Rigorous Design of Complex Distillation Columns Using Process Simulators and the Particle Swarm Optimization Algorithm

We present a derivative-free optimization algorithm coupled with a chemical process simulator for the optimal design of individual and complex distillation processes using a rigorous tray-by-tray model. The proposed approach serves as an alternative tool to the various models based on nonlinear programming (NLP) or mixed-integer nonlinear programming (MINLP) . This is accomplished by combining the advantages of using a commercial process simulator (Aspen Hysys), including especially suited numerical methods developed for the convergence of distillation columns, with the benefits of the particle swarm optimization (PSO) metaheuristic algorithm, which does not require gradient information and has the ability to escape from local optima. Our method inherits the superstructure developed in Yeomans, H.; Grossmann, I. E.Optimal design of complex distillation columns using rigorous tray-by-tray disjunctive programming models. Ind. Eng. Chem. Res.2000, 39 (11), 4326–4335, in which the nonexisting trays are considered as simple bypasses of liquid and vapor flows. The implemented tool provides the optimal configuration of distillation column systems, which includes continuous and discrete variables, through the minimization of the total annual cost (TAC). The robustness and flexibility of the method is proven through the successful design and synthesis of three distillation systems of increasing complexity.

Design of composites for thermal management: Aluminum reinforced with diamond-containing bimodal particle mixtures

A new design route is proposed in order to fabricate aluminum matrix diamond-containing composite materials with optimized values of thermal conductivity (TC) for thermal management applications. The proper size ratio and proportions of particulate diamond–diamond and diamond–SiC bimodal mixtures are selected based on calculations with predictive schemes, which combine two main issues: (i) the volume fraction of the packed particulate mixtures, and (ii) the influence of different types of particulates (with intrinsically different metal/reinforcement interfacial thermal conductances) on the overall thermal conductivity of the composite material. The calculated results are validated by comparison with measurements on composites fabricated by gas pressure infiltration of aluminum into preforms of selected compositions of particle mixtures. Despite the relatively low quality (low price) of the diamond particles used in this work, outstanding values of TC are encountered: a maximum of 770 W/m K for Al/diamond–diamond and values up to 690 W/m K for Al/diamond–SiC.