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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 77843-3136. 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.

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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

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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?

• What characteristics distinguish smart materials from other materials?

• What are the main classes of smart materials?

• 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.

• How to model smart structures.

• 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.

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

• 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?

• 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.

• How to assess the suitability of various methods of reasoning and confirmation

when approaching a problem.

• 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.

• How to write a scientific document.

• 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,

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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 solid-

state 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 helicopter-

aided 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

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22

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23

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25

List of Tables

Table 1. Course Syllabus

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

26

Table 1. Course Syllabus Topic hour Introduction: Definition of Smart Structures, History 1 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)

9

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

3

Smart Materials: Piezoceramics, Piezoelectric Polymers, Electrostrictive Material, Magnetostrictive Material, Shape Memory Alloy (SMA), Magneto- and Electrorheological Fluids: Magnetorheological Effect, Electrorheological Effect, Chemomechanical Materials

5

Sensor Technology: Piezoelectric Sensors, Force Cells, Accelerometers, Charge amplifiers, Laser Doppler Interferometer, Strain Gages, Optical Fibers, Optical Fiber Sensors, Intensity-Based Sensors, Phase Modulated Optical Fiber Sensors, Wavelength Based Sensors

4

Modeling of Smart Structures: Sandwich Beam (Symmetric Configuration, Antisymmetric Configuration, Asymmetric Configuration), Sandwich Plate (Antisymmetric Configuration, Asymmetric Configuration)

4

Signal Processing Methods: Fourier Series, Fourier Transform, 2D Fourier Transform, Time-Frequency Representations (TFRs) (Short-Time Fourier Transform (STFT), Wigner-Ville Distribution (WVD), Smoothed Wigner-Ville Distribution (SWVD), Wavelet Transform (WT), Empirical mode decomposition (EMD) and the Hilbert spectrum, Reassignment Method, Comparison)

3

Control Concept: Feedforward Control, Feedback Control, PID-Controller, State Variable Approach, Output Feedback and State Feedback, State Estimation and Observers, Modal Control

4

Semi-Passive Damping: Resistive Shunting, Modal Strain Energy Approach Optimal Placement of Piezoceramic Elements, Added Damping and Frequency Tuning, Experimental Setup and Results

2

Semi-Active Damping: Semi-Active Lap Joint, Semi-Active Rotational Joint, Two Beam Model, Controller Design, Friction Observer, Closed Loop System, Experimental Results

2

Active Vibration Control: Modal State-Space Formulation, Modal Control Strategy, Test Object, Controlled Modes, Experimental Setup and Results

2

Active Vibration Isolation: Equation of Motion, Vibration Suppression, Vibration Isolation, Feedforward Control, Feedback Control

2

Structural Health Monitoring: Passive Sensing Diagnostics (Localization and Identification of Impacts) Active Sensing Diagnostics (Smart Layer, Detection of Discontinuities)

3

Shape Adaptation: Aerodynamic Forces on an Airfoil, Concept of Variable Camber 1

27

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

Assignments (%)

Midterm (%) Term project (%)

Final (%) Overall (%)

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 57-100

78 - 100

69 - 100

0-100

50-100

78- 100

80 - 100

70-100

68-100

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

Fig. 7: Schematic of the MR damper.

28

Frequency (Hz)

Tran

smis

sibi

lity

(dB

)

passive

MIMO

SISO

Frequency (Hz)

Tran

smis

sibi

lity

(dB

)

passive

MIMO

SISO

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

29

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.