be written in vector form as ∇ ∙ u ൌ 0, (1) ଵ ሺu ∙ ∇ሻu ൌ − ∇ + ߥ∇ଶ ܝ. (2) ఘIn Eqs. (1) and (2), commonly known as continuity and Navier-Stokes (N-S) equations, u ൌሺݑ, ݒ, ݓሻ is the three-dimensional Cartesian velocity vector of components ݑ, ݒ,andݓ, in thedirections ݔ, ݕ,andݖ, respectively; is the pressure, ߩ is the fluid density, and ߥ is the kinematicviscosity. The solution of these equations is complex and difficult because (a) the momentumequation has
software for future updates or revisions. A tutorial isincluded that provides teams with instructions on the software usage, facilitating the decision-making process earlier in the capstone design schedule than would otherwise be possible.BackgroundAt the Milwaukee School of Engineering (MSOE) Mechanical Engineering students are requiredto complete either a two-term or three-term Senior Design sequence. Most students opt tocomplete the three-course sequence that begins in September and ends in May. The first termfinds students developing a proposal for their group‟s design goals for the year. In the secondterm analysis, design and initial building or testing is accomplished. The third term in spring isdevoted to building the project and perhaps
– 23, 2004.5. Steif, P. S., and Dollár, A., “Reinventing The Teaching Of Statics,” International Journal of Engineering Education, Vol. 21, No. 4, pp 723-729, 2005. Page 23.1014.106. Newcomer, J. L., “Many Problems, One Solution Method: Teaching Statics without `Special Cases’”, in Proceedings of the 2006 Frontiers in Education Conference, San Diego, CA, October 28 – 31, 2006.7. Dollár, A., and Steif, P. S., “Enhancing Traditional Classroom Instruction with Web-based Statics Course,” in Proceedings of the 2007 Frontiers in Education Conference , Milwaukee, WI, October 10 – 13, 2007.8. Yang, E., and Withiam, B
= 0.05 ± 0.01)compared with “Control” (average = 0.23 ± 0.08).No statistical difference was observed between the two methods for the other categories ofmistakes individually. p-values for categories 1, 2, 3, 4, and 6 were found to be 0.8, 0.23, 0.25,0.13, and 0.43, respectively. Figure 1: Comparison of mistakes per student for the eight classesOther observations. Mistake type 2 shows a significant reduction with time for instructor 1.However, this is attributed not to AR, but to the collaborative problem-solving that was part ofInstructor 1’s teaching method. This effect relates to fundamental conceptual learning achievedfrom peer teaching and has been studied in a separate work of the authors. [23]Mistake type 6 was generally
at the Active Learning for Mechanics of Materials website(http://www.me.utexas.edu/~alps/). Understand the Educational Goals and Objectives • Define Stakeholders and Collect Stakeholders’ Input • Define Educational Goals and Objectives Based on Stakeholders Input • Prioritize Goals and Determine Metrics • Define Topics • Select Topic(s) for Developing ALPs Based on Goals and Metrics Generate Possible Active Learning Product (ALPs) Educational • Generate Ideas and Create Variant ALPs
concepts explained the following application of Reynolds transport equation is effectively the formulation of the Second Law of Thermodynamics :- Page 11.227.7 S%in / S%out - (m% s ) in / (m% s ) out - S% gen ? S%CV Second Law of ThermodynamicsNet Direct Entropy Transferred in(i.e. Via heat conduction) Net Energy accumulated in the control volume
the relative velocity. Their resulting calculation of Coriolisacceleration is plotted in Figure 3 above. For the experimentally determined Coriolisacceleration, the team reached a value of 0.1305 m / s 2 while their theoretical calculation wasfound to be 0.1608 m / s 2 . A sample is given here from the team’s concluding remarks:“From our data we can conclude that we successfully isolated the phenomenon. We did this bycalculating our theoretical acceleration and comparing it to what the sensors actually recorded.Areas of improvement would be a more rigid base, smoother running surface, a constant angulardrive and linear velocity for the car.”B. Sample 2: “Trebuchet”The students in this project constructed a homemade launching apparatus known
as an adjunct Professor. Prof. Dasgupta worked for Wentworth University for more than 19 years in the Electrical and Computer Engineering Department. He taught various courses at Wentworth which includes. Motors and Controls, Power Systems, Analog and Digital Control Systems, Analog and Digital Communications, Digital Signal Processing, Electrome- chanical Systems etc. Major achievements during Prof. Dasgupta ’s tenure at Wentworth are as follows: developments of Motors and controls lab, introduction of Power Systems course as an elective, develop- ment of Feedback and Controls lab, development of Digital signal processing lab, development of Analog and Digital Communication lab and introduction of PIC
element in both versions of the course.For the recorded videos, the students were able to review the videos as much as they needed. Therewere also embedded quizzes and questions in the recorded online videos to help students stay on trackand to engage students in actively applying their learning. The course connected students to EverydayExamples in Engineering (E³s) 5, engineering concepts to which students can readily relate. Some E3sused were: Using a tire gauge to measure the pressure in a bicycle tire, Using mobile devices to findthe current outdoor temperature, and then converting that reading to different temperature scales,Discussing open and closed systems and the properties of pure substances while brewing and drinkingcoffee
workforce and empowering those interested in STEM, regardless of their background. Dr. Huderson was a 2015-2017 American Association for the Advancement of Science, Science and Technology Policy (AAAS S&T) Fellow in the Engineering Education and Centers’ division (EEC) at the National Science Foundation, where she provided leadership on developing, coordinating, and im- plementing support for programs that foster an inclusive climate for pre-collegiate and collegiate STEM students. Currently Dr. Huderson serves as the Manager of Engineering Education at the American Soci- ety of Mechanical Engineers (ASME), where she is responsible for advancing and managing the research, development, promotion, implementation
General PM Test; DFEM Only, 2001-2005 Page 12.260.5 65 Average % Correct 60 55 50 er er s s
). This sensor vs. intuitor category is seen by mostresearchers to be the most important of the four categories in terms of implications foreducation8,15,28. Table 1: Overview of MBTI Manner in Which a Person Interacts With Others E Focuses outwardly. Gains energy from others. Focuses inwardly. Gains energy from cognition I EXTROVERSION INTROVERSION Manner in Which a Person Processes Information S Focus is on the five senses and experience. Focus is on possibilities, use, big picture. N SENSING
AC 2007-195: TEACHING PSYCHROMETRY TO UNDERGRADUATESMichael Maixner, U.S. Air Force AcademyJames Baughn, University of California-Davis Michael Rex Maixner graduated with distinction from the U. S. Naval Academy, and served as a commissioned officer in the USN for 25 years; his first 12 years were spent as a shipboard officer, while his remaining service was spent strictly in engineering assignments. He received his Ocean Engineer and SMME degrees from MIT, and his Ph.D. in mechanical engineering from the Naval Postgraduate School. He served as an Instructor at the Naval Postgraduate School and as a Professor of Engineering at Maine Maritime Academy; he is currently a member of the
suggests a mechanism design to achieve higher deflection. The paper will discuss thefirst two models. In conclusion, the paper points out how engineering education could benefitfrom exposure and participation in such a design process even though students were not involvedin this study originally.IntroductionThermoelectric generators convert heat to electricity. Current geometry and materials used indesigns shown in figures 1 and 2 result to rigid devices. The geometry ensures no moving partswhile the materials provide a high figure of merit (ZT). ZT=S2σ/k, where k is thermalconductivity, σ is the electrical conductivity, and S is the Seebeck coefficient. The figure ofmerit, ZT, is dimensionless and is formed by multiplying Z with the average
givenairspeed. To maintain steady, level flight, this power consumption must be matched by thepropulsive power available; thus, the final step was to estimate the power generated by theengine-propeller system. This engineering model embodied the analysis necessary for makingsound performance predictions of the lab’s Alpha.60 airplane.Analysis of the data revealed the engineering characteristics of maximum airspeed, range,endurance, and maximum rate of climb summarized in Table 3. TABLE 3 Alpha.60 Predicted Engineering Characteristics Parameter Symbol Value Units 34.5 ft/s Stall Speed Vstall
T_ph uV_p p_hs T_ps uL_p p_hrho T_hs uV_T Specific Enthalpy, h Spe cific Entropy, s uL_T hV_p sV_p u_pT hL_p sL_p u_ph hV_T sV_T u_ps hL_T sL_T Specific Volume, v h_pT s_pT vV_p h_ps s_ph vL_p h_px
with CDS alumni and current students may reinforce these observations of the advisors.Nonetheless, continual improvement is being sought with regards to the entrepreneurial mindsetof the students, and improvement to assessment techniques will be sought to ultimately producebetter graduating engineers.AcknowledgmentsThe authors thank Dr. Arslan and Dr. Xie for their contributions as project advisors during thecourse of the work described. The authors also acknowledge support of this work at all levels ofadministration by Dr. Jawad, Dr. Grace, and Dr. Vaz.References [1] J. Mynderse, S. Arslan and L. Liu, "Using A Funded Capstone Project To Teach Fluid Power," ASME 2014 International Mechanical Engineering Congress and Exposition, 2014.[2] J
same as texts inother courses. Compared to a previous course offering using a traditional textbook, studentsscored better on two module-level assessments, on the topics of conduction temperature profilesand forced convection in internal flow. Future work includes writing chapters for an opentextbook aligned with the learning outcomes for this course and gathering more student feedbackon the course materials.AcknowledgmentThis project was supported by a Curriculum Enhancement Grant from the Center for Teachingand Learning at Indiana University-Purdue University Indianapolis. Elizabeth Lynch assisted inidentifying and reviewing existing OER and other digital materials.References[1] U. S. Government Accountability Office, “College Textbooks
Processing Workshop, 2004 and the 3rd IEEE Signal Processing Education Workshop. 2004 IEEE 11th, pages 58–62, Aug 2004. doi: 10.1109/DSPWS.2004.1437911. [2] Xuemin Chen, Gangbing Song, and Yongpeng Zhang. Virtual and remote laboratory development: A review. In Proceedings of Earth and Space 2010: Engineering, Science, Construction and Operations in Challenging Environments, pages 3843–3852, Honolulu, HI, 2010. [3] Lyle D. Feisel and Albert J. Rosa. The role of the laboratory in undergraduate engineering education. Journal of Engineering Education, 94(1):121–130, 2005. [4] S. Dormido Bencomo. Control learning: Present and future. In Annual Reviews in Control, pages 115–136, 2004. [5] Nancy Roberts. Teaching dynamic feedback
t A A s B X B y C X C n D X X D n E X E X n F X X F s G X X G s H X X H s I X I g J X X J t K X K Page 12.1450.7 Figure 5. Design Structure Matrix 62.4 Needs-Functional RelationshipThe
furtherFigure 6: The 30-day challenge problems helped me to understand the applicationof course topics to engineering practiceAppendix A: Three challenge problems from Class A Thirty-Day Dynamics Challenge Challenge Problem 2Projectile Motion and Impact: Just for fun, a golfer throws a golf ball horizontallythrough the air and watches it bounce again and again down a long straight concretepath. The ball is thrown horizontally from a height of h0 = 1.5 m with an initialspeed of V0 = 28 m/s. The coefficient of restitution between the golf ball and theconcrete is e = 0.92.(A) Determine the maximum vertical height the golf ball will reach after its third bounce, h3.(B) Determine a formula for the maximum
change request 10 LCA of efficient airplane Comparison between Results for water table wings experimental and experiments computational results Joint ReviewHomework and project assignments are due weekly and cover manufacturing, design andthermo-fluid dynamics. The teaching assistant/s will have office hours with access to the watertable later in the quarter so that students can access the table and conduct tests for the project.Airplanes fly because their wings cause a lift force when air flows past the wings. In addition tothe lift force, the flying airplane experiences thrust, drag, and weight forces (Anderson
assessment evolutions. Based onfeedback from each assessment, the program evolves as the Center seeks to close gaps betweenthe program expectations and goals, and students’ experiences. Moreover, the Center strives tointegrate best practices per new research. Concurrently, assessment instruments are updated toreflect the updated programs elements and activities. For example, 50% or more of all theparticipants in the Cohort 2 reported large or very large gains in their laboratory safetyknowledge, openness to having their views challenged, openness to work with people withdifferent beliefs, and openness to consider and discuss new research ideas; however these itemswere added to the assessment after review of Cohort 1’s experiences (thus Table 3 does
% Relief% Valve% FT% Thermocouple% City% Probe% Water% S% S% Thermocouple% Probe% S% S% Solenoid%Valve% To%Drain% Figure
presenter are TBPsmooth and effectiveUse of Presentation Media - Effectiveness of use of media (e.g., graphics, MEDCAD models, handouts, video clips, prototype, physical mockups) andtheir formats (e.g., font, color, units)Questions and Answers - Questions are answered accurately and concisely QAif the presenter(s) knows the answer, or handled appropriately if thepresenter(s) doesn’t know the answer, or taken as opportunity to delvedeeper into the topicAdherence to Time Limit - Presentation delivered within the allowed time TLlimitProblem Definition - A clearly stated design problem definition is PDEFpresented (e.g. what need(s) does this design meet, what are
verses for acetylene.References [1] Jeremy Allaire. (2009, Allaire, Jeremy. “Macromedia Flash July 8) Macromedia Flash MX- A next generation rich client. [Online]. http://www.adobe.com/devnet/flash/whitepapers/richclient.pdf [2] (2009, July) Flash Player penetration. [Online]. http://www.adobe.com/products/player_census/flashplayer/ [3] C. P. Paolini and S. Bhattacharjee, "A Web Service Infrastructure for Thermochemical Data," J. Chem. Inf. Model., vol. 48(7), pp. 1511-1523, 2008. [4] C. P. Paolini and S. Bhattacharjee, "A Web Service Infrastructure for Distributed Chemical Equilibrium Computation," in Proceedings of the 6th International Conference on Computational Heat and Mass Transfer
for Engineering Education, 2018 Two Approaches to Optimize Formula SAE Chassis Design Using Finite Element AnalysisAbstractThis paper documents two approaches used by undergraduate students to design and optimize asteel space frame chassis using Finite Element Analysis (FEA) for the Society of AutomotiveEngineers’ Formula SAE (FSAE) collegiate design competition. Junior level students inVehicle Design I used CATIA V5’s Generative Structural Analysis workbench to analyze theirindividual FSAE chassis designs. A tutorial is presented that allows a quickly modeled CADwireframe to be analyzed within CATIA using FEA with beam elements. Senior vehicle designstudents in a course titled Introduction to Finite Element
relationship between two randomvariables are linear, and, therefore correlated instead of random. R1’s and R2’s correlation onthe coding of McGown level sketches is statistically significant (p-value = 0.048). R1’s andR2’s correlation on the coding Yang level sketches is also statistically significant (p-value =0.006). The relationships between R1 and R2 coding with McGown and Yang sketch codingschemes are strong, 0.881 and 0.972 respectively. Page 14.1063.9The results of the coding indicate that the vast majority of the 418 sketches were coded in thelowest 2 levels of both sketch-coding schemes. The average number of sketches in level 1 forMcGown’s
: 100,000×0.6 m= =0.765 kg 287×273.15The specific heat cv is a function of temperature, and is evaluated at the target temperature of0oC, i.e., cv = 0.717 kJ/kg-K. The equation for Qopening can then be simplified as j Q opening=mc v ∑ ,.T -k k=1An assumed door-use behavior is given in Table 2 below (j = 5): Table 2. Pattern of Refrigerator Door Opening. Duration of Air Exchange, Δt Ti = 0.1xΔt ΔT = Ti - 0 (s
Paper ID #11558Integrating MS Excel in Engineering Technology CurriculumMr. Dustin Scott Birch, Weber State University Dustin S. Birch possesses a Master of Science in Mechanical Engineering from the University of Utah, a Bachelor of Science in Mechanical Engineering from the University of Utah, and an Associate of Science in Design and Drafting Engineering Technology from Ricks College. Birch is an Assistant Professor and Program Coordinator in the Mechanical Engineering Technology Department at Weber State University. He also serves as the Chairman of the Board of the Utah Partnership for Education. He is a member of the