Session 3253 Using Cooperative Learning in a Freshman Summer Engineering Orientation Program Connie Kubo Della-Piana, Elsa Q. Villa, Sylvia D. Pifion The University of Texas at El PasoABSTRACT The College of Engineering at the University of Texas at El Paso (UTEP), the largest university in thecontinental United States with a majority-Hispanic student population, has offered a variety of freshman summerorientation programs for entering freshmen since 1976. Drawing from past experiences, the program has evolvedinto the Summer Engineering Enrichment Experience (SEEE
followingexperimental analysis techniques:1. The elimination of “bad” data using the statistical q-test.2. The determination of 95% confidence intervals from standard deviations using the statistical t-tables. Homework Problem #l An inventor claims that he can increase the tensile strength of a polymeric fiber by adding a small quantityof the rare element toughenitupneum during spinning, To prove her claim she provides data obtained by testingsamples with and without her addition. The six samples tested without the addition had tensile strengths of 3100,2577,2715,2925,3250, and 2888 GPa, respectively. Six samples tested with the added element has strengthsof 3725, 3090, 3334, 3616, 3102, 3441 GPa. Has the
of the evaluation? (Q- 1), Attitude (Q-2), Learning Behavior (Q-3), and2. What questions are we trying to answer? Background Variables (Q-4) . This instrument3. How will you collect the information needed to collected quantitative data that were analyzed usinganswer the questions? inferential statistics. Post-test Instrument set- 1 used4. How will you analyze and interpret the the same questionnaire designated as Q- 1, Q-2, Q-3,information? Q-4, for statistical analysis. An interview guide, Q-55. How will you communicate the findings of the will be used for qualitative
, which permitteddiscussion of methods to solve a single nonlinear algebraic equation. Vk~c Q(c_ci~)=_ (l+ Klc)2Next an unsteady CSTR at constant temperature was treated to introduce solving ordinary differential equationsas initial value problems.The model was then expanded to be steady but with heat effects included, and the Newton-Raphson method wasintroduced to solve sets of non-linear equations. Q % (yin -Y)= ~ v r(y,V Q Ctot M C& (T - Tin) = u v (-AH,..) r(y,T) kl y 0.05 10 r= kl = 6.70x 10 exp (–12556/T ), K, = 65.5 exp (961/T) T(l+K, y)2’In
water in a cup for tea or coffee) to heat the water-spoons mixtme Ipocmto 37°C (body temperate). Consider the water as a system. Heat Q is added to the ~water nom the spoons and work W (electric energy) is also added to the water. The _—change in internal energy of the water is AU. Use data from this experiment to verify m ‘——the first law of thermodynamics.Results: Home experiment AU/(Q-W) = 1.15 Error = 15% Published value: AU/(Q-W) = 1 A3 Ideal gas law: Place an empty mug in boiling water at100”C. Attach the open end of a small plastic bag at the mouth of themug and seal it with a rubber band around the rim
network configuration (Figure 1) is as follows: 386PC 486PC ,2 [ ,2 [ ,2 [ IR Q = 2 ,2 [ IR Q = 3 IR Q = 5 IR Q = 3 ,2 [ . . . . ,2 [ I /O = 0 x 2 8 0 IR Q = 3 IR Q = 3 IR Q = 3 286PC 386PC SUN
shown on a pump and system curve plot, which is providedwith the problem statement. Increasing the reactor feed temperature can be accomplished by increasing the air and natural gasflows to the fired heater; but, the reactor operation is limited by heat transfer. The performance equation forthe reactor Q = UAATmust be obeyed. Since the remedy involves maintaining the cumene production rate, the heat removal rate, Q,remains constant. Since overall flows on the process side are almost constant, and the process side is likelythe limiting resistance, U remains constant. The heat transfer area, A, is also constant. Therefore, thetemperature difference, AT, must also remain constant. Here, it
; .:4 } 1996 ASEE Annual Conference Proceedings ‘Q,.,pllll’;? .— . Figure 1. Graph of F. Since formula (2) requires multiple uses of [t], which in turn involves (l), approximations would beuseful to avoid cumbersome calculations. As shown in Figure 1, the function F has a parabola-like graph.The fact that $’ mimics a parabola so much inspired us to find quadratic functions to approximately match it.We replace [z] with z in (2) to obtain the quadratic function ql(~) . *so that ql (x) agrees with F(z) for integral x. We note that ql is a lower bound of F. In order to find anupper bound, we shift the
’..’ . Several observations lead to this conclusion about this link,A. The inputs to the network can take on any real value, positive or negative.B. The weights of the connecting links can take on any real value, positive or negative.C. The internal signals, and the outputs can only take on values between zero and one.In this list, A and B imply that the input layer determines the truth level, in a fuzzy system sense, ofstatements about the input variables, and C implies a set of logical statements that use the truth levels at theoutputs of the first layer. We will consider these two stages separately.The Input Layer Each neuron in the input layer determines, as its output, the truth of a statement:Quality Q. is true.The quality, Qn, is a
another. Thereader of this paper can be referred to any of the books listed in the reference section for a completeunderstanding of the design and analysis of transistor circuits. In electronic courses and laboratories students and engineers go through a complete design of BJTamplifiers. An essential parameter of BJT is the large signal forward current ratio Beta (13). This parameter isfound mathematically by going through the specific transistor circuit and model or by using the characteristiccurves of transistors as seen on a curve tracer. A student also goes through design of a sound biasing circuit tooperate the BJT at a certain Q point. The main BJT amplifier configuration depends on 13, its importance forsome configurations is shown
improved because of this tool? If O means not at all, and 10 means you couldn’t pass the course without it, what number would describe your response the best?A6. a.lOQ, b. 9&, c. 81, d.7Q, e. 64, f. 51, g. 41, h. 3a, i.2~, j.l Q, k. O _O_.Q7. Did you feel less pressured to take notes in class because of this tool?A7. a. a lot less ~, b. somewhat less ~, c. no pressure relief ~.Q8. Did you find yourself less interested in attending class because of this tool?As. a. less interested Q, b. more interested a, c. no difference ~.Q9. Do you think that a similar tool should be developed for other Aerospace Engineering courses? If yes, name two in particular.A9. a. no Q, b. yes Gas Dvnamics
collection can be stopped whenthe estimates have converged.4 Recursive Parameter Estimation Algorithm The recursive algorithm is implemented using the following steps. 1. Make initial estimates A = A. and a = cto. 2. Solve equation (2) for AA and Aa using the first three measurements, y, (tl ), y,(t2), and y.(t~) and with N = 3. 3. Obtain the new estimates of A and a by forming A. + AA and Q. + Aa. If either value of A or Q is negative, then use the previous value. 4. Measure the next data point, increment N, and evaluate ji in (3) and gi in.,(4) for z = 1,2,..., N using the new values for A and CY. 5. Solve equation (2) for AA and Aa, and go to step 3 until the stopping criteria is reached
) Justify all your design decisions such as number of stages, gain of each stage, type of transistor, type of stage, battery selection and Q point placement.iii) Explain everything you do. Your design and analysis equations should be derived in the theory section of your report.iv) Output wave forms for each stage are required.v) Q point coordinates, transistor characteristic curves (generated using Spice), and a sketch of dc and ac load lines, including Q point, are required for each stage.vi) After the design has been completed calculate your current gain, power gain and power consumption. (By hand and using Spice).vi) Voltage gain obtained, input impedance, current gain, power gain, output impedance
problem-solvingsetting that closely parallels the work environment of engineers. Eight students will be chosen from the Rose-Hulman sophomores who completed the IFYCSEM program. The IFYCSEM students will be chosen toapproximate a “typical sample” based on their predicted index, earned grade-point averages at the end of theirfreshman year, and scores on the California Critical Thinking Skills Test 0, and the California CriticalThinking Dispositions Inventories Q. The comparison groups will consist of eight sophomores whocompleted the traditional program. All sixteen students received letters asking them to participate in thisproject and noti&ing them that they would be paid a stipend. Students enter the IFYCSEM voluntarily and may
into the curriculum. However, due to its complexity, it must be implemented properly or it can be disastrous to your students. Page 1.449.1... .- . . .- {ti:b’~ 1996 ASEE Annual Conference Proceedings ‘...,~yy$: - ~Q how complex is “complex software”? To illustrate how complex a software can be, Figure 1 shows the number of manuals and pages that come with a typical CAD software. Keep in mind that each student will also have a theory text of about 600 pages and many drawing assignments. You can see that t; ‘e addition of CAD software to the first
Annual Conference Proceedingsand the associated degrees of freedom are S2q S2m 2 + n n ν= q m −2 , (2) Sq 2 Sm 2 nq nm
tanks to reduce heat loss and evaporation. The balls floating on the surface ofthe liquid act as a "blanket" cover. The balls will arrange themselves uniformly on the liquid and adjust toobstacles in the fluid so that a work piece can be easily immersed and removed. The annual energy savings resulting from this proposed project, ES with units MMBtu/yr, can beestimated as follows: N ES = (Q) x (A) x (H) x (PA) x ( ) x (C) EFF Where: Q = Heat lost per unit area, Btu/ft2*h A = Area of each tank, ft2 H = Annual
b- Vertical Interpolation c- Diagonal Interpolation p measured point q interpolated point Figure 2. Interpolation of area features. Generation of Triangle Lists A list of four triangles per quadrant is generated through the entire quadtree. First, an intermediate pointin each quadrant is found. If the quadrant is empty, its center point is chosen to be the intermediate point.Then, the four triangles are formed by connecting that center point to the quadrant four corner points. Thebackground color is given to those triangles. When a quadrant has a point or more inside, the point that isclosest to the center of the
. . _ Q-describing our methodology for organizing a class, we begin by assuming that the classroom isequipped with the engineering educator’s most important physical resource--a large blackboard. Indeed, weassert that the blackboard is an essential and irreplaceable tool for the effective conduct of engineering classes. Inthis ma of high-technology multi-media teaching tools, the old-fashioned blackboard is often scorned or, at best,overlooked. Yet, having tried most of the modern electronic alternatives, we invariably return to the oldstandard. As a medium for presenting information, the blackboard is far superior to the projector screen orcomputer monitor, in the following significant respects: . An instructor can write on a blackboard
q w 1. c p . T 02 T 01 Rearranging equation (1) and then combining with equation (2) and the equation of sta V2 ρ1 T1 T2 M2 . ρ2 T2 V1 M1 T1 P1 R gas . T 1 T1 M2
obtain the properties at each defined point in the We now extend these 1st an 2nd Law techniques process. These properties are fwst obtained from theto the evaluation of cooling the same house with the prcwre vs enthalpy chart in Figure 4 and then from Page 1.503.3same inside and outside air temperatures by means the computer based data for more prtilon andof a one ton or 28S,000 (Btu/daY) electric summarized in Table 1.compression air conditioner sho~fi.~ie 3. ?q~~j 1996 ASEE Annual Conference Proceedings ‘.,+,Hly
. Measurement I Mean I Standard Deviation Tensile Bar #2 Mass I 1.52546 g 10.00650 g Tensile Bar #5 Mass I 1.52521 Q 10.00556 LZ Tensile Bar #2 Lerwth I 6.29077 cm I 0.00719 cm Tensile Bar #5 Length ] 6.27847 cm I 0.01405 cm Tensile Bar #2 Thick. 10.32700 cm 10.00218 cm Tensile Bar #5 Thick. 10.32962 cm 10.00246 cm Table 3. Mean and standard deviation of physical characteristics following material contamination. Measurement Mean Standard
Session 2 2 5 1 Engineering Education by An Application Oriented Design Ron K. Bhada, Abbas Ghassemi, J. Derald Morgan New Mexico State University Waste-management Education & Research ConsortiumIntroduction: Efficient and safe management of a sustainable environment is an increasingly critical national goal. It is a b r o a d i s s u e which c a n n o t b ea d d r e s s e d b y a n y o n e entity a n d r e q u i r e s a multi-disciplinary, multi-organizational a p p r o a c h . In 1990, the U . S . D e p a r t
polymers. Page 1.110.5 fitii’ } 1996 ASEE Annual Conference Proceedings q.1111~’;: .
. Page 1.7.5 $hx~j 1996 ASEE Annual Conference Proceedings ‘“q!!!..!;Bibliography1] Froyd Jeff, Integrated Engineering Curricula, these Proceedings, Session 1230.2] Richards, Don E., A New Sophomore Engineering Curriculum - The Rose-Hulman Experience, these Proceedings, Session 1230.3] Kinney, John J., The Use of COmputer Algebra Systems in Courses in Probability and Statistics for Engineersz these Proceedings, Session 3520.Biographical InformationJohn Kinney is Professor of Mathematics at Rose-Hulman Institute of Technology where hehas taught courses in probability and statistics for engineers and scientists since 1974. Heholds a Ph.D. degree in Statistics from Iowa State University. He is
seniors in the Stevens Institute of Technology class of 1996: Peter Lepp, Valerie Mercer, and Carol Neary. References 1. Smith, B. D., “Design of Equilibrium Stage Processes,” McGraw-Hill, New York, 1963, p.118 2. Kern, P. Q., “Process Heat Transfer,” McGraw-Hill, New York, 1959 3. Goyal, O. P., Guidelines on Exchangers, Hydrocarbon Processing, 64, 8, 55, 1985. Biographical Information Harry Sills is a professor and Department Head of Chemical Sciences and Engineering at Stevens Institute of Technology in Hoboken, N.J. Pamela Brown is a Visiting Assistant Professor at Stevens. Together they teach Senior Design
logic Page 1.164.2analyzers and emulators. Students use logic analyzers to monitor timing signals, address lines, data lines, and ~tix~j 1996 ASEE Annual Conference Proceedings ‘..+,q : *:,..” —. —_. . . . .handshaking bus signals to understand various bus cycle timing of 8086-based boards. They also use emulators to trace and execute programs, and exercise various control commands to configure memory mapping, set breakpoints, display and modify registers and memory locations, and
. Figures 4, 5, and 6 show compari web versions of what was shown in figures 1, 2, and 3. Figure I : Ihe Database Menu Page 1.458.2--- $it&’ } 1996 ASEE Annual Conference Proceedings ‘..,,HJ?:.$ . Page 1.458.3---- @--L&:} 1996 ASEE Annual Conference Proceedings “q!!!’..-;Figure 4: The Database Menu: Web Version Engineering Problems Page 1.458.4 {hgti~ 1996 ASEE Annual
product design, materials selection and manufacturingprocesses to reduce manufacturing’s impact on the environment. Under the previous po}Iutant-by-pollutantpolicy, industries tended to continue their previous practices and simply add controls, rather than adopt newtechnologies. Environmental engineers were called upon to find control and remediation solutions within the Page 1.199.1 #@x& F 1996 ASEE Annual Conference Proceedings ‘Q,.,cilyp,:context of the existing set of manufacturing technologies. Now, there will
. Students rated thedifficulty of the case as average to slightly below average (Figure 1). The scores on the overall value of the case Page 1.233.2 .pii”$’} 1996 ASEE Annual Conference Proceedings “.+.q!!.:~ Iand library research indicate a respect for the case’s value and even the research it required, although some studentsrequested less emphasis on this aspect. Finally, the students appeared satisfied with the class lectures and