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The demand for autonomous energy solutions in seismic regions is increasing for the uninterrupted operation of structural health monitoring systems. In this context, energy harvesting systems offer a solution for low-power devices, especially in earthquake zones where external energy sources may be interrupted. This study evaluates the energy harvesting capacity of a piezoelectric energy harvesting mechanism placed at specific locations in the columns of a reinforced concrete structure, considering both earthquake and live load conditions. A smart building model is developed by placing sensor modules with piezoelectric material on the columns of a three-story reinforced concrete building. The finite element model of the smart building, which is formed by integrating various technologies and sensors, is created in ANSYS, and specific locations on the columns are selected as sensor points. Dynamic analyses are performed under earthquake conditions by considering seismic records from the Imperial Valley, Erzincan, and Darfield earthquakes. Experimental results of a smart structure with patched piezoelectric material are used to verify the simulation results. The voltage, current, and power responses obtained from the sensor points are examined with the payload effect placed at the end point of the sensor module. When the power values collected from the sensor points are compared, it can be said that the maximum power obtained from the smart building under both earthquake and live load is 0.355 W, while the minimum power value reaches 0.168 W. The results show that the energy harvesting mechanism can provide external power to support electronic devices in regions where earthquake effects are frequent and high. Thus, this study presents an innovative contribution to smart building systems by investigating the energy harvesting potential under earthquake and live loads in a reinforced concrete structure equipped with piezoelectric sensors. The model, validated with numerical and experimental analyses, proposes a sustainable energy source for structural health monitoring systems in seismic regions.
Introduction
Vibrations occur in high-rise buildings due to earthquakes, wind, and other loads. Unwanted vibrations can damage the structural integrity of structures and also make people uncomfortable [1]. Various control methods are being studied to reduce vibrations. Mainly, the most popular vibration damping systems such as popularly tuned-mass damper [2], active tuned-mass damper [3, 4], and active vibration control methods [5] are presented. The use of various sensor networks is needed for the application of control methods. Wired and wireless energy sources are needed to provide energy to the sensors [6]. Wireless sensors are more convenient regarding cable requirements and installation costs. However, to meet the energy needs of wireless sensors, external batteries are needed at approximately microwatt levels for each sensor operation [7]. Moreover, despite the use of limited-capacity rechargeable batteries so that the sensor points can work for a long time [8], it may be an impractical practice to replace the batteries besides the harmful environmental effects [8, 9]. For this reason, meeting the energy needs of batteries with energy harvesting methods can be an essential solution to provide a complementary effect. Therefore, the energy harvest obtained from the vibrations of the structures under earthquake loads has been comprehensively evaluated in this paper.
Energy harvesting systems are mechanisms that convert mechanical energy into electrical energy. In energy harvesting, it can be considered as a potential option to be preferred as a power source in terms of transmitting the small amount of electrical energy captured from the environment to small electronic devices such as IoT devices, data transmitters, and sensors [6, 10, 11]. Literature reviews of common studies on the conversion of thermal, light, water flow, radio waves, electromagnetic, and kinetic energy sources into electrical energy as environmental potential energy sources in energy harvesting systems in buildings have been reported by researchers [6]. Thermoelectric energy harvesters obtain electrical energy from thermal energy and are considered a potential power source widely used in building heating and cooling processes [12]. Thermoelectric energy harvesters can achieve a power conversion efficiency of up to 20% [13]. Due to their long life and high reliability [14, 15], Aranguren et al. [16] used a thermoelectric energy harvesting system to generate electrical energy from waste heat by utilizing the temperature of the flue gases. In another study, a physical model is presented in thermoelectric energy harvesting in which waste heat recovery is enhanced with a heat spreader's aid [17]. The three-dimensional simulation model is evaluated in ANSYS [18] to verify the physical model in which the power is increased by about 20% with the heat spreader. Guan et al. [19] proposed an experimental system with a two-stage amplifier and self-starting capability to achieve high efficiency from the thermoelectric energy harvester. At the wireless sensor point that captures thermal energy, the current values obtained from the thermoelectric heating and cooling modules under three different operating conditions and at different temperature distributions are evaluated [20]. In buildings, the use of light energy harvesters is becoming widespread to convert the light energy of the environment into electrical energy to power wireless sensors. Li et al. [21] created light energy harvesters from four types of solar cells exposed to different light sources inside the building. In another study, Vasiliev et al. [22] used solar energy harvesters with highly transparent surfaces, providing practical application to take advantage of the building's surfaces and windows. The method of obtaining electrical energy from the flow energy of the water in the water transmission lines of the building is considered another energy harvester [23]. Changes in water pressure, potential energy, and kinetic energy in water lines serve as an energy source for fluid energy harvesters. Moreover, electromagnetic energy harvesters have been designed to generate electrical energy by utilizing electromagnetic inductions [24, 25]. Radiofrequency energy collectors that provide power for low-power sensors inside buildings from radio waves emitted by devices with frequency ranges of 3 kHz and 300 kHz are becoming widespread [26, 27].
Besides water flow, waste thermal energy, electromagnetic, and radio waves in a building, and structural vibrations caused by external effects such as earthquakes and wind are potential environmental power sources for piezoelectric energy collectors [28, 29]. Piezoelectric energy harvesting systems based on the conversion of mechanical energy in structural vibrations into electrical energy are investigated intensively by researchers because they are not affected by environmental effects such as humidity and temperature [29, 30]. Also, in recent years, piezoelectric-based energy harvesting mechanisms have benefited from essential power sources based on vibration, flow, and strain [21, 31, 32]. To evaluate the kinetic energy caused by the movements of the feet of the people in the building, Elhalwagy et al. [33] proposed piezoelectric-based floors that could power small electrical devices and lighting of buildings. Kathpalia et al. [34] proposed a piezoelectric energy harvester that generates electrical energy through smart paver tiles using human steps and various excitations in structures. In the reference study [35], the aim is to reduce the power requirement of the building in real time based on occupancy density and mapping in smart buildings with a piezoelectric material placed on a floor tile. In a similar study, Hwang et al. [36] aimed to increase the electrical power by utilizing the resonant vibration frequency of the piezoelectric structure by modifying the tile with a mechanical system consisting of springs and an end mass. Piezoelectric energy harvesting systems have been developed for different structures and studies in which human movement in buildings is considered. Mainly for applications in civil structures, electrical power outputs based on vibration are presented by coating bimorph piezoelectric materials placed on a thin bridge surface under the action of live loads and a selected region on the bridge with piezoelectric material [37].
Among the innovative solutions to increase energy efficiency in buildings today, hybrid energy harvesting systems that combine multiple energy conversion mechanisms offer remarkable solutions in terms of sustainability. Hybrid systems where piezoelectric and electromagnetic mechanisms are used together enable higher energy production from building vibrations [38, 39], while systems where solar energy and piezoelectric mechanisms are integrated are advantageous in terms of piezoelectric components being activated and providing uninterrupted energy, especially in conditions where sunlight is insufficient [40]. Systems that use wind and solar energy together offer functional solutions in terms of both energy production and system maintenance, especially in smart agriculture and building applications [41]. On the other hand, the dual-source energy harvesting system proposed by Chen et al. attracted attention to its performance flexibility in complex environmental conditions by simultaneously collecting multi-directional vibration energies and flow-sourced energy [42]. Han et al. [43] examined the structural designs and performance advantages of piezoelectric–electromagnetic hybrid systems for different applications. One of the real-world examples of hybrid systems integrated into building design is energy harvesting mechanisms integrated with solar panels and piezoelectric materials into façade systems [44]. The studies in the literature clearly demonstrate the increasing importance and potential of hybrid energy harvesting systems in structural applications.
In order to meet the energy needs of buildings and support the existing system, electrical energy harvesting from environmental energy sources such as flow, kinetic, electromagnetic, heating, and cooling systems is common. However, small-scale energy harvesting systems that support the energy requirements of various sensors used in the building are potential work areas. Moreover, the application of micro-scale piezoelectric energy harvesting systems to buildings that benefit from dynamic loads such as earthquakes is limited. In this paper, a piezoelectric energy harvester is proposed to generate electrical energy from structural vibrations resulting from the building being exposed to different seismic and live loads. The study presents an advanced model that integrates the innovative building solution into the traditional building design, combining structural health monitoring and energy production in the same system. To evaluate the energy efficiency of the RC building, the voltage, current and power responses of the piezoelectric energy harvesting mechanism placed on different column surfaces and different positions of the building under dynamic loads are investigated. When the electrical power values are examined, it is predicted that the piezoelectric energy harvester can produce electricity on a micro-scale, and the energy requirement of small electronic devices such as wireless sensors can be supported. The combination of numerical analyses and experimental results verified with real earthquake data strengthens the practical aspect of the study. In this respect, the study proposes a sustainable and integrated solution that can support the operation of independent sensor systems by generating energy through piezoelectric sensors, especially in buildings located in regions with high seismic risk. In addition, the most important scientific contribution of the study is the comprehensive evaluation of the energy harvesting potential under earthquake and live load conditions through piezoelectric materials integrated into the structural elements of reinforced concrete structures.
Studies
This part is divided into three main sections; i) Model description of energy harvesting structure, ii) Defining earthquake loads and performing transient analyzes, and iii) Verification of energy harvesting structure. All studies carried out under these headings are given in detail in the following sections, respectively.
Model description of energy harvesting structure
The structure discussed in this study is a reinforced concrete building (RC) consisting of a traditional frame system with three floors, each 3 m high. The building has two spans, 5 m each, in both the x and y directions. The vertical carrier system of the building consists of only columns, their dimensions do not change along the height of the building, and the cross-section size of each is 40/40 cm. There are a total of 36 beams with cross-sectional dimensions of 25/50 cm in the building, and there is a 13-cm-thick brick wall on all of them, except for the roof beams. A live load of 0.2 t/m2 is taken into account on all slabs, and the thickness of each is 15 cm. C25/B420C type material is used in all structural system elements of the building. The geometric features of the building are given in Fig. 1. The reinforcing bars are not explicitly modeled using separate discrete elements. Only the concrete material is defined in the modeling process, and the reinforcement is ignored in terms of structural behavior. However, to consider the contribution of the reinforcement to the total weight of the structure, the density of the reinforced concrete (2500 kg/m3), not the concrete (2400 kg/m3), is defined in the structural elements. Thus, the mass contribution of the reinforcement is indirectly included in the model.
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Fig. 1
Geometric features of the building
To transform the RC building into an energy harvesting structure, the sensor segment made of steel and piezoelectric material has adhered to the sensor points (SP) determined in different columns in the building. SP is placed on different columns and positions by taking into account the structural vibrations of the building, and the smart RC building is modeled as shown in Fig. 2.
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Fig. 2
FE model and sensor locations (SP-A, B, C, D) of smart RC building
The figure illustrates the sensors (SP-A, B, C, D) positioned in the energy harvesting mechanism specially designed to extract energy from vibrations caused by seismic movements. Strategic sensor points are selected on the building columns to maximize the energy harvesting performance. The sensors are placed on the surface of the structure placed on the building columns. In order to evaluate the effects of the vibrations of the structure, the SP-A sensor placement is located at the base of the building column, while SP-B, SP-C, and SP-D are distributed to different columns and floors in a way that covers the structure. A detailed cross section showing how the energy harvesting mechanism placed on the building columns is given. The sensor modules are the entirety of the smart structure consisting of piezoelectric material and metal listed in Table 1. The physical dimensions of the piezoelectric sensor are defined by PT, PL, and PH, and their values are 1 mm, 20 mm, and 5 mm, respectively. The dimensions of the smart structure are defined by ST, SH, and LB, and their values are defined as 1 mm, 400 mm, and 40 mm, respectively. The payload point is determined to be 20 mm from the end point of the energy harvesting mechanism. Since the effect of the load can change the dynamic characteristics of the piezoelectric structure, the study aims to increase the vibration amplitude and support energy production at a basic level. A total of four different sensor modules are placed in the building to harvest electrical energy from structural vibrations during seismic and live loads via the piezoelectric effect.
Table 1. Material properties
Steel |
|---|
Density (ρ) = 7800 kg/m3 |
Young’s modulus (E) = 207 GPa |
Poisson’s ratio (v) = 0.3 |
PZT-5A piezoelectric | ||
|---|---|---|
Elastic stiffness matrix (N/m2) | Piezoelectric strain matrix (C/m2) | Dielectric matrix (F/m) |
C11 = 120.35 × 109 | E31 = −5.35 | ϵ11 = 1.5 × 10–8 |
C12 = 75.18 × 109 | E33 = 15.78 | ϵ22 = 1.5 × 10–8 |
C13 = 75.09 × 109 | E15 = 12.29 | ϵ33 = 1.3 × 10–8 |
C33 = 110.87 × 109 | ||
C44 = 22.57 × 109 | ||
Defining earthquake loads and performing transient analyses
Dynamic loads are defined to examine the energy harvesting performance of the three-story smart RC structure. Three different earthquake loads and live loads created by people and furniture on the slabs are planned as the loads defined on the building. In Fig. 3, while the live loads are applied as a uniformly distributed load on all slabs of each floor, the dynamic shear force generated as a result of ground motion acts on the base of the building. The acceleration records have been hit in the Z-direction, which is the dominant vibration mode of the building. Considering the primary purpose of use of the building, the live load affecting each slab is chosen as 2 kN (TS500). Moreover, three different earthquake inputs are considered to evaluate the structure’s energy harvesting performance under seismic load.
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Fig. 3
Live and earthquake loads
In selecting earthquake events used in the dynamic analysis of the building in question, a scenario related to the seismicity of the region where the structure is located is developed first. Then, appropriate earthquake records are selected from the Pacific Earthquake Engineering Research Center (PEER) [45] database, considering earthquake magnitudes, fault distances, source mechanisms, and local ground conditions compatible with the design-based earthquake ground motion level. The characteristic features of the earthquakes are shown in Table 2, and the acceleration records of both horizontal components are given in Figs. 4, 5 and 6.
Table 2. Selected records for earthquake analysis of the building
ID | Record Seq | Event | Year | Station | Mag | Mechanism | Vs30 (m/s) | Rjb (km) | Rrup (km) |
|---|---|---|---|---|---|---|---|---|---|
1 | 159 | Imperial Valley-06 | 1979 | Agrarias | 6.53 | Strike Slip | 242.05 | 0.00 | 0.65 |
2 | 821 | Erzincan, Türkiye | 1992 | Erzincan | 6.69 | Strike Slip | 352.05 | 0.00 | 4.38 |
3 | 6911 | Darfield, New Zeal. | 2010 | HORC | 7.00 | Strike Slip | 326.01 | 7.29 | 7.29 |
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Fig. 4
Both horizontal components of the Imperial Valley-06 earthquake
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Fig. 5
Both horizontal components of the Erzincan, Türkiye earthquake
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Fig. 6
Both horizontal components of the Darfield, New Zeal. earthquake
Although both horizontal acceleration records of earthquakes are given in Fig. 3, only the component with the peak ground acceleration value is used in the analysis.
The dynamic analyses of the building are made using ANSYS. The building is modeled in 3D, adhering to the geometric and material properties given in the previous section and the finite element method (FEM) criteria. In the FE model of the reinforced concrete structure, the Solid186 element is used in ANSYS and convergence analyses are performed by taking into account the frequency results. The optimum mesh size is determined as 50 mm in line with the convergence analyses. A total of 383,648 elements and 684,121 nodes are obtained in the structure. Additionally, in order to increase the reliability and quality of the mesh, the mesh parameter (SMRTSIZE command) is used for smart element sizing. Therefore, the mesh transition between the reinforced concrete structure and the sensor module is performed more regularly and accurately.
According to the preliminary dynamic analysis, the building’s concrete and rebar materials remained in the liner elastic area. The second-order effects are additionally inside the permitted limit values. There are no discernible changes between the linear and nonlinear analysis results when the structural behavior is studied. In addition to all of the above, linear analysis is chosen as the dynamic analysis technique in this study due to its efficiency and simplicity.
Verification of energy harvesting structure
Although FEM is widely used in solving complex structural problems, its validation by experimental and analytical results is essential. The FE model of the reinforced concrete structure was validated with numerical models created in SAP2000 and ideCAD programs [46]. Then, the integration of piezoelectric sensor modules into the reinforced concrete structure is performed. In this context, the validation setup in the study focused on the validation of the numerical approach used in the dynamic modeling of the piezoelectric sensor module. For this purpose, before the energy harvesting analysis of the RC building, validation is performed in an experimental system to increase the reliability of the FEM. In this context, an experimental system of a smart structure [47] is created with piezoelectric materials adhered to the surface of the aluminum beam, as shown in Fig. 7. In order to create the smart structure, the bonding method is preferred for patching the piezoelectric material. This is achieved by cleaning and smoothing the plate surfaces before the bonding process. Epoxy-based conductive adhesive is used to increase the surface contact. Then, a certain pressure application is carried out with the plates fixed during the curing process. Before the experimental process, the vibration responses of the piezoelectric energy harvesting structure under cyclic loads are checked.
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Fig. 7
Experimental system of the smart structure
As shown in Fig. 7, the experimental system consists of a smart beam, electromagnetic coil, laser displacement sensor (LDR), and controller. One end of the smart beam is fixed, and the other is set to be free. With the electromagnetic coil placed at the free end, the endpoint of the smart beam is released from the defined position under the initial value conditions. The displacement responses are obtained with the help of the LDR sensor to measure the vibrations occurring at the tip of the smart beam. The displacement responses are converted to analog voltage (± 10 V DC) by the controller of the LDR sensor. Then, the displacement data is recorded to the computer with the NI MYRIO1900 data acquisition card [48].
As shown in Fig. 8, the FEM of the smart structure is created in ANSYS to verify the experimental results. The Solid226 element, which has six structural and one-volt degrees of freedom (DOF) at each node, is specified to model both the aluminum section and the piezoelectric material in the smart beam. In the FEM, the upper surfaces of the piezoelectric material are defined as “volt” boundary conditions, and the bottom surfaces are defined as “ground” boundary conditions. The FEM of the smart beam with a mesh size of 2 mm is created from 5302 nodes and 2520 elements in total.
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Fig. 8
FE model of the smart structure
To validate the FEM of the smart beam, transient analyzes are performed under two different initial conditions. Comparative simulation results and experimental results for free vibration responses at 18 mm and 28 mm initial conditions are presented in Fig. 9.
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Fig. 9
Experimental and simulation vibration responses at a 18 mm and b 28 mm initial conditions
Figure 9 contains the experimental and numerical comparison of the endpoint displacement responses of the smart beam. When the results are examined, it is observed that both the experimental and simulation results are compatible under two different initial conditions. Therefore, verifying the FEM with the empirical study of the smart beam increases the reliability and accuracy of the finite element analysis (FEA) for the energy harvesting analysis of the RC structure.
The production of a real-scale reinforced concrete structure in a laboratory environment was excluded from the scope of the study due to cost, safety, and technical limitations. The validation study is carried out with a controlled experimental setup to test the basic characteristics of the piezoelectric energy harvesting mechanism. Although the simplified nature of the experimental setup limits the generalization of the results directly to a three-story reinforced concrete structure, it provides a valid framework for evaluating the accuracy of the piezoelectric behavior in the numerical model.
Results
This part is divided into two main sections; i) Sensor responses, ii) Power outputs. All studies carried out under these headings are given in detail in the following sections, respectively.
Sensor responses
The voltage responses obtained from different sensor points of a-e) SP-A, b-f) SP-B, c-g) SP-C, and d-h) SP-D placed on the structure are presented in Figs. 10, 11 and 12 for earthquake inputs of RSN159, RSN821, and RSN6911, respectively. In order to examine the effect of the energy harvesting mechanism on producing energy with and without payload, it is investigated separately under payload point and 0.250 kg. In the figures, the vibration results labeled (a-b-c-d) are without payload, while (e–f-g-h) has a payload of 0.250 kg.
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Fig. 10
Voltage responses from different sensor points under earthquake input of RSN159 without a–b and with e–h payload
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Fig. 11
Voltage responses from different sensor points under earthquake input of RSN821 without a–d and with e–h payload
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Fig. 12
Voltage responses from different sensor points under earthquake input of RSN6911 without a–d and with e–h payload
The sensor responses of the building’s energy harvesting mechanism under different loads are presented in Figs. 10, 11 and 12. As seen in Fig. 10, the maximum sensor values for mp = 0.250 kg are found to be 47.99 V, 47.63 V, 47.78 V, and 48.98 V for the sensor points, respectively, while these values for mp = 0 kg are 2.644 V, 2.617 V, 2.013 V, and 2.684 V. It is clear that as the payload at the end point of the energy harvesting mechanism increases, there is an increase in the sensor values.
In Fig. 10(a), the maximum sensor values obtained under E load are 2.632 V, while this value increases to 2.644 V with Q and E loads. While the sensor values are low only under Q loads, there is a significant increase in the building’s sensor values under E and Q loads.
When the sensor values obtained from the sensor points are compared as shown in Figs.10, 11 and 12, in no payload condition, the data of the sensor points are found to be close to each other, while in the payload condition, lower values are obtained in SP-A, B and D, and higher values are found in SP-C. For example, in Fig. 11, the sensor values for no payload are 1.535 V, 1.516 V, 1.486 V, and 1.558 V for SP-A, B, C, D, respectively, while these values with payload are 28.27 V, 28.08 V, 33.45 V, and 28.94 V, respectively. Power outputs are obtained to evaluate the sensor responses in terms of the performance of the energy harvesting mechanism.
Power outputs
The power outputs under resistance load are examined to evaluate the energy harvesting performance efficiency of the RC building under earthquake (E) and live (Q) loads. The energy harvesting circuit is set up to obtain the power outputs corresponding to the resistive load, as shown in Fig. 13.
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Fig. 13
Circuit of power output
To examine the energy harvesting performance, it is necessary to determine the current values of the system against the resistive load. Therefore, the current under voltage in the piezoelectric material against the resistive load of the system is found by using Ohm’s law. The electrical power equation P = I*V = V2/R is used to calculate the output power in the piezoelectric element. Thus, the instantaneous current and power obtained from the RC building under Q and E loads with or without payload are calculated and are shown in Figs. 14, 15 and 16 for earthquake loads of RSN159, RSN821, and RSN6911, respectively.
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Fig. 14
Current and power outputs of RSN159 at sensor points for a SP-A, b SP-B, c SP-C, and d SP-D
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Fig. 15
Current and power outputs of RSN821 at sensor points for a SP-A, b SP-B, c SP-C, and d SP-D
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Fig. 16
Current and power outputs of RSN6911 at sensor points for a SP-A, b SP-B, c SP-C, and d SP-D
The current and power responses obtained from the energy harvesting analysis of the RC building are presented in Figs. 14, 15 and 16 for different sensor points and defined loads. When the sensor points are compared, the maximum power output is 0.355 W for the sensor point SP-C, while the minimum power value is found as 0.296 W for the sensor point SP-B. For instance, as shown in Fig. 14, maximum power values are calculated as 0.3 W, 0.296 W, 0.355 W, and 0.314 W for SP-A, B, C, and D, separately.
It is clear that the energy harvesting mechanism increases its energy performance as the payload increases. For example, for the no payload case shown in Fig. 14, the obtained power values are 0.95 × 10–3 W, 0.93 × 10–3 W, 0.71 × 10–3 W, and 0.98 × 10–3 W for the SP-A, B, C, and D, respectively, while these values in the payload case are 0.3 W, 0.296 W, 0.355 W, and 0.314 W.
When the effect of E and Q loads is evaluated in addition to the payload, it is clear that Q load causes a very small change in current values, but it does not affect the power outputs. Additionally, it can be concluded that the effect of the E load is more effective than the Q load. For example, in Fig. 16(a), for the payload case, the maximum power outputs are 0.228 W and 0.228 W for the E and Q and E loads, respectively, while the change in current values is found as 2.778 × 10–5 A and 2.779 × 10–5 A.
When the performance of the energy harvesting mechanism under the effect of earthquake input is examined, the maximum power output is obtained with the earthquake input of RSN159, while the minimum is found with RSN821.
The results of this study are consistent with the principles of piezoelectric energy harvesting, where mechanical stress/strain caused by structural vibrations is converted into electrical energy. The observed energy increase at the column bases is consistent with the high stress/strain intensities predicted by structural dynamics theories under seismic loading. Furthermore, the synergistic effect of live and earthquake loads on energy harvesting reveals the complex interaction between static and dynamic forces in real structures. These results reinforce the potential of piezoelectric materials integration into smart building systems to create sustainable, self-generating monitoring systems and bring together structural engineering and energy harvesting technology.
Conclusions
In this paper, the energy harvesting performance of the smart RC building under earthquake and live loads is investigated. A smart building is achieved by placing piezoelectric sensor modules on building columns for energy harvesting. Structural loads of the smart building are defined, and voltage responses are obtained from the sensor points by applying different earthquake loads. To calculate the power obtained by energy harvesting from the smart building, the current, power, and total battery power values measured from the piezoelectric patch under resistive load are presented comparatively for just earthquake loads, live and earthquake loads.
When the results are evaluated, it is concluded that the results obtained from the sensor points differ under different earthquake and live loads. It is observed that higher voltage and power values are obtained due to increased strain values when the sensor location is close to the root of the building column. Since the live load is statically loaded on the building, although it has a small effect during the transient analysis process, it can be said that the live load significantly affects the energy harvesting performance of the smart building together with the earthquake load. The voltage, current, and power results show that the energy harvest to be obtained during an earthquake of a smart building to be built in the region where seismic movements are intense is a logical method for operating electronic devices such as sensors and storing excess energy.
Integrating piezoelectric sensors into RC structures, especially in regions with intense seismic activity, can provide a sustainable energy source that meets the energy needs of structural health monitoring and low-power electronic devices. Placing sensors at the right points according to the vibration characteristics of the structure significantly increases energy harvesting efficiency; the combined effect of earthquakes and live loads further strengthens energy production. In this context, piezoelectric-based energy harvesting systems can be considered a feasible and effective solution in future innovative building technologies.
The system offers a practical solution to meet critical energy needs after a disaster with its ease of application and low maintenance cost. However, piezoelectric material can be affected by factors such as material fatigue and environmental effects in the long term. Although this study focused on short-term dynamic conditions, in future studies, it will be a critical step to perform different earthquake scenarios, long-term energy harvesting performance, and cost-time-benefit analyses.
Acknowledgements
The authors express their special thanks for the experimental study opportunities provided by Dokuz Eylül University for this study.
Funding
The authors received no financial support for the research and publication of this article.
Declarations
Conflict of interests
The authors declare no potential conflicts of interest concerning the publication of this article.
Angela Ourivio Nieckele
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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