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Invited Lectures 16th Brazilian Congress of Mechanical Engineering Engineering for the New Millennium INVITED LECTURES ISBN 85-85769-06-6 XVI CONGRESSO BRASILEIRO DE ENGENHARIA MECÂNICA 16th BRAZILIAN CONGRESS OF MECHANICAL ENGINEERING Invited Lectures SMART STRUCTURES: EXAMPLES AND NEW PROBLEMS Inman, Daniel J. 4 INTERDISCIPLINARY STUDIES IN MECHANICS: A DIFFUSION MODEL FOR THE KNOWLEDGE TRANSFER Bevilacqua, Luiz 14 HOW TO HAVE A BETTER INTEGRATION BETWEEN UNIVERSITIES AND COMPANIES Salej, Stefan D. 24 MECHANICAL CIRCULATORY ASSIST: FROM DISPLACEMENT TO ROTARY BLOOD PUMPS Reul, Helmut 25 ROBOTICS IN SURGERY Slade, Alan 26 APPLICATION OF NON INVASIVE METHODS IN MEDICINE AND IN ENGINEERING Tomasini, Enrico 27 MICROFLUID DYNAMICS Lysenko, Olga 28 THE ROLE OF MATERIALS’ DESIGN IN ENGINEERING DESIGN PROCESS OF PRODUCTS AND THEIR ELEMENTS Dobrzanski, Leszek A. 29 THE Ti+TiN, Ti+Ti(CXNX-1), Ti+TiC PVD COATINGS ON THE ASP 30 SINTERED HIGH SPEED STEEL Dobrzanski, Leszek A. 44 ABRASION IN WEAR AND MANUFACTURING PROCESSES Hutchings, Ian M. 45 COMPARISON OF WEAR RESISTANT MMC AND WHITE CAST IRON Berns, Hans 52 REFRIGERATION AND AIR CONDITIONING SYSTEMS FOR THE NEW MILLENNIUM UNDER THE IMPACT OF ENVIRONMENTAL CHALLENGES Kruse, Horst 61 XVI CONGRESSO BRASILEIRO DE ENGENHARIA MECÂNICA 16th BRAZILIAN CONGRESS OF MECHANICAL ENGINEERING SOME SELECTED PROBLEMS IN SUPERSONIC COMBUSTION Sabel’nikov, Vladimir A. 75 THE ROLE OF TECHNOLOGICAL DEVELOPMENT ON THE BRAZILIAN COMPANY EMBRAER Resende, Hugo Borelli 65 LATTICE-GAS MODELS FOR FLUID FLOW Philippi, Paulo C. 96 ELEMENTS OF INDUSTRIAL HEAT TRANSFER PREDICTIONS Menter, Florian 117 A GENERALISED FRACTIONAL DERIVATIVE APPROACH TO VISCOELASTIC MATERIAL PROPERTIES MESUREMENT AND VIBRATION CONTROL DESIGN Espíndola, José João 128 THE STRUCTURAL DYNAMICS MID-FREQUENCY CHALLENGE: THE GAP BETWEEN FEA AND SEA Arruda, José Roberto de França 131 THE CHALLENGES FOR MACHINE AND MECHANISM DESIGN AT THE BEGINNING OF THE THIRD MILLENNIUM AS VIEWED FROM THE PAST Ceccarelli, Marco 132 OPTIMIZATION OPPORTUNITIES IN THE BRAZILIAN AEROSPACE INSUSTRY Resende, Hugo Borell i 152 ON THE THERMAL ANALYSIS OF MANUFACTURING PROCESSES Komanduri, Ranga 153 FRACTURE OF FUNCTIONALLY GRADED MATERIALS Paulino, Gláucio 178 GRAIN REFINING MECHANISMS OF CAST Mg-Al-Zn ALLOYS Motegi, Tetsuichi 179 MICROFABRICATION OF POLYMER-COMPONENTS AND SYSTEMS. Saile, Volker 184 NEW DEVELOPMENTS IN LASER DOPPLER VIBROMENTER OPTICAL SYSTEMS AND DEMODULATION SCHEMES FOR MEASUREMENTS ON MEMS AND OTHER MICRO STRUCTURES Johansmann, Martin 185 XVI CONGRESSO BRASILEIRO DE ENGENHARIA MECÂNICA 16th BRAZILIAN CONGRESS OF MECHANICAL ENGINEERING SMART STRUCTURES: EXAMPLES AND NEW PROBLEMS Inman, D. J Center for Intelligent Material Systems and Structures Department of Mechanical Engineering 310 NEB, Mail Code 0261 Virginia Tech Blacksburg, VA 24061 Phone:540 231 4709 fax 231-2903 http://www.cimss.vt.edu , [email protected] Abstract: Smart materials, or active materials, offer a host of new solutions to engineering problems in control and identification. In addition they offer new modeling and analysis challenges. Here we examine the use of smart materials in structural applications: called smart structures. An introduction to smart structures and their use in vibration suppression, flight control and structural health monitoring is presented. A summary of the issues and problems of structural health monitoring using smart materials is presented. The article concludes with some thoughts on open problems in smart structures and structural health monitoring. 1. Smart Materials and Structures Evolution processes became recently one of the most important research focuses of applied mathematics and computational modeling. The driving force behind this importance research field is the application it finds mainly in biological, ecological and social systems. This extraordinary advance, I dare to say, is mainly due to the computational capacity at our disposal nowadays. The progress in the development of hard- and software as well, has enabled us with the possibility of dealing with thousands and hundred of thousands equations that appear frequently in the solution of complex systems. As a matter of fact, computational modeling, considered in its broad spectrum, is growing very rapidly, combining the contribution of natural scientists, mathematicians, engineers and social scientists to the solutions of complex problems. This mixing of people coming from different areas of knowledge is creating new interdisciplinary areas that will probably be of fundamental importance in the near future, if not right now. This paper presents a model that is intended to help understanding the process of knowledge transfer among groups belonging to a certain segment of the same society or possibly the interaction process between different societies. The first version of this paper was published a long time ago, in 1980 [1]. After that, no effort was made to elaborate the theory or test the theory against some empirical data. A relatively recent paper was encouraging and has shown that similar ideas were being explored. This reference [2] considers both genotype and phenotype factors to study the evolution of social groups. That is, inheritance and social interaction are both shaping the history of the group. We are interested here in a relatively short period of time, and the horizontal aspect, interaction among individuals or sub- groups constitutes the predominant factor. Despite the limitations of the model, the results are plausible and intuitively consistent. So, if the model doesn't reflect completely the reality nonetheless it allows for some enlightenment that puts in evidence important and some times hidden correlation among concrete facts. If taken judiciously the results could help decision makers to implement important actions to foster the generation and transmission of knowledge. It is never too much to insist that social modeling, where the behavior of human being play a key role should be seen very carefully. It is impossible to model perfectly the behavior of human social groups and frequently we are faced with big surprises. It is a system that admits contradictory outcomes, where adaptation and rebellion walk side by side. In the next sections it is presented a temptative approach to the process of transfer of knowledge. Certainly the model is a simplification but as a first approximation suggests very interesting correlation, particularly the relative importance of knowledge generation, knowledge transmission and learning speed. 2. Structural Health Monitoring Structural heath monitoring (SHM), also called damage detection or diagnostics, is the concept of using structural measurements to determine the condition, integrity or state of a structure. A basic goal of SHM is to determine if a structure is in danger of failing or not. Examples of common objectives of SHM are to determine if and cracks exist in the structure, if bolted or welded joints are intact and up to specification, if there are any holes or other structural damage present in the structure. In some sense one might fit this topic in with non-destructive evaluation (NDE) methods. The difference between classic NDE methodology and SHM is that of immediacy. In NDE parts or systems are taken out of service to be inspected and a goal of SHM is to leave the structure in service while the analysis is performed. An example of current SHM is the NASA space shuttle that undergoes a vibration test (modal test) before and after each flight. Differences in modal information are then used to determine damage incurred during the flight. While not quite an “on-line” system it does capture the function of SHM. Proceedings of COBEM 2001, Invited Lectures, Vol.20, 5 The problem of damage analysis can be sub divided into four sub problems or levels of health monitoring (Doebling, et al, 1998): 1) Detect the existence of damage. 2) Detect and locate the damage. 3) Detect, locate and quantify the damage. 4) Detect, locate, and quantify the damage then estimate its remaining service life. Each level requires more modeling and hence more mathematics in order to solve. The Level 1 problem has numerous solutions listed in the literature and in fact has been implemented in practice. Fewer solutions are available for the remaining topics. Level 4 leads to the emerging area called “Prognosis” which has few solutions and is motivating several large programs in government laboratories. Here we propose to expand this list to include several more possibilities: 5) Combine Level 4 with smart structures to form Self Diagnostic Structures. 6) Combine Level 4 with smart structures and control to form Self-Healing Structures. 7) Combine Level 1 with active control and smart structures to from simultaneous control and health monitoring. Taking the simplified point of view that health monitoring involves looking for changes in a system’s physical parameters (such as mass, damping or stiffness) leads to the observation that much of the mathematics associated with SHM will come from the field of parameter identification. This is clear in the work of Banks et al (1996b) who solve a Level 3 heath-monitoring problem by adapting techniques form identification theory to solve a damage detection problem for simple beams using piezoceramic actuators and sensors, as well as traditional instrumentation. Obviously, each level problem becomes more difficult to solve. The problem of Level 1 can be solved with out any reference to a structural model by using simple signal
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