Studies on pore blocking mechanism and technical feasibility of a hybrid PAC-MF process for reclamation of irrigation water from biotreated POME

An integrated low-cost adsorption (with powdered activated carbon, PAC) and cross-flow membrane filtration (with microfiltration membranes of 0.1 and 0.2 μm pore sizes) process was employed for the treatment of biotreated palm oil mill effluent (POME) to produce irrigation water that is fully benchmarked with water-quality standards. The permeate quality was within the recommended standard for irrigation water, as the concentrations of all critical constituents were well below their recommended values. Sustainability of the process integration was further confirmed with the domination of cake filtration over other blocking mechanisms with higher R² values at all trans-membrane pressures. Suitable extended usage of permeate was found for toilet/urinal flushing.     

Usage of inherent storage for minimisation of wastewater in multipurpose batch plants

Wastewater minimisation in batch plants is gaining importance due to intensifying environmental legislation and the gradual reduction in the number of freshwater sources. Intrinsic in the minimisation of wastewater in batch plants is the reuse of wastewater through intermediate storage vessels. However, the intermediate storage vessels take up unnecessary space which is undesirable in processes which are generally undertaken in limited spaces. Furthermore, in any batch process there are processing units that are not used extensively in the time horizon. In other words, these units remain idle for the major part of the time horizon, amounting to wasted return on capital investment. The idle processing units can be used as storage vessels, since any processing unit is, in essence, a storage vessel. In doing this one can reduce the size of the central storage and increase the utilisation of capital intensive processing units. The methodology presented in this paper deals with the minimisation of single contaminant wastewater by exploiting the inherent storage possibilities in idle processing units. The methodology is applied to two cases. In the first case the objective is to minimise the amount of effluent and the size of the central storage vessel through the usage of inherent storage, as commonly encountered in grassroot design. In the second case the objective is to determine the minimum wastewater target through the usage of both inherent storage and fixed central storage, as encountered in retrofit design.     

Wastewater minimization in multipurpose batch plants with a regeneration unit: Multiple contaminants

Wastewater minimization can be achieved by employing water reuse opportunities. This paper presents a methodology to address the problem of wastewater minimization by extending the concept of water reuse to include a wastewater regenerator. The regenerator purifies wastewater to such a quality that it can be reused in other operations. This further increases water reuse opportunities in the plant, thereby significantly reducing freshwater demand and effluent generation. The mathematical model determines the optimum batch production schedule that achieves the minimum wastewater generation within the same framework. The model was applied to two case studies involving multiple contaminants and wastewater reductions of 19.2% and 26% were achieved.     

A robust mathematical formulation for multipurpose batch plants

Several scheduling techniques exist in literature based on continuous time representation. The models based on unit specific time points have shown better solution efficiency by reducing the number of time points and problem size. In this paper novel scheduling techniques based on unit specific time point continuous time representation are presented. The proposed models allow nonsimultaneous material transfer into a unit. Nonsimultaneous transfer refers to when a task requires more than one intermediate state it is possible for one state to be transferred and stored in a unit that is processing it for a while and wait for the other intermediates to come together to start the task. This approach gives a better schedule as compared to most published models. The developed MILP scheduling models are based on state sequence network representation that has proven to inherently result in smaller problems in terms of binary variables. The models require a smaller number of time points as compared to single-grid and multi-grid continuous time models. Consequently, they exhibit much better computational performance. Numerical evaluation using literature examples indicate in some of the complex examples that the proposed models give a better objective value as compared to other scheduling models. An added feature of the proposed models is their ability to exactly handle fixed intermediate storage operational philosophy, which has proven to be a subtle drawback in most published scheduling techniques.     

Flexible mass transfer model for water minimization in batch plants

This paper presents the least constrained mass transfer mathematical formulation for freshwater minimization in multipurpose batch chemical processes with central reusable water storage. The mathematical formulation is an extension of the model developed by Majozi [T. Majozi, Wastewater minimization using central reusable water storage in batch processes, Computers and Chemical Engineering Journal 29 (7) (2005) 1631–1646]. In the latter model four scenarios were considered with various limitations or constraints. In the scenario presented in this paper only the mass load is fixed, whilst both the quantity of water used in a particular operation and outlet concentration are allowed to vary. In essence, fixing the mass load is more representative of the practical case. A solution procedure for the resultant nonconvex mixed integer nonlinear programming (MINLP) model is also presented. The solution procedure first involves reformulating the MINLP into a relaxed linear model (MILP). The MILP is first solved, the solution of which forms a feasible starting solution for the MINLP. Presented are two illustrative examples.     

A novel technique for prediction of time points for scheduling of multipurpose batch plants

This paper presents a mathematical technique for prediction of the optimal number of time points in short-term scheduling of multipurpose batch plants. The mathematical formulation is based on state sequence network (SSN) representation. The developed method is based on the principle that the optimal number of time points depends on how frequent the critical unit is used throughout the time horizon. In the context of this work, a critical unit refers to a unit that is most frequently used and it is active for most of the time points when it is compared to other units. A linear model is used to predict how many times the critical unit is used. In conjunction with knowledge of recipe, this information is used to determine the optimal number of time points. The statistical R² value obtained between the predicted and actual number of optimal time points in all the problems considered was 0.998, which suggests that the developed method is accurate in determining optimal number of time points. Consequently this avoids costly computational times due to iterations. In the model by Majozi and Zhu (2001) the sequence constraint that pertains to tasks that consume and produce the same state, the starting time of the consuming task at time point p must be later than the finishing time of the producing task at the previous time point p?1. This constraint is relaxed by the proposed models if the state is not used at the current time point p. This relaxation gives a better objective value as compared to previous models. An added feature of the proposed models is their ability to exactly handle fixed intermediate storage (FIS) operational philosophy, which has proven to be a subtle drawback in published scheduling techniques.     

Optimum heat storage design for heat integrated multipurpose batch plants

Heat integration to minimise energy usage in multipurpose batch plants has been in published literature for more than two decades. In most present methods, time is fixed a priori through a known schedule, which leads to suboptimal results. The method presented in this paper treats time as a variable, thereby leading to improved results. Both direct and indirect heat integration are considered together with optimisation of heat storage size and initial temperature of heat storage medium. The resulting model exhibits MINLP structure, which implies that global optimality cannot generally be guaranteed. However, a procedure is presented that seeks to find a globally optimal solution, even for nonlinear problems. Heat losses from the heat storage vessel during idling are also considered. This work is an extension of MILP model of Majozi (2009), which was more suited to multiproduct rather than multipurpose batch facilities. Optimising the size of the heat storage vessel as well as the initial temperature of the heat storage fluid decreased the requirement for external hot utility for an industrial case study by 33% compared to using known parameters.     

Simultaneous targeting and design for cooling water systems with multiple cooling water supplies

This paper presents a technique for simultaneous targeting and design in cooling water systems comprising of at least two cooling towers and several cooling water using operations. The presented technique is based on a superstructure from which a mathematical formulation is derived using system specific variables and parameters. It is demonstrated that in a system like this, true optimality can only be realized by a holistic consideration of the entire cooling water system. Consideration of individual subsets of cooling towers with their dedicated cooling water operations yields suboptimal results. Four operational cases are considered and structural considerations of corresponding mathematical formulations presented. The first case results in a linear programming (LP) formulation, the second case yields a mixed integer linear programming (MILP) formulation whilst the other two cases yield mixed integer nonlinear programming (MINLP) formulations which cannot be exactly linearized. However, in all cases significant improvements in excess of 40% were realized in targeting, without compromising the heat duty of the cooling water using operations. The main objective of this investigation is to debottleneck the overall cooling water supply for the cooling water network.