Smart Structures in Engineering Education

Stefan Hurlebaus M.ASCE1, Tim Stocks2 , and Osman E. Ozbulut M.ASCE3

Abstract As technologies evolve, academia must follow suite to best use these technological strides to advance structures for better reliability and overall safety. One such advancement is subsumed under the title “smart structures” which uses smart materials possessing unique qualities to collectively generate an adaptive structural system. While the smart structure concept is widely used in the mechanical and aerospace engineering industry, the civil engineering community has been slow to adopt because of system complexity and high cost. In addition, there are still many universities that do not include smart structures in their curricula, which has hindered their broad implementation into modern structures. Therefore with the development of a specialized course on smart structures described here we hope to further the use of smart technologies in engineering education and ultimately the real world. Therefore, with the development of a specialized course on smart structures described here, we hope to further the use of smart technologies in engineering education and ultimately the real world. Included in the background is a look at the institutions that have already provided classes on the subject and how one such university (Texas A&M University) organized the class including lab demonstrations, homework, projects, lecture outline, and even student evaluations of the class. Keywords: Smart Structures, Adaptive Structures, Intelligent Structures, Education 1

Assistant Professor, Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 778433136. 2 Structural Engineering EIT, Jaster Quintanilla, San Antonio, TX 78209. 3

Doctoral Student, Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843-3136. 1

Introduction Smart structures as a concept has scientific literature dating back to 1970 but has only recently gained world-renowned recognition in the academic arena. Smart structures integrate various elements such as sensors, actuators, power sources, signal processors, and communications network to sense and react to their environment in an expected and desired manner. Smart structures not only support or resist mechanical loads but also may reduce vibration, mitigate acoustic noise, monitor their own integrity while in operation and throughout their lives or alter their shape or mechanical properties under external stimuli. In general, smart structures incorporate smart materials. Smart materials are not smart in and of themselves but are smart in their adaptation into structural systems. Smart materials are further defined as capable of automatically and inherently sensing or detecting changes in their environment and responding to those changes with some kind of an actuation or action. Additionally, they posses or show a survival strategy in the sense that the appropriate actions or actuations initiated in response to environmental changes sensed or detected must preserve the sustainability of the states of material under consideration. With the increasing demands for high structural performance, smart material and structural systems have received considerable attention from different engineering disciplines due to their appealing characteristics such as immediacy (ability to respond in real-time), efficiency, self-actuation, adaptability, self-monitoring and self-healing, and decision making. The extensive reviews on the application of smart systems in the fields of aerospace and aeronautical, mechanical and civil engineering can be found in Giurgiutiu (2000), Giurgiutiu et al. (2002), Chopra (2002), Holnicki-Szulc and Rodellar (1999), Hurlebaus and Gaul (2006), and Cheng et al. (2008).

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At the university level, engineering colleges have recently begun to incorporate into their curriculums ‘smart structure’ classes. Nihon University of Japan incorporated smart materials and structural systems into its international research studies with American students since the summer of 2002. The University of Stuttgart at Germany offered its first smart structures course in the summer semester of 2003. The students of different educational background including engineering cybernetics, aerospace engineering and mechanical engineering enrolled to the course. The enrollment to the course increased from 8 in summer 2003 to 26 in summer 2004, which demonstrates increasing student’s interest to the course. Among nationwide academic institutions, Lehigh University debuted its first smart structures class in the spring of 2006 (Zhang and Lu, 2008). A year later in the spring of 2007, the University of Texas at Arlington offered a graduate course based on intelligent structural materials. When the Zachry Department of Civil Engineering at Texas A&M University first introduced the graduate course ‘Smart Structures’ as a technical elective into its curriculum in fall 2006, a total of 11 students from various engineering departments including civil, mechanical, and aerospace engineering enrolled. The second time the course was taught in fall 2008 with a total of 16 students. Upon completion of the course, the instructor asked to the students to participate in a course evaluation resulting in an overall positive feedback of the course. It is clear that as smart structures pave their way into future structural endeavors, Texas A&M University will be nurturing the much needed education in smart structures. This paper presents the development and implementation of a specialized graduate level course. The course is developed to meet the need of introducing the rapidly evolving technologies in smart material and structural systems to graduate level students within the engineering departments. In what follows, a brief description of the course is first given. Then,

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the objectives of the course are presented. The teaching methods and course materials are thoroughly described. Following this, a number of demonstration models used during lectures to increase student understanding of the concepts demonstrated and to increase student enjoyment of class are presented. Discussed next are the description of course activities other materials used for the course. The paper is concluded by discussing several different methods used for analyzing and documenting student learning.

Course Description The course “Smart Structures" is an elective course for graduate students majoring in civil engineering and ocean engineering but also open to other engineering disciplines and taught at the Zachry Department of Civil Engineering at Texas A&M University. This course is an introductory course on smart structures technologies and covers a variety of subjects associated with smart materials and structures. The graduate course catalog lists the subjects presented in this course as follows: “Definition of smart structures, structural dynamics of smart systems, constitutive theory of smart materials, measurement techniques, modeling of smart structures, signal processing methods, structural control concepts for smart systems, shunted piezoelectricity, active vibration isolation, semi-active damping, active vibration control, active structural acoustic control, structural health monitoring, and shape adaptation”. The prerequisites of this course are graduate standing in engineering and completing introductory courses in Dynamics and Vibrations, Mechanics of Materials, Physics and Differential Equations.

Objectives of the Course The objective of this course is to have students learn the basic aspects of smart structural systems including smart materials, sensor technology, signal processing methods, modeling of smart structures and structural control concepts and expose them diverse and rapidly expanding 4

applications of smart materials and technologies. In particular, there are seven major goals that are aimed to be accomplished throughout the course. 1. Students will leave this course with an understanding on the definition of smart structures and their components and on the categorization of smart materials. The students will be able to answer questions such as: •

What makes a structure smart?

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What characteristics distinguish smart materials from other materials?

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What are the main classes of smart materials?

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In what kinds of applications (sensor, actuator, transducer etc.) the unique capabilities of each class of smart materials can be exploited?

To accomplish this goal, the instructor presents a comprehensive coverage of the definition of smart structures together with introductory information on smart structural components such as sensors, actuators and controllers and their integration in a structure. Also, the instructor provides information on piezoelectric materials, electrostrictive materials, magnetostrictive materials, shape memory alloys, magneto- and electrorheological fluids and chemomechanical materials. The discussion for each smart material includes the fundamental properties of the material and the potential use of it in different applications. 2. Students will identify different sensor technologies and describe their applications and limitations. The students will be able to answer questions such as: •

What are the main types of sensor?

•

What is the basic operating principle of each sensor type?

To realize this goal, the instructor provides essential information on most commonly used sensor types such as strain gages, accelerometers, piezoelectric sensors, laser Doppler

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interferometer, wireless sensors, optical fiber sensors and wavelength-based sensors. Furthermore, relevant design application and limitation of each sensor type are presented. 3. Students will be able to analyze and design basic systems that incorporate smart materials. The students will learn: •

How to integrate smart materials to structures.

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How to model smart structures.

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How to design smart structures.

To achieve this goal, the instructor presents sample analysis and design problems in class and assigns short design problems as homework. Moreover, each student makes an individual term project where the student applies smart technologies to a specific problem. Throughout the project, the student gain considerable practice and confidence in modeling, analysis and design of smart structures. 4. Students will be able to explain basic signal processing methods and structural control concept. The students will learn: •

How to analyze non-stationary signals.

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How to design an output feedback and a state feedback controller.

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How to develop an estimator or observer.

To accomplish this goal, the instructor presents signal analysis techniques such as short-time Fourier transform, wavelet transform and Hilbert-Huang transform and introduces classical approaches to feedback control systems using state variable representation. 5. Students will discover some important applications of smart materials and structures. The students will be able to answer questions such as: •

What kind of structural control systems do exists for vibration control?

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What is vibration isolation?

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What is structural health monitoring?

To achieve this goal, the instructor describes structural control systems using semi-passive damping, semi-active damping, active vibration control, and active vibration isolation and provides information on such technologies that can be employed to monitor in-service health of structures by detecting and evaluating damage in real time. 6. Students will be able to apply critical thinking effectively to their subject-matter learning and writing. The students will learn: •

How to identify and differentiate questions, problems and arguments.

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How to assess the suitability of various methods of reasoning and confirmation when approaching a problem.

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How to evaluate the quality of evidence and reasoning to draw reasonable conclusions.

To realize this goal, the instructor asks the students to work in small groups during class to solve in-class assignments that require critical thinking, analysis of problems and drawing conclusions. The instructor encourages the students to criticize or defend their arguments with the use of logical reasoning and evidence in discussion of alternative points of view. Also, the instructor prepares homework assignments and exams such that they promote critical thinking. Another method used to teach critical thinking is to require that students complete a term

project where students learn to organize their thoughts, contemplate their topic, assess their findings, and present their conclusions in a persuasive manner. 7. Students will acquire key communication skills needed to do scientific research. The students will learn:

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How to present the results in a scientific manner.

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How to write a scientific document.

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How to write up scientific reports

To accomplish this goal, the instructor teaches effective scientific communication skills and describes standard scientific writing structure. The homework assignments, reports, and term project serve as tools to exercise these communication skills. The students get immediate feedback and are able to improve their skills.

Teaching Methods The teaching method chosen for this class is (1) to discuss the material in general (verbal); (2) to write key points on the white board (visual); and (3) to encourage the students to transmit these key points in form of note taking. Encouraging the students to copy the material presented gives them comprehensive study material and references as well as stimulates retention of the key issues. Sample problems are presented in class by actively interacting with students during the solution process. This promotes them to analyze, synthesize and evaluate problems on their own. Before the midterm and the final exam, special review sessions (outside regular class) are offered. During these voluntary review sessions exam related sample problems are solved by intensively involving students in discussions. Such review sessions give the opportunity to spend more time on a problem than during regular class and so to better prepare students for the tests.

Course Materials Several excellent textbooks in the field of smart structures, adaptive structures, intelligent structures, active vibration and noise control exist (e.g. Bies and Hansen 1996, Clark et al. 1998, Elliot and Nelson 1995, Fuller et al. 1996, Gautschi 2002, Janocha 1999, Preumont 1997, 8

Srinivasan and McFarland 2001). Most of the textbooks cover aerospace, biomedical, and/or mechanical engineering applications. Moreover, civil engineering students usually possess little or no knowledge of the field of control and/or signal processing. Therefore, there is a need to provide the basic fundamentals of smart structures combined with applications from the field of the civil engineering. In order to fill this gap and prepare lecture notes that can be used as a good reference in all engineering disciplines, a 256-page booklet of lecture notes entitled ‘Smart Structures - Fundamentals and Applications’ (Hurlebaus, 2005) is provided to the students in this specific course. Students are expected to read the related chapter before class and understand most of the content. Readiness Assignment Tests (RATs) are a strong encouragement for them to do this. The content of the lecture notes is briefly described in Table 1 which also reflects the course syllabus. The fundamentals include an understanding of structural dynamics such as free and forced vibrations of single- and multi-degree-of-freedom systems.

A review of the basic

equations for a linear elastic continuum, including the strain-displacement relationship, the conservation equations such as the balance of linear and angular momentum, and the generalized Hooke’s law is provided. Wave propagation is an important part of nondestructive testing commonly used in smart systems because propagation of waves account for much of the damages in structural systems. An understanding of wave propagation in elastic solids is therefore necessary in the detection of structural damages.

Covered in this course is the

propagation of waves in infinite and semi-infinite media, differing wave propagation theories of continuous and non-continuous systems such as plates, rods and beams.

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Damping has an important role in applications of wave propagation and vibrations as damping forces can greatly affect structural response when dealing with the edge of dynamic system stability limits. Damping of complex materials requires an understanding of linear viscoelastic behaviors like relaxation and creep, and the corresponding models used to represent inelastic material behavior. Also friction damping which is more common among moving structural parts must be studied more deeply as to the many different mechanisms which make up this friction phenomena, and to apply classical models of frictional damping. Then the course moves into more directly related topics such as “smart materials” to discover the material properties which have given so much drive to the field of intelligent design. The “smart materials” are covered in depth: piezoelectrics, electro- and magnetostrictive solidstate energy-transformers, metallic shape memory alloys, electro- and magnetorheological liquids, and also polymers having chemomechanical energy transformers. Each material is reviewed for its properties of sensing or actuating and the parameters or limitations such as temperature and electrically controlled actuation. Understanding the capabilities of these materials become important to grasp the sensors which have been made from these materials as well as other smart technologies. In order to create a structural system that adapts to environmental changes, one must be able to detect such changes. Sensor technology is largely based on the ability of materials to convert mechanical motion into electrical signals to some degree or another.

These sensors are piezoelectric

accelerometers and force transducers, foil type strain transducers, and optical fiber sensors. Strain gages have an extensive range able to produce highly sensitive strain transducers capable of isolating exact material strains such as shear, axial or torsional. Optical fiber sensors which ranges from intensity based to phase modulated and wavelength based have the capacity to

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operate in highly electromagnetic environments creating a range of sensors from accelerometers to even pressure gages. Also covered is a quick look into laser Doppler interferometry which is a contact-less sensor able to detect surface vibrations and is used to relate changes in surface waves with structural damages (Hurlebaus and Jacobs 2006). Modeling of smart structures based on the theory of distributed piezoelectric actuators is another way to understand structural complexities and here it is covered through the use of piezoelectric elements sandwiching structural components in differing configurations. When dealing with signal producing sensors it becomes important to understand different processing methods to isolate and clean up signals for more accurate signal interpretations. In this course only basic signal analysis is considered including for stationary signals, Fourier series and Fourier transform, and for time varying signals, time-frequency representations such as, short-time Fourier transform (STFT), Wigner-Ville distribution (WVD), smoothed Wigner-Ville distribution (SWVD), wavelet transform (WT), chirplet transform (Kuttig et al. 2006), empirical mode decomposition (EMD) and Hilbert spectrum. Lastly, fuzzy arithmetic which is basically used to determine the influence of model parameters whose values are uncertain is also covered. Another important subject in the development of smart structural systems is control concept. As an introduction to control theory, the topics covered in this course include state variable, output feedback, state feedback, state estimation and observers, and modal control. In particular, the conventional approach to feedback control systems with multiple control sensors and multiple control actuators using the state variable description is presented together with a discussion of observers. Also, additional topics such as stability, controllability, observability as well as spillover effects are discussed.

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Once fundamental concepts of smart structures are covered, some applications of smart materials and systems are presented in the rest of the course. While the first part of the course is designed to introduce a semi extensive background of knowledge, the second part of the course presents potential applications of this knowledge which captured much more of the student’ interests. Some of the applications mentioned in the course are discussed below. Semi-passive damping which is an adaptation of passive damping systems commonly uses piezoelectric elements distributed throughout a system in conjunction with tuned electrical circuits to increase the damping of a structure. In this course, the placing of piezoceramic elements in a resistively-shunted network is discussed for optimization and also the results of a simple experimental setup are presented. Semi-active damping uses dry friction already available in structural systems such as joints with adaptations to increase the energy dissipation inherent in those joints. By adding stacked piezoceramic actuators to a joint, it is possible to create two very distinctive and effective damping joints such as “the lap joint” and “the rotational joint”, which are capable of varying the friction within the joint. Active vibration control uses real time data of changing modal parameters as an input into an actuation through the use of modal filters and control laws. As an example of active vibration control, this course covers modal control strategies for active vibration isolation and suppression. Structural health monitoring (SHM) is commonly a class in and of itself but in the context of smart structures it becomes important to touch on the ability for smart materials to aid in SHM. In this course, passive sensing diagnostics such as delamination detection with laser

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Doppler vibrometers are given as an example as well as active sensing diagnostics using PVDF films and also using laser ultrasonics. Lastly, as an example of aerospace engineering application, shape adaptation of an aircraft is introduced. Shape adaptation is capable of reducing the drag of aerodynamic crafts by adapting the foil structure of a wing for example, to make subtle changes in response to changing air currents.

Course Activities Course activities include lecture as well as use of demonstration models described thoroughly in the next section. Extensive homework problems that cover about a week of material and help students understand the concepts are assigned after the presentation of the material in class. A qualitative grading rubric that facilitates to precisely define instructor expectations is used to grade the homework. A midterm exam is given during the semester. On a voluntary basis the students can do a midterm exam correction. The process consists of three parts as described by Cress (2002). First, students correct their midterm exam. Second, they conduct a failure analysis of their mistakes to examine why they made them. Finally, students create an avoidance strategy to minimize the likelihood of repeating the same or similar mistake. They submit the corrections along with the comments documenting the process. By completing the midterm exam correction exercise students recoup as many as one half of the points lost. Students are asked to complete a term project assignment. The objective of this term project is to give students the opportunity to research a smart structure topic, which interest them. Several other objectives are to help students to improve their technical writing skills, provide them with practical experiences in several aspects of scientific investigation, help them to understand a review process that is how to constructively, yet critically, review scientific reports. The project

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includes writing a proposal in the field of smart structures according to National Science Foundation standard including project summary, project description, references, resume and table of contents. The students submit three hardcopies of the proposal to the instructor and the draft papers are reviewed by the instructor and two of their classmates. The students then receive the reviewer’s comments and have time to make appropriate changes to the paper to reflect the comments and resubmit an improved version of the proposal. The project grade consists of the quality of the first version of the proposal, the reviews and the final version of the proposal. At the end of the semester the students can work on three extra credit problems. Each problem is worth 1 point on the final average. The extra credit problems help the students to further occupy with the material and prepare for the final.

Demonstration Models Interactive demonstrations enable students to become more actively engaged in a lecture and provide unique opportunities for critical thinking and student reflection. Students' interest is peaked if they are asked to make predictions and vote on the most probable outcome of a demonstration before it is done. When used thoughtfully, in-class demonstrations can better illustrate important concepts than a straight lecture, and can provoke students to think for themselves. In addition, demonstrations employ physical models which are smaller and simpler in scope than the real system they mimic. This allows instructor and students to focus in on key aspects of the system's behavior. This simplicity also makes it easier comparatively for students to manipulate, measure, and modify the model, than it would be in a real-world system. For the class several demonstration models are developed which are described in the subsequent sections.

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Smart Layers for Damage Diagnostics Smart layers which consist of a piezoelectric film are frequently used as a self-sensing actuating layer (see Fig.1). Often this thin layer is made of a polyvinylidene fluoride (PVDF) copolymer which is better suited for structural monitoring compared to conventional films because of its sprayed on application. Smart layers made of the PVDF can be an important tool for the detection of cracks and any surface defects, ranging from composite delamination to ferric corrosion (Hurlebaus and Gaul 2004). Using smart layers within the class room is an effective way of demonstrating the applicability of piezoelectric films as both a sensor and a control in ultrasonics. Smart Joints Smart joints which are shown in Fig. 2 are another structural integration of piezoelectric elements for which certain nodes in a structure are modified with semi-active capabilities. These smart joints are passive systems relying on the interfacial frictional force to dissipate energy. The dry friction within a joint is controlled by varying the normal force with a piezoelectric stack actuator and a load cell for algorithmic adjustments (Karnopp et al. 1974; Gaul and Hurlebaus 2008). Active Vibration Isolation Technologies today have become sensitive enough to be limited by the vibrations of Earth's crust stemming from severe weather over some of the world's oceans. This type of sensitivity requires the means to dampen these vibrations along with unnatural vibrations (e.g. automobile traffic, wind induced building sway etc.). Active Vibration Isolation (AVI) is an element of smart structures essential for highly sensitive technologies. AVI is a spring mass system with low-pass characteristics affective at reducing excitation frequencies higher than the

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eigenfrequency of the spring mass system (Kerber et al. 2009).

The active vibration isolation

system depicted in Fig. 3 uses the replacement of a typical passive viscous damper with a magnetic actuator. This system is a great tool for teaching students about applied dynamic solutions and demonstrating frequency sweeps to identify structural eigenfrequencies. Shape Memory Alloys Shape memory alloys (SMAs) are named for their ability to recover from tremendous strains by changing the alloy’s crystalline structure through a change in temperature (shape memory effect) or stress (superelastic effect). The elevation of temperature changes the alloy from one structural phase (martensite) to another structural phase of higher modulus (austenite). This change in its structural characteristic lends credit to its advantage as a thermal activated actuator, which can even be heated by an electrical current. Electrical control means SMA actuators can be used effectively as active elements used for structural control or some other applications. Also, since superelastic SMAs possess considerable energy dissipation capacity and re-centering ability, they can be used passively in seismic control of civil engineering structures (Ozbulut and Hurlebaus, 2010). Fig. 4 illustrates an SMA device and its installation to a three-story frame as diagonal bracing element. The device simply consists of multiple bundled superelastic NiTi wires wrapped around two wheels. Within the confinements of this course, SMAs are evaluated on strength, resilience, and hysteretic characteristics for different alloy compositions and transition temperatures (i.e. metallurgical procedures). Wireless Sensors Distributing sensors into a structural system allow continual monitoring of the structural performance and reliability. Wireless sensors are becoming a popular method for this structural health monitoring because they are cheaper, scalable, easier to install, and less susceptible to

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exterior interference than wire sensors. Within a wireless sensor network there exists in-network data processing, capable of gathering data from its sensors and fusing it into a high-level sensing result (see Fig. 5). This demonstration is used as a way to combine accelerometer data from wireless sensors and compare different network topologies such as physical nodal arrangement, information protocol/clustering, and sleep cycle management, for energy efficiency and data reliability. Monitoring of Overhead Transmission Lines Overhead power lines are periodically inspected using both on-ground and helicopteraided visual inspection. With this demonstration model, the feasibility of continuous, on-line monitoring of power lines using ultrasonic waves is shown. A sending/receiving transducer located on the power line generates an ultrasonic wave in the cable. A defect in the cable will cause a portion of the incident ultrasonic wave to be reflected back to the transducer (see Fig. 6). Data acquired by the transducer can be relayed to a central communication node via a wireless transmitter (Branham et al. 2006, Benz et al. 2003). The methodology presented can also be applied to other cable monitoring applications such as bridge cable monitoring. Magnetorhelogical Dampers Semi-active devices have attracted considerable attention for the seismic protection of structures in recent years. These devices only absorb or store the vibratory energy and they do not input the energy to the system. Therefore, they do not induce adverse effects on the stability of the system. The versatility and adaptability of the active devices and the reliability of the passive devices are offered by semi-active devices. One of the most promising semi-active devices is the magnetorheological (MR) damper. A schematic diagram for the MR damper is shown in Fig. 7. MR dampers are controllable fluid devices that employ MR fluids whose

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rheological properties may be rapidly varied by an applied magnetic field. They can provide large force capacity, high stability, robustness and reliability. Because of their mechanical simplicity, high dynamic range and low power requirements, they are considered as good candidates for reducing the structural vibrations (Kim et al. 2009). In this course, several control strategies such as simple adaptive control and fuzzy logic control that are employed to determine the command voltage of MR dampers are introduced to the students to illustrate the advantageous use of MR dampers for seismic control of multi-story buildings.

Other Course Material CEnotes is an extremely flexible and powerful tool that allows the instructor to distribute, display, and retrieve class related materials over the World Wide Web. This tool was developed by Maxwell et al. (2003). It allows you to provide a weekly schedule, give assignments on the internet, to write an email to the entire class, to record the student’s grade, incorporate manuals, handouts, extra information, and many other sources into questions. During this course, CEnotes is effectively used to communicate with students, organize the classes, inform the students on their assignments and grades, and provide various supplementary handouts. The instructor archives both process and product of course activities in CEnotes enabling access to course content beyond the timeframe of the class. Moreover, students can browse and retrieve the material organized by: topic, by function, or by schedule according to their needs. Student surveys indicate that they want the material organized according to their learning styles, background, and personal desires (Maxwell 2003). Students can also retrieve individual grade reports enabling quick feedback on homework assignments and exam scores. At the beginning of the course the students are asked to complete a student information form. This gives information on what the students expect during the course and what the

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instructor has to know of the students. Furthermore, it includes an assignment return policy that states graded work, other than major exams, is returned by passing it out in a single bundle for each student to retrieve their own paper.

Analyzing and Documenting Student Learning Several different criteria are used to evaluate student learning, understanding, and attitudes in this course. They include: student assessment of learning gains, homework, projects and exams, and student’s comments. The student’s comments on the question “What are the most positive aspects of this course?” are as follows: “It exposes us to the vast possibilities of smart structures”“Very different from other structural engineering courses, learned something completely different and new”, “I like that his class takes material from other courses and showed how the information could be applied to real situations”, “The course is the leading edge of civil engineering in new developing area. Civil engineering is shifting from traditional design to smart interactive with outside environment.”, “This course fulfills students’ need to catch up tomorrow’s technology. It provides students essential material.” and “Fundamental are elaborated very clearly, real world applications are used to explain concepts” Students completed homework assignments, readiness assignment tests, exams, and projects throughout the semester. The mean, standard deviation, and range of class marks recorded in all evaluations are listed in Table 2 for two different semesters when the course taught. The high marks in assignments, midterm and final exam demonstrate the student’s understanding of the material by solving problems in a way the instructor expects. Also, the average marks for the project are 77.4% for Fall 2006 and 95.1% for Fall 2008. This suggests that the students successfully applied their knowledge to a research project. A more detailed examination of the evaluations reveals that the stated objectives of the course were achieved in

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both semesters. For example, Problems 8 and 10 on the midterm exam and Problem 8 on the final exam directly assess course objective #2 in Fall 2006 and Fall 2008. On average, students scored 85% and 92% on the midterm exam questions and 93% on the final exam question. Also, Problem 5 on midterm exam and Problems 2 and 9 on the final exam directly assess course objective #3. The average marks were 90% for the midterm exam question and 95% and 91% for the final exam questions. Therefore, we assess that objective #2 and objective #3 was successfully achieved. Similar conclusions can be drawn for other objectives. The students’ enthusiasm is also demonstrated by the fact that 8 out of 11 students taking this course in Fall 2006 and 9 out of 16 students taking this course in Fall 2008 selected a research topic in the field of smart structures for their graduate study. The remaining students either picked a topic outside the field or pursued a master of engineering which is a course work based degree not requiring any research at all. This demonstrates that the student’s interest in the field of smart structures was fostered and the course highly impacted the student’s further career.

Conclusions By setting a precedent to include smart materials and intelligent design in the engineering curriculums, structures only stand to gain with tighter operational tolerances without sacrificing our current level of safety from failure. Economically this means that the upfront costs of structures will be reduced due to the reduced safety factors in initial designs. The reliability of structures will greatly improve as structures adapt to even unknown structural characteristics and construction flaws. From a safety stand point the use of smart materials and intelligent design shifts the way engineers monitor structural health from ‘acute care’ to ‘preventative medicine.’ With the use of preventative structural health techniques structures are guaranteed longer design lives, because

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this ‘early warning’ type system allows engineers to detect problems in a stage when repairs are easy and economically cheaper then complete system overhauls. In this paper, a graduate level course that aims to integrate smart structural systems into engineering curricula for engineering departments is described. In particular, the “Smart Structures” course taught at the Zachry Department of Civil Engineering at Texas A&M University is thoroughly introduced by providing the course description, the course objectives, the course activities, the demonstration models as well as the lecture notes. For the improvements of structural systems in the future, it is held against the education system to develop the knowledge and spur the beginning of intelligent design through the use of ‘smart’ adaptive structural classes. As universities drive the edge of intellect in the general field of research, it behooves them to look to smart materials as the next forefront in structural systems.

References Benz, R., Niethammer, M., Hurlebaus, S. and Jacobs, L.J. (2003): Localization of Notches with Lamb Waves, Journal of Acoustical Society of America, 114(2), 677-685 Bies, D.A. and Hansen, C.H. (1996): Engineering Noise Control: Theory and Practice; E & FN Spon, London Branham, S.L., Wilson, M.S., Hurlebaus, S., Beadle, B.M., Gaul, L. (2006): Nondestructive Testing of Overhead Transmission Lines. Conference on Damage in Composite Materials, Stuttgart Cheng, F.Y., Jiang, H., Lou, K. (2008): Smart structures: Innovative systems for seismic response control. CRC Press, Boca Raton, FL. Chopra, I. (2002): Review of state of art of smart structures and integrated systems, AIAA Journal, 40, 2145–2187

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Clark, R.L.; Saunders, W.R., and Gibbs, G.P. (1998): Adaptive Structures: Dynamics and Control; John Wiley & Sons, Inc. New York Cress, D. (2002): The F Word in the Classroom: Fail and Learn, Proceedings of the 2002 American Society for Engineering Education Annual Conference & Exposition, Montreal, Quebec, Canada Elliot, S.J. and Nelson, P.A. (1995): Active Control of Sound, Academic Press, London Fuller, C.R., Elliot, S.J., and Nelson, P.A. (1996): Active Control of Vibration, Academic Press, London Gaul, L., Hurlebaus, S., Albrecht, H. and Wirnitzer, J. (2008): Enhanced damping of lightweight structures by semi-active joints. Acta Mechanica, 195, 249-261 Gautschi, G. (2002): Piezoelectric Sensorics: Force, Strain, Pressure, Acceleration and Acoustic Emission Sensors, Materials and Amplifiers, Springer Verlag, Berlin Giurgiutiu, V. (2000): Review of Smart-Materials Actuation Solutions for Aeroelastic and Vibration Control, Journal of Intelligent Material Systems and Structures, 11:525-544 Giurgiutiu, V., Bayoumi, A.-M. E. and Nall, G. (2002): Mechatronics and smart structures: emerging engineering disciplines for the third millennium, Mechatronics 12, 169-181. Holnicki-Szulc, J. and Rodellar, J. (1999): Smart structures: Requirements and potential applications in mechanical and civil engineering. NATO Science Series, Kluwer Academic Publishers, Dordrecht, The Netherlands Hurlebaus, S. (2005): Smart Structures - Fundamentals and Applications: Lecture Notes, 256 pages, Zachry Department of Civil Engineering, Texas A&M University Hurlebaus, S. and Gaul, L. (2004): Smart Layer for Damage Diagnostics, Journal of Intelligent Material Systems and Structures, 15, 729-736

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Hurlebaus, S. and Gaul, L. (2006): Smart structure dynamics. Mechanical Systems and Signal Processing, 20(2), 255–281 Hurlebaus, S. and Jacobs, L.J. (2006): Dual-probe laser interferometer for structural health monitoring, Journal of Acoustical Society of America, 119(4), 1923--1925 Janocha, H. [ed.] (1999): Adaptronics and Smart Structures: Basics, Materials, Design and Applications, Springer Verlag, Berlin Karnopp, D. C., Crosby, M. J. and Harwood, R. A. (1974): Vibration control using semiactive force generators. ASME Journal of Engineering for Industry, 96(2):619–626 Kerber F., Hurlebaus S., Beadle B.M., Stöbener, U. (2007): Control concepts for an active vibration isolation system. Mechanical Systems and Signal Processing, 21 (8), 3042-3059. Kim, Y., Langari, R. and Hurlebaus, S. (2009): Semiactive nonlinear control of a building using a magnetorheological damper system. Mechanical Systems and Signal Processing, 23 (2), 300-315 Kuttig, H., Jacobs, L.J., Hurlebaus, S. and Niethammer, M. (2006): Model-based Signal Processing of Dispersive Waves with Chirplets. Journal of Acoustical Society of America, 119(4), 2122- 2130 Maxwell D., Morgan, J. and Fowler, D. (2003): Developing a Multi-Author Web Site to Support Large ACL Engineering Classes, ASEE, Nashville, Tennessee. Ozbulut, O.E., and Hurlebaus S. (2010): Evaluation of the performance of a sliding-type base isolation system with a NiTi shape memory alloy device considering temperature effects, Engineering Structures 32, 238-249. Preumont, A (1997): Vibration Control of Active Structures - An Introduction; Kluwer Academic Publishers, Dordrecht

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Srinivasan, A.V. and McFarland, D. M. (2001): Smart Structures - Analysis and Design, Cambridge University Press Yang, G., Spencer, B.F., Carlson, J.D., Sain, M.K. (2002): Large-scale MR fluid dampers: modeling and dynamic performance considerations, Engineering Structures 24, 309–323. Zhang, Y. and Lu, L.W. (2008): Introducing Smart Structures Technology into Civil Engineering Curriculum: Education Development at Lehigh University, Journal of Professional Issues in Engineering Education and Practice, 1, 41-48

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List of Tables Table 1. Course Syllabus Table 2. Mean, standard deviation, and range of class marks recorded in all evaluations

25

Table 1. Course Syllabus Topic Introduction: Definition of Smart Structures, History Structural Dynamics: Vibration of Discrete Systems (Free and Forced Vibration of a SDOF, Free and Forced Vibration of a MDOF), Linear Elasticity (Strain-Displacement Relationship, Stress, Mass Balance, Balance of Linear Momentum, Balance of Angular Momentum, Generalized Hooke's Law), Wave Propagation in Elastic Solids (Infinite Media, Semi Infinite Media, Double-bounded Media), Wave Propagation in Plates (Exact Theory, Mindlin Plate Theory, Classical Plate Theory, Comparison), Wave Propagation in Beams (Timoshenko-Beam Theory, Bernoulli-Euler Beam Theory), Wave Propagation (Rods, Phase velocity versus group velocity), Vibrations of Continuous Systems (Rods, Beams, Plates) Damping: Classification of Damping, Linear Viscoelasticity: Memory Integrals, Relaxation, Creeping Maxwell Model, Kelvin-Voigt Model, 3-Parameter Model, N-Parameter Model, Frequency domain representation; Friction Damping: Phenomena, Modeling, Classical Models, LuGre Model Smart Materials: Piezoceramics, Piezoelectric Polymers, Electrostrictive Material, Magnetostrictive Material, Shape Memory Alloy (SMA), Magneto- and Electrorheological Fluids: Magnetorheological Effect, Electrorheological Effect, Chemomechanical Materials Sensor Technology: Piezoelectric Sensors, Force Cells, Accelerometers, Charge amplifiers, Laser Doppler Interferometer, Strain Gages, Optical Fibers, Optical Fiber Sensors, IntensityBased Sensors, Phase Modulated Optical Fiber Sensors, Wavelength Based Sensors Modeling of Smart Structures: Sandwich Beam (Symmetric Configuration, Antisymmetric Configuration, Asymmetric Configuration), Sandwich Plate (Antisymmetric Configuration, Asymmetric Configuration) Signal Processing Methods: Fourier Series, Fourier Transform, 2D Fourier Transform, Time-Frequency Representations (TFRs) (Short-Time Fourier Transform (STFT), WignerVille Distribution (WVD), Smoothed Wigner-Ville Distribution (SWVD), Wavelet Transform (WT), Empirical mode decomposition (EMD) and the Hilbert spectrum, Reassignment Method, Comparison) Control Concept: Feedforward Control, Feedback Control, PID-Controller, State Variable Approach, Output Feedback and State Feedback, State Estimation and Observers, Modal Control Semi-Passive Damping: Resistive Shunting, Modal Strain Energy Approach Optimal Placement of Piezoceramic Elements, Added Damping and Frequency Tuning, Experimental Setup and Results Semi-Active Damping: Semi-Active Lap Joint, Semi-Active Rotational Joint, Two Beam Model, Controller Design, Friction Observer, Closed Loop System, Experimental Results Active Vibration Control: Modal State-Space Formulation, Modal Control Strategy, Test Object, Controlled Modes, Experimental Setup and Results Active Vibration Isolation: Equation of Motion, Vibration Suppression, Vibration Isolation, Feedforward Control, Feedback Control Structural Health Monitoring: Passive Sensing Diagnostics (Localization and Identification of Impacts) Active Sensing Diagnostics (Smart Layer, Detection of Discontinuities) Shape Adaptation: Aerodynamic Forces on an Airfoil, Concept of Variable Camber

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hour 1 9

3

5

4 4 3

4 2 2 2 2 3 1

Table 2. Mean, standard deviation, and range of class marks recorded in all evaluations Assignments (%)

Midterm (%)

Term project (%)

Final (%)

Fall 06

Fall 08

Fall 06

Fall 08

Fall 06

Fall 08

Fall 06

Fall 08

Fall 06

Fall 08

Mean

93.3

88.7

92.1

93.2

77.4

95.0

94.9

96.1

93.4

95.4

Standard deviation

4.3

10.6

6.2

8.0

38.6

13.2

7.2

6.6

11.6

8.6

Range

84-98

57100

78 100

69 100

0100

50100

78100

80 100

70100

68100

Fig. 1: Smart layer (left) and wind turbines (right)

Fig. 7: Schematic of the MR damper.

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Overall (%)

Transmissibility (dB)

passive MIMO

SISO

Frequency (Hz)

Fig. 3: Active vibration isolation system (left) and transmissibility (right)

Fig. 4: Shape memory alloys and their application as a passive device for structural control

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Fig. 5: Wireless sensor network (left) and wireless sensor (right)

Fig. 6: Piezoelectric ring actuator (left) and overhead transmission lines (right)

Fig. 7: Schematic of the MR damper.

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