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On possible applications of smart structures controlled by self-stress
ACME-254; No. of Pages 10 archives of civil and mechanical engineering xxx (2014) xxx–xxx
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Original Research Article
On possible applications of smart structures controlled by self-stress W. Gilewski *, A. Al Sabouni-Zawadzka Faculty of Civil Engineering, Warsaw University of Technology, Al. Armii Ludowej 16, 00-637 Warsaw, Poland
article info
abstract
Article history:
Civil Engineering (CE) is one of the many fields of possible implementation of smart or
Received 2 April 2014
intelligent technologies. The present paper is an attempt to specify and estimate problems
Accepted 25 August 2014
and areas of CE suitable for the application of such technologies, with the focus on Bridge
Available online xxx
Engineering (BE). Precise definitions, explanations and classifications of terms used in smart
Keywords:
smart systems and biological ones are indicated. The paper presents some of the research
Smart structure
projects carried out in the field of CE, according to the current state-of-the-art. Concepts of
Structural control
smart bridges are proposed and several examples of structural control performed on space
Tensegrity
trusses and tensegrity structures with self-stress are introduced.
technique are introduced and components of smart systems are defined. Analogies between
Self-stress
Examples of structural control presented in the paper show that characteristic displacements of the analysed structures may be reduced by changing the prestressing force applied to the single modules, which are a part of the structure. Results of the performed analysis indicate that tensegrity structures are much more prone to the changes in the value of prestressing force than truss structures, which makes them a promising solution as far as structural control is concerned. # 2014 Politechnika Wrocławska. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.
1.
Introduction
Engineering structures, such as buildings or bridges, are subject to various actions, among which the most dangerous ones are accidental loads. It may be a challenge for an engineer to design a structure that would react to such accidental loading by modifying its own properties. It is possible with the use of smart technologies. Such intelligent technologies apply to both materials and structures. However, considering the immense costs of implementing
smart materials into structural elements, the authors focus on structural smartness rather than material one. The present paper discusses possible applications of smart technologies in the field of CE, with the focus on BE. The concepts of smart structures, materials and systems, as well as other terms used in smart technique are precisely defined and classified. The study introduces principal elements which make the system smart and it indicates analogies with biological systems. Several applications in CE are presented and a concept of a smart bridge is proposed.
* Corresponding author. Tel.: +48 22 2345753. E-mail address: [email protected] (W. Gilewski). http://dx.doi.org/10.1016/j.acme.2014.08.006 1644-9665/# 2014 Politechnika Wrocławska. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.
Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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Buildings or bridges can be regarded as smart or intelligent due to the advanced structural health monitoring (SHM) systems, which are very often installed on the existing and newly built structures. However, the authors suggest a slightly different approach to the topic of smart structures. According to the authors, ‘‘smartness’’ should regard a structure itself, not the advanced technologies, with which buildings or bridges are equipped. Intelligent systems, understood in such way, may have various applications: vibration damping, reduction of displacements, acoustic isolation, damage localization and repair, stress reduction, etc. According to the authors' opinion, one of the most interesting possibilities of structural control lies in a control of truss and tensegrity elements through self-stress state adjustment [1–3]. Such structural elements may be used as parts of bigger structures, for example decks or pylons of lightweight footbridges. Results of the performed analyses indicate that the structural displacements might be significantly reduced by adjusting the initial self-stress state in such elements. The paper introduces examples of structural control performed on a space truss with self-stress and a plate based on tensegrity modules. An influence of several self-stress states on displacements is analysed.
2.
General characteristics of smart structures
The topic of smart structures is relatively new [4]. It commenced to be qualified as a distinct field of applied science in the 1980s, when, thanks to the technological progress, scientists joined together in small groups working on the subject. At the beginning, all the research carried out in the area of smart technologies were funded by the government. In the early 1990s private companies started to invest money in this field, providing necessary funding and application possibilities. The cooperation between government research organizations, scientists and companies resulted in several multi-year programs dedicated to the development of smart products and their implementation. The definition of smart structures has been a disputable issue for as long as the topic exists. There are numerous methods of approaching to this subject. Each author [5,6] defines and classifies smart structures in a different way. These differences arise from distinct ways of perceiving work of such structures and methods of their analyses. Some examine a whole structure, while others focus on a specific part of it – a single structural element. Another reason of such differences is the fact that the word ‘‘smart’’ itself has various meanings. According to the dictionary, its original significance was ‘‘stinging, sharp’’. The present meaning of the word ‘‘smart’’ – ‘‘clever, intelligent’’ – has taken over from its original definition the element of quick energetic movement and sharp thought. This original meaning characterizes perfectly the idea of smart structures. In relation to the structures, the word ‘‘smart’’ means: capable of acting in a quick way and making corrections that resemble human decisions, particularly in response to changeable conditions. The present significance, ‘‘intelligent’’, is also applied to the structures, but it is not fully adequate. Intelligence is a human feature and should be reserved for
humans. Although the classification distinguishes a group of very smart structures, calling them intelligent, it does not mean that those structures possess intelligence. The only attribute, which makes them resemble humans, is the ability to learn. There are various types of ‘‘smartness’’. A smart building, for example, can be understood in many different ways. For an occupant of the building it will signify high-tech equipment, such as electronics controlling ambient environment, air conditioning systems, lighting and alarm installations. For an engineer designing the structure, it will indicate that the building is equipped with a smart monitoring and damping system. There are three concepts related to the topic of smart structures (Fig. 1). Smart structures are the structures with the ability to sense and respond adaptively to changes in their environment. This feature distinguishes them from the conventional ones. Whereas the main purpose of the traditional structures is to provide strength and carry loads acting on them, the smart ones adapt in a pre-designed manner to a functional need, modifying their shape, stiffness or damping characteristics in order to minimize deflection and possible damage. Smart materials are the materials which are able to convert one form of energy (mechanical, magnetic, electrical, etc.) into another in a reversible and repeatable process. They are capable of sensing changes in the environmental conditions, responding to them in a predetermined manner, in an appropriate time and returning to their original shape as soon as the stimulus is removed. Smart materials are often used in actuation systems of smart structures, stimulating them to adapt to the variable conditions. Smart systems are the systems composed of a smart material, a smart structure and an expert data processing. Smart systems ensure that during normal conditions, the structure carries all the loads without any help of smart components and on the other hand, it uses specific actuation systems to tackle abnormal load cases. An important concept related to the topic of smart structures is learning control [7]. The point of this phenomenon, also known as a case-based reasoning, is that the structure has a base, in which variable possible cases and
Fig. 1 – Schematic diagram showing a smart concept. The diagram presents three concepts related to the topic of smart technologies that can be implemented in the field of CE: smart structures, smart materials and smart systems.
Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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control commands are stored. When the structure is subjected to a load, the suitable case is applied and the structure receives a certain command. As time goes by and different load cases arise, the structure adapts past control demands to the new loads. This ensures that the structure improves progressively its behaviour, reacting to the abnormal loads each time more rapidly. The structures with the ability of learning are often called intelligent or very smart. They not only respond in a predesigned manner, but also have the capability of adapting to the new conditions.
3.
Components of smart systems
The main idea of smart structures [8] is the integration of sensors, actuators and control mechanisms into one, fully functional and coherent system that becomes an integral part of the structure. Such system is able to sense changes in the environmental conditions and react to the stimulus in a predicted way, in real or close to real time. Each smart system consists of three key elements: sensors, actuators and a control unit (Fig. 2). Sensors are the elements responsible for structural health monitoring. They detect changes in the environment, record the structural response (stress, strain, etc.) and generate appropriate signals which are then sent to the control unit. Control unit is the element responsible for data analysis. The control centre gathers all the information received from sensing devices, processes them and, basing on the given algorithm, reaches the conclusion about further action. If the specific response is required, the control unit sends a signal to the appropriate actuator. Actuators are the elements responsible for reduction of the structural response. They change properties of the structure by applying a force that was computed by the control unit. This makes it possible to reduce the structural damage and avoid the catastrophic global collapse.
Fig. 2 – Components of a smart system. The drawing presents the three key elements of each smart system: sensors, actuators and a control unit. These elementary components work together using signal transferring devices which transmit: first collected data and then produced control commands, between separate parts of the system.
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These elementary components work together using signal transferring devices which transmit: first collected data and then produced control commands between separate parts of the system. As far as sensors and actuators are concerned, there are numerous types of devices used [5,6,9,10]. The most popular ones are: Fibre Bragg Grating (FBG) sensors and piezoelectric actuators (PZT). Other commonly utilized actuators are shape memory alloys (SMA). While analysing the idea of smart structures, one can notice obvious correlations between performance of smart systems and biological ones. Such correlations were mentioned in some sources [8]. Likewise smart structures, biological systems include three elementary components: nerves (sensors), motor units (actuators) and a brain (a control unit). Nerves, just like sensors, are responsible for detecting external stimulus such as touch (stress) and sending signals to the brain. The signals have a form of electrochemical waves travelling along thin fibres (cables). The brain processes the information received from nerves and arrives at a decision about further action. In the next step, it sends a signal to motor units which consist of a single neuron and a few muscle fibres. Their role is to move a specified part of the body (structure) by transferring the electrochemical signal into the mechanical energy.
4. Smart CE structure – dream of the future or today's reality? Smart systems have a wide range of applications in various areas [6,10,11] – from aerospace and space engineering, through automotive industry, robotics and biomedical engineering, up to Civil Engineering. The last field of application is relatively new and so far, it is dominated by other areas. Nevertheless, there are a few research units which explore the topic of smart structures for CE applications. Among their projects, it is worth to mention: Research on a full-scale smart tensegrity structure at Ecole Polytechnique Fédérale de Lausanne [7], Research on a two-storey model building in the Smart Structures Technology Laboratory at the University of Illinois at UrbanaChampaign [12], Research on a carbon fibre structure at Politecnico di Milano [13], Research on an elevated water tank column at the University of British Columbia [14], Research on a sensing system for a continuous structural monitoring at the National Taiwan University [15]. Apart from buildings, the significant groups of smart CE structures are: bridges, roads, dams, etc. As far as bridges are concerned, the most important element of a smart system is structural health monitoring (SHM). A typical SHM system consists of: sensors that are embedded in the structural elements or attached to their surface, cables and a data acquisition unit. The aim of SHM is to detect structural damage and determine the current state of the structure. The system can work continuously, performing measurements at regular intervals, or it might be used as a temporary monitoring. After each measurement, all the data are sent to the data acquisition centre, where they are processed and analysed. In case of any anomaly or exceeding of the maximum set values, the computer sends warning messages that inform the earlier defined units about potential danger.
Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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Fig. 3 – Example of a smart system implemented in a bridge structure. The drawing presents an example of a smart system that can be applied to bridges. It indicates elements that might be controlled and shows necessary components which make the system smart.
The monitoring system is a necessary, but not sufficient condition. In order to call a bridge structure ‘‘smart’’, the system has to be supplemented with a control unit and actuators (Fig. 3). Only then will it be a complete smart system, reacting to the condition changes, capable of vibration damping, self-diagnosis and self-repair, acoustic isolation, etc. When do we need such a system? Numerous cases might be listed. Most of them concern abnormal loading such as seismic excitation, dynamic wind action, fast trains dynamic impact, vandalism, strong storms influence, etc. In such situations, the quick reaction is needed. To summarize, one has to combine three elements to obtain a smart bridge: structural health monitoring, control unit and actuators. Sensors, which are a part of the SHM system, measure response of the structure to the applied load. The control unit analyses data received from the SHM and sends signals to actuators, which exert an influence on the structural members changing characteristics of the bridge and improving its performance. However, after studying literature, professional journals or technical newspapers, it is very easy to gain an impression that a smart bridge equals a bridge containing an SHM system. There are numerous examples of ‘‘smart’’ structures understood in such way: Design of a smart composite bridge at the University of Missouri-Rolla [16], The first smart bridge in Canada [17], Research on a smart timber bridge [18], Smart bridge in Minnesota [19]. All of these examples show perfectly that the word ‘‘smart’’ is often misused. There might be various reasons for such tendency. Sometimes it is a simple intension of an author to draw reader's attention, sometimes it comes from a conviction that the bridge is in fact intelligent. SHM is the key element of all smart systems, but it does not mean that any structure equipped with such monitoring system is intelligent or smart. What is missing here is a feedback system. In each smart system, the data gathered by sensors is sent to the control unit, where it is analysed and the proper decision is made. If any parameter is exceeded, the control unit
sends information to actuators, which are responsible for the reduction of structural response. In the SHM system, the described process ends on the level of data analysis. Of course, as a result of such analysis, the proper decisions concerning structural control are made, but this action involves human engagement, it does not function automatically. ‘‘Smartness’’ of the bridge may be realized in various ways. The structure might be built of intelligent materials – one could imagine bearings or expansion joints made of smart memory alloys (SMA). It can be equipped with a smart system controlling the whole structure or its separate elements, for example adjustment of prestressing force in cables of cablestayed and suspension bridges or prestressed concrete structures, adjustment of structural stiffness in footbridges, control of lightweight structures under dynamic loads. Using smart systems, numerous parameters might be controlled: vibration and dynamic response of the structure, its acoustic parameters, displacements of the specific points, elements characteristics, such as stiffness. A particularly important issue is control of structures subject to dynamic actions [5]. Thus, great possibilities of application of smart systems lie in structures constructed in seismic regions [9,12], railway bridges and lightweight footbridges under dynamic wind actions and pedestrian loads.
5. Smart structures controlled by self-stress state adjustment Structures and their separate elements can be controlled in many various ways [9,15,20–23]. An interesting possibility lies in a control of truss and tensegrity elements by adjusting the self-stress state. Examples of such structural control are presented below. The main aim of the performed analyses was to investigate how the self-stress in truss and tensegrity structures influences their displacements. Change in the value of prestressing force may work as an actuator – element that
Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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reacts to the changing environmental conditions and reduces the structural response. The following examples are constructed to show the character of the described phenomenon and thus cannot be directly put into practical implementation. Control of truss structures. Space trusses with at least one module with self-stress were taken into consideration. Steel bars were used as truss members, there were no cables applied. Calculations were performed in SOFiSTiK 2010 (Educational License) using the following data: Young modulus of steel: 210 GPa, cross-sectional area of bars: 16 cm2, force P: 200 kN in the separate module (Fig. 4) and 2000 kN in the truss structure (Fig. 5). The analysis was performed using the geometrically nonlinear second order theory. The diagram (Fig. 6) shows how the applied self-stress influences the characteristic displacement of the separate three-dimensional module. It might be observed that by changing the value of the prestressing force, displacements
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can be reduced. Similar situation is to be noticed in the truss structure. Influence of the applied self-stress in one of the seven modules on the characteristic displacements of the structure is presented on the diagram (Fig. 7). The modules were being prestressed one by one, in order to obtain a curve for each module. Depending on the module, different curves are observed – starting from insignificant (close to zero) decrease in displacement value, up to considerable (more than a half). Considering the qualitative character of the presented diagrams, the obtained results can be a sign that truss structures may be controlled using various configurations of modules with self-stress. Location of such modules affects differently the structural response. Nevertheless, in order to effectively control these structures, huge forces have to be applied. The obtained values are far too big as far as typical materials, such as steel, are concerned.
Fig. 4 – Geometry of the single three-dimensional truss module. The drawing presents a single truss module in three views. It indicates location and direction of the applied force and the measured nodal displacement. Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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Fig. 5 – Geometry of space truss based on truss modules. The drawing presents three views of a space truss constructed using separate truss modules. It indicates location and direction of the applied force and the measured nodal displacement, as well as numbering of the prestressed modules.
Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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δ [mm]
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Fig. 6 – Influence of self-stress in the single truss module on its characteristic displacement. The diagram shows how the applied prestressing force influences the characteristic displacement of the separate three-dimensional module.
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Fig. 7 – Influence of self-stress in the corresponding truss module on the characteristic displacement of the space truss. The diagram shows how the applied prestressing force influences the characteristic displacement of the space truss, depending on the module which was prestressed.
Fig. 8 – Geometry of the single tensegrity module in two versions: ‘‘left’’ and ‘‘right’’. The drawing presents a single tensegrity module in two views. It shows two types of the modules used and indicates location and direction of the applied force and the measured nodal displacement.
Control of tensegrity structures. A plate structure based on tensegrity modules [24] was analysed. Two types of single modules were used: ‘‘left’’ and ‘‘right’’, depending on the direction of rotation of the upper triangle. Calculations were performed in SOFiSTiK 2010 (Educational License) using the following data: Young modulus of steel: 210 GPa, crosssectional area of struts: 7.26 cm2, cross-sectional area of cables: 2.01 cm2, force P: 20 kN in the separate module (Fig. 8) and 10 kN in the tensegrity plate (Fig. 10). The analysis was performed using the geometrically nonlinear second order theory. The diagram (Fig. 9) shows how the value of prestressing force in the single module influences horizontal deflection of the upper triangle, caused by a horizontal point load. It is easy to notice that by changing the value of the prestressing force, displacements can be significantly reduced. If prestressing force is sufficient (bigger than about 150 kN in Fig. 9) small change of displacements is observed. The diagram shows that with the force value approaching zero, displacements approach infinity, which is characteristic for tensegrity structures with infinitesimal mechanisms.
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Fig. 9 – Influence of self-stress in the single tensegrity module on its characteristic displacement. The diagram shows how the applied prestressing force influences the characteristic displacement of the single tensegrity module.
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The second object of the analysis was a plate structure (Fig. 10), consisting of 14 presented above, reversed modules. The modules were located and combined in such a way that their lower nodes met. The plate was supported in four
points on the upper surface and loaded with 13 point loads applied to the upper nodes of the plate, acting downwards. The aim of the analysis was to investigate how the selfstress value applied to the single modules influences the displacement of the central node of the upper surface. The
Fig. 10 – Geometry of plate structure based on tensegrity modules: axonometry with an indication of the applied forces and three views. The drawing presents axonometry and three views of a plate structure constructed using single tensegrity modules. It indicates location and direction of the applied forces. Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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Fig. 11 – Numbering of the prestressed modules with an indication of the characteristic displacement. The drawing presents a view of the plate structure with a numbering of its modules and indicates location and direction of its characteristic displacement.
self-stress was applied successively in modules 1–7 (Fig. 11), and in the whole plate. Curve number 1 (Fig. 12) was obtained for the self-stress applied to the first module with a value changing from 0 to 400 kN, while the rest of the structure remained unprestressed. Curve number 2, 3, . . ., 7 were obtained analogically for the second, third, . . ., seventh module with self-stress. Curve designated as 1 + + 14 was obtained for the self-stress applied to the whole structure. The results show (Fig. 12) that, similarly to the single module, when the value of prestressing force increases, the displacements are significantly reduced. When the self-stress value approaches zero, displacements approach infinity, what indicates that the structure has an infinitesimal mechanism. The biggest reduction of displacements is to be observed when the selfstress is applied in all 14 modules. Application of self-stress in more than one module will be a subject of the future research. The analysis will be performed basing on real engineering structures, such as bridge decks or
their supports, considering different loads acting on structures during their lifetime. Nevertheless, further research will concern only tensegrity structures, as they are more prone to any changes in the value of prestressing force. The results presented in this chapter may be considered as a contribution to the evaluation of possible control of bar structures using self-stress in the selected modules. The analysis provides promising results which encourage to futher research in the field. Such structures migth have real applications in CE and BE, they could be used as bridge decks, ceiling structures, columns, pylons, etc. The structural elements designed in this way would respond to the changing environental conditions: live loads, environmental and special loads, abnormal loads.
δ [mm]
The study discusses possible applications of smart technologies in the field of Civil Engineering. According to the authors' opinion, there are various possibilities for the future implementations of smart structures in these fields. Smart materials are probably too expensive at the moment, but smart structures can be developed. Every now and then, numerous sources provide information about new intelligent buildings, smart bridges, etc., which are under construction or already finished. It does not necessarily mean that these structures are smart in the true sense of the word. As shown above, the high-tech equipment and sublime electronics do not make the building smart, neither does the SHM system with the bridge. ‘‘Smart’’ means ‘‘capable of acting in a quick way and making corrections that resemble human decisions, particularly in response to changeable conditions’’. Therefore, the system that only provides information about the structure and its behaviour and does not react to the changes in its environment, cannot be called smart, nor intelligent. The concept of a smart bridge presented in the paper shows how the real smart system should look like.
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Fig. 12 – Influence of self-stress in the corresponding tensegrity module on the characteristic displacement of the tensegrity plate. The diagram shows how the applied prestressing force influences the characteristic displacement of the tensegrity plate, depending on the module which was prestressed.
6.
Conclusions
Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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An interesting possibility lies in the implementation of tensegrity elements with self-stress. They could be applied as parts of bigger structures or separate structural elements designed to react to the changes in the environmental conditions and to carry the abnormal loads, such as very strong wind gusts or seismic loads. Presented examples of structural control performed on the space truss and the tensegrity plate show that displacements of such structures may be reduced by changing the prestressing force applied to the single modules, which are a part of the structure. The results of the performed analysis indicated that tensegrity structures are much more prone to the changes in the value of prestressing force than truss structures, which makes them a promising solution as far as structural control is concerned.
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[12]
[13]
[14]
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concrete beam-column joint, Smart Structures & Systems 7 (5) (2012). M. Farshad, Intelligent materials and structures, Scientia Iranica 2 (1) (1995) 65–87. J.I. Liu, S. Zhu, Y.I. Xu, Y. Zhang, Displacement-based design approach for highway bridges with SMA isolators, Smart Structures & Systems 8 (2) (2011). C.M. Chang, B.F. Spencer, An experimental study of active base isolation control for seismic protection, in: Proc. SPIE 7647, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, San Diego, CA, 2010. G. Cazzulani, S. Cinquemani, L. Comolli, A. Gardella, Reducing vibration in carbon fiber structures with piezoelectric actuators and fiber Bragg grating sensors, in: Proc. SPIE 8341, Active and Passive Smart Structures and Integrated Systems, San Diego, CA, 2012. J. Clarke, S. Tesfamariam, S. Yannacopoulos, Smart structures using shape memory alloys, in: Proc. SPIE 7292, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, San Diego, CA, 2009. K.C. Lu, J.H. Wenig, C.H. Loh, Turning the building into a smart structure: integrating health monitoring, in: Proc. SPIE 7292, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, San Diego, CA, 2009. E.C. Eckhoff, V.M. Eller, S.E. Watkins, R.H. Hall, Interactive virtual laboratory for experience with a smart bridge test, in: Proc. of the 2002 American Society for Engineering Education Annual Conference & Exposition, 2002. S.H. Rizkalla, G. Tadros, First smart bridge in Canada, ACI Concrete International 16 (6) (1994) 42–44. B.M. Phares, T.J. Wipf, U. Deza, J.P. Wacker, Development of a smart timber bridge – a five-year plan, USDA General Technical Report FPL-GTR-195, Madison, 2011. S. Wende, C. Smyth, The new Minnesota smart bridge, Web: www.mnme.com. K. Kebiche, M.N. Kazi Aoual, R. Motro, Continuum model for systems in a self-stress state, International Journal of Space Structures 23 (2008) 113–125. D. Cioranescu, J. Saint Jean Paulin, Mathematical study of large space structures, Lecture Notes in Control and Information Sciences, vol. 147, Springer, Berlin, 1990. W. Gutkowski, et al., Static Calculations of Structural Roofs, Arkady, Warszawa, 1980 (in Polish). W. Gutkowski, Regular Bar Structures, PWN, Warszawa, 1973 (in Polish). W. Gilewski, A. Kasprzak, Introduction to mechanics of tensegrity modules, in: S. Jemioło, S. Lutomirski (Eds.), Theoretical Fundamentals of Building Engineering, Vol. I. Mechanics of Materials and Structures, OWPW, Warszawa, 2012, pp. 83–94 (in Polish).
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Available online at www.sciencedirect.com
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Original Research Article
On possible applications of smart structures controlled by self-stress W. Gilewski *, A. Al Sabouni-Zawadzka Faculty of Civil Engineering, Warsaw University of Technology, Al. Armii Ludowej 16, 00-637 Warsaw, Poland
article info
abstract
Article history:
Civil Engineering (CE) is one of the many fields of possible implementation of smart or
Received 2 April 2014
intelligent technologies. The present paper is an attempt to specify and estimate problems
Accepted 25 August 2014
and areas of CE suitable for the application of such technologies, with the focus on Bridge
Available online xxx
Engineering (BE). Precise definitions, explanations and classifications of terms used in smart
Keywords:
smart systems and biological ones are indicated. The paper presents some of the research
Smart structure
projects carried out in the field of CE, according to the current state-of-the-art. Concepts of
Structural control
smart bridges are proposed and several examples of structural control performed on space
Tensegrity
trusses and tensegrity structures with self-stress are introduced.
technique are introduced and components of smart systems are defined. Analogies between
Self-stress
Examples of structural control presented in the paper show that characteristic displacements of the analysed structures may be reduced by changing the prestressing force applied to the single modules, which are a part of the structure. Results of the performed analysis indicate that tensegrity structures are much more prone to the changes in the value of prestressing force than truss structures, which makes them a promising solution as far as structural control is concerned. # 2014 Politechnika Wrocławska. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.
1.
Introduction
Engineering structures, such as buildings or bridges, are subject to various actions, among which the most dangerous ones are accidental loads. It may be a challenge for an engineer to design a structure that would react to such accidental loading by modifying its own properties. It is possible with the use of smart technologies. Such intelligent technologies apply to both materials and structures. However, considering the immense costs of implementing
smart materials into structural elements, the authors focus on structural smartness rather than material one. The present paper discusses possible applications of smart technologies in the field of CE, with the focus on BE. The concepts of smart structures, materials and systems, as well as other terms used in smart technique are precisely defined and classified. The study introduces principal elements which make the system smart and it indicates analogies with biological systems. Several applications in CE are presented and a concept of a smart bridge is proposed.
* Corresponding author. Tel.: +48 22 2345753. E-mail address: [email protected] (W. Gilewski). http://dx.doi.org/10.1016/j.acme.2014.08.006 1644-9665/# 2014 Politechnika Wrocławska. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.
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Buildings or bridges can be regarded as smart or intelligent due to the advanced structural health monitoring (SHM) systems, which are very often installed on the existing and newly built structures. However, the authors suggest a slightly different approach to the topic of smart structures. According to the authors, ‘‘smartness’’ should regard a structure itself, not the advanced technologies, with which buildings or bridges are equipped. Intelligent systems, understood in such way, may have various applications: vibration damping, reduction of displacements, acoustic isolation, damage localization and repair, stress reduction, etc. According to the authors' opinion, one of the most interesting possibilities of structural control lies in a control of truss and tensegrity elements through self-stress state adjustment [1–3]. Such structural elements may be used as parts of bigger structures, for example decks or pylons of lightweight footbridges. Results of the performed analyses indicate that the structural displacements might be significantly reduced by adjusting the initial self-stress state in such elements. The paper introduces examples of structural control performed on a space truss with self-stress and a plate based on tensegrity modules. An influence of several self-stress states on displacements is analysed.
2.
General characteristics of smart structures
The topic of smart structures is relatively new [4]. It commenced to be qualified as a distinct field of applied science in the 1980s, when, thanks to the technological progress, scientists joined together in small groups working on the subject. At the beginning, all the research carried out in the area of smart technologies were funded by the government. In the early 1990s private companies started to invest money in this field, providing necessary funding and application possibilities. The cooperation between government research organizations, scientists and companies resulted in several multi-year programs dedicated to the development of smart products and their implementation. The definition of smart structures has been a disputable issue for as long as the topic exists. There are numerous methods of approaching to this subject. Each author [5,6] defines and classifies smart structures in a different way. These differences arise from distinct ways of perceiving work of such structures and methods of their analyses. Some examine a whole structure, while others focus on a specific part of it – a single structural element. Another reason of such differences is the fact that the word ‘‘smart’’ itself has various meanings. According to the dictionary, its original significance was ‘‘stinging, sharp’’. The present meaning of the word ‘‘smart’’ – ‘‘clever, intelligent’’ – has taken over from its original definition the element of quick energetic movement and sharp thought. This original meaning characterizes perfectly the idea of smart structures. In relation to the structures, the word ‘‘smart’’ means: capable of acting in a quick way and making corrections that resemble human decisions, particularly in response to changeable conditions. The present significance, ‘‘intelligent’’, is also applied to the structures, but it is not fully adequate. Intelligence is a human feature and should be reserved for
humans. Although the classification distinguishes a group of very smart structures, calling them intelligent, it does not mean that those structures possess intelligence. The only attribute, which makes them resemble humans, is the ability to learn. There are various types of ‘‘smartness’’. A smart building, for example, can be understood in many different ways. For an occupant of the building it will signify high-tech equipment, such as electronics controlling ambient environment, air conditioning systems, lighting and alarm installations. For an engineer designing the structure, it will indicate that the building is equipped with a smart monitoring and damping system. There are three concepts related to the topic of smart structures (Fig. 1). Smart structures are the structures with the ability to sense and respond adaptively to changes in their environment. This feature distinguishes them from the conventional ones. Whereas the main purpose of the traditional structures is to provide strength and carry loads acting on them, the smart ones adapt in a pre-designed manner to a functional need, modifying their shape, stiffness or damping characteristics in order to minimize deflection and possible damage. Smart materials are the materials which are able to convert one form of energy (mechanical, magnetic, electrical, etc.) into another in a reversible and repeatable process. They are capable of sensing changes in the environmental conditions, responding to them in a predetermined manner, in an appropriate time and returning to their original shape as soon as the stimulus is removed. Smart materials are often used in actuation systems of smart structures, stimulating them to adapt to the variable conditions. Smart systems are the systems composed of a smart material, a smart structure and an expert data processing. Smart systems ensure that during normal conditions, the structure carries all the loads without any help of smart components and on the other hand, it uses specific actuation systems to tackle abnormal load cases. An important concept related to the topic of smart structures is learning control [7]. The point of this phenomenon, also known as a case-based reasoning, is that the structure has a base, in which variable possible cases and
Fig. 1 – Schematic diagram showing a smart concept. The diagram presents three concepts related to the topic of smart technologies that can be implemented in the field of CE: smart structures, smart materials and smart systems.
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control commands are stored. When the structure is subjected to a load, the suitable case is applied and the structure receives a certain command. As time goes by and different load cases arise, the structure adapts past control demands to the new loads. This ensures that the structure improves progressively its behaviour, reacting to the abnormal loads each time more rapidly. The structures with the ability of learning are often called intelligent or very smart. They not only respond in a predesigned manner, but also have the capability of adapting to the new conditions.
3.
Components of smart systems
The main idea of smart structures [8] is the integration of sensors, actuators and control mechanisms into one, fully functional and coherent system that becomes an integral part of the structure. Such system is able to sense changes in the environmental conditions and react to the stimulus in a predicted way, in real or close to real time. Each smart system consists of three key elements: sensors, actuators and a control unit (Fig. 2). Sensors are the elements responsible for structural health monitoring. They detect changes in the environment, record the structural response (stress, strain, etc.) and generate appropriate signals which are then sent to the control unit. Control unit is the element responsible for data analysis. The control centre gathers all the information received from sensing devices, processes them and, basing on the given algorithm, reaches the conclusion about further action. If the specific response is required, the control unit sends a signal to the appropriate actuator. Actuators are the elements responsible for reduction of the structural response. They change properties of the structure by applying a force that was computed by the control unit. This makes it possible to reduce the structural damage and avoid the catastrophic global collapse.
Fig. 2 – Components of a smart system. The drawing presents the three key elements of each smart system: sensors, actuators and a control unit. These elementary components work together using signal transferring devices which transmit: first collected data and then produced control commands, between separate parts of the system.
3
These elementary components work together using signal transferring devices which transmit: first collected data and then produced control commands between separate parts of the system. As far as sensors and actuators are concerned, there are numerous types of devices used [5,6,9,10]. The most popular ones are: Fibre Bragg Grating (FBG) sensors and piezoelectric actuators (PZT). Other commonly utilized actuators are shape memory alloys (SMA). While analysing the idea of smart structures, one can notice obvious correlations between performance of smart systems and biological ones. Such correlations were mentioned in some sources [8]. Likewise smart structures, biological systems include three elementary components: nerves (sensors), motor units (actuators) and a brain (a control unit). Nerves, just like sensors, are responsible for detecting external stimulus such as touch (stress) and sending signals to the brain. The signals have a form of electrochemical waves travelling along thin fibres (cables). The brain processes the information received from nerves and arrives at a decision about further action. In the next step, it sends a signal to motor units which consist of a single neuron and a few muscle fibres. Their role is to move a specified part of the body (structure) by transferring the electrochemical signal into the mechanical energy.
4. Smart CE structure – dream of the future or today's reality? Smart systems have a wide range of applications in various areas [6,10,11] – from aerospace and space engineering, through automotive industry, robotics and biomedical engineering, up to Civil Engineering. The last field of application is relatively new and so far, it is dominated by other areas. Nevertheless, there are a few research units which explore the topic of smart structures for CE applications. Among their projects, it is worth to mention: Research on a full-scale smart tensegrity structure at Ecole Polytechnique Fédérale de Lausanne [7], Research on a two-storey model building in the Smart Structures Technology Laboratory at the University of Illinois at UrbanaChampaign [12], Research on a carbon fibre structure at Politecnico di Milano [13], Research on an elevated water tank column at the University of British Columbia [14], Research on a sensing system for a continuous structural monitoring at the National Taiwan University [15]. Apart from buildings, the significant groups of smart CE structures are: bridges, roads, dams, etc. As far as bridges are concerned, the most important element of a smart system is structural health monitoring (SHM). A typical SHM system consists of: sensors that are embedded in the structural elements or attached to their surface, cables and a data acquisition unit. The aim of SHM is to detect structural damage and determine the current state of the structure. The system can work continuously, performing measurements at regular intervals, or it might be used as a temporary monitoring. After each measurement, all the data are sent to the data acquisition centre, where they are processed and analysed. In case of any anomaly or exceeding of the maximum set values, the computer sends warning messages that inform the earlier defined units about potential danger.
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Fig. 3 – Example of a smart system implemented in a bridge structure. The drawing presents an example of a smart system that can be applied to bridges. It indicates elements that might be controlled and shows necessary components which make the system smart.
The monitoring system is a necessary, but not sufficient condition. In order to call a bridge structure ‘‘smart’’, the system has to be supplemented with a control unit and actuators (Fig. 3). Only then will it be a complete smart system, reacting to the condition changes, capable of vibration damping, self-diagnosis and self-repair, acoustic isolation, etc. When do we need such a system? Numerous cases might be listed. Most of them concern abnormal loading such as seismic excitation, dynamic wind action, fast trains dynamic impact, vandalism, strong storms influence, etc. In such situations, the quick reaction is needed. To summarize, one has to combine three elements to obtain a smart bridge: structural health monitoring, control unit and actuators. Sensors, which are a part of the SHM system, measure response of the structure to the applied load. The control unit analyses data received from the SHM and sends signals to actuators, which exert an influence on the structural members changing characteristics of the bridge and improving its performance. However, after studying literature, professional journals or technical newspapers, it is very easy to gain an impression that a smart bridge equals a bridge containing an SHM system. There are numerous examples of ‘‘smart’’ structures understood in such way: Design of a smart composite bridge at the University of Missouri-Rolla [16], The first smart bridge in Canada [17], Research on a smart timber bridge [18], Smart bridge in Minnesota [19]. All of these examples show perfectly that the word ‘‘smart’’ is often misused. There might be various reasons for such tendency. Sometimes it is a simple intension of an author to draw reader's attention, sometimes it comes from a conviction that the bridge is in fact intelligent. SHM is the key element of all smart systems, but it does not mean that any structure equipped with such monitoring system is intelligent or smart. What is missing here is a feedback system. In each smart system, the data gathered by sensors is sent to the control unit, where it is analysed and the proper decision is made. If any parameter is exceeded, the control unit
sends information to actuators, which are responsible for the reduction of structural response. In the SHM system, the described process ends on the level of data analysis. Of course, as a result of such analysis, the proper decisions concerning structural control are made, but this action involves human engagement, it does not function automatically. ‘‘Smartness’’ of the bridge may be realized in various ways. The structure might be built of intelligent materials – one could imagine bearings or expansion joints made of smart memory alloys (SMA). It can be equipped with a smart system controlling the whole structure or its separate elements, for example adjustment of prestressing force in cables of cablestayed and suspension bridges or prestressed concrete structures, adjustment of structural stiffness in footbridges, control of lightweight structures under dynamic loads. Using smart systems, numerous parameters might be controlled: vibration and dynamic response of the structure, its acoustic parameters, displacements of the specific points, elements characteristics, such as stiffness. A particularly important issue is control of structures subject to dynamic actions [5]. Thus, great possibilities of application of smart systems lie in structures constructed in seismic regions [9,12], railway bridges and lightweight footbridges under dynamic wind actions and pedestrian loads.
5. Smart structures controlled by self-stress state adjustment Structures and their separate elements can be controlled in many various ways [9,15,20–23]. An interesting possibility lies in a control of truss and tensegrity elements by adjusting the self-stress state. Examples of such structural control are presented below. The main aim of the performed analyses was to investigate how the self-stress in truss and tensegrity structures influences their displacements. Change in the value of prestressing force may work as an actuator – element that
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reacts to the changing environmental conditions and reduces the structural response. The following examples are constructed to show the character of the described phenomenon and thus cannot be directly put into practical implementation. Control of truss structures. Space trusses with at least one module with self-stress were taken into consideration. Steel bars were used as truss members, there were no cables applied. Calculations were performed in SOFiSTiK 2010 (Educational License) using the following data: Young modulus of steel: 210 GPa, cross-sectional area of bars: 16 cm2, force P: 200 kN in the separate module (Fig. 4) and 2000 kN in the truss structure (Fig. 5). The analysis was performed using the geometrically nonlinear second order theory. The diagram (Fig. 6) shows how the applied self-stress influences the characteristic displacement of the separate three-dimensional module. It might be observed that by changing the value of the prestressing force, displacements
5
can be reduced. Similar situation is to be noticed in the truss structure. Influence of the applied self-stress in one of the seven modules on the characteristic displacements of the structure is presented on the diagram (Fig. 7). The modules were being prestressed one by one, in order to obtain a curve for each module. Depending on the module, different curves are observed – starting from insignificant (close to zero) decrease in displacement value, up to considerable (more than a half). Considering the qualitative character of the presented diagrams, the obtained results can be a sign that truss structures may be controlled using various configurations of modules with self-stress. Location of such modules affects differently the structural response. Nevertheless, in order to effectively control these structures, huge forces have to be applied. The obtained values are far too big as far as typical materials, such as steel, are concerned.
Fig. 4 – Geometry of the single three-dimensional truss module. The drawing presents a single truss module in three views. It indicates location and direction of the applied force and the measured nodal displacement. Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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Fig. 5 – Geometry of space truss based on truss modules. The drawing presents three views of a space truss constructed using separate truss modules. It indicates location and direction of the applied force and the measured nodal displacement, as well as numbering of the prestressed modules.
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δ [mm]
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Fig. 6 – Influence of self-stress in the single truss module on its characteristic displacement. The diagram shows how the applied prestressing force influences the characteristic displacement of the separate three-dimensional module.
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Fig. 7 – Influence of self-stress in the corresponding truss module on the characteristic displacement of the space truss. The diagram shows how the applied prestressing force influences the characteristic displacement of the space truss, depending on the module which was prestressed.
Fig. 8 – Geometry of the single tensegrity module in two versions: ‘‘left’’ and ‘‘right’’. The drawing presents a single tensegrity module in two views. It shows two types of the modules used and indicates location and direction of the applied force and the measured nodal displacement.
Control of tensegrity structures. A plate structure based on tensegrity modules [24] was analysed. Two types of single modules were used: ‘‘left’’ and ‘‘right’’, depending on the direction of rotation of the upper triangle. Calculations were performed in SOFiSTiK 2010 (Educational License) using the following data: Young modulus of steel: 210 GPa, crosssectional area of struts: 7.26 cm2, cross-sectional area of cables: 2.01 cm2, force P: 20 kN in the separate module (Fig. 8) and 10 kN in the tensegrity plate (Fig. 10). The analysis was performed using the geometrically nonlinear second order theory. The diagram (Fig. 9) shows how the value of prestressing force in the single module influences horizontal deflection of the upper triangle, caused by a horizontal point load. It is easy to notice that by changing the value of the prestressing force, displacements can be significantly reduced. If prestressing force is sufficient (bigger than about 150 kN in Fig. 9) small change of displacements is observed. The diagram shows that with the force value approaching zero, displacements approach infinity, which is characteristic for tensegrity structures with infinitesimal mechanisms.
δ [m mm] 20 00 17 75 15 50 12 25 10 00 7 75 5 50 2 25 0
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Fig. 9 – Influence of self-stress in the single tensegrity module on its characteristic displacement. The diagram shows how the applied prestressing force influences the characteristic displacement of the single tensegrity module.
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The second object of the analysis was a plate structure (Fig. 10), consisting of 14 presented above, reversed modules. The modules were located and combined in such a way that their lower nodes met. The plate was supported in four
points on the upper surface and loaded with 13 point loads applied to the upper nodes of the plate, acting downwards. The aim of the analysis was to investigate how the selfstress value applied to the single modules influences the displacement of the central node of the upper surface. The
Fig. 10 – Geometry of plate structure based on tensegrity modules: axonometry with an indication of the applied forces and three views. The drawing presents axonometry and three views of a plate structure constructed using single tensegrity modules. It indicates location and direction of the applied forces. Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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Fig. 11 – Numbering of the prestressed modules with an indication of the characteristic displacement. The drawing presents a view of the plate structure with a numbering of its modules and indicates location and direction of its characteristic displacement.
self-stress was applied successively in modules 1–7 (Fig. 11), and in the whole plate. Curve number 1 (Fig. 12) was obtained for the self-stress applied to the first module with a value changing from 0 to 400 kN, while the rest of the structure remained unprestressed. Curve number 2, 3, . . ., 7 were obtained analogically for the second, third, . . ., seventh module with self-stress. Curve designated as 1 + + 14 was obtained for the self-stress applied to the whole structure. The results show (Fig. 12) that, similarly to the single module, when the value of prestressing force increases, the displacements are significantly reduced. When the self-stress value approaches zero, displacements approach infinity, what indicates that the structure has an infinitesimal mechanism. The biggest reduction of displacements is to be observed when the selfstress is applied in all 14 modules. Application of self-stress in more than one module will be a subject of the future research. The analysis will be performed basing on real engineering structures, such as bridge decks or
their supports, considering different loads acting on structures during their lifetime. Nevertheless, further research will concern only tensegrity structures, as they are more prone to any changes in the value of prestressing force. The results presented in this chapter may be considered as a contribution to the evaluation of possible control of bar structures using self-stress in the selected modules. The analysis provides promising results which encourage to futher research in the field. Such structures migth have real applications in CE and BE, they could be used as bridge decks, ceiling structures, columns, pylons, etc. The structural elements designed in this way would respond to the changing environental conditions: live loads, environmental and special loads, abnormal loads.
δ [mm]
The study discusses possible applications of smart technologies in the field of Civil Engineering. According to the authors' opinion, there are various possibilities for the future implementations of smart structures in these fields. Smart materials are probably too expensive at the moment, but smart structures can be developed. Every now and then, numerous sources provide information about new intelligent buildings, smart bridges, etc., which are under construction or already finished. It does not necessarily mean that these structures are smart in the true sense of the word. As shown above, the high-tech equipment and sublime electronics do not make the building smart, neither does the SHM system with the bridge. ‘‘Smart’’ means ‘‘capable of acting in a quick way and making corrections that resemble human decisions, particularly in response to changeable conditions’’. Therefore, the system that only provides information about the structure and its behaviour and does not react to the changes in its environment, cannot be called smart, nor intelligent. The concept of a smart bridge presented in the paper shows how the real smart system should look like.
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Fig. 12 – Influence of self-stress in the corresponding tensegrity module on the characteristic displacement of the tensegrity plate. The diagram shows how the applied prestressing force influences the characteristic displacement of the tensegrity plate, depending on the module which was prestressed.
6.
Conclusions
Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006
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An interesting possibility lies in the implementation of tensegrity elements with self-stress. They could be applied as parts of bigger structures or separate structural elements designed to react to the changes in the environmental conditions and to carry the abnormal loads, such as very strong wind gusts or seismic loads. Presented examples of structural control performed on the space truss and the tensegrity plate show that displacements of such structures may be reduced by changing the prestressing force applied to the single modules, which are a part of the structure. The results of the performed analysis indicated that tensegrity structures are much more prone to the changes in the value of prestressing force than truss structures, which makes them a promising solution as far as structural control is concerned.
[10] [11]
[12]
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Please cite this article in press as: W. Gilewski, A. Al Sabouni-Zawadzka, On possible applications of smart structures controlled by selfstress, Archives of Civil and Mechanical Engineering (2014), http://dx.doi.org/10.1016/j.acme.2014.08.006