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Problem-based Learning Module for Teaching Thermodynamic Cycle Analysis using PYroMat

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Software and Related Tools for Teaching and Course Efficiencies

Tagged Division

Mechanical Engineering

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Paper Authors


Christopher Reed Martin Pennsylvania State University

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Dr. Martin received his PhD in mechanical engineering from Virginia Tech, where his research focused on reduced order modelling of combustion instabilities. He worked for ESAB Welding and Cutting in plasma torch research and development, and has taught at four drastically dissimilar universities over ten years. His primary area of research is in the area of research is thermal fluid control.

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Joseph Ranalli Pennsylvania State University, Hazleton Campus Orcid 16x16

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Dr. Joseph Ranalli is an Assistant Professor at Penn State Hazleton, and is the Program Option Coordinator for the Alternative Energy and Power Generation Engineering program. He previously earned a BS from Penn State and a PhD from Virginia Tech, both in Mechanical Engineering. Prior to his current appointment, he served as a postdoctoral research fellow at the National Energy Technology Lab in Morgantown, West Virginia. Dr. Ranalli's current research interests include development of tools and methods for solar energy resource assessment and the role of technology in engineering pedagogy.

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Jacob Preston Moore Pennsylvania State University, Mont Alto Orcid 16x16

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Jacob Moore is an Assistant Professor of Engineering at Penn State Mont Alto. He has a PhD in Engineering Education from Virginia Tech and a Bachelors and Masters in Mechanical Engineering. His research interests include concept mapping, digital textbooks, and additive manufacturing.

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This paper details a problem-based-learning module for addressing student difficulties in thermodynamics. Using the PYroMat open source software platform to automate more basic skills (like table look-ups and interpolation), learners are called on to design a cycle to meet certain criteria. In the module we detail here, students are provided costs and operational data for sets of candidate components from which to construct a Rankine cycle. Students are provided with fuel cost and the market value for electricity, and asked to make recommendations for the system's return on investment. To perform their analysis, students are provided a Python code implementing the PYroMat package, which they modify and run to determine the performance of their design. We provide advice on implementation and resources to support the module in a sophmore-level class.

Martin, C. R., & Ranalli, J., & Moore, J. P. (2017, June), Problem-based Learning Module for Teaching Thermodynamic Cycle Analysis using PYroMat Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28757

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