The role of Computer Aided Process Engineering in physiology and clinical medicine

This paper discusses the potential role for Computer Aided Process Engineering (CAPE) in developing engineering analysis and design approaches to biological systems across multiple levels—cell signalling networks, gene, protein and metabolic networks, cellular systems, through to physiological systems. The 21st Century challenge in the Life Sciences is to bring together widely dispersed models and knowledge in order to enable a system-wide understanding of these complex systems. This systems level understanding should have broad clinical benefits. Computer Aided Process Engineering can bring systems approaches to (i) improving understanding of these complex chemical and physical (particularly molecular transport in complex flow regimes) interactions at multiple scales in living systems, (ii) analysis of these models to help to identify critical missing information and to explore the consequences on major output variables resulting from disturbances to the system, and (iii) ‘design’ potential interventions in in vivo systems which can have significant beneficial, or potentially harmful, effects which need to be understood. This paper develops these three themes drawing on recent projects at UCL. The first project has modeled the effects of blood flow on endothelial cells lining arteries, taking into account cell shape change resulting in changes in the cell skeleton which cause consequent chemical changes. A second is a project which is building an in silico model of the human liver, tieing together models from the molecular level to the liver. The composite model models glucose regulation in the liver and associated organs. Both projects involve molecular transport, chemical reactions, and complex multiscale systems, tackled by approaches from CAPE. Chemical Engineers solve multiple scale problems in manufacturing processes – from molecular scale through unit operations scale to plant-wide and enterprise wide systems – so have an appropriate skill set for tackling problems in physiology and clinical medicine, in collaboration with life and clinical scientists

Smart process manufacturing for formulated products

We outline the smart manufacturing challenges for formulated products, which are typically multicomponent, structured, and multiphase. These challenges predominate in the food, pharmaceuticals, agricultural and specialty chemicals, energy storage and energetic materials, and consumer goods industries, and are driven by fast-changing customer demand and, in some cases, a tight regulatory framework. This paper discusses progress in smart manufacturing—namely, digitalization and the use of large datasets with predictive models and solution-finding algorithms—in these industries. While some progress has been achieved, there is a strong need for more demonstration of model-based tools on realistic problems in order to demonstrate their benefits and highlight any systemic weaknesses

Water desalination by capacitive electrodialysis: Experiments and modelling

Electrodialysis-related technologies keep spreading in multiple fields, among which water desalination still plays a major role. A new technology that has not yet been thoroughly investigated is capacitive electrodialysis (CED), which couples the standard ED with capacitive electrodes. CED has a number of advantages such as removal of toxic products and system simplification. Little mention is made of this technology in the literature and, to the best of our knowledge, no modelling works have ever been presented. In this work, the CED process has been studied through experiments and modelling. A CED model is presented for the first time. With a simple calibration based on macroscopic membrane properties and the characterisation of electrode behaviour, the model is able to simulate the dynamics of simple as well as more complex layouts. An original experimental characterisation of electrodes is presented, showing how the collected data can be implemented into the model. After a successful validation with experimental data, dynamic simulations of a single pass CED unit have been performed with the aim of assessing the effect of different capacitive electrode properties on process performance. Results show how the impact of these properties is different depending on the number of cell pairs

Comparison of a reduced order model for packed separation processes and a rigorous nonequilibrium stage model

The large dimensionality of the system of algebraic (and differential) equations of the models for packed distillation columns makes their solution difficult to be achieved. Aiming the solution of this problem, a reduced order model was developed for steady state packed separation processes. The model was developed transforming the differential equations of the rigorous model into algebraic equations through the use of the orthogonal collocation technique. The heat and mass transfer rates through the vapor-liquid interface were rigorously computed. The performance of this reduced order model was assessed comparing its results with those obtained with a rigorous rate based model. The results of the reduced order model were in good agreement with those from the rigorous model. Furthermore, the solution of the new model was the easiest to be obtained due to the robustness of the reduced order model