ChEn-3170 Computational Methods in Chemical Engineering

University of Massachusetts Lowell, Fall 2018  
Prof. Valmor F. de Almeida ([email protected])

The goal of this course is to present to students of 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 reactor engineering and separations with applications in nuclear and biochemical engineering.

This three-credit lecture course (and one additional contact hour) over fourteen weeks, consists of Jupyter notebooks used for lectures (numbered 01 to XX) and laboratory work (labwork-01 to XX) for students to practice their skills in computer-aided problem solving (see notebooks/). The assumption is that students have very little computer pragramming experience and have not taken any of the core courses in chemical engineering. 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.

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 is clicked on. This will not allow for rendering mathematical formulae. Alternatively you can render the notebooks on NBViewer by clicking on the render|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 download button above on the right upper side of the page and download a ZIP archive to your local machine. Unzip the archive. Then use your own Jupyter Notebook server to navigate to the directory created by the unzip operation and upload the notebook files. In this case the files will not be updated and you will need to return to the repository for getting new files or updated versions of previously downloaded files.

Thanks in advance for inputs to improve this course.
Regards,
Valmor.