Faculty Profile

Peter Johnson, Ph.D.

Associate Professor and Chair of Mechanical Engineering

GEM 205

Curriculum Vitae


Ph.D. - Iowa State University 2003
M.S.M.E. - Iowa State University 2001
B.A. Physics - Gustavus Adolphus College 1998

Areas of Specialization

Small wind turbine optimization, virtual reality in the classroom, virtual engineering, thermofluids optimization, complex adaptive systems, computational fluid dynamics (CFD), humanitarian engineering.

Courses Taught

  • GE 100 Fundamentals of Engineering
  • GE 109 Mechanics – Statics
  • ME 209 Mechanics – Dynamics
  • ME 215 Mechanics of Materials
  • ME 225 Computational Techniques for Mechanical Engineers
  • GE 301 Financial and Ethical Decisions in Engineering
  • ME 332 Mechatronics Laboratory (laboratory section only)
  • ME 333 Mechanical Measurements Laboratory (laboratory section only)
  • ME 370 Thermodynamics
  • ME 373 Fluid Mechanics
  • ME 374 Heat Power Laboratory
  • ME 376 Heat Transfer
  • ME 476 Advanced Topics in Fluid Mechanics – Introduction to Computational Fluid Dynamics
  • ME 499 Undergraduate Research in Mechanical Engineering
  • GE 497/498 Senior Design Project I and II
  • MEM 703 Best Practices for Managing Technical Teams

Research Interests

Optimization of small-scale wind turbines for developing regions
As the size of wind turbines increase, the cost per kilowatt-hour generated tends to decrease, which is why most commercial wind turbines are so large. For Americans, residential-scale wind turbines (1kW-100kW) are expensive and the payback period is not significantly shorter than the expected lifetime of the turbine. Small-scale wind turbines (< 1kW) are not useful for most locations. The total expected power output is much lower than what is typically used in homes in the developed world. However, in developing countries, electricity is in short supply, expensive, and prone to disruptions in service. Small-scale wind turbines are better suited for these regions due to the fact that they are less expensive and more easily maintained than commercial-scale or even residential-scale machines. One drawback to small-scale wind turbines is that they are typically of the one-size-fits-all variety – you can purchase the entire system off the shelf, so to speak – making it difficult to ensure that the wind turbine is well-suited for the particular wind speeds that it will encounter. To go into further detail, the “type” of wind that a particular region experiences is completely different from the “type” of wind in any other region. Likewise, each wind turbine will behave differently depending on the “type” of wind it encounters. For example, the average wind speed at location A may be 4 m/s, and the average wind speed at location B may also be 4 m/s. The difference is that at location A, the wind blows at 8 m/s all summer long and hardly blows at all in the winter whereas at location B the wind stays pretty steady at 4 m/s all year long. The type of wind turbine one would put up in either location is different. Or in other words, if the same wind turbine was placed in both locations, it might generate an average of 50 W at one location and 100 W at the other. The goal of this research project is to model various components that make up a wind turbine, specifically at these small scales. With these models, an optimization routine can be developed that will take into consideration the “type” of wind in a given region so that an optimal device can be created.

Virtual reality applications for engineering education
Dr. Michael Hagenberger, Dr. Jeff Will, and I have been working for the last few years on a project related to the teaching of our Mechanics-Statics course here at Valparaiso University. An important part of this course is the analysis of three-dimensional (3D) vector systems. Through teaching the course in Fall 2003, I noticed that many students had difficulties visualizing 3D vector systems out of the textbook. I also noticed that these students had a variety of intellectual abilities. To study these observances more scientifically, we developed a 3D visualization tool that can be used in the classroom. StaticVU, as it is called, has been used to study students’ abilities to interpret 3D vector systems. Through in-class surveys, we have gathered data comparing student performance using StaticVU, the actual textbook problems, and a hybrid version in which StaticVU is used in 2D rather than 3D.


  • “Direct and Indirect Benefits of an International Service-Learning Design Project: Educational Effects on Project Members and Their Peers”, International Journal for Service-Learning in Engineering , April 2009 
  • “Improved Pedagogy for Engineering Ethics Instruction”, Proceedings of the 2007 American Society for Engineering Education Annual Conference and Exposition, June 2007  (R. Freeman and K. Leitch)
  • “Balancing Learning Objectives and Success in a Multidisciplinary Senior Design Project” , Proceedings of the 2007 American Society for Engineering Education Annual Conference and Exposition , June 2007  (K. Sevener, P. D. Tougaw, and J. D. Will )
  • “Motivation, Inspiration, and Economics of an International Service Project”, Proceedings of the 2007 National Capstone Design Course Conference, June 2007  (M. Budnik, K. Sevener, J. D. Will)
  • “Understanding the Costs and Benefits of Using 3D Visualization Hardware in an Undergraduate Mechanics-Statics Course”, 2006 Frontiers in Education Conference, October 2006  ( M. Hagenberger and J. D. Will)

Professional Affiliations

  • American Society of Mechanical Engineers
  • American Society of Engineering Education