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Eden, Mario R.

Publications and source records attributed to Eden, Mario R..

Computer–aided process intensification: Challenges, trends and opportunities

Chemicals based products and the processes that manufacture them play important roles in sustaining our society. Chemical, biochemical, petrochemical and related processes are characterized by either conversion of specific raw materials to desired chemicals or extraction of desired chemicals from specific raw materials. Well–known examples in the first category are the conversion of methanol and acetic acid to form methyl acetate and water, and, carbon dioxide hydrogenation to methanol via the reverse water gas shift reaction. In the second category, the use of de–methanizer, de–ethanizer, de–propanizer, and so on, separation steps in gas processing plants are well–known. In the conversion–based processes, as the conversions of raw materials are usually not 100% complete, energy intensive downstream separation techniques need to be employed to separate the desired products and recycle the unreacted raw materials. Note that the conversion process itself may also be energy intensive. In the extraction–based processes where product chemicals do not usually represent 100% of the raw material, energy intensive separation techniques are commonly employed to achieve the desired separations. This means that for both categories of processes, energy in different forms need to be supplied and the processes during operation have the potential to produce waste that may lead to negative environmental impacts and cause supply chain issues. Furthermore, planet earth is facing challenges with respect to energy, water, food, and environment, and significant improvements in process efficiencies of new and/or existing processes are needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systematic Method and Tool for Sustainable Process Synthesis, Designanalysis and Innovation

Computer-aided tools have been successfully developed and used in different segments of the entire process development cycle. For example, there are established tools for chemical process design, simulation, heat exchanger network synthesis and many more. However, one needs an integrated platform to perform process synthesis, design and analysis of chemical processes in a systematic manner. Also, in order to obtain a truly innovative and sustainable solution, it is necessary to search the entire feasible search space of alternatives and select the best process alternative, which is not very easy and will be time consuming. Therefore, it is beneficial to utilize computer-aided methods and tools to enumerate, analyze and determine within the design space, the more sustainable processes. This work highlights the development of a computer aided methodology and corresponding integrated platform for fast, reliable and consistent generation of process flowsheets. As a result, this paper gives an overview of the key concepts and the method is presented along with details of the developed computer-aided tool.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ProCAFD: Computer-aided Tool for Sustainable Process Synthesis, Intensification and Hybrid solutions

Process industry is always in quest for innovative designs which are both efficient, safe and sustainable. The feasible search space of all unit operations that can be combined to generate process flowsheet alternatives for a given synthesis problem can be large and difficult to manually navigate in order to determine the best processing route. Therefore, it is helpful to utilize computer-aided methods and tools to enumerate, analyze and determine within the design space, the more sustainable processes. In this study, an integrated computer-aided method and corresponding software-tool that’s capable of generating and searching the entire design space for more sustainable process options is presented. In this work a comprehensive analysis method consisting of economic, life cycle, sustainability and process safety indicators is used to identify process bottlenecks on the selected alternative which are translated to design targets. Matching of these design targets minimizes/eliminates the process hot-spots and, thereby generating non-trade-off innovative process designs.

97 MATHEMATICS AND COMPUTING↗

Component based development of computer-aided tools for different applications

Computer-aided methods and tools are used at different stages of chemical process development. However new tools are needed to meet the current and future challenges through innovative and more sustainable solutions that the currently available tools may not be able to provide. This work focuses on component-based software architecture for development of tailor-made computer-aided tools for specific application objectives. The architecture is based on “components”, which can be model-objects that are stored in a library; collection of property models; databases; numerical solvers; design-algorithms (work-flows) etc. Furthermore, the main idea of these components is to incorporate a plug & play framework, where for a specific purpose, after the work-flow and associated data-flow are established, a specific computer-aided tool can be configured through a library of software components. Also, through the use of software components that are based on predictive model-based solution techniques, the final software can be reliably used to provide innovative and more sustainable solutions over a wide range of problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient Surrogate Model Development: Impact of Sample Size and Underlying Model Dimensions

This study compares eight surrogate-model construction approaches using computational experiments. Here, the construction approaches considered include: Artificial Neural Networks (ANNs), Automated Learning of Algebraic Models using Optimization (ALAMO), Radial Basis Networks (RBNs), Extreme Learning Machines (ELMs), Gaussian Progress Regression (GPR), Random Forests (RFs), Support Vector Regression (SVR), and Multivariate Adaptive Regression Splines. Each approach is used to construct surrogate models for predicting the outputs of thirty-four test functions. The data used to construct surrogate models were generated using Latin Hypercube Sampling (LHS), Halton and Sobol sampling methods. We studied the impact of sampling method, sample size, and challenge function characteristics on the accuracy of surrogate model predictions. Our results revealed that for smaller sample sizes, on average, surrogate models trained using the data points generated by Sobol sequences provided the best estimation for all surrogate model construction approaches. As the sample size increased, the impact of sampling methods diminished. The comparison of surrogate-modeling construction approaches at large sample sizes revealed that surrogate models trained using ANN, ALAMO, and ELM yielded smaller root mean squared error and higher adjusted R-squared values than the models trained using the rest of the approaches.

42 ENGINEERING↗

Foreward

This special issue of Computers & Chemical Engineering contains extended versions of selected contributions from the 8th International Conference on the Foundations of Computer-Aided Process Design (FOCAPD-2014), held at the Suncadia Resort in Cle Elum, Washington, USA, July 13–17, 2014. These papers were recommended by the International Programming Committee and constitute a representative sample of the invited plenary lectures,future perspectives, and contributed papers.

99 GENERAL AND MISCELLANEOUS↗