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Optimising Work and Heat Exchange Networks Towards Improved Energy Efficiency Processes

   School of Engineering and the Built Environment (SEBE)

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  Dr V Onishi, Dr Z Cai  No more applications being accepted  Self-Funded PhD Students Only

About the Project

Work and heat exchange networks (WHENs) have become increasingly important for industrial processes in the past few years. Growing research has distinctly shown that work and heat integration plays a critical role in reaching significant energy and cost savings while enhancing system energy efficiency and reducing environmental impacts. This is especially relevant for energy-intensive processes in oil refineries and cryogenic technology, such as the air separation, hydrogen liquefaction and production of liquefied natural gas (LNG). In LNG plants, excessive energy consumption is associated with compressing and cooling streams at sub-ambient conditions. Besides, the continuous rise in global energy demand, highly volatile energy prices, and stricter environmental policies towards the reduction of carbon emissions, have also boosted the development of more efficient process integration techniques and work and heat recovery strategies for industrial processes.

Within this framework, this project is aimed at developing new mathematical modelling approaches for the cost-effective design and optimisation of WHENs. The models will be mainly based on mathematical programming techniques, including deterministic and/or stochastic optimisation. The main objectives include developing improved energy efficiency solutions, reducing process costs, and decreasing environmental impacts through comprehensive energy, economic and environmental analyses.

Academic qualifications

A first degree (at least a 2.1) ideally in Mechanical Engineering or Chemical Engineering with a good fundamental knowledge of thermodynamics and applied mathematics.

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:

· Experience of fundamental research analysis skills.

· Competent in mathematical modelling in MATLAB.

· Knowledge of fundamental energy transfer processes.

· Good written and oral communication skills

· Strong motivation, with evidence of independent research skills relevant to the project

· Good time management

Desirable attributes:

- Knowledge of mathematical programming in GAMS software.

- Knowledge of life-cycle analysis.

- Experience in using engineering software tools (SimaPro, EES, TRNSYS Professional, or HOMER pro).

- Experience in undertaking independent research.

- A completed or near-completition MSc in a relevant subject area.

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