Eftychia C. Marcoulaki

On the development of novel chemicals using a systematic optimisation approach. Part II. Solvent design

Abstract A new approach is presented for the optimal selection of solvents. The approach is using group contribution methods and a vector representation to formulate an optimisation problem with respect to desired properties for the solvent. The formulation can employ conceptual flowcharts or detailed flowsheets. The synthesis objectives are expressed either as a function of the solvent properties or alternatively as functions of design parameters and variables of the flowsheet. The optimisation is facilitated with a stochastic tool in the form of simulated annealing. The examples address literature problems and industrial case studies involving the design of separation enhancing materials. Applications are presented for liquid–liquid extraction processes, extractive distillation problems, retrofit designs and gas absorption processes.

On the development of novel chemicals using a systematic synthesis approach. Part I. Optimisation framework

This paper presents a computer-aided technology for the synthesis of molecules with optimal properties. The approach combines stochastic optimisation and group-contribution methods to search and select chemicals of desirable performance. The stochastic search is in the form of a simulated annealing algorithm. For the application of the annealing algorithm the molecular system is mapped in terms of problem states. A set of moves is applied to generate alternatives and monitor the synthesis search. Molecules are represented by molecular and composition vectors of UNIFAC groups, but most appropriate group-contribution methods are also considered. Size and composition of the molecular vector are optimised on the basis of the selected synthesis criteria without limitations on the type of calculations required. The application of the approach is illustrated with three synthesis examples.

Molecular design synthesis using stochastic optimisation as a tool for scoping and screening

This paper presents optimisation technology for the computer-aided design of molecules. A new approach is presented that combines stochastic optimisation and group-contribution methods to select chemicals with optimised properties. Each molecule is represented as a set of functional groups. The search follows an iterative procedure, where new molecules are generated, evaluated and subjected to acceptance. The evaluation stage calls upon calculation of molecular properties using available group-contribution expressions and databases. The proposed methodology is illustrated with literature examples involving the design of refrigerants and liquid-liquid extraction solvents. The efficiency of the search and the thermodynamic models employed are validated through process simulation studies. The work reports novel molecular structures and significant improvements over conventional techniques.

Novel chemicals for clean and efficient processes using stochastic optimization

Abstract This paper presents a computer-aided technology for the synthesis of environmentally bengign materials with optimal properties. The approach combines stochastic optimization and group contribution methods. Stochastic optimization is in the form of the Simulated Annealing algorithm and is used to search and select chemicals of desired performance. The paper discusses the representation schemes and the synthesis algorithm developed for molecular design. The proposed synthesis technology is extended to problems related to environmental concern and the applications include examples of solvent design. In these studies, the requirements for advanced performance address separation-enhancing alongside with environmental behavior.

Restructuring the Keywords Interface to Enhance CAPE Knowledge Acquisition via an Intelligent Agent

Abstract This work proposes an improved KeyWord Interface (KWI) to enhance the efficiency of information retrieval when using an advanced search engine, as an intelligent agent. This can be achieved by restructuring the KWI into a new hierarchical structure based on an { n domains} by {3 levels} arrangement of keywords ( n ×3 KWI), forming a loose/adaptive semantic network. The hierarchical levels used in the suggested implementation are set of species, logical category , and holistic entity . As an illustration, the method is applied to an example of literature survey concerning a well-documented process engineering field. The results of the proposed technology are compared with the outcome of general-purpose search-engines built in common academic publication databases. The comparison reveals the advantage of intelligent searching in creating a local base according to the orders/interests of the researcher.

Stochastic optimisation of complex reaction systems

This work presents a new synthesis approach for the design of chemical reactors. The proposed method is based upon a general system representation which assumes the form of a superstructure network with different types of reactors and interconnections among the units. The superstructure provides the domain of a stochastic optimisation search which is achieved using Simulated Annealing. The search is based upon the successive generation and evaluation of reactor configurations in which changes of stream locations, unit sizes and operating conditions are addressed within a statistical cooling schedule. The application of the annealing algorithm enables uphill and downhill moves and represents a reliable optimisation procedure to bypass local extrema and limitations arising from nonconvexities and multiplicities which regularly appear in complex reaction processes.

Design of Separation Trains and Reaction-Separation Networks Using Stochastic Optimization Methods

The paper presents a vector representation for simulated annealing problems in separation. The approach enables the use of rigorous models in the optimization. The representation accounts for the development of moves with ease and efficiency. The vector co-ordinates the perturbations and the evolution of states, and is combined with operational moves with adjustable controls. The representation applies to separation related problems and the paper illustrates applications in separation sequencing and reaction-separation systems.

A dynamic screening algorithm for multiple objective simulated annealing optimization

Abstract This work proposes new multiple objective optimization (MOO) technology, using a Monte Carlo-based algorithm stemmed from simulated annealing (SA). Since the expected result in MOO tasks is usually a set of Pareto-optimal solutions, the optimization problem states assumed here are themselves sets of solutions. The stochastic search follows a series of reversible state transitions at constant probability, to enjoy convergence properties of stationary Markov processes. The proposed technology is tested against the optimal design of a process system involving equipment placed in a serial/parallel arrangement, with three optimization objectives: the system cost, reliability and weight.

Dynamic failure assessment of incidents reported in the Greek Petrochemical Industry

Abstract This paper presents a Bayesian statistical analysis on real incident data collected from the Greek Petrochemical Industry for a period of 6 years (1997–2003). The analysis provides an assessment of the database to support predictions of dynamically updated incident occurrence frequencies. Results are reported for two different categories of incidents, namely the industrial and the occupational ones.

The impact of collaborative forecasting in the supply chain management of high technology products

Abstract This paper considers the advantages and potential of collaborative forecasting and its impact on supply chain management. The collaboration process brings together information and data resources from various departments of the company and outputs a single integrated forecast. The increased accuracy of this forecast yields benefits to all the aspects of the supply chain, starting from the product procurement and production up to the customer service. The process application is demonstrated using the paradigm of a company that produces and sells high technology products. In this case, the forecasting can not rely entirely on historical data, which may be unavailable or out of date. The results from the adoption of collaborative forecasting show improvement in the inventory, the operational costs, the profits, the product availability and the customer service.