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Project Descriptions
Fall 2025

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Showing 2 projects out of 2 found. On page 1 out of 1.
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Machine learning for PV performance optimization

Thomas Schutzius - Professor, Mechanical Engineering

Status: Current Term Now Closed     Weekly Hours: 12 or more hours     Location: On Campus

This project aims to apply supervised machine learning techniques to optimize the performance of photovoltaic (PV) systems. By analyzing real-world operational data such as weather conditions, soiling levels, shading patterns, and energy output, we will develop predictive models that can accurately forecast PV performance and identify factors that reduce...

Machine learning for modeling ice growth dynamics and crystal morphology

Thomas Schutzius - Professor, Mechanical Engineering

Status: Current Term Now Closed     Weekly Hours: 12 or more hours     Location: On Campus

This project aims to apply supervised machine learning to understand and predict the ice growth process in various solutions. Beyond modeling the overall freezing rate, we seek to capture detailed aspects of ice crystal morphology — such as tip radius, dendrite arm spacing, and branching patterns — under different thermal and chemical...

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