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ChEn-3170 Computational Methods in Chemical Engineering

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The goal of this course is to present to students of (nuclear) chemical engineering an interconnected set of computational methods needed in the core undergraduate chemical engineering curriculum. In particular, methods that assist the students in solving problems in the core areas of chemical reaction equilibria, separations, unit operations, and chemical reactor engineering with applications in nuclear and biochemical engineering.

This three-credit lecture course (and one additional contact hour) over fifteen weeks, consists of Jupyter notebooks used for lectures (numbered 01 to 21) and laboratory work (labwork-01 to 14) for students to practice their skills in computer-aided problem solving (see notebooks/). The assumption is that students have little computer pragramming experience and are currently taking the core courses in chemical engineering up to the second semester of the junior year. Therefore this course is a mix of computational methods and computer programming (in python language) aimed at helping students in the remaining portion of their curriculum course work.

Past versions of this course are available in this repository as releases including labwork and exams.

Feedback and collaboration to improve this course are welcome through GitHub pull requests and issues or direct email.

This course uses Jupyter Notebooks in Python programming language. The content can be accessed in the following ways:

  • Static HTML version of the notebooks will be displayed on the current browser if a notebook file listed in the code repository, notebook/ is clicked on. This will not allow for rendering mathematical formulae. Alternatively you can render the notebooks on NBViewer by clicking on the NBViewer badge above.
  • Click on the launch/binder badge above to launch a Jupyter Notebook server for the course notebooks. There will be a delay for the Binder cloud server to build a Python (Anaconda) programming environment for you. However once it is done, it will start a Jupyter Notebook server on your web browser with all notebooks listed. Upon clicking on individual notebook files, you will access the live course notebooks.
  • Use the green Code button above on the right upper side of the page and either download the repository using GitHub Desktop or download a ZIP archive to your local machine. Unzip the archive. Then use your own Jupyter Notebook server (see Syllabus or Introduction notebooks on how to install Anaconda) to navigate to the directory created by the unzip or GitHub Desktop operation and upload the notebook files. In the case of a ZIP download, the files will not be updated on your local machine and you will need to return to the repository for getting new files or updated versions of previously downloaded files as the course progresses. If you use GitHub Desktop, the repository will be in sync.

Thanks in advance for inputs to improve this course.
Regards,
Prof. Valmor F. de Almeida