A r m y S c i e n c e & Te c h n o l o g y Army Science and Technology Dr. Thomas Russell Deputy Assistant Secretary of the Army for Research and Technology 4 April 2017 20170404 Coral Gables Army S&T PrinciplesMISSION: Identify, develop and demonstrate technology options that inform and enable effective and affordable capabilities for the SoldierVISION: Providing Soldiers with the technology to Win Current Force
dynamics of a chemical process as shown in Figure 6. The flows into the CSTR contain thefluid temperature (oC), mass flow rate (kg/s), reactant concentration (kg/m3), density (kg/m3),specific heat capacity (J/kgoC), and heat of formation (J/kg).Figure 6. Example model configuration for the formation of propylene glycol specifically and in general an A B C D example CSTR process.Within each block, the dynamic differential equations for how values change, such as thetemperature or concentration, are embedded. For example, within the CSTR block, the energybalance dT UAr (Ta T ) W FA0C ps (T T0 ) H RX (kC AV
The Office of Naval Research - Science and Technology in Support of the US Navy and Marine Corps -Dr. Reginald G. WilliamsOffice of Naval ResearchMarch 2017 The Office of Naval ResearchThe S&T Provider for the Navy and Marine Corps • 4,000+ People • 23 Locations • $2.1B / year • >1,000 PartnersDiscover Develop Technological Deliver Advantage 2 ONR Organization Chief of Naval
Paper ID #19184MAKER: Smart Multipurpose Drainage SystemDr. Hugh Jack P.E., Western Carolina University Dr. Jack is not the author. The abstract has been submitted on behalf of B. Joseph Britto, S. Gowri Shankar, B. Ganga Gowtham Prabhu - Kumaraguru College of Technology, Coimbatore, India. c American Society for Engineering Education, 2017 Smart Multipurpose Drainage SystemAuthorsB. Joseph Britto, S. Gowri Shankar, B. Ganga Gowtham PrabhuKumaraguru College of Technology, Coimbatore, IndiaAbstract The drainage systems are required to be monitored in order to maintain its
Paper ID #18600Apply Second Order System IdentificationsDr. Tooran Emami, U.S. Coast Guard Academy Tooran Emami is currently a faculty member in the Department of Engineering at the U. S. Coast Guard Academy (USCGA). She received her M.S. and Ph.D. degrees in Electrical Engineering from Wichita State University (WSU) in 2006 and 2009, respectively. Her research interests are in control systems and particularly are dynamic positioning, autonomous vessel, Proportional Integral Derivative (PID) con- trollers, robust control, time delay, compensator design for continuous-time and discrete-time systems, and analog or digital
/ Caucasian 566 438 1004 Hispanic / Latino 84 62 146 Multiracial 44 73 117 Other 40 34 74 Total 1043 936 1979InstrumentParticipants completed the Student Attitudes toward STEM (S-STEM) survey, developed by theFriday Institute for Educational Innovation (2012), assessing attitudes toward science,technology, engineering and mathematics as well as postsecondary pathways and careerinterests. The S-STEM survey was validated and found to be reliable with this sample ofparticipants (Friday Institute for Educational Innovation, 2012, Unfried, Faber
steam. Properties are calculated as a function of temperature and pressure. Theinterface allows users to call out temperature (T ) and pressure (p) explicitly by name or simplypass them in order like in a traditional function call. Here, we calculate the enthalpy (h) andspecific heat (c p ) of air at 450K and 1.47bar.>>> steam.h(T=450., p=1.47)2827.075794818073>>> steam.cp(450., 1.47)2.000229350330389>>> steam.cp()4.181097326774104In the last example, no arguments are given, so PYroMat defaults to standard values for tem-perature and pressure (300K, 1.013bar). The interested user can reconfigure those numbers. Allof the properties are standardized to a kJ, kg, s, K, bar system. These units were chosen to
can greatly improve students’understanding of thermodynamics by visualizing property relationships. As a highly visual andintuitive tool, property diagrams eliminate the time devoted to mastering steam tables. Afterteaching steam tables for multiple years within a year-long thermal-fluid sciences course andrecognizing the poor pedagogic utility, the steam tables were entirely replaced by thetemperature-entropy (T-s) diagram as the primary source for water thermodynamic properties.This paper discusses the implementation, challenges, and the outcomes of this introduction.Apart from developing instructions aligned solely to property diagrams, a number of visual toolswere identified, adopted, and developed to facilitate the transition. The
New Opportunities - CreatingCorporate/University PartnershipsKnow What You Have to Offer• What is the stage of development of the research• What products or services does the research relate to• Do you understand the industry(s) this product or service will fit into• What is the cost of commercialization; by phase of development• What is the current state of the market• Will your invention create incremental or disruptive change• Is there strategic value for industry to your researchKnow What You Want• Are you trying to fund basic science, translational science or something else• Are you trying to create a product or service• Do you ultimately intend to license the technology• Do you ultimately intend to launch a start-upWhat Unique
firstattempt, while additional attempts are recognizing the fact that they are still in the learning phaseand may require some “guidance”. No partial credit is given for problems with incorrect answer.The overall strategy is to simulate learning progression from educational environment toindustry/work setting. Although these modifications were initially greeted by students withapprehension, at the end of the course students recognized the benefits of this structured andrigorous approach and expressed very positive attitude towards the examination strategy.ResultsThe study was performed on the results collected during eight semesters (S’13 – F’16). Thecourse modification was made in the Fall ’14 and implemented in the Spring ’15. The reportedresults
life cycle engineering has been developed based on this approach through a multi-university research project, entitled “Constructionism in Learning: Sustainable Life CycleEngineering (CooL:SLiCE).” The pedagogic significance of CooL:SLiCE is that it enables betterlearning within the sustainable engineering domain by utilizing effective learning modules forpersonalized environmentally responsible product design. The CooL:SLiCE platform provides aweb-based portal with three learning modules: 1) Visualization and online computer-aideddesign (CAD), 2) Sustainable product architecture and supplier selection (S-PASS), and 3)Manufacturing analysis. These modules were first piloted by a team of students from threeuniversities with different
papersthat were reviewed: 5 in pre-college, 25 in college, and 6 in post-college. A code sheet was developed using the categories necessary to answer the two researchquestions. The categories for the code sheet were ethnicity, race, gender, language(s), generationin the U.S., generation in college, and institution (college-only). When reviewing each article,the authors noted how each category was used for the purpose of data analysis. Additionally, inthe review of each article, the authors also noted the main conclusions of each study as theserelated to the status of Latinxs in engineering. After reviewing the majority of the assignedarticles, the authors met to review the preliminary findings and patterns they saw in theirrespective notes
concepts in a team report.Data AnalysisThe design concepts were examined to identify the presence of Design Heuristics in individualdesign concepts and team design concepts3. Students indicated the title(s) of Design Heuristic(s)incorporated into their concepts during the idea generation session. For example, a directapplication of Provide sensory feedback in a design concept would be to add lights to indicatehow much force a doctor is exerting while using a medical device. For each individual concept,we documented students’ reported use of heuristics as well as how they applied the heuristic(s)they reported.Subsequently, we analyzed the extent to which heuristic-driven ideas from individuals werepresent in team-selected ideas. We used this
Theory and Mechatronics.3.1 PID Control in a Robot Arm Figure 2: Robotic ArmConsider a robotic arm (Figure 2) with four joints:1: Turntable, 2: Bicep, 3: Forearm, 4: WristJoints are moved by a DC/Servo motor. The Robotic Arm controller consists offour PIDs (one per joint). 𝐾𝑝, 𝐾𝑖, 𝐾𝑑 for each PID loop is calculated separately.This process can be time-consuming. Alternatively, you can tune all four PID loopssubject to system-level requirements. MATLAB has the tools to calculate PIDvalues. The transfer function of a PID controller is found by taking the Laplacetransform.We can also define a PID controller in MATLAB directly using the transferfunction, for example: Kp = 1; Ki = 1; Kd = 1; C = Kp + Ki/s + Kd*s C
(Exam (Final exam, intervention) improvement 1, improvement1, control) control) intervention) Data Set 1A: X = 75.4 X = 77.8 X = 6.0 X = 6.6 Control vs. All intervention, participants s = 12.9 s = 12.8 s = 10.9 s = 10.1 Prof. X N = 30 N = 27 N = 30 N = 27 (Fall 2015) X = 67.5 X = 69.8 X = 8.8 X = 8.6 Q1
students’ experiences as they leave their capstone(aka senior) design courses and enter engineering workplaces. The project is currently in itsinitial phase, with instrument development and pilot testing currently underway.Multiple studies show significant gaps between school and work with respect to engineeringpractice 1-3. That gap is clear, for example, in a recent American Society of MechanicalEngineering (ASME) survey that found weaknesses among new graduates in skills includingpractical experience, systems perspectives, project management, problem solving, and design 4, 5.Equally important, industry supervisors identified such gaps more frequently than early careerengineers or academic department heads 4, reinforcing Stevens et al.’s claim
Scholars Program” Award # 1153281AbstractThe National Science Foundation awarded the University of Southern Maine with a grant forSTEM Opportunities for Academically Capable and Financially Needy Students entitled the“University of Southern Maine STEM Scholars Program,” Award # 1153281. At the completionof our fifth year, this poster presentation provides an opportunity to present data on the successof our S-STEM program, as well as share some of the best practices learned and applied. TheUSM STEM Scholars Bridge Program has been a model for blending the elements ofrecruitment, retention, and placement into an integrated, comprehensive but non-intrusiveprogram that promotes student success in transitioning from high schools and communitycolleges
with engineeringoutreach activities to enhance the learning experience of the students enrolled in an engineeringcourse (EGR 299 S course). The objective was to improve the retention of underrepresentedengineering students (majority at CPP) by providing them with opportunities to use theirtechnical engineering skills and by providing them with opportunities to work in diverse andmultidisciplinary teams (building confidence in their knowledge) in order to build relationshipswith K-12 students and to motivate the K-12 students to pursue STEM fields.Introduction to CPP engineering programsCal Poly Pomona is a four-year institution well-known by the diversity of its student population(0.2, 23.6, 3.3, 38.9, 0.1, 19.7, 3.9, 4.4 and 5.7 % of American
engineeringResearch suggests engineering-based instruction can boost student interest/achievement in S,T, M, but such “integrated” teaching and learning requires time and new pedagogy NATIONAL ACADEMY OF ENGINEERING Emerging Consensus on the “Big Ideas” in PreK-12 EngDesign Process • Constraints and specifications • Modeling • Analysis • Optimization and trade-offs • System(s)Connections to S,T, and MHabits of Mind • systems thinking, creativity, optimism, collaboration, communication, attention to ethical considerations NATIONAL ACADEMY OF ENGINEERING Positive Trends/Forces of NoteBroadening interest in more “integrated” forms of STEAM in both K-12 and in UG (e.g., +CS
electrical at higherrates than traditional students (McNeil, Ohland, & Long, 2016). This paper focused on thestickiness measure for NTS students, and other statistical tests of prediction were outside thescope of this paper. Further research is needed to explore why NTS’ stickiness follows adifferent trend than traditional students. 5 ReferencesAlvord, C. J. (2004). First-time freshman graduation rates Fall 1980-Fall 1997 entering classes (Biennial Report). Retrieved from http://ms7.dpbwin2k.cornell.edu/documents/ 1000024.pdfAstin, A. W., & Astin, H. S. (1992). Undergraduate science education
many seconds) does it become possible to determine if a student will struggle. Asimple neural network is proposed which is used to jointly classify body language and predicttask performance. By modeling the input as both instances and sequences, a peak F Score of0.459 was obtained, after observing a student for just two seconds. Finally, an unsupervisedmethod yielded a model which could determine if a student would struggle after just 1 secondwith 59.9% accuracy.1 IntroductionIn this work, the role of machine learning for planning student intervention is investigated.Specifically, t his w ork a sks t wo q uestions: ( i) C an a s tudent’s s truggles b e p redicted basedon body language? (ii) How soon can these struggles be predicted
motivations or reasons fortransferring to a different institution; an important aspect of our study is to untangle thosereasons for engineering transfer students in Texas. Students accumulate transfer student capital,or knowledge about the transfer process, at sending institutions (i.e., the place(s) where studentsbegin their degree paths), receiving institutions (i.e., the final degree-granting institution), andpotentially from non-institutional sources. The development of transfer student capital maycome from experiences related to learning and study skills, course learning, perceptions of thetransfer process, academic advising and counseling, and experiences with faculty. Upon arrivingat the receiving institution, students must adjust to the new
assignment was due for MAE 434W,which could have influenced questions 8 and 11. Based on the instructors’ feedback, Expertizawas updated between semesters and the scores from the spring semester suggest the studentsfound the newly adjusted system easier to use.Table 2. Average Survey Results per Class from the Fall and Spring Semesters. Survey Question Fluid Mechanics Capstone Design 1. The reviews I received addressed F 3.41 F 3.63 the questions/concerns I had about S 3.79 S 3.43 my work. 2. The reviews I received gave me F 3.50 F 3.63 new insight into my work. S 3.80
bringing the entrepreneurial mindset to engineering education. c American Society for Engineering Education, 2017 The rise of rapid prototyping in a biomedical engineering design sequenceIntroductionPrototyping has always played an important role in the design process as way to determineconceptual viability and iterate upon an idea. Over the last decade, the decreasing costs,improved accuracy, and wide-spread availability of rapid prototyping (RP) technology haslowered the barriers to early-stage prototyping. At universities, the result has been the rise ofmaker’s spaces, skill-based pop-up classes and rapid design challenges. In this paper, we explorethe history of rapid prototyping throughout the 1990’s and 2000
θo n (∆t )1 ( ∆t ) 2 (∆t )3 ∆t 10° 6 2.99 s 3.01 s 3.00 s 3.00 s 20° 6 3.15 s 3.11 s 3.13 s 3.13 s 30° 6 3.29 s 3.26 s 3.23 s 3.26 sTable 2. Natural Period and Frequency for Half-Disk Oscillation θo Pexper (ωn )exper (ωn ) theor Ptheor Rel. Error 10° 0.500 s 12.57 rad/s 11.58 rad/s 0.542 s 7.75% 20° 0.522 s 12.04 rad/s 11.58 rad/s 0.542 s 3.69% 30° 0.543 s
Brainstormingtended to focus students on generating holistic systems. The results suggest why different ideageneration tools are important for novice engineers, and which in contexts students may find thetools most valuable. This investigation has value for educators who are considering how to fostervaried concept development in the early phases of design.References[1] D. P. Crismond and R. S. Adams, “The Informed Design Teaching and Learning Matrix,” J. Eng. Educ., vol. 101, no. 4, pp. 738–797, Oct. 2012.[2] S. R. Daly, S. Yilmaz, L. . Murphy, and A. Ostrowski, “Tracing problem evolution - factors that impact design problem definition.,” Des. Think. Res. Symp. 11 Peer Rev., Nov. 2016.[3] J. Kim and D. Wilemon, “Focusing the fuzzy front-end in new
Paper ID #18232A Classification System for Higher Education MakerspacesDr. Vincent Wilczynski, Yale University Vincent Wilczynski is the Deputy Dean of the Yale School of Engineering and Applied Science and the James S. Tyler Director of the Yale Center for Engineering Innovation & Design. As the Deputy Dean, he helps plan and implement all academic initiatives at the School. In addition, he manages the School’s teaching and research resources and facilities. As the James S. Tyler Director of the Center for Engineer- ing Innovation & Design he leads the School’s efforts to promote collaboration, creativity, design
. In order to answer the question, “dDo web-based programming environments increase learner content gains during and after initialinstruction?” this study focused on a subset of the pre/post assessment questions related to thefundamental CS theory. Table 5.3.1 contains some of the questions from the actual assessment. Itis important to note that question seven, regarding the illustration of sequential operation, onlycontained graphical illustrations while all the remaining questions were related to real codestatements in one of three programming languages: C++, Python or Logo. Table 5.3.1 Assessment question and corresponding computer science concept(s). Q Session (Lang) Location Assessment Question (Summary
. Goldstein, MH., Meji, CV., Adams, RS, Purzer, S. (2016). Developing a measure of quality for engineering design artifacts. Proceedings of the ASEE/IEEE Frontiers in Education Conference, October
been incorporated to treat the collected stormwater and the resultshave shown that this material can removal heavy metal contaminants and provide purified water.This would provide an effective way to removal toxic pollutants such as heavy metals whilemaintain versatile and compact. Overall, this portable stormwater collection and treatment systemprovides an effective and economical affordable solution to process non-point pollutions,especially the stormwater runoff for urban residents.Spring 2017 Mid-Atlantic ASEE Conference, April 7-8, 2017 MSUBibliography[1] Savage, N., and Diallo, M. S., 2005, "Nanomaterials and water purification: Opportunities andchallenges," Journal of Nanoparticle Research, 7(4-5), pp. 331-342.[2] 2013, "Emerging