panel discussion: student engagement with real-world data · student engagement with real-world...
TRANSCRIPT
![Page 1: Panel Discussion: Student Engagement with Real-World Data · Student Engagement with Real-World Data. #OSIsoftUC #PIWorld ©2018 OSIsoft, LLC 2 Erica Trump, Ph.D. Program Manager,](https://reader036.vdocuments.site/reader036/viewer/2022062506/5f18bf057b09e26bd206b3db/html5/thumbnails/1.jpg)
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Panel Discussion:
Student Engagement with Real-World Data
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Erica Trump, Ph.D.
Program Manager, Academic Learning
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• Skills in visualization and analytics
• Open-ended design problems• Original ideas, practical applications
Industry Innovation 🔗 Engineering Education
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W. Pratt Rogers, Ph.D.
Assistant Professor of Mining Engineering
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The University of Utah: College of Mines and Earth Sciences
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Background
• University of Arizona – PhD Mining Engineering
• MISOM Technologies
• Currently at University of Utah
• Large assets to “small metal bubbles”
Expertise
• Socio-technical systems
• Data management
• Analytics, BI, OI, etc.
• Health and safety
• Machine learning
• Short-term mine planning
Approach
• Train next generation of mining engineers
• Bring data into classroom
• Speed up decisions
• Engage industry
Background and areas of expertise
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George Paterson
Manager, Energy Control Center
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Campus Chilled Water Demand and
Thermal Energy Storage
Cameron Whittaker, Justin Williams and MichaelWatkins
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Project Introduction
• Studied problem description, PI software and the systemitself
• Created one line process flow diagram
• Defined needed data
• Found needed data using PI
• Data analysis using Excel
• Results and conclusions
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West Chilled Water Plant TES System
• Consists of 10 interconnected tanks placed 50 feet
underground
• Each tank has a capacity of 100,000 gallons, totaling
1,000,000 gallons of storage
• The total energy stored can be
converted into about 2000 tons of
refrigeration for 4 hours
• Used for a total of 4 hours in 2016
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• Temperature effect on capacity-Capacity decreases as temperature increases
- cooling towers are unable to effectively reject heat to atmosphere-Cooling towers release thermal energy to atmosphere
-ΔT of the system decreases (the outside temperaturebecomes
warmer)-The cooling tower’s ability to reject thermal energy is reduced
• Comparison of Chilled Water Production Demand curve with Maximum Capacity insummer
-Reduced Capacity-Increased Demand
-TES currently only used to meet absolute maximumdemand.
Results of Analysis
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Steve Moore
Instructor of Process Technology
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Leo Vitor
Project Manager
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Questions
Please wait for the microphone
before asking your questions
State your
name & company
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Optional: Click to add a takeaway you wish the audience to leave with.
Thank You
Merci
Grazie