projects for classroom applications. These projects need to: a. be limited in scope, b. align and sequence with subject material being taught in the class, and c. support current AMP and CAMP projects. 3. As with CAMP and AMP, these projects should produce an environment similar to that the students will encounter during high-level capstone design activities and should include specific tasks such as “statement of work” and “deliverables”. 4. Staff from CAMP and/or AMP should co-lead the class during this teach- ing/learning process.As an example, we have developed a design analysis project for the Spring 2007 offeringof Heat Transfer. The following section briefly presents the project
Paper ID #7719Design and Analyze the Frame for the Global Sustainable Urban Transport(SUT) VehicleDr. Mohammad Kamal Hossain, Tuskegee University Mohammad Kamal Hossain is an Assistant Professor in the Department of Mechanical Engineering at Tuskegee University. He received his Ph.D., M.S., and B. Sc. in Mechanical Engineering from the University of Nevada, Las Vegas (USA), Tuskegee University (USA), and Bangladesh University of En- gineering and Technology (Bangladesh), respectively. His specialization is in the areas of materials and design. Before coming to Tuskegee University (TU), he worked as a Visiting Assistant
assumptions. Quantifying theimpact of their assumptions through analysis of uncertainty will accompany the validation oftheir simulations.Based on the literature reviewed, the current treatment of uncertainty in numerical modelingfollows the general form of the quantification of uncertainty in physical modeling. Therefore, thelesson content on quantification of uncertainty reviews what is commonly covered whendiscussing physical experiments, and demonstrates how that can be extended into the numericalmodeling realm. Both Type A and Type B evaluations of uncertainty are covered. Incorporatedthroughout the educational tools presented in this paper is a vocabulary necessary to discusscomputer-based numerical simulations.IntroductionEngineers are
conditions in the tank are P=200 kPa and T = 300 K. A normal shockstands in the diverging portion of the nozzle at a location where A=100 cm2. The exit area of thenozzle is 200 cm2. Find: a) A* from the tank to the shock location, b) A* from the shock to theexit, c) the Mach number at the exit, d) stagnation pressure at exit, e) exit plane static pressure.SolutionThe solution to the problem is seen in the screen shots in Figures 7 and 8. Note the use of theExcel “Goalseek” capability to do the “reverse lookup” to find the Mach number correspondingto a known A/A* ratio in part b). Page 14.600.17 Table 4 - Gas Dynamics Excel
account that there is statistical variation ismaterial properties such as yield strength. Finally, students have to be reminded thatcomputer tools (such as Finite Element Analysis) are good, powerful tools – but that theyshould not be trusted blindly – they still rely on assumptions, and require that the userproperly describes the geometry and material, and properly applies the loads.Finally, much of the content of this course used to be in the junior year. However, studentscomplained that there was too much time between the introduction of this content and theircapstone projects. As such, the course was moved into the senior year to be concurrentwith capstone during a recent curriculum revision.REFERENCES[1] Estell, J. K., Jaeger, B., Whalen
) coordinate pairs can be similarly defined. For the planar four-bar, with each body-fixed coordinate system x-axis lined up with a line connecting each body’s revolute joints, themoving link is will be either 0 (i=3,5,7) or (i=2,4,6). If the fixed link d is horizontal as shownand its coordinate system is chosen to be coincident with the absolute coordinate system, whichlocated at the ground-crank revolute joint, then 1 = 8 = 0. The is define the absolute angle ofrotation of each moving link. If the mass center of each link is also at the link mid-point, thenr1=0, r2=r3=a/2, r4=r5=b/2, r6=r7=c/2 and r8=d. Applying Newton’s Second Law in 2-D form to body 2 yields k3•(x6-x5) – k2•(x4-x3) = m2•X2 k3•(y6-y5) – k2•(y4-y3) = m2•Y2
course, key activities took place before class, during class, andafter class. Before class and at least one week in advance, lecture notes were given to students,pre-recorded video lectures were posted, and the FLS was also given. Students were expected towatch the videos ahead of class. At the beginning of class, students submitted a hard copy of theFLS, which included (a) their questions about the material covered in the video, (b) a signatureacknowledging that they watched the video, and (c) feedback to continuously improve the pre-recorded video. FLS submission counted as part of the homework grade. During class,approximately one-third of the time was focused on answering and discussing the questionssubmitted on the FLS. This process
. The latter are listed as close as possible to the solutionorder as best determined by the team. A generic design project DSM is shown in Figure 5. Notethat the sub-problems may also be listed along the diagonals to make the matrix easier to read.Reading across rows, Xs indicate column sub-problems that provide direct input tocorresponding row sub-problems. For example, reading across row D sub-problems B and Cprovide direct input to sub-problem D and are therefore marked with Xs. Likewise, reading downcolumns, Xs indicate row sub-problems that directly receive input from a particular column sub-problem. For example, reading down column D sub-problems E and F are marked. This meansthat E and F receive direct input from D. Sub-problems
in Table 1on the next page. Page 13.552.6 Table 1. Student Participation Section Survey I Survey II Pilot 34 25 Control A 35 27 Control B 37 6The instructor who administered Survey II in the Control B section noted that many of thestudents in that section did not seem interested in completing the survey. Since participation wasvoluntary, we had no recourse to obtain more student responses.The main purpose of Survey I was to determine whether or not all class sections were composedof students we could assume to be
Page 15.1110.9first given the quiz learning objectives. The reviewers were also provided the quizzes from thecontrol and experimental groups. The group associated with each quiz was not identified to theindependent reviewers. Each reviewer independently evaluated each quiz. Independentreviewers were provided the Independent Reviewer Multiple-Choice Quiz Question AssessmentForm, in Appendix B, to record their evaluation. This assessment form is almost identical to theMultiple-Choice Quiz Question Checklist Form in Figure 1. One difference between the twoforms is that the checklist form items are written as questions and the assessment form items arewritten as statements. A second difference is that each item in the checklist form is evaluated
: F(2), D(0), C+(1), B-(1), B(4), B+(1), A-(2), A(3)The PercentileThe Pth percentile of the overall course grade, G, was evaluated by sorting G from low tohigh. A desired Pth percentile was obtained by (n+1)*P. For n=14 students the 25th, 50thand 70th percentiles were:G = 16.3 56.7 77.7 80.4 82.8 83.1 85.0 85.4 86.8 89.6 89.9 91.3 92.1 92.2For the 25th percentile we selected 0.25*(n+1) =3.75 or roughly 4 observations. Thisvalue corresponds to 80.4. The grades show 10 observations larger than 80.4, and threeobservations smaller than 80.4. The 50th and 70th percentiles were evaluated similarly:50th Percentile=7.5 or roughly 8 observations corresponding to 85.4%. This correspondsto: six grades larger than, and five grades smaller than 85.4
simulations performed for this class, a chain end was allowed to bondwith a reactive agent only once while reactive agents could join with up to four chain ends. Thissimulation contains difunctional polymer chains and tetrafunctional reactive agents. Simulationof polymerization, the actual linking of the molecules and the crosslinking agents, is carried outin a nearest neighbor fashion. The nearest neighbor approach seeks to find the closest crosslink,a, to chain end, b, that is itself not closer to any other crosslink.Students are first given a set of random x-y points representing crosslink and chain end positions.Next they are given the problem of determining the crosslinks which are nearest neighbors ofeach chain end. Students quickly see that
using35 infinitely slow reversible processes during which all properties are spatially uniform. The insight gained36 by following and understanding the derivation is not directly transferable to the second law analysis of37 any real system.38 b. Specific-to-general approach: The derivations are undertaken with specific devices (heat engines) and39 processes (reversible processes) but students are expected to apply the second law to general problems40 that do not use these particular devices or processes, e.g. exergy analysis of a real (irreversible) fuel cell.41 This specific-to-general approach is an exception to the general pedagogical practice of deriving results42 for a general situation that is then applied to specific cases
AC 2008-323: POWER PLANT ANALYSIS WITH MATHCADJason Christopher, Rice University Jason Christopher graduated from the United States Air Force Academy (USAFA) in 2007 at the top of his major, Mechanical Engineering. Jason is currently pursuing a Master of Science in Mechanical Engineering at Rice University, where his research focuses on computational fluid dynamics (CFD), with specific emphasis on work related to the NASA Crew Exploration Vehicle parachutes. After finishing his studies, he will work as an Air Force developmental engineer.Adam Parks, Air Force Research Laboratory, Wright-Patterson Air Force Base Adam Parks graduated from the United States Air Force Academy (USAFA) in 2007 with a
). Reaching Students: What Research Says About Effective Instruction in Undergraduate Science and Engineering, The National Academies Press.9. Freeman, S., Eddy, S. L. et al., (2014). Active learning increases student performance in science, engineering, and mathematics, Proceedings of the National Academy of Sciences of the United State of America, 111(23), 8410- 8415.10. Schmidt, B., (2011). Teaching engineering dynamics by use of peer instruction supported by an audience response system, European Journal of Engineering Education, 36(5), 413-423.11. Wilson, T. A., (2002). Applications of Peer-Instruction Concepts to Engineering Education, Frontiers in Education, 32(1), T2A-6.
) Figure 1c Figures 1a,b,c. The P-v, T-s, and T-v diagrams created by running graphing functions programmed into the Xsteam compilation. Running these functions automatically produces the saturations curves and formatting seen in the figures.In thermodynamics, constant pressure and temperature processes are often discussed and plottedon various diagrams. A function was created for each of the three previously discussed diagramsto draw a line of constant pressure on the temperature diagrams and constant temperature on thepressure diagram. The sub function ‘pvtemperatureline’ plots a constant temperature line on a P-v diagram by first displaying a message box requesting the temperature the user wishes to plot.As with
’ perceived anxiety levels related to course,assessment, and graduation outcomes [24]. The scale consists of 14 items each defined by a seriesof symptoms, and measures both psychic anxiety (mental agitation and psychological distress) andsomatic anxiety (physical complaints related to anxiety). For the purpose of this study, the authorsfocus on item 1 of the scale, anxious mood, to help assess the degree of students’ perceived anxietylevels.Question 1, for example, provided feedback regarding Stage 1, Questions 2-9 corresponded toStage 2, and Question 10 complied with Stage 3. Descriptive statistics were employed for analysisand presentation of data results. The authors note the following limitations of the study: (a) smallsample size; (b) self
: Learning Anywhere, Anytime,’ Journal of Engineering Education, pp 131-146. (2.) Mulligan. B, Coll, B, and Corcoran, G, 2007, ‘A Lean Approach to Engineering Education Online,’ International Symposium for Engineering education, Dublin City University, Ireland. [Online]. Available: http://doras.dcu.ie/447/1/Mulligan-corsoran_ISEE07.pdf (3.) Weaver, W. , Anderson, C. , Naber, J. , Keith, J. , Worm, J., Beard, J. , Chen, B. , and Hackney, S., 2011, ‘An interdisciplinary program for education and outreach in hybrid & electric drive vehicle engineering at Michigan Technological University,’ 7th IEEE Vehicle Power and Propulsion Conference, (4.) Watson, J.L., Bibel, G., Ebeling, K., Erjavec, J., Salehfar, H., and
2006-2546: ENGINEERING EDUCATION THROUGH REVERSE ENGINEERINGPedro Orta, ITESM MonterreyRicardo Ramirez Medoza, Institute Tecnologico De MonterreyHugo Elizalde, Monterrey TechDavid Guerra, Monterrey Tech Page 11.554.1© American Society for Engineering Education, 2006 USE OF REVERSE ENGINEERING AS A TEACHING TOOLS IN MECHANICAL ENGINEERING EDUCATIONABSTRACT:Our University has been working in a new teaching-learning model for several years.. .. The fundamentalsof the Engineering Education are the active learning technique and Reverse Engineering based on theassembly and construction of an experimental aircraft RV-10. Reverse Engineering (RE) teachingtechnique is
based on the cost of the design, its creativity,aesthetics, craftsmanship, and quantitative test results, etc. Out of the ten teams, five chose towork on the first problem (solar power plant), out of which four had a successful workingprototype; and the other five chose to work on the second problem (water purification andtransportation), all of which were able to solve the problem successfully. The figures belowshow examples of final student designs. Figure 4(a). Three examples of solar power plants designed and built by student teams Figure 4(b). Three examples of water purification and transportation devices designed and built by student teamsSolid Mechanics Truss Bridge Design ProjectDeliverables of
process of implants starts with a MRI scan - Ma et al., (2013).Figure 1 below shows some of the student work including simple stress analysisthat they performed. Figure 2 shows some of the students’ project they did in thecourse. Figure 1: Design and analysis of a custom knee implant Figure 2: Some of the students’ projects in the Advanced Solid Modeling course.Stage 2: Summer Training Program:The objective of this training is to provide students with a more in depth experiencein AM and design. The training includes: a. Hands on workshop on how to build a 3D printer: students build, calibrate, and test their own 3D printers. This training lasts for three days. b. Seminars by faculty and professionals from the
engineering, (b) an ability to design and conduct experiments, as well as to analyze and interpret data, (c) an ability to design a system, component, or process to meet desired needs, (d) an ability to function on multidisciplinary teams, (e) an ability to identify, formulate, and solve engineering problems, (f) an understanding of professional and ethical responsibility, (g) an ability to communicate effectively, (h) the broad education necessary to understand the impact of engineering solutions in a global and societal context, (i) a recognition of the need for, and ability to engage in, lifelong learning, (j) a knowledge of contemporary issues; (k) an ability to use the techniques, skills, and modern engineering tools
࢙࢙, ൌ ࢙ Equation 26 To find the specific entropy at state-point one (ݏଵ ) Equation 27 uses a propertyrelationship based on the two independent, intensive properties known at state-point one,namely, temperature and quality. ࢙ ൌ ࢌሺࡾࢇ, ࢀ࢙ࢇ࢚,ࢋ , ࢞ ൌ ሻ Equation 27 You may find it helpful to refer to Appendix B once again to follow the next chain ofevents. With the pressure and specific entropy at state point 2s you are able to use the propertyrelationship represented in Equation 24 to find the ideal specific enthalpy. Now you haveeverything you need to calculate the ideal rate of work into the compressor using Equation 12.Next, calculate the actual rate of work into the compressor using
0.002% uncertainty. To somestudents, this appears to be a reasonable if not a preferred representation of the final answer. Inan engineering thermodynamics course, this concept is more difficult for students since propertyvalues reported in tables often are specified at 6 significant digits, which can be interpreted as1/500000 or 0.0002% uncertainty. Having property values in thermodynamic tables expressed to6 significant digits, contributes to the students’ perception that more digits are better.Students are expected to learn to estimate uncertainties in laboratory measurements and be ableto propagate these to final reported measurement values. This is expected in ABET1 outcome (b)describing the “ability to design and conduct experiments
trigger curricular change. Table I showsa subset of courses from the ME curriculum to illustrate some of the embedded assessments.Each PO is typically assessed in 3-4 courses with no course spanning more than 3 Criterion 3(a-k). Page 15.1271.4 Table I Subset of courses used for PO assessment ME Program Required Program Outcomes [Criterion 3(a-k)] Course/Course Title a b c d e f g h i j kES 101 Engineering Freshmen Dialogue
experience involving manufacturing, design and analysis of Submarine Components and Navy related equipment. In addition Dr. Gates has worked in the aerospace industry, helicopter fuselage and rotor blade aerodynamics coupled with wind tunnel testing. Currently Dr. Gates is involved with high temperature Fuel Cell Research and development. Dr Gates earned a Ph.D. in Mechanical Engineering from the University of Connecticut and BS ME and MS ME from Rochester Institute of Technology. E-mail: GatesA@ccsu.eduZdzislaw Kremens, Central Connecticut State University Zdzislaw B. Kremens received the M.Sc. and Ph.D, degrees in Electrical Engineering from Wroclaw University of Technology, Wroclaw
everything works as planned or as intended, so the sooner this can be called to the instructor’s attention, the sooner improvements can be implemented. This also communicates to the students that the instructor cares about their learning experience.AcknowledgementsWe gratefully acknowledge the financial support from the University of Kansas Center forTeaching Excellence for CL as a Teaching Fellow and from the School of Engineering for MMas a Postdoctoral Teaching Fellow.References[1] M. Prince, R. Felder, and R. Brent, "Active Student Engagement in Online STEM Classes: Approaches and Recommendations," Advances in Engineering Education, vol. 8, 2020.[2] L. K. Michaelsen, A. B. Knight, and L. D. Fink
the function. Unfortunately for the two groups, the nature of thecombined-cycle optimization caused Mathcad to find local-maximums for specific power basedon the groups’ initial guesses that were less than the class maximum specific power. However,consideration was given to the groups for ingenuity and resolve.ME 321 Introduction to Fluid MechanicsAppendix B presents the project assigned during the Fall 2003 offering of ME 321 Introductionto Fluid Mechanics. The project required designing a thrust reverser to retrofit the Gulfstream IIbusiness jet owned by Virtucon Inc., the cover company for Dr. Evil’s empire. The thrustreversers were needed to safely land the Gulfstream II on the 0.5-mile landing strip on Dr. Evil’sIsland. The specifics of
0 F D C- C C+ B- B B+ A- A A+ Figure 3 Usage of Video AI Based on Incoming GPAExtended Results and DiscussionSince Video AI is a new idea within our department and institution, we administered a surveywithin the first two days of the semester to gain insight into perceived student preferences. Thesurvey asked questions about whether or not they had used short videos to supplement learningin previous classes; if they had used videos before, what they thought about it; what type ofvideo they would be most likely to use; and trends in podcast and RSS use.We had an 85% response rate (156 of the 184 students enrolled in
Video AI access data were available. Intotal, medium-term retention was analyzed for 113 students, most of whom were third-yearengineering majors at the time that concept retention was assessed. Page 14.1206.4 Figure 1: The QuizPredicted versus Actual RetentionTo measure the student retention, it was necessary not just to measure student performance onproblems from Statics-Strengths, but to correct that performance to normalize for the rawcapability of each student, similar to the method suggested by Klosky et al. (2006)5. Thus, astudent who earned an A in the course but earned a B on the retention test related