Computing and data science skills are without doubt extremely valuable for modern (chemical) engineers. Big data, machine learning, predictive modeling, decision science and similar terms are ever-present in job posting, scientific literature, funding announcements, and popular news. Yet, many chemical engineers lack a background in the fundamentals of computer programming, applied statistics, and mathematical modeling for problem solving. Often, student excitement in data-centric topics manifest through self-study with tutorials, extracurricular projects, and online classes whereby students assemble a toolbox of skills but do not learn the fundamentals that transcend each technique.

In this contribution, I will discuss our ongoing efforts at the University of Notre Dame to create a coherent, integrated strategy for computing and data analysis in the undergraduate curriculum. A key focus is retooling the sophomore-level “Numerical and Statistical Analysis” course (required) to provi... [more]

In this talk, I give an overview of the chemical engineering curriculum at McMaster University as it relates to the 1.5 year process design sequence. The courses outside the design sequence were recently restructured and redesigned to create an environment with more modelling and algorithmic thinking/algorithmic problem solving. This includes a statistics course and a big data / machine learning course. The end result is that the design sequence is able to focus on state of the art tools and methods for process design because students receive many fundamental principles before the design sequence begins.

In order to support the development of early career researchers involved in chemical and biological process/systems engineering, Processes launched the second Travel Awards for Post-doctoral Fellows and Ph. [...]

This paper describes the progress of our efforts to lead the CACHE (Computer Aids for Chemical Engineering Education) Task Force in transforming from chemical process design toward chemical product design. Through CACHE, we are coordinating the development of a library of product-design case studies. Beginning with preliminary product designs created previously over several semesters, we are arranging for faculty experts, knowledgeable in the underlying technology platforms, to work with student groups to enrich the product designs. Over a 3-year period, a collection of approximately 25 case studies is being prepared. This article describes the research envisioned as innovative product designs are created, both egarding applications of new technologies, and product design evolution/evaluation; and in advancing strategies for teaching product design. The anticipated use of these case studies in departments worldwide for design courses taught by similar technology experts, just a few in... [more]

Blackout! Is a classroom game (suitable for middle school and up to and including university students) which simulates open electricity markets. Up to eight players compete on the open market to build power plants, bid on sale prices, and deliver the most electricity to their customers. Demand changes each turn (one simulation hour) over the course of a day. The game helps to teach about the trade-offs between different kinds of power plants, such as cost (capital cost vs. operating cost), reliability (thermal vs. renewables), flexibilty (such as base-load vs. peaking power), and so on. The current version includes wind, solar, nuclear, coal, and natural gas based power plants. Also included in this submission are sample workshop materials (i.e. instructional slides) useful in a classroom setting. Please see also the linked academic research article discussing the statistical outcomes of using the game with middle and high school students.

An article in Chemical Engineering Educatio... [more]