. Maynard, and E.D. Kuempel, Airborne Nanostructured Particles and Occupational Health, Journal of Nanoparticle Research 7(6) (2005) 587-614. 3. V. Uskokovi5, Nanotechnologies: What we do not know, Technology in Society 29(1) (2007) 43-61. 4. D.G. Rickerby and M. Morrison, Nanotechnology and the environment: A European perspective, Science and Technology of Advanced Materials (In Press), November 2006. 5. A.D. Maynard and David Y. H. Pui, Nanotechnology and occupational health: New technologies – new challenges, Journal of Nanoparticle Research 9 (2007) 1-3. 6. S. Panero, B. Scrosati, M. Wachtler and F. Croce, Nanotechnology for the progress of lithium batteries R&D, Journal of Power Sources 129 (2004) 90-95
AC 2010-355: DESIGN AND IMPLEMENTATION OF A SOLAR BATTERYCHARGERLiping Guo, Northern Illinois University Liping Guo received the B. E. degree in Automatic Control from Beijing Institute of Technology, Beijing, China in 1997, the M. S. and Ph. D. degrees in Electrical & Computer Engineering from Auburn University, AL, USA in 2001 and 2006 respectively. She is currently an Assistant Professor in the Electrical Engineering Technology Program in the Department of Technology at the Northern Illinois University. Her research interests are mainly in the area of power electronics, renewable energy, embedded systems and control. Dr. Guo is a member of the ASEE, IEEE and a member of
AC 2010-2282: A PRACTICAL BLADE MANUFACTURING TECHNIQUE FOR AWIND TURBINE DESIGN PROJECT IN A RENEWABLE ENERGYENGINEERING COURSEMario Gomes, Rochester Institute of Technology (COE) Page 15.74.1© American Society for Engineering Education, 2010 A practical blade manufacturing technique for a wind-turbine design project in a renewable energy engineering course1 AbstractA blade design project for a horizontal-axis wind-turbine was developed for a renewableenergy course. The objective of the project was to design a set of blades for a turbine rotorto extract the maximum amount of power from a given 12 m/s wind speed while beingconstrained to a
4.37 4.57 Q 18 4.05 4.43 Q 19 4.84 4.43 Q 20 4.79 4.71 Q 21 4.16 4.43 Q 22 4.05 4.57 Average 4.4 4.5Q 1: I attended class regularly.Q 2: I prepared for class (e.g., assigned readings, online materials, etc.).Q 3: I completed the assigned work for the class.Q 4: I asked the instructor for help/guidance when I needed it.Q 5: The textbook(s) and other course resources enhanced my understanding of
used to evaluate cyber countermeasures capable of defending or preventing harmto the power grid.6. AcknowledgementThis research was supported in part by grants from the National Science Foundation CNS-1446574, CNS-1446570, and CNS-1446621 and by the Office of Naval Research grant N00014-15-1-2922.7.0 References[1] E. J. Markey and Henry A. Waxman, “Electric Grid Vulnerability: Industry Responses Reveal Security Gaps”, U.S. House of Representatives, Washington, DC, 2013.[2] B. Wingfield, “Power-Grid Cyber Attack Seen Leaving Millions in Dark for Months”. Online at http://www.bloomberg.com/news/2012-02-01/cyber-attack-on-u-s-power-grid-seen-leaving-millions-in- dark-for-months.html, 2012.[3] R. Rantala, “Cybercrimes
thisevent came, in part, from Suffolk’s partners in the power industry who are in need of recentgraduates to replace their aging workforce, and from the knowledge that new and renewablesources of electric power are becoming more important, and that the current aging system ofpower generation and delivery needs to be overhauled. This event is part of an NSF S-STEMgrant awarded on January 1st 2014 to Suffolk’s EE program to encourage students from BostonPublic High Schools, who are predominantly from underrepresented groups, to study EE and tobe exposed to the power industry. The event was held the day after spring semester finalexaminations, allowing Suffolk EE students to present demos of renewable electricitygeneration, to lead high school
28 10 29 0 30 ur s s s s s s s s
the world‟s fastest growing renewable energy where the average annual growth rate ofwind turbine installation is around 30% during the last 10 years [10]. Several researchers haveinvestigated the feasibility of wind energy utilization in the Persian Gulf region [17–21].Figure 9 shows the regional installed wind power where the growth of Asia is significant but notin the Middle East including Qatar. Fig. 10. Global annual installed capacity 1996-2007 [10] Fig. 9. Annual installed capacity by region 2003-2007 [10]A major challenge in using wind as a source of power is that wind is intermittent and it does notalways blow when electricity is needed. Wind energy cannot be stored (unless batteries areused); and
Turbine Exit Temperature & Pressure BOILER AMPS VOLTS C Boiler Pressure O N D Variable Resistive Load E BURNER N S
(4) * h exit ? h inlet / j s h inlet / h exit , s + (5) Ã 1 ÔÃ 60 Ô Torque ? m% r *h inlet / h exit +Ä ÕÄ Õ (6) Å N ÖÅ 2r ÖThe pressure loss through the condenser was specified at a constant value and the exit pressurewas found by subtracting the loss from the inlet pressure. In the actual condenser there is apossibility for the refrigerant exiting to still be superheated, saturated, or liquid. At this stage itwas assumed that the exit enthalpy of the
characteristics of solar cells and isa powerful teaching tool to facilitate hands-on experiments to the students, thus achievingimproved student learning.AcknowledgementsThe author would like to acknowledge financial support under the ‘Course Design EnhancementFund (CDEF)’, 2015 awarded by the ‘Center for Excellence in Teaching and Learning (CETL)’,Kennesaw State University for this work. Also, the author would like to thank senior ElectricalEngineering undergraduate students, Alan Gregg Jr., Mathew Ginn, and Duane Wright for theirhelp in building the prototype solar module.References[1] http://www.thesolarfoundation.org/national/[2] http://fortune.com/2015/01/16/solar-jobs-report-2014/[3] S. Das, R. N. Bhattacharya, and K. C. Mandal, “Performance
, “Hybrid diesel generator/renewable energy system performance modeling,” Renew. Energy, vol. 67, pp. 97–102, Jul. 2014.2. J. E. Paiva and A. S. Carvalho, “Controllable hybrid power system based on renewable energy sources for modern electrical grids,” Renew. Energy, vol. 53, pp. 271–279, May 2013.3. Y.-C. Kuo, Y.-M. Huang, and L.-J. Liu, “Integrated circuit and system design for renewable energy inverters,” Int. J. Electr. Power Energy Syst., vol. 64, pp. 50–57, Jan. 2015.4. H. Belmili, M. Haddadi, S. Bacha, M. F. Almi, and B. Bendib, “Sizing stand-alone photovoltaic–wind hybrid system: Techno-economic analysis and optimization,” Renew. Sustain. Energy Rev., vol. 30, pp. 821–832, Feb. 2014.5. D. Saheb-Koussa, M
toparticipate at the national and international level.References[1] S. Foroudastan, “Mechanical engineering education: Not just about the math,” IMECE Conference Proceedings, November 2004.[2] National Academy of Engineers, “Make solar energy economical,” in Grand Challenges for Engineering, May 2011. http://www.engineeringchallenges.org/cms/8996/9082.aspx[3] S. Foroudastan, Engineering Technology Department Exit Survey, MTSU, 2015.[4] S. Foroudastan, “Enhancing undergraduate performance through peer-led, team-learning (PL-TL),” ASEE Conference Proceedings, 2009.[5] S. Foroudastan, R. Klapper, and S. Hyde, “Intercollegiate design competitions and Middle Tennessee State University’s machine shop: Kindling
Autonomous System Power Consumption Duration Energy Load Element Current (A) Duration (s) (Hours) (Ah) System @ idle 0.059 259200 72 4.248 Movement routine 4 750 0.208 0.833 Reset movement 4 120 0.033 0.133 Battery charging -0.49 36000 10 -4.9 Total per period 0.314Based on Table 2, the energy consumed during the 72 hour period may exceed the energyavailable to
involves a nominal amount of research to be completed and the use ofcomputational modeling tools – this segment addresses the RO segment of the learning cycle.Soon after the assignments are completed, the teams conduct laboratory experiments to verifytheir solutions and to examine the validity and limitations of the analytical model – this segmentaddresses the AE segment of the learning cycle. A discussion of the consequences andapplications of the findings brings a tentative closure to the inquiry process. This step leads intothe lesson theme for the next real world inspired inquiry process.Thus, each inquiry-based lesson module is designed to proceed through the ‘problemidentification s theoretical analysis s computer modeling s design solution
with a 1992 manual Chevy S-10 pickup as shown in figure 1. This vehiclewas chosen as its bed gave us an easy location to store batteries, its manual transmission allowsfor an easier adaptation to an electric motor, and it was readily available.We calculated the power required to reach a number of different top speeds as well as the rangeassociated with them based on the weight of the truck, weight of the proposed electricalcomponents, dimensions, and the desired range. Figure 1: The Manual Chevy S-10pPickupFirst, to determine the power needed to reach the targeted highway speeds, the forces acting onthe moving truck were considered. The truck dimensions and weight were determined after theconversion and are shown in
Optimization ResultsFrom these charts, conclusions were drawn that for a speed of 2.5 mph (1.2 m/s), the maximumvelocity increase will come from a 25° angle and the largest feasible outlet area.4.4 Preliminary Shroud TestingThe current testing setup measures free stream velocity but not velocity within the shroud, so adirect assessment of velocity increase is not possible. However, testing does show increasedpower output from shrouded geometry that can be compared to unshrouded tests to determineand “effective” velocity to see what speed is necessary to produce the same power without ashroud.To further confirm CFD predictions, three different shroud sizes were tested: 20°, 25°, and 30°.All had an outlet area to inlet area ratio of four
efficiency possible from the powercycle? 1 4 3 2 Figure 3a: T-S diagram for Rankine Cycle Figure 3b: Devices in Rankine Power CycleThe temperature entropy (T-S) diagram and the states at the inlet and outlet of the devices areshown in Figures 3a and 3b. For maximum efficiency it can be surmised the power plant willoperate under a Rankine cycle with an isentropic turbine and pump. Ignoring the kinetic and Figure 4a: State Panel (Given P = 2MPa and T=400oC determines all other properties)potential energy effects, the efficiency can be determined using Equation (1) with the enthalpiesat all the states: (ℎ1−ℎ2)−(ℎ4−ℎ3) 𝑛
/electricity/monthly/epm_table_grapher.cfm?t=epmt_1_01_a. RetrievedJanuary 26, 20162- G Barbose, Tracking the Sun VI- An historical summary of the installed price of photovoltaicsin the United States from 1998 to 2012. eScholarship University of California LBNL PaperLBNL-6350E, scholarship.org/uc/item 2j2888zv, 2014. Retrieved January 26, 20163- The State of the Union Address of President Barack Obama. (2016). Retrieved January 22,2016, https://www.whitehouse.gov/the-press-office/2016/01/12/remarks-president-barack-obama-%E2%80%93-prepared-delivery-state-union-address.4- S. Freeman, S. L. Eddy, M. McDonough, M. K. Smith, N. Okoroafor, H. Jordt, and M. P.Wenderoth. Active learning increases student performance in science, engineering, andmathematics
SolidWorks Flow Simulation was performed using thefollowing estimated parameters: Velocity 1m/s Fan swirl 2rad/s Turbulence intensity 5% Turbulence length 0.0254m.These parameters and the physical model require refinement based on both measured data andboundary conditions. In SolidWorks, one boundary condition that is pre-programmed for the useris a fan. However, initial experience with this boundary condition indicates that there may not bea convenient way to simulate the rather large center hub area of the real condenser unit fan thathas no blade surface and does have a vacuum. This might be simulated by working on theaccuracy of the fan swirl estimate and by either putting a blocking plate in the center of the fanopening in
(hrs) * Time (one day/hrs) (4)Where, W: Overall energy stored; Joule (J) = unit of energy (5) P: Number of people a day; 1J=1N.m=1kg.m2/s2 =1V.C =1W.s E: Energy recovered from one person; Watt (W) =unit for power (6) T: Time taken to store energy; and 1W= 1J/s =V.C/s=V.A Time: Time span for one day.In order to calculate the total energy stored in a day (24hrs), it was considered that 1mJ energycould be recovered per person according to the equations 5 and 6. In this case the total energystored in a battery can be calculated for 50 people as
reached maximum fuel consumption rate toward the end of the burn sequencewhereas maximum burn rate was achieved near the beginning of the direct combustion process.For the gasifier running with 30 g and 40 g initial fuel mass, the maximum fuel consumption ratewas 0.093 g/s and 0.100 g/s respectively, and these maximum rates occurred after the entiresystem had time to warm to operating temperature. By contrast, the direct combustor runningwith 40 g of fuel achieved a maximum fuel consumption rate of 0.067 g/s, which occurred nearthe beginning of the process before the system had warmed up. For the direct combustor running30 g of fuel, the wood chips likely had higher moisture content and were too tightly packed tofully burn. So, the flame
AC 2011-2460: STUDYING THE IMPACT ON MECHANICAL ENGINEER-ING STUDENTS WHO PARTICIPATE IN DISTINCTIVE PROJECTS INTHERMODYNAMICSMargaret B. Bailey, Rochester Institute of Technology (COE) Margaret Bailey is Professor of Mechanical Engineering within the Kate Gleason College of Engineer- ing at RIT and is the Founding Executive Director for the nationally recognized women in engineering program called WE@RIT. She recently accepted the role as Faculty Associate to the Provost for Female Faculty and serves as the co-chair on the President’s Commission on Women. She began her academic career as an Assistant Professor at the U. S. Military Academy at West Point, being the first woman civil- ian faculty member in her
hydraulic system.References1. Sullivan, J., Fluid Power Theory and Applications, Prentice Hall Inc., Upper Saddle River, New Jersey, 1998.2. Rydberg, K.; Energy Efficient Hydraulics – System solutions for loss minimization; National Conference on Fluid Power, Linkoping University, Sweden. March 2015.3. Choudhury, A. and Rodriguez, J.; Experimental Analysis for Energy-efficient Product Design, Journal of Engineering Technology, Volume 34(1), 2017.4. Choudhury, A., Rodriguez, P. Ikonomov, J. He, B. De Young, R. Kamm, S. Hinton, Human powered energy efficient vehicle design, Proceedings the American Society for Engineering Education Annual Conference, San Antonio, TX, June 2012.5. Borghi, M., Zardin, B. Pintore, F., and Belluzi, F.; Energy
engineering development.Bibliography1. Nikitin, N.I., et. al., The Chemistry of Cellulose and Wood (translated in 1966 from Russian by J. Schmorak,Israel Program fro Scientific Trasnlations, Jerusalem, Israel), Academy of Sciences of the USSR, Institute of HighMolecular Compouns, Moscow-Leningrad.2. Gaur, S. and Reed, T.B., An Atlas of Thermal Data For Biomass and Other Fuels. NREL/TP-433-7965, June1995.3. Klass, D.L., Biomass for Renewable Energy, Fuels, and Chemicals, Academic Press, 1998.4. Mani, S., and Tabil, L.G., “Compaction of Corn Stover,” American Society of Agricultural and BiologicalEngineers, Paper number 041160, 2004 ASAE Annual Meeting.5. Mani, S., et. al., ”Specific Energy Requirements for compacting Corn Stover,” Bioresource
. 82. H. Li, C.C. Liu, and M.J. Damborg – Web-Based Tutoring in Power Engineering – IEEE Trans. on PowerSystems, Vol. 18, no. 4, pp 1227-1234, 2003.3. L.J. Bohman, B. A. Mork, and D. O. Wiitanen – Power Engineering Design Projects - IEEE Trans. onPower Systems, Vol. 19, no. 1, pp 152-156, 2004.4. R.S. Balog et. al. – Modern Laboratory-Based Education for Power Electronics and Electric Machines -IEEE Trans. on Power Systems, Vol. 20, no. 2, pp 538-547, 2005.5. M. E. H. Benbouzid and G. A. Capolino – A Project-Oriented Power Engineering Laboratory - IEEE Trans.on Power Systems, Vol. 11, no. 4, pp 1663-1669, 1996.6. S. Chedid and S. Rahman – A Decision Support Technique for the Design of Hybrid Solar-Wind PowerSystems - IEEE Trans. on Energy
in Washington D.C.’s Petworth neighborhood consisting of twenty separateresidences. Two of these are multi-family residences, consisting of six apartments each, with asquare footage of 700 square feet with a variance of 50 square feet. The other 18 residences weresingle-family homes with a square footage of 1700 feet, with a variance of 400 feet. These valueswere obtained with the assistance of the U.S. Census Bureau’s American Housing Survey, whichcan be used as a basis for determining the nature of housing in a given area [10]. With GridLab-D, these variances allow for randomization in the model with 400 feet as the value for onestandard deviation. In addition, five separate power demand schedules were generated anddistributed amongst the
further their own sustainability initiatives by having their buildings certifiedthrough the LEED for Existing Buildings: Operations and Maintenance process. This paperprovided a description of one institution’s implementation of LEED Lab, from initiation throughbuilding certification. Readers might find, as the authors did, that the LEED Lab programprovides a tremendous opportunity to incorporate sustainability education and action into asingle course that prepares students with the knowledge and experience to be the green buildersof the future.Bibliography1. Buente, S. (2016, February 10). LEED Lab: Sustainability in higher education goes global. Retrieved from http://www.usgbc.org/articles/leed-lab-sustainability-higher-education-goes
able to answer correctly all the technical questions. It is concluded thatimproving the simulation tutorials, changing the mode of tutorial sessions from face-to-face toonline sessions and changing the quizzes from voluntary to graded quizzes could help to furtherboost the learning outcomes and the direct assessment results.References:1. http://www.thesolarfoundation.org/national/2. http://fortune.com/2017/02/07/us-solar-jobs-2016/3. S. Das, K. C. Mandal, and R. N. Bhattacharya, “Earth-Abundant Cu2ZnSn(S,Se)4 (CZTSSe) Solar Cells”, Semiconductor Materials for Solar Photovoltaic Cells, Springer Series in Materials Science, Vol. 218, pp. 25-74, 2015 (ISBN: 978-3-319-20330-0).4. S. Das, R. N. Bhattacharya, and K. C. Mandal, “Performance
a more representative average.PID Controller Algorithm: disturbance(s) + Set Point (SP) Process Variables (PV) Error PID Controller Process + + - Measured Process Variables SensorsFigure 6: PID ControllerPID control is very important in distributed control