● 課程說明(Course Desc<x>ription)
<br>Thermal and Fluid Science I is focused on Thermodynamics, a foundation for 
<br>analysis of thermal systems on the basis of conservation of mass and 
<br>conservation of energy principles, as well as the second law of 
<br>thermodynamics. An introduction to the power and refrigeration vapor cycles 
<br>will be provided to further illustrate the application of thermodynamics on 
<br>R&D of engineering systems. 
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<br>● 指定用書(Text Books)： Lecture notes
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<br>● 參考書籍(References)
<br>1.Cengel, Y. A. et al., McGraw Hill, Fundamentals of thermal-fluid sciences, 
<br>McGraw Hill, 2016
<br>2.Potter, M. C. and Scott, E. P., Thermal sciences: an introduction to 
<br>thermodynamics, fluid mechanics, and heat transfer, Thomson Brooks Cole, 
<br>Cengage Learning, 2004
<br>3.Moran M. J. et al., Introduction to Thermal Systems Engineering, Wiley, 2003
<br>4.Turns, S. R., "Thermal-Fluid Sciences, An Integrated Approach" Cambridge 
<br>University Press, 2006
<br>5.Cengel, Y. A. and Boles, M., Thermodynamics: An engineering approach, McGraw 
<br>Hill, 2018
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<br>● 教學方式(Teaching Method)
<br>Lecturing, Lab, Hands-on project
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<br>● 教學進度(Syllabus)
<br>1. Concepts, Definitions, and Basic Principles of thermodynamics
<br>2. Properties of Pure Substances
<br>3. Work and Heat
<br>4. The First Law of Thermodynamics
<br>5. Second Law of Thermodynamics
<br>6. Power and Refrigeration Vapor Cycles
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<br>● 成績考核(Evaluation)
<br>Midterm exams, Final project, Homework, Lab and Quiz, Class participation 
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<br>基於透明與負責任的原則，本課程鼓勵學生利用AI進行協作或互學，以提升本門課產出品質。根據
<br>本校公布之「大學教育場域AI協作、共學與素養培養指引」，本門課程採取有條件開放，說明如下
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<br>學生須於課堂作業或報告中的「標題頁註腳」或「引用文獻後」簡要說明如何使用生成式AI進行議
<br>題發想、文句潤飾或結構參考等使用方式。若經查核使用卻無在作業或報告中標明，教師、學校或相
<br>關單位有權重新針對作業或報告重新評分或不予計分。
<br>本門課授課教材或學習資料若有引用自生成式AI，教師也將在投影片或口頭標注。
<br>修讀本課程之學生於選課時視為同意以上倫理聲明。
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<br>Ethics Statement on Generative Artificial Intelligence
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<br>Grounded in the principles of transparency and responsibility, this course 
<br>encourages students to leverage AI for collaboration and mutual learning to 
<br>enhance the quality of course outputs. In accordance with the published 
<br>Guidelines for Collaboration, Co-learning, and Cultivation of Artificial 
<br>Intelligence Competencies in University Education, this course adopts the 
<br>following policy: Conditionally open
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<br>Students must briefly explain how generative AI was used for topic ideation, 
<br>sentence refinement, or structural reference in the footnotes of the ti<x>tle page 
<br>or after the reference in their assignments or reports. If usage is discovered 
<br>without proper disclosure, instructors, the institution, or relevant units have 
<br>the right to reevaluate the assignment or report or withhold scores. If the 
<br>course materials or learning resources have been derived from generative AI, the 
<br>instructor will also indicate this in the slides or orally. Students enrolled in 
<br>this course agree to the above ethics statement if registering for the class.
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