Mahdi Sharifzadeh

Technology performance and economic feasibility of bioethanol production from various waste papers

Producing bioethanol from various wastes is a promising strategy to meet part of the transport energy demand and also to contribute to waste management. Waste papers (newspaper, office paper, magazines and cardboard in this work) with their 50% to 70% carbohydrate content are potential raw materials for bioethanol production. From both technical and economic aspects, bioethanol production processes for various waste papers were evaluated in this study. High-solids loading (15% w/w) enzymatic hydrolyses using two enzyme alternatives (Celluclast 1.5 L supplemented with Novozyme 188 and Cellic Ctec 1) achieved glucan conversion efficiencies from waste papers of 50% to 76%. Base case process models developed using these experimental data were then applied to an economic analysis to determine the minimum ethanol selling price (MESP) for bioethanol derived from the waste papers using a discounted cash flow method. The effects of several processing parameters: alternative product recovery processes, enzyme loading, enzymatic hydrolysis residence time and two enzyme alternatives on the MESP are explored. Bioethanol produced from cardboard (using Cellic Ctec 1) resulted in the lowest MESP. Two state-of-the-art technologies, dilute acid pre-treatment on office paper and oxidative lime pre-treatment on newspaper, were also investigated. This study suggests that bioethanol production from waste papers is feasible and profitable from both technical and economic points of view.

Optimal selection of control structure using a steady-state inversely controlled process model

The profitability of chemical processes strongly depends on their control systems. The design of a control system involves selection of controlled and manipulated variables, known as control structure selection. Systematic generation and screening alternative control structures requires optimization. However, the size of such an optimization problem is much larger when candidate controllers and their parameters are included and it rapidly becomes intractable. This paper presents a novel optimization framework using the notion of perfect control, which disentangles the complexities of the controllers. This framework reduces the complexity of the problem while ensuring controllability. In addition, the optimization framework has a goal-driven multi-objective function and requires only a steady-state inverse process model. Since dynamic degrees of freedom do not appear in a steady-state analysis, engineering insights are employed for developing the inventory control systems. The proposed optimization framework was demonstrated in a case study of an industrial distillation train.

Integrated design and control using a dynamic inversely controlled process model

The profitability of chemical processes depends on their design and control. If the process design is fixed, there is little room left to improve control performance. Many commentators suggest design and control should be integrated. Nevertheless, the integrated problem is highly complex and intractable. This article proposes an optimization framework using a dynamic inversely controlled process model. The combinatorial complexities associated with the controllers are disentangled from the formulation, but the process and its control structure are still designed simultaneously. The new framework utilizes a multi-objective function to explore the trade-off between process and control objectives. The proposed optimization framework is demonstrated on a case study from the literature. Two parallel solving strategies are applied, and their implementations are explained. They are dynamic optimization based on (i) sequential integration and (ii) full discretization. The proposed integrated design and control optimization framework successfully captured the trade-off between control and process objectives.

Optimal controlled variable selection using a nonlinear simulation-optimization framework

Abstract In feedback control, controlled variables are those process variables which are measured and fed back to controllers. Then in the presence of disturbances, controllers by the means of manipulating the inputs aim to maintain the controlled variables at their setpoints. The objectives for the selection of controlled variables can be conflicting and competing. These objectives include minimization of (1) economic losses, (2) input manipulations, (3) output variations and (4) changes in process states. This research aims to present a systematic framework for optimal selection of controlled variables. Each of the above-mentioned objectives is defined within a multi-objective function. In addition, the reasoning behind the selection of nonlinear steady state model is explained. The proposed methodology is benchmarked on an industrial distillation train. Optimization programming is presented and the paper discusses how the size of the optimization problem can be reduced by means of engineering insights and addressing the concerns regarding feasibility of the developed control structure. The methodology is scalable to large industrial problems, while maintaining its rigour. The results confirm that a very good trade-off is established between different objectives.

Iterative peptide synthesis in membrane cascades: Untangling operational decisions

Abstract Membrane enhanced peptide synthesis (MEPS) combines liquid-phase synthesis with membrane filtration, avoiding time-consuming separation steps such as precipitation and drying. Although performing MEPS in a multi-stage cascade is advantageous over a single-stage configuration in terms of overall yield, this is offset by the complex combination of operational variables such as the diavolume and recycle ratio in each diafiltration process. This research aims to tackle this problem using dynamic process simulation. The results suggest that the two-stage membrane cascade improves the overall yield of MEPS significantly from 72.2% to 95.3%, although more washing is required to remove impurities as the second-stage membrane retains impurities together with the anchored peptide. This clearly indicates a link between process configuration and operation. While the case study is based on the comparison of single-stage and two-stage MEPS, the results are transferable to other biopolymers such as oligonucleotides, and more complex system configurations (e.g. three-stage MEPS).