Teaching

Prerequisites:

• ABE20200: Undergraduate level ABE 20100 Minimum Grade of D- and (Undergraduate level MA 26100 Minimum Grade of D- or Undergraduate level MA 17200 Minimum Grade of D- or Undergraduate level MA 17400 Minimum Grade of D- or Undergraduate level MA 27100 Minimum Grade of D- or Undergraduate level MA 27101 Minimum Grade of D- or Undergraduate level MA 26300 Minimum Grade of D- or Undergraduate level MA 18200 Minimum Grade of D-)

• BME29500: Undergraduate level MA 26100 Minimum Grade of D- or Undergraduate level MA 17200 Minimum Grade of D- or Undergraduate level MA 17400 Minimum Grade of D- or Undergraduate level MA 27100 Minimum Grade of D- or Undergraduate level MA 27101 Minimum Grade of D- or Undergraduate level MA 26300 Minimum Grade of D- or Undergraduate level MA 18200 Minimum Grade of D-)

Course Description: The major objective for this course is to understand and exploit basic principles of thermodynamics as they apply to biological systems and biological processes. Specifically, the course will focus on biological processes across scales: from the nanometer scale of biomolecules, the micrometer scale of cells, the millimeter and meter scales of tissues and organisms, all the way up to the 100+ meter scale for bioprocess equipment and industry-scale production. The course can be loosely classified into two parts: (i) guiding principles and fundamental equations for thermodynamics in biological and biomedical engineering, and (ii) applications of engineering principles to the study of biological systems.

How will computation be used in this class? What if I don’t know how to code? 

• This course uses Jupyter Notebooks (in the form of Google Collaboratories), an open-source web application that provides an interactive online environment for computing.  What this means is that in each lecture you’ll get a link to an online worksheet that will contain the lecture notes as well as the computing exercises for that class period. These documents can be modified by each student to add their own notes, comments, questions and code.

• All computing exercises are in python.  However, in the first half of the semester all the computing exercises are going to be tightly related to the provided examples.  You will be doing things like modifying an example script to change the inputs or to add new variables to a system of equations. 

• Later in the semester, as you become more familiar with the Jupyter notebook environment, you will be asked to develop models from scratch, but by that point you will have many examples to draw upon. We do not anticipate that python coding will be a source of difficulty in this class but if it is we will provide the resources to help you through this hurdle.

• We strongly encourage you to bring a laptop or tablet to this class.  If you do not own or a laptop or tablet please let me know and we can make arrangements to facilitate your full class participation/learning.

How will active learning work in this course?

• Modeling activities in which you will iteratively develop predictions/hypotheses about how systems work and then compare your predictions to data from computational models. In these exercises you will iteratively refine your understanding of thermodynamics principles and develop intuition about the function of thermodynamics systems.

Class-based research

• This course is the product of funded design-based research. We are continuously examining our teaching practices to see how we can provide the most educational value to our students. To support this process we will be observing the classroom and qualitatively examining classroom materials produced in this course. All data and observations from this course will be de-identified to respect student privacy. Consent forms that will allow you to opt-in or opt-out of data collection, will be administered before any classroom observation or materials collection. Your classroom experience and your grade will not be affected in any way. Please contact your instructors with any concerns or questions you might have about this process.

Learning Resources, Technology & Texts

• Textbook

  • • The fundamental thermodynamic concepts and some of the examples are from Stanley Sandler's 5th Edition textbook Chemical, Biochemical, and Engineering Thermodynamics.

• Brightspace learning management system will be used to communicate course materials and grades.

• Gradescope will be used for some assignments and homeworks.

• CATME will be used to assign teams and perform peer evaluations of team members.

Learning Outcomes

• Successful completion of the course will enable students to meet the following learning objectives:

• Understand basic principles of Mass, Energy, and Entropy balance equations that describe thermodynamic processes (SO 1, 6, 7)

•  Apply the following concepts to solve problems in the biological engineering and biomedical engineering disciplines (SO 1, 6, 7)

  • First & Second Law of Thermodynamics 

  • Open vs closed systems 

  • Balances of mass, heat, work, and entropy/energy flow 

  • Reversibility/irreversibility

• Gain knowledge of the main factors that determine numerical values of physical-chemical properties associated with bioprocesses. (SO 7)

• Solve problems for thermodynamic processes using the computer. (SO 1, 2, 5, 7)

Additionally, students will benefit in the following ways:

• Students will develop the attitudinal dimensions of computational thinking (SO 2)

  • Confidence in dealing with complexity

  • Persistence in working with difficult problems

  • Tolerance for ambiguity

  • The ability to deal with open ended problems

  • The ability to communicate and work with others to achieve a common goal or solution

• Students will gain experience in working with non-linear systems and systems away from equilibrium (SO 1, 6)

Prerequisites: ABE 202; MA 262 (or MA 272); MA 265 (or MA 350 or MA 351); MA 266 (or MA 303 or MA 304 or MA 366); ME 200 (or ME 350)

Description: This course will introduce students to the tenets of critical thinking/arguments as well as principles of analysis, setup, and modeling of biological engineering phenomena using fundamental principles of engineering, such as material and energy balances, elementary thermodynamics, transport phenomena, reaction kinetics, and engineering economics.  Development of algebraic and differential models of steady-state and transient processes involving material and energy balances, elementary thermodynamic, transport, and kinetic reaction principles, and economics in biological engineering systems. Emphasis on the use of computational tools for modeling and solution of problems.   A variety of computational numerical modeling skills will be introduced for the solution of these models, including interpolation, cubic splines, finding roots, statistical regression modeling, and numerical solution of differential equations.  Software programming tools will be used for computational analysis.

Course Learning Objectives:  The primary objectives of this course are for you to acquire the abilities to: 

1. Identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics (ABET criteria 1)

a) Choose/develop an appropriate mathematical model of a system or process 

b) Apply mathematical/computational principles to achieve analytical or numerical solution to model equations

c) Analyze/evaluate approaches to solving an engineering problem for effectiveness

2. Acquire and apply new knowledge as needed, using appropriate learning strategies (ABET criteria 7)

a) Analyze/evaluate the need for information to solve a problem

b) Find information relevant to problem solution without guidance

c) Understand/awareness that education is continuous/required after graduation

3. Communicate effectively with a range of audiences (ABET criteria 3)

a) Writing conforms to appropriate technical style and format appropriate to the audience

b) Clear organization/format of information for convenience of the audience

c) Appropriate use of graphical information

d) Correct/appropriate mechanics and grammar

e) Clarity in analysis/evaluation of information to meet purpose/objectives of communication

Specific goals are to:

1. Understand the purpose and structure of critical arguments (ABET criteria 3)

2. Develop skills to analyze written, visual critical arguments on contemporary issues (ABET criteria 3)

3. Develop skills to create critical arguments (ABET criteria 3,7)

4. Understand the structural similarities between critical arguments and quantitative modeling (ABET criteria 3)

5. Understand ethical behavior in academic setting (ABET criteria 3)

6. Understand process of how to develop mathematical models involved with food and biological phenomena (ABET criteria 1, 7)

7. Understand the types of models and their purpose/utility from an engineering context (ABET criteria 1)

8. Understand the application of the numerical modeling principles and techniques of modeling and solutions (ABET criteria 1)

9. Understand the limitations related to computational accuracy/error and statistical precision of numerical modeling (ABET criteria 1)

10. Develop skills to create numerical models involving biological engineering systems using mechanistic concepts, such as reaction kinetics, transport phenomena, and thermodynamics (ABET criteria 1,7)

11. Develop skills for creating computational tools to quantify/evaluate numerical models (ABET criteria 1)