Development of a Cloud-Based Real-Time Building Health Monitoring and Prediction System Using AI and IoT Sensors

In this study, a cloud-based real-time building health monitoring and prediction system using AI and IoT sensors was developed. To predict the building condition, which constitutes time-series data, statistical-based ARIMA and AI-based LSTM prediction models were designed, and the effectiveness of the proposed prediction models was experimentally verified using a 1/8-scaled miniaturized structure. The prediction accuracy in terms of MAPE (less than 1%) was experimentally confirmed to be satisfactory. Moreover, a method for analyzing dimensional structure deformation was developed by combining multiple sensor measurements, and its effectiveness was verified through the case study of a real earthquake-damaged building.

A simple seismic input model for estimating the seismic resistance of structures

The paper formulates the principles for shaping the design input, in particularly that the design input is not required to be similarto the real input. It is suggested that the seismic input should be set as a sinusoidal segment. This requires that the sinusoid be hazardous to the structure and causes it to reach the same limit state as a real earthquake. The amplitude of the sine wave is set equal to the average value of the peak boosts. The frequency of the exposure is set as dangerous for the structure to be designed and the duration is set according to the frequency of the exposure. The proposed seismic modelling approach makes it possible to assess the potential for progressive collapse and low-cycle fatigue of the designed structure. The model is based on statistical data on past earthquakes to estimate the average level of peak accelerations and the correlation between the prevailing period and the duration of the seismic event. The proposed input model greatly simplifies the computational assessment of seismic stability and the modeling of inputs on the seismic platform.

Design, Implementation and Testing of a Network-Based Earthquake Early Warning System in Greece

In this study we implemented and tested the Earthquake Early Warning system PRESTo (PRobabilistic and Evolutionary early warning System, Satriano et al., 2011) on the Greek Ionian islands of Lefkada, Zakynthos and Kefalonia. PRESTo is a free and open source platform for regional Earthquake Early Warning developed at the University of Naples Federico II, which is currently under experimentation in Southern Italy, in the area covered by the Irpinia Seismic Network. The three Ionian islands selected for this study are located on the North-Western part of the Hellenic trench. Here the seismicity rate and the seismic hazard, coupled with the vulnerability of existing critical infrastructures, make this region among the highest seismic risk areas in Europe, where the application of Earthquake Early Warning systems may become a useful strategy to mitigate the potential damage caused by earthquakes. Here we studied the feasibility of implementing an Earthquake Early Warning system on an existing seismic network, which was not specifically made for earthquake early warning purposes, and evaluated the performance of the system, using a data set of real-earthquake recordings. We first describe the technical details of the implementation of PRESTo in the area of interest, including the preliminary parameter configuration and the empirical scaling relationship calibration. Then we evaluated the performance of the system through the off-line analysis of a database of real earthquake records belonging to the most recent M > 4.0 earthquakes occurred in the area. We evaluated the performance in terms of source parameter estimation (location, magnitude), accuracy of ground shaking prediction and lead-time analysis. Finally, we show the preliminary results of the real-time application of PRESTo, performed during the period 01–31 July 2019.

Application of the wavelet transform in filtering the noise of real earthquake accelerograms

In the deterministic analysis of building structures, real accelerograms are used as input data. Very often, only instrumental recordings of accelerograms that are not cleared of noise are publicly available. Such accelerograms cannot be used directly in the analysis of building structures. Various broadband filters are used to adjust the instrumental recordings of accelerographs. This article discusses the possibility of applying filters based on the wavelet transform. The technique of the algorithm of filtering from the noise of the source data is considered. As an efficiency of this filtering algorithm, a comparative analysis of the dynamic coefficient and the energy criteria of the pulse and Arias for the corrected and instrumental accelerograms is carried out.

An Improved Quadtree Sampling Method for InSAR Seismic Deformation Inversion

With the development of interferometric synthetic aperture radar (InSAR), the seismic deformation observation density increases sharply. Data down-sampling can effectively reduce the observation density and the computational cost for subsequent researches. Considering the saliency of the deformation field, we introduce a saliency-based quadtree algorithm for down-sampling (SQS). Three simulation experiments show that SQS can effectively distinguish the near-field and far-field deformation, as well as reduce the amount of observation, while keeping the detailed information of the main deformation near the fault. SQS can avoid the interference of far-field local deformation better than the traditional quadtree sampling algorithm (QS), thus obtaining better inversion results. We took the Dingri earthquake on 20 March 2020 as a case study to verify the advantages of SQS in dealing with real earthquake deformation. We obtained the co-seismic deformation from the ascending and descending Sentinel-1 for the Dingri earthquake, using QS and SQS for sampling and inversion separately. The results show the advantages of SQS in data volume reduction, observation distribution, anti-interference of local deformation, and inversion accuracy. Our preferred solution based on SQS shows that the Dingri earthquake was caused by a normal fault slip. The main slip area is 2–5.5 km deep with a maximum slip of 0.68 m. The estimated geodetic moment is 3.14 × 1017 Nm, corresponding to a magnitude of Mw5.63.

Estimation Method for Roof‐damaged Buildings from Aero-Photo Images During Earthquakes Using Deep Learning

Issuing a disaster certificate, which is used to decide the contents of a victim’s support, requires accuracy and rapidity. However, in Japan at large, issuing of damage certificates has taken a long time in past earthquake disasters. Hence, the government needs a more efficient mechanism for issuing damage certificates. This study developed an estimation system of roof-damaged buildings to obtain an overview of earthquake damage based on aero-photo images using deep learning. To provide speedy estimation, this system utilized the trimming algorithm, which automatically generates roof image data using the location information of building polygons on GIS (Geographic Information System). Consequently, the proposed system can estimate, if a house is covered with a blue sheet with 97.57 % accuracy and also detect whether a house is damaged, with 93.51 % accuracy. It would therefore be worth considering the development of an image recognition model and a method of collecting aero-photo data to operate this system during a real earthquake.

STIFF vertical seismic absorbers

Seismic isolation is proven to be an effective technology for seismic protection of building structures, equipment, and industrial facilities. The majority of the existing isolation systems and techniques are related to horizontal ground motions, whereas there are only a few vertical isolation systems. The main reason is because of the conflict concerning the demand for isolation stiffness. More specifically, a vertical isolated system must have sufficient vertical rigidity to sustain the weight of the isolated object/system and retain the static vertical deflection in reasonable limits. On the other hand, the isolated system must also have enough flexibility to isolate the accelerations. In order to overcome this difficulty, a novel vertical seismic absorber system is proposed, that combines negative stiffness-driven absorbers with inerters. The inerter manages to reduce the frequency of the system, without weakening the structure or increasing the seismic load. At the same time, the effective damping is significantly increased with the KDamper. This way, the dynamic behavior of the system is improved, in terms of absolute accelerations, and simultaneously, the static settlements are retained at any desired level. The design of the vertical seismic absorber is based on engineering criteria, and the excitation input is selected according to the seismic design codes. The dynamic performance of the vertical seismic absorber is also evaluated with real earthquake records, using a realistic displacement-dependent configuration for the realization of the negative stiffness element. Finally, the detuning phenomena are observed and discussed via sensitivity analysis.

WATER TANK AS A TUNED MASS DAMPER

Water tanks are integral part of all buildings and they impart large dead load on the structure. This additional mass can be utilized as TMD to absorb extra energy imparted on the structure during earthquake. The present work is limited to linear analysis of 10 & 15 storey buildings subjected to real earthquake data. Water tank position is changed by keeping it at center and at extreme corners of the building. Also effect of water tank as TMD with variation of sizes is checked.

Influence of Nonlinear Fluid Viscous Dampers on Seismic Response of RC Elevated Storage Tanks

The numerical investigation on the seismic response of RC elevated liquid storage tanks installed with viscous dampers is presented. A discrete two-mass model for the liquid and multi-degree of freedom system for staging, installed with the dampers are developed for Reinforced Concrete (RC) elevated liquid storage tanks. The elevated tank is assessed for seismic response reduction when provided with Linear Viscous Damper (LVD) and Nonlinear Viscous Damper (NLVD), installed in the staging. The RC elevated liquid storage tanks are analyzed for two levels of liquid containment in the tank, 100% and 25% of the tank capacity. Three Configurations of placements of dampers viz. dampers at alternate levels (Configuration I and Configuration II) and dampers at all the panels of the staging of the tank (Configuration III) are considered. To study the effect of peak ground acceleration, eight real earthquake time histories with accelerations varying from 0.1 g to 0.93 g are considered. The nonlinearity in the viscous damper is modified by taking force proportional to various velocity exponents. It is found that the nonlinear viscous dampers with lower damping constant result in a comparable reduction in the response of RC elevated liquid storage tank, to that of linear viscous dampers with higher damping constant. A lower damping constant signifies compact the size of the damper. Doi: 10.28991/cej-2020-SP(EMCE)-09 Full Text: PDF