1. Development of a Multidisciplinary Curriculum for Intelligent Systems (MCIS)  Dimitris C. Lagoudas  Jeffery E. Froyd  Othon K. Rediniotis  Thomas W. Strganac  John L. Valasek  John D. Whitcomb  Rita M. Caso http://smart.tamu.edu/CRCD

2. Texas A&M University Goals of MCIS Effort at TAMU  Develop new curriculum track on Intelligent Systems emphasizing aerospace technologies.  Increase knowledge and interest in using smart materials to design intelligent systems.  Include a 2 semester design course and a one-on-one directed studies course with a faculty member.  Offer an “Intelligent Systems Track” Certificate.  15 hour program  Includes recognition on transcript URICA and design team Synthetic Jet Actuator

3. Texas A&M University Courses Impacted  AERO 101 – Introduction to Aerospace Engineering (F01)  ENGR 111/112 – Foundations of Engineering I/II (F01/S02)  ENGR 211/213/214 –Basic engineering science courses (S02, F02)  AERO 302 – Aerospace Engineering Laboratory I (S02)  AERO 304/306 – Structural Mechanics I/II (F01, F02)  AERO 401/402 – Senior design sequence (F03, S04)  AERO 405 – Aerospace Structural Design (F01)  AERO 489* – Special Topic: MEMS for Aerospace Engineering (F01)  AERO 489* – Special Topic: Aerospace Intelligent Systems (S02) *New Course

4. Texas A&M University Foundations of Engineering (ENGR 111/112) Activities with Shape Memory Alloys (SMA) Heat Engine Demo: SMA Efficiency/ Thermodynamics Butterfly Demonstration: SMA Linear Actuator Thermobile ™ Demo: SMA Properties/ Thermodynamics Stiquito Project: Application of SMA

5. Texas A&M University ENGR 111 Project Walking Robot  Robot (Stiquito) specifications:  Must be actuated by SMAs  Goal is maximum distance in 3 minutes  Only contact can come from ground  Must be an autonomous system  Assigned to 24 four-person student teams in ENGR 111  Maximum distance traveled was 48cm.

6. Texas A&M University ENGR 11x/21x Demonstration Piezoelectric Beam Demo  Demonstration for Freshman/Sophomore to show the basic function of a piezoelectric patch Beams with patches and amplifier Planned Setup Piezo patch Shaker  Piezoelectric patches will be used to cancel a known vibration.

7. Texas A&M University  There are two primary objectives:  Let first year students gain practical experience working on the design and construction of an aerospace vehicle while working with upperclassmen.  Allow seniors to learn and develop important project management skills needed in the workplace today. ENGR 111/112 Integrated with AERO 401/402

8. Texas A&M University AERO 302 Project Synthetic Jet Actuators Introduction into the classroom: AERO 302 (Aerospace Engineering Laboratory 1) Use of Hot-Wires and Fast- Response Pressure Probes to measure actuator exit velocity as a function of operating frequency Visualization of the effect of Synthetic Jet Actuators on airflow Without Actuation With Actuation

9. Texas A&M University AERO 306: Design Optimization of a Reconfigurable Active Wing Demonstration Model Rib with Embbedded SMA Actuators Synthetic Jet Nozzles Pressure Sensor Arrays Rib with Embbedded SMA Actuators

10. Texas A&M University AERO 306: Active Reconfigurable Wing Experimental Model - Structural Concept Compression SpringsInternal Support StructureSMA Wires Schematic Drawing FEM Analysis SpringsSpar SMA tensioner bolts Rib Linkage to Skin Flow Direction Springs Experimental Model

11. Texas A&M University AERO 405: Urica I Flying Wing (FEA Spar & Rib Von-Mises Stresses)

12. Texas A&M University AERO 306/405 Finite Element Analysis Environments Three Alternatives  Commercial finite element programs with integrated pre- and post-processor  Examples: FEMAP  Advantages: tested, reliable, flexible  Disadvantages: multiple options, steep learning curve  In-house codes  Examples: alpha, plot2000  Advantages: few options, shallow learning curve  Disadvantages: lower reliability, less flexibility  Partial differential equation solver (FlexPDE, PDEase2D, FemLab)  Examples: FlexPDE, PDEase2D, Femlab  Advantages: great flexibility, customization  Disadvantages: slower execution due to non-optimized code

13. Texas A&M University AERO 401/402 Autonomous Intelligent Reconfiguration Knowledge & Feasibility Criteria Knowledge Identify needs for reconfiguration Facilitator Structural Reconfiguration Flow Reconfiguration

14. Texas A&M University SMA experiment SJA experiment  Hybrid Simplex-Genetic Algorithm  Improve and Refine Existing Algorithm  Hysteretic Actuators  Extend Current Actuators from SISO to MIMO Type  Synthetic Jet Actuator Flow Regime Expansion  Extend Low Speed Results to High Speed Regime  Evaluate in Non-Laboratory Environment  Fly on UAV Testbed AERO 401/402 Autonomous Intelligent Reconfiguration Electrical Control Surfaces Data Firewall SMA wires

15. Texas A&M University AERO 489: Special Topics in MEMS for Aerospace Engineering FABRICATION  Photolithography  Wet and dry etching  Oxidation, nitridation  Evaporation, sputtering  Electrodeposition  CVD, LPCVD, PECVD  Surface micromachining  Bulk micromachining THEORY  Scaling laws  Electrostatics, capacitive devices  Magnetostatics, inductive devices  Surface tension  Fluid mechanics  Electro-fluid mechanics Adaptive Microscope Lens

16. Texas A&M University AERO 489: Special Topics in Aerospace Intelligent systems  Basics of Aerodynamics, Structures and Controls  Fundamentals of Fluid Motion and Aerodynamics  Fundamentals of Structural Mechanics  Fundamentals of Systems Control  Experimental Techniques in Fluids and Structures  Data-Acquisition Fundamentals  Intelligent Flow Diagnostics  Intelligent Structures Monitoring  Smart or Active Materials  Shape Memory Alloys  Piezoceramic Materials  Magnetostrective and Electrorheological Materials  Sensors and Actuators  Conventional Sensors and Actuators in Aerospace Engineering  Intelligent Sensors  Smart material Actuators  Intelligent Systems in Flow Control  Passive Flow Control Techniques  Active Flow Control Techniques  Synthetic Jet Technology in Flow Control  Traveling Waves and Skin Friction Reduction  Biomimetics in Aerospace Engineering  Fundamentals of Fish Swimming  Fundamentals of Bird Flight  Biomimetic Underwater Vehicles  Flapping-Wing Uninhabited Air Vehicles (UAV)  Micro Air Vehicles (MAV)  Lotus Leaves and Hydrodynamic Skin Friction Reduction  Intelligent Techniques in Systems Modeling  Artificial Neural Networks  Fuzzy Logic  Multiresolution Analysis  Proper Orthogonal Decomposition

17. Texas A&M University  Typical activities include  static and dynamic behavior  aerodynamic-structurally coupled systems  forced response from control systems  equilibrium vs. stability concepts  consistent measurements  validation and verification Wing support system AERO 489: Special Topics in Aerospace Intelligent systems – Aeroelasticity  Objectives  Examine the interdependence of engineering disciplines such as aerodynamics, structural, and control  Examine the contributions of design concepts that employ “intelligent systems” such as distributed controllers, active materials, and flow control.  Illustrate behavior via benchmark experiments. Multi-control surface wing in 2x3 wind tunnel

18. Texas A&M University Assessment and Evaluation Plan Year 1 Outcome Measurement (Implemented 1 and/or Projected ) 1 Levels at which Implemented ( i.e., F=Freshman, S=Senior)

19. Texas A&M University Assessment & Evaluation Results Knowledge of Team Design Process, Teamwork & Communication 1 Freshmen vs. Seniors (Baselines -- Beginning Fall 2001 Samples) AERO CRCD Students 0—5.5 ScaleDesign Process Team WorkCommunication Freshmen 2 (n=88) Mean Scores 4 2.722.651.76 Std. Dev.11.279.177.11 Seniors 3 (n=23) Mean Scores3.302.302.04 Std. Dev.11.467.948.52 1 Adapted TIDEE Project Mid Program Assessment Instrument #1, Design Knowledge 2 Members of one ENGR 111 class which utilized AERO CRCD Project curriculum 3 Members of AERO Senior Design course 4 Scores given on a scale of 0 – 5.5, with 0=no knowledge & 5.5=exceptional knowledge

20. Texas A&M University Assessment & Evaluation Results Knowledge of Team Design Process, Teamwork & Communication One Semester Improvement in Freshmen 1 Design Assessment Instruments 0—5.5 ScaleDesign Process Team Work Communication Team Design Knowledge Pre-Test 2 (Sept. 2001) Mean Scores 4 2.722.651.76 Std. Dev.11.279.177.11 Reflective Essay on Team Design Experience-Based Knowledge 3 (Dec. 2001) Mean Scores3.493.453.29 Std. Dev.8.096.937.34 1 Members of one ENGR 111 class which utilized AERO CRCD Project curriculum, Fall 2001 2 Adapted TIDEE Project Mid Program Assessment Instrument #1, Design Knowledge (n=88), Sept 2001 3 Adapted TIDEE Project Mid Program Assessment Instrument #3, Reflective Essay (n=87), Dec 2001 4 Scores given on a scale of 0 – 5.5, with 0=no knowledge & 5.5=exceptional knowledge