To give students practical knowledge and understanding of various software packages to design chemical processes. The module is tutorial-based (computer lab), and will allow students to develop basic skills in (i) process flowsheeting and in the use of industry-standard computer packages for modelling/simulation of steady-state and non-steady-state chemical processing operations; (ii) the construction neural network models and use of artificial intelligence and data science in chemical engineering, (iii) the simulation of computational fluid dynamic (CFD) problems, (iv) the application of molecular modelling tools.

Flowsheet construction, analysis and evaluation: modular - and unit equation-based modes for flowsheet synthesis; rigorous unit equation models for flash, distillation, and heat exchange operations; recycle of process mass and energy streams; sensitivity analysis; convergence criteria. To use industry-standard computer packages for modelling/simulation of steady-state and non-steady-state chemical processing operations. Application to describe unit operation, in which separation can be understood by application of knowledge of phase equilibria (e.g. ideal distillation; azeotropic mixtures; distillation sequences). Develop predictive neural network models to solve chemical engineering problems. To build and use CFD models to simulate flow processes. To use molecular simulations (e.g. Monte Carlo, Grand Canonical Monte Carlo, Molecular Dynamics) to solve a few of the current problems in the field of chemical engineering, like material screening for targeted applications like H2 storage, natural gas storage, water purification, gas separations, catalysis, carbon capture.

On successful completion of this module, students should be able to: 1. Demonstrate competence in the application of quantitative design methods for non-reaction and reaction-containing unit operations. 2. Show proficiency in process flow sheeting and in the use of computational tools for steady-state and dynamic process simulation. 3. Apply skills in the field of neural network models, artificial intelligence, data science, and molecular modelling. 4. Show and apply pinch principles for energy management. Evaluate the cost benefit gained after the application of heat integration software. 5. Show sustainability assessment procedure in design practice. 6. Recognize the Relevance of software packages in Chemical Engineering: Students will acknowledge the practical relevance and versatility of tools in the context of process engineering, realizing their critical role in data analysis, modelling, and simulation for industry applications.

On successful completion of this module, students should be able to: 7. Demonstrate a willingness to work in groups and deliver group presentations. 8. Participate in class discussions regarding computational problem solving particularly in the context of process engineering, recognizing their significance in solving complex real-world problems. 9. Value a willingness to work independently and with initiative.

On successful completion of this module, students should be able to: 10. To draw and/or assemble process flowsheets, unit operations, molecular model systems (on the computer) 11. To perform a group presentation, and engage actively in question and answer session with fellow students.

The students will be taught in the computer lab, based on tutorials organized in the computer lab. The module will be assessed via a combination of individual and group work for different assignments, in which students will apply software packages to solve problems and case studies. There will be a continuous assessment and submission of assignment reports.