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Process Systems Engineering
CEN 501

Description
The aim of the course is to introduce students to basic principles of Chemical Engineering, with particular emphasis on designing unit operations and to the use of numerical analysis to solve problems via numerical methods. First, students will be introduced to the fundamental principles of mass and energy balance which are a prerequisite for the in-depth understanding and implementation of processes. The course will continue with the analysis of  basic principles of Chemical Engineering concerning fluid mechanics (Uncompressed flow in pipelines-Flow around submerged bodies, Transfer and measurement of fluids, Stirring and mixing of liquids) heat transfer (heat exchangers, evaporators, dryers, heat pumps), and the basic methods of separating various mixtures (gas-gas, gas-liquid, gas-solid, liquid-liquid, liquid-solid, solid-solid) and learn methods of designing basic units of separation processes and ways calculations of mass and energy balances (emphasis in fractional distillation, absorption, and solid fluidized beds). This part of the course is distinctive as the industry is dominated by the need for cooling or heating of fluids (e.g., transferring from the warehouse to the chemical reactor with simultaneous cooling/heating of the reactor) and the production of the desired product/ingredient in the chemical industry requires its separation from a mixture of different ingredients. The final part of the course aims to give students a deep understanding of the fundamental numerical methods and simulate them in MATLAB programming language. The most important ways a student will learn are through teaching using MS PowerPoint slides diagrams and interactive simulations, and by answering oral questions from students during lectures. As part of the assessment, students will need to prepare relevant assignment work that analyzes the theory and experimental practices used in research publications that address unit operations within the Chemical Engineering industry using computational means.  The use of computational and simulation tools, such as available tools available on the LearnChemE platform (https://learncheme.com/) will enhance the students’ educational experien

ECTS credits
8

Teaching Language
English

Exam Language
English

Support Materials Language
English

Basic Learning Outcomes
  • Analyse and evaluate alternatives on technical, environmental, economic and social criteria and develop the most sustainable solution, justifying the choice.
    (F3_BEEm8 - EEM - Analyse and evaluate alternatives on technical, environmental, economic and social criteria and develop the most sustainable solution, justifying the choice.)
  • Critically formulate conclusions on the applicability and sustainability of a research theme.
    (F19_BEEm65 - EEM - Critically formulate conclusions on the applicability and sustainability of a research theme.)
  • Ability to set and solve the microscopic and macroscopic balances of mass, energy and momentum (transport phenomena) using appropriate simplifying assumptions, and to theoretically predict the behaviour of environmental systems.
    (F1_BEEm2 - EEM - Ability to set and solve the microscopic and macroscopic balances of mass, energy and momentum (transport phenomena) using appropriate simplifying assumptions, and to theoretically predict the behaviour of environmental systems.)
  • Ability to develop, calibrate and validate process and system models of environmental relevance, both natural and artificial, and to use them to simulate and optimise their performance with computational and process modelling tools
    (F2_BEEm4 - EEM - Ability to develop, calibrate and validate process and system models of environmental relevance, both natural and artificial, and to use them to simulate and optimise their performance with computational and process modelling tools)
  • Ability to apply advanced statistical, uncertainty and decision-making techniques to large environmental data sets and to validate models against monitoring data.  
    (F2_BEEm6 - EEM - Ability to apply advanced statistical, uncertainty and decision-making techniques to large environmental data sets and to validate models against monitoring data.  )

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