Jason Kolodziej Headshot

Jason Kolodziej

Associate Professor

Department of Mechanical Engineering
Kate Gleason College of Engineering

585-475-4313
Office Location

Jason Kolodziej

Associate Professor

Department of Mechanical Engineering
Kate Gleason College of Engineering

Education

BS, MS, Ph.D., State University of New York at Buffalo

Bio

Dr. Jason Kolodziej is an Associate Professor of Mechanical Engineering at the Rochester Institute of Technology (RIT). He received his BS, MS, and Ph.D. in mechanical engineering from SUNY at Buffalo. His research focus was primarily in controls and nonlinear system identification for parameter and state estimation from measurement data using a statistical variance approach.

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585-475-4313

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Published Conference Proceedings
Chenes, Jacob, Jason Kolodziej, and Danel Nelson. "A Statistical Classification Approach to Valve Condition Monitoring Using Pressure Features." Proceedings of the ANNUAL CONFERENCE OF THE PROGNOSTICS AND HEALTH MANAGEMENT SOCIETY 2022 - November 1-4, 2022 Nashville, TN. Ed. PHM Society. Nashville, TN: n.p., Web.
Kolodziej, Jason R and John N Trout. "Reciprocating Compressor Valve Condition Monitoring Using Image-based Pattern Recognition." Proceedings of the Annual Conference of the Prognostics and Health Management Society 2016. Ed. PHM Society. Denver, CO: n.p., 2016. Web.
Rana, Rohit, Karl Q. Schwarz, and Jason R. Kolodziej. "Non-Invasive Fault Detection in an Axial Flow Blood Pump Used as a Ventricle Assistive Device." Proceedings of the ASME Dynamic Systems and Control Conference. Ed. ASME. San Antonio, TX: ASME, 2014. Print.
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Full Patent
Kolodziej, Jason R. "Self-Tuning Thermal Control of an Automotive Fuel Cell Propulsion System." U.S. Patent 9437884. 6 Sep. 2016.
Journal Paper
Chirico, Anthony J. III and Jason R. Kolodziej. "Data-Driven Methodology for Fault Detection in Electromechanical Actuators." ASME J. Dyn. Sys., Meas., Control 136. 4 (2014): 1-16. Print.
Guerra, Christopher J. and Jason R. Kolodziej. "Data-Driven Approach for Condition Monitoring of Reciprocating Compressor Valves." ASME J. Eng. Gas Turbines Power 136. 4 (2014): 1-13. Print.
Nolan, John P. and Jason R. Kolodziej. "Modeling of an Automotive Fuel Cell Thermal System." Journal of Power Sources 195. (2010): 4743-4752. Print.
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Currently Teaching

MECE-115
1 Credits
This hands-on laboratory course introduces students to Radio Control model airplane construction. Students learn how to construct their own airplanes from balsa and birch ply, how to install control hardware, and how cover these airplanes using heat-shrink covering materials. Students are required to purchase a kit-of-parts to cover material costs, which will allow them to keep their constructed airframe at the end of the course. Radio control hardware will be provided to students for use during the course, and students will have the option to purchase their own RC hardware to turn their airframe into a fully functional RC model airplane.
MECE-543
3 Credits
This course introduces students to the study of linear control system behavior for design and use in augmenting system performance. This is accomplished through classical control methods using Laplace transforms, block diagrams, root locus, and frequency domain analysis. Topics include: Laplace transform review, system modeling for control, fundamentals of time response behavior, stability analysis, steady-state error and design, feedback control properties, PID control, root locus analysis and design, and frequency response design. A laboratory will provide students with hands-on analysis and design-build-test experience.
MECE-606
3 Credits
This course is designed to introduce the student to advanced systems modeling techniques and response characterization. Mechanical, electrical, fluid, and mixed type systems will be considered. Energy-based modeling methods such as Lagrange’s methods will be used extensively for developing systems models. System performance will be assessed through numerical solution using MATLAB/Simulink. Computer projects using Matlab/Simulink will be assigned and graded in this course including concepts of data analysis and how it performs to parameter estimation. Linearization of nonlinear system models and verification methods are also discussed.
MECE-643
3 Credits
This course introduces students to the study of linear control systems, their behavior and their design and use in augmenting engineering system performance. Topics include control system behavior characterization in time and frequency domains, stability, error and design. This is accomplished through classical feedback control methods that employ the use of Laplace transforms, block diagrams, root locus, and Bode diagrams. An integrated laboratory will provide students with significant hands-on analysis and design-build-test experience.

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