funding: full tuition fees for EU/UK students plus for UK students, an enhanced stipend of £15,285 tax-free per annum for up to 3.5 years. 

How To Apply

Applications should be made online, please select the academic session 2020-21 “PhD Eng & Env (Full time)” as the programme. Please enter Dominic Hudson under the proposed supervisor.

Applications should include

Curriculum Vitae

Two reference letters

Degree Transcripts to date

Apply online:

For further information please contact: 

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