Objectif
Research objectives and content
The goal of this research is to develop an improved network model of effluent treatment systems by focusing on the modelling of dissolved air flotation (DAF) units. The Petrochemical Industry especially generates aqueous process effluents with high oil content and other contaminants causing high biological (BOD) and carbon oxygen (COD) demand in their treatment before safe discharge into the waterways. Typically, the effluent is transported a network of ducts connecting unit operations. In order to simulate treatment performance under altered operating conditions or with modifications to the treatment system, models are necessary for the behaviour of the process units. In many cases, simple steady state models suffice for planning purposes. But to meet future consent levels and restrictions on process units, more accurate steady state, transient and internal models of process elements are necessary. Previous projects between the Thornton Research Centre, Stanlow Refinery, and UMIST have focused on steady state models in dissolved air flottation (DAF) units. DAF units are commonly used in waste- . water treatment to separate solids which are skimmed from the top surface and to oxidize contaminants which are responsible for COD and BOD. Generally, existing predictive models of mass transport and oxidation within DAF units are insufficient to permit accurate retrofit of industrial plants. There are two reasons for this: (1) effluent treatment systems are networks which must be considered in totality, rather then just as individual units, (2) performance of DAF units in place modifies over time and empirical models must be recalibrated from either direct experimental; measures or simulation. These models are already included in a superstructure simulation of effluent treatment networks. Other process elements require improved models for the whole simulation to be effective. This project will model time dependent effects resulting from 3-D mixing and phase separation in buffer tanks. This should be especially useful in retrofiting existing equipment. Training content (objective, benefit and expected impact)
There will be multiple benefits derived from the training on the methods of research in this project. Primarily, the training will permit me to take up an academic research post in a prominent Greek university and to apply my industrial insight to wastewater treatment in Greek chemical and water industries. Secondarily, the engineering community will benefit from the case study of technology transfer of theories developed in interfacial transport to practical models of DAF performance for use . in retrofit and design. Finally, Shell, which is contributing information and kind support, will benefit from the NN models . developed by direct incorporation into their effluent treatment system superstructure simulation, which will improve their capacity to minimize the environmental impact of process effluent.
Links with industry / industrial relevance (22) . Dr AR Godley (Thornton), Dr Simon Chynoweth (Thornton), and Mr Ed Scriven (Stanlow) of Shell will comprise the industrial CASE management team and provide access to several aspects of wastewater management. Dr Godley focuses . on biotreaters, which are increasingly important in this field; Dr Chynoweth is developing a network model for operations . simulations, planning and retrofit design. Mr Scriven oversees several operations at the refinery that require oily water .effluent treatment currently. It is envisaged that I will make regular visits to collect data from the refinery treatment plant and to consult with the case management team.
Champ scientifique
Appel à propositions
Data not availableRégime de financement
RGI - Research grants (individual fellowships)Coordinateur
MANCHESTER
Royaume-Uni