Mauro A.S.S. Ravagnani

Automated heat exchanger network synthesis by using hybrid natural algorithms and parallel processing

Abstract Heat exchanger network (HEN) synthesis can be formulated as an optimization problem, which can be solved by meta-heuristics. These approaches account for a large computational time until convergence. In the present paper the potentialities of applying parallel processing techniques to a non-deterministic approach based on a hybridization between Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) were investigated. Six literature examples were used as benchmarks for the solutions obtained. Comparative experiments were carried out to investigate the time efficiency of the method while implemented using series or parallel processing. The solutions obtained led to lower Total Annual Costs (TAC) than those presented by the literature. As expected, parallel processing usage multiplied the algorithm speed by the number of cores used. Hence, it can be concluded that the proposed method is capable of finding excellent local optimal solutions, and the application of multiprocessing techniques represented a substantial reduction in execution time.

Multi-objective Heat Exchanger Networks Synthesis Considering Economic and Environmental Optimization

Abstract In the present paper it is presented a model for the synthesis of HEN considering both economic and environmental features. The model presents a multi-objective mixed-integer non-linear programming (MINLP) formulation. The optimization problem aims to find the optimal HEN considering the total cost as well as the environmental impact minimization. Environmental aspects are incorporated to the objective function by considering Life Cycle Assessment (LCA), using SIMAPRO software. ReCiPe methodology is used and 18 impact categories from midpoint to endpoint are evaluated. An algorithm based on Particle Swarm Optimization (PSO) was developed to solve the model and a superstructure that considers the number of stages as an optimization variable is proposed. A literature case was chosen to test the model applicability. Results are better than the previously published ones, even considering environmental impacts. Furthermore, not all impact metrics are in conflict with the cost function.

Modeling and optimization of an ammonia reactor using a penalty-like method

Abstract Ammonia is one of the most important chemicals produced in the world. Due to its broad applicability, modeling and simulation of process of ammonia has received considerable attention among the industrial processes. Ammonia is produced from the reaction of hydrogen and nitrogen at high temperature and high pressure along with a catalyst. Its production depends on temperature of feed gas at the top of the reactor, the partial pressures of the reactants and the reactor length. The optimal design problem requires obtaining the optimal reactor length with maximum economic return subject to a number of equality constraints involving solution of coupled nonlinear differential equations. A more efficient algorithm for the solution of optimization-constrained differential equations is proposed by coupling numerical techniques (barrier function with a direct search method) with Runge–Kutta method. The global convergence of the proposed algorithm is established under some usual conditions. Numerical results showed that the resulting algorithm, based only on function values, is highly competitive with other global optimization methods.

Heat Exchanger Network Synthesis using a Genetic Algorithms-Particle Swarm Optimization Hybrid Method and Parallel Processing

Abstract In Heat Exchanger Network (HEN) synthesis capital savings and pollutant emission reduction can be achieved. The mathematical modeling of the HEN synthesis problem requires elaborated solution strategies given the particularities of their non-linear formulations and non-convex problems. The use of heuristic approach accounts for a large computational load, and hence a high processing time until convergence. In the present paper a hybrid model for HEN synthesis using Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) is presented. The potentialities of applying parallel processing techniques to solve the problem were studied. Two examples from the literature were used as benchmarks for the solutions obtained. Comparative experiments were carried out to investigate the time efficiency of the method while implemented using series or parallel processing. The solutions obtained in both cases with the proposed methodology led to Total Annual Costs (TAC) equal or lower to those presented by the literature. As one could expect, parallel processing usage multiplied the algorithm speed by the number of cores used (processing time was close to 75% lower by using 4 processing cores). Hence, it can be concluded that the hybrid algorithm proposed has potential to find near-optimal solutions, and the application of multiprocessing techniques to such non-deterministic approaches represents a substantial reduction in the execution time.

Synthesis of Multicomponent Reuse Water Networks by PSO Approach

In the present paper the problem of reuse water networks (RWN) have been modeled and optimized by the application of a modified Particle Swarm Optimization (PSO) algorithm. A proposed modified PSO method lead with both discrete and continuous variables in Mixed Integer Non-Linear Programming (MINLP) formulation that represent the water allocation problems. Pinch Analysis concepts are used jointly with the improved PSO method. Two literature problems considering mono and multicomponent problems were solved with the developed systematic and results has shown excellent performance in the optimality of reuse water network synthesis based on the criterion of minimization of annual total cost.

Optimal Shell and Tube Heat Exchangers Design

Due to their resistant manufacturing features and design flexibility, shell and tube heat exchangers are the most used heat transfer equipment in industrial processes. They are also easy adaptable to operational conditions. In this way, the design of shell and tube heat exchangers is a very important subject in industrial processes. Nevertheless, some difficulties are found, especially in the shell-side design, because of the complex characteristics of heat transfer and pressure drop. Figure 1 shows an example of this kind of equipment. In designing shell and tube heat exchangers, to calculate the heat exchange area, some methods were proposed in the literature. Bell-Delaware is the most complete shell and tube heat exchanger design method. It is based on mechanical shell side details and presents more realistic and accurate results for the shell side film heat transfer coefficient and pressure drop. Figure 2 presents the method flow model, that considers different streams: leakages between tubes and baffles, bypass of the tube bundle without cross flow, leakages between shell and baffles, leakages due to more than one tube passes and the main stream, and tube bundle cross flow. These streams do not occur in so well defined regions, but interacts ones to others, needing a complex mathematical treatment to represent the real shell side flow. In the majority of published papers as well as in industrial applications, heat transfer coefficients are estimated, based, generally on literature tables. These values have always a large degree of uncertainty. So, more realistic values can be obtained if these coefficients are not estimated, but calculated during the design task. A few number of papers present shell and tube heat exchanger design including overall heat transfer coefficient calculations (Polley et al., 1990, Polley and Panjeh Shah, 1991, Jegede and Polley, 1992, and Panjeh Shah, 1992, Ravagnani, 1994, Ravagnani et al. (2003), Mizutani et al., 2003, Serna and Jimenez, 2004, Ravagnani and Caballero, 2007a, and Ravagnani et al., 2009). In this chapter, the work of Ravagnani (1994) will be used as a base to the design of the shell and tube heat exchangers. A systematic procedure was developed using the Bell-Delaware method. Overall and individual heat transfer coefficients are calculated based on a TEMA (TEMA, 1998) tube counting table, as proposed in Ravagnani et al. (2009), beginning with the smallest heat exchanger with the biggest number of tube passes, to use all the pressure drop

Optimization-based approach for maximizing profitability of bioethanol supply chain in Brazil

Abstract In this work, a mathematical approach for optimizing and planning the Brazilian bioethanol supply chains (SC) is presented. The optimization problem has an MILP formulation, aiming to maximize the net present value (NPV) of the entire SC of the sugar and bioethanol sector in Brazil. The model takes into account seven different production technologies, two types of warehouses, three types of transportation modes and seven exportation options, whose data were obtained from Brazilian industrial practices. The model aims to propose the optimal configuration of a bioethanol network, that is, the locations of the production and storage facilities, their capacity of expansion policy, the technology selected for manufacturing and materials storage and the flows of all feedstock and final products involved in the bioethanol SC in Brazil. A comparison between the current situation of Brazilian bioethanol SC and the optimal configuration achieved by the proposed model is also included.

Coevolutionary Genetic Algorithm to Solve Economic Dispatch

Two approaches based on genetic algorithms (GA) to solve economic dispatch (ED) problems are presented. The first approach is based on the hybrid genetic algorithm (HGA). Undesirable premature convergence to local minima can be avoided by means of the mutation operator, which is used to create diversity in the population by penalization or perturbation. Nevertheless, HGA needs to tune parameters before starting a run. A coevolutionary hybrid genetic algorithm (COEHGA) is proposed to improve the performance of the HGA.The COEHGA effectively eliminates the parameter tuning process because the parameters are adjusted while running the algorithm. A case from the literature is studied to demonstrate these approaches.

Redução da emissão de poluentes líquidos por reutilização de água em processos industriais

In this work a methodology to reduce pollutant emissions in industrial processes by water reuse is proposed. The pollutant emission reduction is achieved by the synthesis of mass exchange equipment (MEN). Pinch Analysis is used. The proposed methodology to the MEN synthesis initially sets the targets relative to the minimum global cost, the minimum number of mass exchange equipment and the minimum water flowrate. After the synthesis step, the MEN is evolved, by identifying and breaking mass exchange loops, without water flowrate changes. After the evolution step, an economical analysis is achieved. An industrial case published in the literature was used to show the efficiency of the proposed methodology. Results reflect the importance of economical analysis jointly with the MEN synthesis.