Optimization and CFD modeling of an improved rustic oven for producing bricks

Clean Technologies and Environmental Policy - This paper presents an optimization formulation and a computational fluid dynamic study for a new proposal of a rustic oven that uses natural gas...     

Incorporation of process integration into life cycle analysis for the production of biofuels

This article presents a new approach for incorporating process-integration tools into life cycle analysis (LCA) for biofuel production. Process synthesis techniques using mass- and energy-integration tools are employed to generate various scenarios for reducing mass and energy consumption in the process. The global implications of these changes and the associated trade-offs are assessed using the LCA tool: GREET. The developed approach enables the consideration of several levels of process integration while tracking the process economics and the reduction of the net greenhouse gas emissions. Several cases of biofuels with different processing technologies have been considered in this study, and the results show that when the process-integration tools are effectively utilized and combined with LCA, better insights are obtained and the net greenhouse gas emissions decrease drastically for different biofuels.     

Multi-objective optimization of steam power plants for sustainable generation of electricity

A unified framework that combines process simulation and multi-objective optimization is presented to simultaneously maximize the annual profit, while minimizing environmental impact (i.e., greenhouse gas emissions) of steam power plants with fixed flowsheet structures. The proposed methodology includes the selection of suitable primary energy sources (i.e., fossil fuels, biomass, biofuels, and solar energy) for sustainable electricity generation. For solving the problem of optimal selection of energy sources, a linear model is developed and included within a highly nonlinear simulation model for the parameter optimization of steam power plants that is solved by using genetic algorithms. This approach is robust and avoids making discrete decisions. Life cycle assessment technique is used to quantify the greenhouse gas emissions resulting from different combinations of energy sources and operating conditions of the power plants. The thermodynamic properties for liquid water and steam are calculated rigorously using the IAPWS-IF 97 formulation. An example problem of an advanced regenerative-reheat steam power plant is presented to illustrate the proposed method, which provides the Pareto optimal solutions, the types and amounts of primary energy sources as well as the optimal values of the operating conditions of the plant that simultaneously maximize the profit while minimizing environmental impact.     

Multi-objective optimization of process cogeneration systems with economic, environmental, and social tradeoffs

Process cogeneration is an effective strategy for exploiting the positive aspects of combined heat and power in the process industry. Traditionally, decisions for process cogeneration have been based mostly on economic criteria. With the growing interest in sustainability issues, there is need to consider economic, environmental, and social aspects of cogeneration. The objective of this article is to develop an optimization framework for the design of process cogeneration systems with economic, environmental, and social aspects. Process integration is used as the coordinating framework for the optimization formulation. First, heat integration is carried out to identify the heating utility requirements. Then, a multi-header steam system is designed and optimized for inlet steam characteristics and their impact on power, fixed and operating costs, greenhouse gas emissions, and jobs. A genetic algorithm is developed to solve the optimization problem. Multi-objective tradeoffs between the economic, environmental, and social aspects are studied through Pareto tradeoffs. A case study is solved to illustrate the applicability of the proposed procedure.     

Optimal synthesis of heat exchanger networks involving isothermal process streams

This paper proposes a new MINLP model for heat exchanger network synthesis that includes streams with phase change. The model considers every possible combination of process streams that may arise within a chemical process: streams with sensible heat, streams with latent heat, and streams with both latent and sensible heat. As part of the optimization strategy, the superstructure is modeled with logical conditions that are used for the proper placement of heat integration for streams with change of phase. The proposed MINLP model provides the network structure that minimizes the total yearly cost. Several examples are presented to illustrate the capabilities of the proposed model.     

A global optimal formulation for the water integration in eco-industrial parks considering multiple pollutants

A mathematical programming formulation for the water integration in eco-industrial parks considering streams with several pollutants is presented. The formulation is based on a superstructure that allows the wastewater reuse in the same plant, the water exchange with different plants, and a shared set of interceptors that must be selected to determine the network configuration that satisfies process equipments and environmental constraints. The model formulation considers wastewater with several pollutants, and optimizes the network according to the minimum total annual cost, which includes the costs of fresh water, piping and regeneration. A new discretization approach is also proposed to handle the large set of bilinear terms that appear in the model in order to yield a near global optimal solution. The results obtained in several examples show considerable savings with respect to the solutions of the individual plant integration policy commonly employed for these types of problems.     

MINLP optimization of mechanical draft counter flow wet-cooling towers

In this paper, the problem of the optimal design of mechanical draft counter flow cooling towers that meets a set of specified constraints is formulated as a mixed-integer nonlinear programming (MINLP) problem. The Merkel's method is used to specify the characteristic dimensions of cooling towers, together with empirical correlations for the loss and overall mass transfer coefficients in the packing region of the tower. Water-to-air mass ratio, water mass flow rate, water inlet and outlet temperatures, operational temperature approach, type of packing, type of draft, height and area of the tower packing, total pressure drop of air flow, power consumption of the fan, and water consumption provide the set of optimization variables. The MINLP problem is formulated so as to minimize the total annual cost of the cooling tower. The performance of the proposed procedure is shown with the solution of six examples.     

Global optimization of mass and property integration networks with in-plant property interceptors

This paper presents a mathematical programming model for the optimal design of mass and property integration networks that include property interceptors within the structure of the network, as opposed to the end-of-pipe use of such interceptors. The model is based on a recycle and reuse scheme that simultaneously satisfies process and environmental constraints. The properties considered in this work are composition, toxicity, theoretical oxygen demand, pH, density and viscosity. The property mixing rules included in the model give rise to bilinear terms for the property operators, and a global optimization algorithm is used for the solution of the model. The model minimizes the total annual cost of the network, which includes the fresh sources cost and the annualized property treatment system and the piping costs. Three examples are included to show the applicability and advantages of the proposed model.