The use of the pilot plant facility in teaching process control engineering at Murdoch University

The Pilot Plant at Murdoch University is equipped with a Honeywell Supervisory Control System, known as SCAN3000. The plant was designed to simulate three stages: grinding and digestion, clarification, and precipitation of the Bayer Process to manufacture alumina from bauxite. This paper presents some examples in design and implementation of a great number of feature-based feedback PI controllers and the implementation of sophisticated control laws such as Generic Model Control (GMC), Dynamic Matrix Control (DMC), Supervisory Control and Fuzzy Control. Although all features of the pilot plant are not currently available for teaching purposes, Process Control Engineering (PCE) students still have the opportunity to operate and implement many different control strategies to various unit operations such as working with a real process to obtain real hands-on experience. A different example is the upgrade and maintenance program based on Programmable Logic Controllers (PLC) which highlights the learning and developing of skills in using PLC and Supervisory Control and Data Acquisition systems (SCADA)

Teaching process control in instrumentation and control laboratory

The Instrumentation and Control Laboratory (IC-lab) was designed to provide separated modules of different types of heat exchangers, air- pressured vessels, water tanks, pumps, flow meters and control valves. These module s can be connected to provide various conventional pieces of process control equipment. Through the experiments designed for the IC-lab, students can obtain real hands-on experience. In the first two years of the IC course students learn to perform step-tests, develop linear and non-linear model, then design and implement P, PI and PID cont rollers in the real time systems. More sophisticated control schemes such as Cascade, Feedforward, Generic Model Control (GMC) or Fuzzy Logic Control can also be achieved in the lab. This paper demonstrated an example of generating a nonlinear system by connecting two pressured- air tanks and other modules. A step test is perform ed to determine an approximate model for the PI controller design. At the same time a mathematical model of the system is developed based on measurements and calibrations of the system. A GMC scheme is applied based on this model. Comparison of performances of the PI and GMC controllers to control the pressure in the vessel are finally presented and discussed

Modelling the simultaneous heat and mass transfer of direct contact membrane distillation in hollow fibre modules

This paper presents a new procedure for modelling the simultaneous heat and mass transfer in direct contact membrane distillation (DCMD) in a hollow fibre configuration. Iterative calculations in classic dimensionless analysis were applied to develop semi-empirical models, employing the analogy between heat and mass transfer. The procedure incorporated the significant effect of the membrane module's geometry: length and tortuosity of fibres in the bundle and fibres' size. Additionally, the new procedure showed the influence of the exponent β of Prandtl and Schmidt numbers on the validity of the models to simultaneously describe heat and mass transfer in the DCMD process. Current results agreed well with other analyses in the literature. The value close to 0.33 of β, as conventionally used, could be applied for heat transfer and minimal mass transfer. In other more intensive mass transfer cases, it was found that the values of β could go up to 0.55. The new models demonstrated a linear relationship between heat and mass fluxes and their respective driving forces, namely conductive heat flux against temperature gradient and mass flux against water vapour pressure difference across the membrane. Finally these semi-empirical models were applied to evaluate the performance of various hollow fibre modules of different length and types

Steady state modelling, simulation and optimisation of a multi stage cobalt solvent extraction circuit

The cobalt solvent extraction (CoSX) system using Cyanex 272 as the organic extractant, has been modelled for single, two and three stage extraction circuits using MATLAB and Aspen Custom Modeler (ACM) mathematical modelling software. Steady state simulations and optimisations have been conducted on the developed models. An initial sensitivity analysis has shown that increasing pH or the organic to aqueous (O:A) ratio significantly increases individual metal extraction efficiencies. However to achieve the ultimate aim of maximising cobalt extraction while minimising magnesium and nickel co-extraction and reagent consumption, an economic objective function has been formulated within the optimisation problem to solve for the optimum pH setpoint and O:A ratio. For this case study a two stage Co SX circuit with the (O:A) ratio at 0.162 and pH at 4.64 was found to be optimal. This set of conditions would achieve 99% cobalt extraction, while limiting magnesium co-extraction to 9% and nickel co-extraction to <0.5%

pH control strategy testing in a bioreactor

A 5-L bioreactor was set up with an impeller, cooling and heating coils, probes for measuring pH, temperature and dissolved oxygen concentration. The reactor instrumentation was interfaced with a computer via data acquisition hardware. LabVIEW, a graphical programming language was used in all measurement and control programs. The reactor temperature control could be achieved by a conventional proportional-integral (PI) controller. In contrast controlling pH was difficult due to a considerable variation in the slope of the titration curve. A simple PI loop resulted in aggressive pH control actions, causing excessive base addition and likely demise of the microorganisms. In this work synthetic waste water was used for testing control schemes. The Generic Model Control (GMC) and gain-scheduling adaptive control strategies were investigated and compared with a PI control scheme. In these strategies, the rate change of pH was assumed to be a function of residence time, base addition, and pH, allowing the continuous calculation of base added against the pH measured. Some experimental and simulated results are presented for comparison

Steady state optimization of design and operation of desalination systems using Aspen Custom Modeler

In this paper Multistage flash (MSF), Reverse Osmosis (RO) and hybrid MSF/RO desalination systems are optimized. A superstructure is set up for analyzing various process configurations in a single flowsheet. Detailed steady state models for MSF and RO sections of the superstructure are developed incorporating comprehensive physio-chemical properties and design characteristics. The model for the hybrid system combines individual models of MSF and RO systems and additional separators and mixers. The optimization variables consist of the operating and design variables, and the objective function is developed on the basis of economic and technical performance indicators. Primary results show that the hybridization of MSF and RO systems sharing common intake-outfall facilities presents lower cost with the additional benefits of higher overall recovery than MSF system and higher product quality than RO system. The sensitivity analysis of the cost parameters is performed to realize their effects on the selection of process configuration

The assessment of switching policies in chemical plants

No abstract availabl

Implementation of switching policies in real systems

No abstract availabl

Simulation and optimisation of direct contact membrane distillation for energy efficiency

This paper describes the formulation of a computational framework for simulating and optimising DCMD to minimise the consumed energy. A simulation procedure for DCMD was established on the basis of equating heat and mass fluxes through different domains in the process. Steady-state simulations for a wide range of operating conditions were carried out. It was revealed that the highest achievable energy efficiency of DCMD within the tested range was about 49.9%. A double loop optimisation problem was formulated in MATLAB to solve the highly nonlinear equations with unknown outlet and membrane surface conditions to implement the simulation procedure. An additional outer loop was also implemented to accommodate the dynamic condition of a real lab-scale DCMD system concentrating 1.5 kg glucose solution from 30 to 60% w/w. A pseudo-real-time dynamic optimisation was performed to minimise the energy expenses for the DCMD process. This energy accounted for the heat exchanged between the feed and permeate streams within the membrane module and the power for their pumping, while maintaining a minimum mass flux of 0.5 kg m- 2 h- 1. The optimal operating conditions found in this study could save the total energy consumption by 26.3%

Operability considerations in chemical processes: A switchability analysis

A formulation for simultaneous operability and switchability is proposed, leading to an uncertain dynamic nonlinear programming problem that can be solved by two different approaches: sequential and simultaneous optimisations. Both techniques are used to test the effectiveness of the proposed strategy on the mini integrated plant. Some studies on the effect of scaling the state and control variables are carried out. Adding proper control strategies and number of degrees of freedom may speed up the switching time and reduce the integral square error. Due to possible disturbances entering the plant during the switch, closed-loop back-off from the nominal optimal trajectories should also be taken into consideraation. Different optimisation problems generated in this study are solved using the software package GAMS with MINOS 5.3 optimiser and numerical results are tested against the plant simulations using SPEEDUP flowsheeting package