Purpose This paper proposes an in-network vibration data processing using Wireless Sensor Network (WSN) leveraging Machine Learning (ML) for damage detection and localization. The study also presents the ML algorithms comparison that is suitable to be deployed in WSN and implemented the proposed cluster-based WSN topology on the bridge simulation test.Methods The bridge vibration data was acquired using accelerometer-based wireless sensor nodes. The data collected are transformed using Fast Fourier Transform (FFT) to obtain fundamental frequencies and their corresponding amplitudes. The machine learning method i.e., Support Vector Machine (SVM) with linear and Radial Basis Function (RBF) kernel was used to analyze the vibration data collected from the WSN. In-network data processing and cluster-based WSN topology is implemented and the programmable wireless sensor nodes is utilized in this study.Results The experiments were conducted using real programmable wireless sensor nodes and developed our test bed bridge which makes this work different from the previous studies. The classification and predicting results shows 97%, 96%, 97%, and 96% for accuracy, precision, recall rate, and f1-score, respectively.Conclusion Machine learning methods can potentially be combined with the vibration WSN for bridge damage detection and localization.

A large steel water tank installed at a coal power plant in Cilegon, West Java, Indonesia, faced stability and strength concerns due to significant tilting observed during a water load test. As a precautionary measure, the tank was emptied, and a thorough assessment was initiated to evaluate its fitness for purpose and to determine the strength and stability of both the tank and its foundation for long-term use. The site investigation identified uneven settlement and tilting of the foundation. To conduct a root cause analysis, finite element analysis was performed, with soil properties calibrated based on measured settlement. The mapped deformation of the tank's base was compared to industry standards such as API 653, EEMUA 159, and PIP STE02030. The analysis revealed that the failure resulted from an error in calculating the strength of the base soil during the design phase. Fortunately, the tank itself did not sustain significant damage, experiencing only rigid body displacement with minimal out-of-plane deformation, rendering repairs unnecessary. A proposed retrofit solution to enhance the strength of the soil beneath the tank is to implement soil improvement by concrete jet grouting. Once the soil characteristics have been improved, a comprehensive finite element analysis confirmed that both the steel water tank and the reinforced soil surrounding it will remain within acceptable stress and deformation levels for both short-term and long-term conditions. Field measurements further validate that the application of concrete jet grouting has effectively reduced the settlement potential of the tank.

Monitoring the structural health of civil structures is an important research area for continuously monitoring the condition of structures and predicting possible damage. One example is bridge monitoring. To estimate the damage to the bridge structure, it is necessary to continuously monitor the modal parameters, namely the natural frequency of the structure. This is generally measured using the accelerometer sensor. The accuracy of the monitoring system depends not only on accurate sensors, but also on the wireless sensor network used to collect data and transmit it from the sensor nodes to the processing center. In calibrating the accelerometer sensor, we use the VCD21D vibration calibrator tool to test and calibrate the accuracy of the sensor. The experiment was carried out by comparing the accelerometer measurement results with the reference value from the vibration calibrator. The experimental results show that the accelerometer calibration works well, resulting in a maximum measurement error of about 0.3 %. In addition, we also tested WSNs (Wireless Sensor Networks) synchronization using the RBS (Reference Broadcast Synchronization) method with a synchronization error of $\boldsymbol{2049.5}\ \boldsymbol{\mu}\mathbf{s}$ . The experimental results show that the RBS method successfully synchronizes the sensor nodes in the WSNs accurately and efficiently. The time difference between neighboring nodes is measured in very small timescales (microseconds).

Lemah Ireng II Bridge is a type of box girder balance cantilever bridge located in Semarang Regency, Central Java, which was completed in 2014. The renewal of bridge loading regulations in 2016 consisted of SNI 1725:2016 for standard load and SNI 2833:2016 for earthquake load. Changes in earthquake loading regulations resulted in an increase in the ground surface spectra value in the short period (Sds, T=0,2 second) in the longitudinal direction by 38.47% and in the transverse direction by 45.39% as a result of updating the earthquake map and the earthquake response modification factor. To determine the level of bridge performance against the applicable earthquake regulations based on the pier structure parameters, the Non-Linear Time History Analysis (NLTHA) method is used. The NLTHA method uses seven deaggregated ground motion records which aim to represent the ground motions that occur at the bridge site. Parameter limits at the pier to determined performance level of bridge based on NCHRP Synthesis 440 and NCHRP Research Report 949. According to the results of performance-based analysis, the bridge pier structure meets the Fully Operational performance level based on the parameters of drift, compressive strain of concrete and tensile strain of steel reinforcement. At this level of performance, after an earthquake the structure suffers very little damage so no repairs are needed and the bridge can function immediately after the earthquake.

AbtractExisting special bridges such as cable-stayed bridges which are complex in structure need to be evaluated against SNI 1725:2016 and SNI 2833:2016. Dr. Ir. Soekarno Bridge located in Manado, North Sulawesi, was used as case study. Analysis based on the performance of the bridge was conducted using the Nonlinear Static Pushover Analysis (NSPA) with three different load distributions and Nonlinear Time History Analysis (NLTHA). Due to the standard load of the bridge, the deflection was still below the allowable deflection. Girder has an overstress of 12% in the Service Ic combination. The cable also has overstress in Cable 7 between 0.4% and 6.2%. Lower segment pylon capacity was exceeded by earthquake load combination of 28%. Bridge performance shows that the bridge structure was at fully operational performance level and the element performance was at immediate occupancy level, each method shows different result in base shear and displacement. The result shows that re-evaluation for existing special bridges is required. The bridge performance has different base shear and displacement for each method. Nonlinear Time History Analysis is the better option for special bridge, Nonlinear Static Pushover Analysis method requires a further study to determine the ideal load distribution for special bridge because the load distribution is crucial to determine the result of pushover analysis. AbstrakJembatan khusus eksisting seperti jembatan cable stayed yang sangat kompleks perlu dievaluasi kinerjanya terhadap SNI 1725:2016 dan SNI 2833:2016. Studi kasus pada penelitian ini adalah Jembatan DR. Ir. Soekarno di Kota Manado, Sulawesi Utara. Dilakukan pula analisis berdasarkan kinerja dengan Nonlinear Static Pushover Analysis dengan tiga pola beban dan Nonlinear Time History Analysis. Akibat beban standar jembatan, lendutan yang terjadi masih dibawah lendutan ijin. Girder mengalami kelebihan tegangan sebesar 12% pada kombinasi beban Layan Ic. Kabel juga terjadi kelebihan tegangan pada Kabel 7 antara 0,4% sampai 6,2%. Kapasitas pylon segmen bawah terlampaui oleh kombinasi beban gempa sebesar 28%. Analisis kinerja struktur jembatan dengan dua metode didapatkan bahwa tingkat kinerja struktur adalah fully operational dan kinerja elemen adalah immediate occupancy, akan tetapi nilai base shear dan perpindahan berbeda untuk masing-masing metode. Hasil analisis menunjukkan bahwa jembatan khusus eksisting perlu di evaluasi ulang terhadap peraturan terbaru. Kinerja jembatan dengan dua analisis nonlinier yang dilakukan menunjukkan hasil yang berbeda, Nonlinear Time History Analysis tetap menjadi metode yang lebih baik untuk jembatan khusus sedangkan metode Nonlinier Static Pushover Analysis perlu penelitian lanjutan untuk menentukan distribusi beban pushover yang cocok digunakan untuk jembatan cable stayed, mengingat pola distribusi beban sangat menentukan hasil dari analisis pushover.

Wireless sensor network (WSN) has played important roles in various aspects of life including in bridge structural health monitoring system. Due to environmental and operational circumstances, a bridge needs to be monitored to make sure its continuous availability and operational safety. The structural stiffness of a bridge will decrease after some period of time due to structural strength declining and cracking. The change in bending stiffness will change the structural dynamic characteristics of the bridge and its capacity. Therefore, an automatic assessment system for bridge capacity is required. This article proposes the development of data acquisition and processing method for bridge capacity determination using its dynamic response, based on agent-based in-network processing. The use of WSN in bridge capacity monitoring and diagnostic also allows for sending warning messages to the control room. Experiment in the laboratory-scale bridge is performed to test the proposed system performance and the result was well validated with the finite-element analysis (FEA) results with modal assurance criterion value 0.90 that shows the high correlation degree between the FEA and the experiment. In addition, the processing time and energy consumption are compared with previous similar work, which shows the efficiency of the proposed system.

Present study investigating the use of wireless sensor networks (WSNs) in the assessment of bridge condition as well as early warning system. The WSNs are used to measure the acceleration occurred on the bridge and the mode shape of the bridge as the excitation loads passing through the bridge. Fast Fourier Transform (FFT) is applied to transform the measured acceleration to get the frequency of the bridge dynamic response. Numerical integration is applied to determined the acceleration to get the displacement of the bridge dynamic response. Implementing structural dynamics equation, the effective stiffness of the bridge can be determined using the frequency. The effective stiffness and the bridge dynamic response are then used to obtained the bridge condition and load ratings. A scaled model of steel truss bridge and miniature truck with various loads were used to simulate the use of WSNs in bridge assessment, which were also used to validate the finite element model. The finite element model was then used to simulate various scenarios, including the scenarios in which the bridge elements had various level of damages. The behaviors of bridge with various level of damages can be used to identify the location and the level of damages in the bridge and were found to be useful as early warning system for bridges condition and load ratings.

The use of high strength reinforcing bars has becoming an interesting and cost-efficient option in construction industry recently. However, their use is limited due to their low deformability which might induce a brittle collapse in the structures. Also, longer development length is needed to transfer stress from reinforcing bars to the surrounding concrete. This paper focuses on investigating the influence of fibrous concrete and high-strength reinforcing bars on the behavior of structural elements. Five half-scaled specimens of interior joints using plain or fibrous concrete, reinforced with conventional 420 MPa or high strength reinforcing bar of 520 Mpa were experimentally tested. The two specimens of plain concrete, reinforced longitudinally with 16 mm and 19 mm reinforcing bars are defined as control specimens. The other test specimens were casted with Polypropylene fiber reinforced concrete (PFRC) with 16 mm and 19 mm longitudinal reinforcing bar. Loading protocol of all test specimens is defined according to ACI 374.2. The structure behavior, such as dissipated energy, bond between reinforcing bars and surrounding concrete, and stiffness degradation of the four specimens were evaluated and compared. The results obtained shows that the use of fiber increase the dissipated energy up to 27.5 % compared to specimens with plain concrete. Moreover, the peak strength of PFRC specimens was slightly increased (3% - 7%) compared to that of specimens with plain concrete. Moreover, there is an increase in peak-to-peak stiffness at elastic range loading with the addition of fiber, while no significant difference after the yields of longitudinal reinforcing bars.

For an earthquake resistant structure, reinforced concrete building must have certain performance level under certain level of earthquakes such as when it is subjected to a strong level earthquake, it may experience severe damages, but without partial or full collapse, thus some reparations could be done to recover the functions of those damaged structures. However, repairing methods were usually done to slightly-damaged structures, while for severely-damaged structures, more studies are still needed to optimize the effectivity of the repair. Therefore, the objective of this study is to evaluate the performance of a structure that is retrofitted using high strength concrete after experiencing severe damage from an earthquake. Reinforced concrete beam column joints - that are used as specimens for this study - were initially subjected to cyclic loading up to 5% drift. The specimens’ beams are then repaired by replacing the damaged concrete with the new, stronger concrete without replacing the existing reinforcement bars. The retrofitted specimens are then subjected to the same cyclic loading and their nonlinear behaviors are compared to the behavior of their initial condition. The experimental results show that there are mostly reductions in lateral strengths, although there is an increase of strength in one specimen, while there are also reductions in energy dissipated.

This paper proposes the development of an autonomous system for dynamic response-based bridge condition assessment using wireless sensor network (WSN). The assessment identifies the bridge's fundamental frequency and uses the information to determine the bridge rating. Due to the computational capability in wireless sensor nodes, it is of practical interest to implement in-network processing in bridge condition monitoring system, in which data processing is conducted within the sensor networks to prevent data flooding in WSN. One of the promising in-network processing approaches is the agent-based processing that leverages the concept of system autonomy. However, uncontrolled in-network processing consumes a lot of energy. Thus, setting all sensors to wake up or sleep deterministically is often not a feasible solution. What is needed is for the system to perform in-network processing only in the event when the bridge is traversed by a single heavy truck, whereas this event occurs randomly. Thus, the two-player game and reinforcement learning algorithm are utilized to control the process. Simulation results show that the proposed control algorithm is able to effectively determine when the process should be executed. A case study, testing the algorithm using real measurements taken from a bridge, and then comparing the test results with the results generated from finite element analysis is provided for validation purpose. Comparison of the proposed approach with earlier works, in terms of processing time and energy consumption, is also presented.

An earthquake resistant structure should be able to perform as expected when it’s struck by an earthquake such as it may experience slight damage and should be able to be repaired to its original state when struck by a design level earthquake. However, there are still debates whether reparation should also be viable when structures are experiencing severe damage. There are still a little to no studies about repairing severely damaged structures, therefore a study was made to see how severely damaged structures behaved after being repaired. Two beam column joints are used as specimens, which were severely damaged by an earthquake simulation before getting repaired. Both their initial and repaired condition are then modeled analytically using SAP2000. Their behaviors such as plastic hinges, joint’s shear deformation, bond slip, and rebars’ residual strain and stress due to previous loading are also implemented to the model. Although the lateral strength of the specimens are similar to their analytical model, the other behavior, especially their stiffness is not similar, therefore needing another parameter implemented in the model.

Wireless Sensor Network (WSN) is small embedded devices deployed in large scale network and has capability to sense, compute, and communicate with others. It combines modern sensor, microelectronic, computer, communication, and distributed processing technology. It takes into account in several aspects of live especially in structural health monitoring system of bridge. Due to environmental circumstance, a bridge should be monitored to make sure that it can perform its service safely. Therefore, it is necessary to develop WSN application to monitor bridge condition and send warning message to control room if the bridge is under abnormal condition. This paper proposes the development of automatic WSN system for measuring the level of bridge structural health based on its dynamic responses. The main contribution of this work is developing WSN system for vibration-based bridge condition assessment in which identifies the bridges fundamental frequency and mode shape. Experimental result shows that the fundamental frequency measured by our proposed system is close to the value analyzed using finite element analysis (FEA) and according to Modal Assurance Criteriation (MAC), our proposed measurement system has correlation with FEA

Currently, design of reinforced concrete buildings is still dominated with normal strength reinforcing bars, not exceeding 420 MPa yield strength. Meanwhile, the use of higher strength reinforcing bars tend to increase due to some benefits in the construction, such as reducing the total weight of reinforcing bars and alleviating reinforcing bars congestions. In this study, reinforcing bars with yield strength of 520 MPa are utilized in the reinforced concrete beam-column joint. The objective is to study the seismic performance of reinforced concrete beam-column joints. A total of 3 interior beam-column joints, half-scaled specimens with different yield strengths and bar diameters was tested. One of the test specimens which was 16 mm diameter and had normal strength reinforcing bar. The other two specimens use high strength reinforcing bars, and have 16 mm and 19 mm diameter bars. Loading protocol of all the specimens is conformed with ACI 374.2. Dissipation energy and deformability of the joints is then compared. Normalized energy dissipation of the specimens with high strength reinforcing bars was slightly lower than that of the specimens with normal reinforcing bars. However, specimens with high strength reinforcing bars tend to have smaller deformability than that of the specimens with normal reinforcing bars.

This paper is concerned with the connection design for a two-floating beam system for minimum hydroelastic response. The frequency domain approach is used for the hydroelastic analysis. The fluid is modelled as an ideal fluid, and the floating beams are modelled by the Euler–Bernoulli beam theory. The boundary element method (BEM) and the finite element method (FEM) are applied to solve the governing equation of the fluid motion and the beam equation of motion, respectively. The study aims to investigate the optimum location and rotational stiffness of the connection for the two-floating beam system with the view to minimize the compliance. The study also investigates the effects of relative beam stiffnesses on the hydroelastic response of the two-floating beam system.

This paper is concerned with the hydroelastic response of interconnected beams by a mechanical joint. A frequency domain approach is developed for the hydroelastic analysis. The fluid is modelled as an ideal fluid, whereas the beam is modelled by the Euler-Bernoulli beam theory. The boundary element method (BEM) and finite element method (FEM) are applied to solve the governing equations of fluid motion and beam equation of motion, respectively. This study investigates the design of the mechanical joint in reducing the hydroelastic response. The design involves varying the rotational stiffness and the location of such a mechanical joint to obtain a significant reduction of the hydroelastic response of the interconnected beams that model a longish very large floating structure (VLFS).

This paper is concerned with the hydroelastic response of multiple floating beams connected together by mechanical joints with rotational spring stiffness under wave action. A frequency domain approach is developed for the hydroelastic analysis. The fluid is assumed to be incompressible, inviscid and its motion irrotational so that a velocity potential exists and thus the fluid motion is governed by the Laplace's equation. The floating beams are modelled by the Timoshenko beam theory which allows for the effects of transverse shear deformation and rotary inertia. The boundary element method (BEM) is used to solve the governing equation and boundary conditions of the fluid domain. The finite element method (FEM) is employed for solving beam equation of motion. The study investigates the effects of shear deformation and rotary inertia, relative beam stiffnesses, rotational stiffness of mechanical joints, and the varying seabed profile on the hydroelastic responses of the interconnected floating beams. Copyright