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Keywords = cumulative absolute velocity

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25 pages, 6448 KiB  
Article
Research on Time Series Monitoring of Surface Deformation in Tongliao Urban Area Based on SBAS-PS-DS-InSAR
by Yuejuan Chen, Cong Ding, Pingping Huang, Bo Yin, Weixian Tan, Yaolong Qi, Wei Xu and Siai Du
Sensors 2024, 24(4), 1169; https://doi.org/10.3390/s24041169 - 10 Feb 2024
Cited by 6 | Viewed by 2122
Abstract
As urban economies flourish and populations become increasingly concentrated, urban surface deformation has emerged as a critical factor in city planning that cannot be overlooked. Surface deformation in urban areas can lead to deformations in structural supports of infrastructure such as road bases [...] Read more.
As urban economies flourish and populations become increasingly concentrated, urban surface deformation has emerged as a critical factor in city planning that cannot be overlooked. Surface deformation in urban areas can lead to deformations in structural supports of infrastructure such as road bases and bridges, thereby posing a serious threat to public safety and creating significant safety hazards. Consequently, research focusing on the monitoring of urban surface deformation holds paramount importance. Interferometric synthetic aperture radar (InSAR), as an important means of earth observation, has all-day, wide-range, high-precision, etc., characteristics and is widely used in the field of surface deformation monitoring. However, traditional solitary InSAR techniques are limited in their application scenarios and computational characteristics. Additionally, the manual selection of ground control points (GCPs) is fraught with errors and uncertainties. Permanent scatterers (PS) can maintain high interferometric coherence in man-made building areas, and distributed scatterers (DS) usually show moderate coherence in areas with short vegetation; the combination of DS and PS solves the problem of manually selecting GCPs during track re-flattening and regrading, which affects the monitoring results. In this paper, 45 Sentinel-1B data from 16 February 2019 to 14 December 2021 are used as the data source in the urban area of Horqin District, Tongliao City, Inner Mongolia Autonomous Region, for example. A four-threshold (coherence coefficient threshold, FaSHPS adaptive threshold, amplitude divergence index threshold, and deformation velocity interval) GCPs point screening method for PS-DS, as well as a Small Baseline Subset-Permanent Scatterers-Distributed Scatterers-Interferometric Synthetic Aperture Radar (SBAS-PS-DS-InSAR) method for selecting PS and DS points as ground control points for orbit refinement and re-flattening, are proposed. The surface deformation results obtained using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) and the SBAS-PS-DS-InSAR proposed in this paper were comparatively analysed and verified. The maximum cumulative line-of-sight settlements were −90.78 mm and −83.68 mm, and the maximum cumulative uplifts are 74.94 mm and 97.56 mm, respectively; the maximum annual average line-of-sight settlements are −35.38 mm/y and −30.38 mm/y, and the maximum annual average uplifts are 25.27 mm/y and 27.92 mm/y. The results were evaluated and analysed in terms of correlation, mean absolute error (MAE), and root mean square error (RMSE). The deformation results of the two InSAR methods were evaluated and analysed in terms of correlation, MAE, and RMSE. The errors show that the Pearson correlation coefficients between the vertical settlement results obtained using the SBAS-PS-DS-InSAR method and the GPS monitoring results were closer to 1. The maximum MAE and RMSE were 13.7625 mm and 14.8004 mm, respectively, which are within the acceptable range; this confirms that the monitoring results of the SBAS-PS-DS-InSAR method were better than those of the original SBAS-InSAR method. SBAS-InSAR method, which is valid and reliable. The results show that the surface deformation results obtained using the SBAS-InSAR, SBAS-PS-DS-InSAR, and GPS methods have basically the same settlement locations, extents, distributions, and temporal and spatial settlement patterns. The deformation results obtained using these two InSAR methods correlate well with the GPS monitoring results, and the MAE and RMSE are within acceptable limits. By comparing the deformation information obtained using multiple methods, the surface deformation in urban areas can be better monitored and analysed, and it can also provide scientific references for urban municipal planning and disaster warning. Full article
(This article belongs to the Section Remote Sensors)
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18 pages, 12123 KiB  
Article
Optimal Earthquake Intensity Measures for Probabilistic Seismic Demand Models of Base-Isolated Nuclear Power Plant Structures
by Duy-Duan Nguyen, Tae-Hyung Lee and Van-Tien Phan
Energies 2021, 14(16), 5163; https://doi.org/10.3390/en14165163 - 20 Aug 2021
Cited by 15 | Viewed by 3074
Abstract
The purpose of this study is to evaluate the optimal earthquake intensity measures (IMs) for probabilistic seismic demand models (PSDMs) of the base-isolated nuclear power plant (NPP) structures. The numerical model of NPP structures is developed using a lumped-mass stick model, in which [...] Read more.
The purpose of this study is to evaluate the optimal earthquake intensity measures (IMs) for probabilistic seismic demand models (PSDMs) of the base-isolated nuclear power plant (NPP) structures. The numerical model of NPP structures is developed using a lumped-mass stick model, in which a bilinear model is employed to simulate the force-displacement relations of base isolators. In this study, 20 different IMs are considered and 90 ground motion records are used to perform time-history analyses. The seismic engineering demand parameters (EDPs) are monitored in terms of maximum floor displacement (MFD), the maximum floor acceleration (MFA) of the structures, and maximum isolator displacement (MID). As a result, a set of PSDMs of the base-isolated structure is developed based on three EDPs (i.e., MFD, MFA, and MID) associated with 20 IMs. Four statistical parameters including the coefficient of determination, efficiency (i.e., standard deviation), practicality, and proficiency are then calculated to evaluate optimal IMs for seismic performances of the isolated NPP structures. The results reveal that the optimal IMs for PSDMs with respect to MFD and MID are velocity spectrum intensity, Housner intensity, peak ground velocity, and spectral velocity at the fundamental period. Meanwhile, peak ground acceleration, acceleration spectrum intensity, A95, effective peak acceleration, and sustained maximum acceleration are efficient IMs for PSDMs with respect to MFA of the base-isolated structures. On the other hand, cumulative absolute velocity is not recommended for determining the exceedance of the operating basis earthquake of base-isolated NPP structures. Full article
(This article belongs to the Special Issue Seismic Isolation of Nuclear Power Plants)
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15 pages, 2598 KiB  
Article
Research on Improved Seismic Instrumentation System for Nuclear Power Plants
by Liang Li, Xiuli Du, Rong Pan, Xiuyun Zhu and Haiyan Luan
Energies 2021, 14(14), 4262; https://doi.org/10.3390/en14144262 - 14 Jul 2021
Cited by 1 | Viewed by 2162
Abstract
According to the requirements of nuclear safety regulations, nuclear power plants must be equipped with seismic instrumentation systems, which are mainly used for monitoring alarm and automatic shutdown alarm during an earthquake. Both the second and third generation NPPs adopt Peak Ground Acceleration [...] Read more.
According to the requirements of nuclear safety regulations, nuclear power plants must be equipped with seismic instrumentation systems, which are mainly used for monitoring alarm and automatic shutdown alarm during an earthquake. Both the second and third generation NPPs adopt Peak Ground Acceleration (PGA). However, among the seismic acceleration characteristics, isolated and prominent single high frequency acceleration peaks have no decisive influence on the seismic response. Especially when the earthquake monitoring alarm is at 1 out of 7, it is likely to cause a false alarm or false shutdown. In addition, it usually takes one month or more for the NPPs to restart after the shutdown. In this paper, an improved seismic instrumentation system based on the existing system is proposed. For high intensity areas, three components resultant acceleration is used to judge the 2 out of 4 logic of the automatic seismic trip system(ASTS). For low intensity areas, the seismic failure level is evaluated quickly by using three components resultant acceleration, seismic instrument intensity, cumulative absolute velocity, floor response spectrum and other multi-parameters, avoiding unnecessary and long-term shutdown inspection. Full article
(This article belongs to the Special Issue Design and Safety Issues of Nuclear Plants and Installations)
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18 pages, 2139 KiB  
Article
Structural Health Monitoring Using Machine Learning and Cumulative Absolute Velocity Features
by Sifat Muin and Khalid M. Mosalam
Appl. Sci. 2021, 11(12), 5727; https://doi.org/10.3390/app11125727 - 21 Jun 2021
Cited by 22 | Viewed by 7896
Abstract
Machine learning (ML)-aided structural health monitoring (SHM) can rapidly evaluate the safety and integrity of the aging infrastructure following an earthquake. The conventional damage features used in ML-based SHM methodologies face the curse of dimensionality. This paper introduces low dimensional, namely, cumulative [...] Read more.
Machine learning (ML)-aided structural health monitoring (SHM) can rapidly evaluate the safety and integrity of the aging infrastructure following an earthquake. The conventional damage features used in ML-based SHM methodologies face the curse of dimensionality. This paper introduces low dimensional, namely, cumulative absolute velocity (CAV)-based features, to enable the use of ML for rapid damage assessment. A computer experiment is performed to identify the appropriate features and the ML algorithm using data from a simulated single-degree-of-freedom system. A comparative analysis of five ML models (logistic regression (LR), ordinal logistic regression (OLR), artificial neural networks with 10 and 100 neurons (ANN10 and ANN100), and support vector machines (SVM)) is performed. Two test sets were used where Set-1 originated from the same distribution as the training set and Set-2 came from a different distribution. The results showed that the combination of the CAV and the relative CAV with respect to the linear response, i.e., RCAV, performed the best among the different feature combinations. Among the ML models, OLR showed good generalization capabilities when compared to SVM and ANN models. Subsequently, OLR is successfully applied to assess the damage of two numerical multi-degree of freedom (MDOF) models and an instrumented building with CAV and RCAV as features. For the MDOF models, the damage state was identified with accuracy ranging from 84% to 97% and the damage location was identified with accuracy ranging from 93% to 97.5%. The features and the OLR models successfully captured the damage information for the instrumented structure as well. The proposed methodology is capable of ensuring rapid decision-making and improving community resiliency. Full article
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17 pages, 2056 KiB  
Article
Dispersion of Graphite Nanoplates in Polypropylene by Melt Mixing: The Effects of Hydrodynamic Stresses and Residence Time
by Luís Lima Ferrás, Célio Fernandes, Denis Semyonov, João Miguel Nóbrega and José António Covas
Polymers 2021, 13(1), 102; https://doi.org/10.3390/polym13010102 - 29 Dec 2020
Cited by 5 | Viewed by 3047
Abstract
This work combines experimental and numerical (computational fluid dynamics) data to better understand the kinetics of the dispersion of graphite nanoplates in a polypropylene melt, using a mixing device that consists of a series of stacked rings with an equal outer diameter and [...] Read more.
This work combines experimental and numerical (computational fluid dynamics) data to better understand the kinetics of the dispersion of graphite nanoplates in a polypropylene melt, using a mixing device that consists of a series of stacked rings with an equal outer diameter and alternating larger and smaller inner diameters, thereby creating a series of converging/diverging flows. Numerical simulation of the flow assuming both inelastic and viscoelastic responses predicted the velocity, streamlines, flow type and shear and normal stress fields for the mixer. Experimental and computed data were combined to determine the trade-off between the local degree of dispersion of the PP/GnP nanocomposite, measured as area ratio, and the absolute average value of the hydrodynamic stresses multiplied by the local cumulative residence time. A strong quasi-linear relationship between the evolution of dispersion measured experimentally and the computational data was obtained. Theory was used to interpret experimental data, and the results obtained confirmed the hypotheses previously put forward by various authors that the dispersion of solid agglomerates requires not only sufficiently high hydrodynamic stresses, but also that these act during sufficient time. Based on these considerations, it was estimated that the cohesive strength of the GnP agglomerates is in the range of 5–50 kPa. Full article
(This article belongs to the Special Issue Polymer Nanocomposites II)
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17 pages, 4282 KiB  
Article
An Improvement on Estimated Drifter Tracking through Machine Learning and Evolutionary Search
by Yong-Wook Nam, Hwi-Yeon Cho, Do-Youn Kim, Seung-Hyun Moon and Yong-Hyuk Kim
Appl. Sci. 2020, 10(22), 8123; https://doi.org/10.3390/app10228123 - 16 Nov 2020
Cited by 9 | Viewed by 2969
Abstract
In this study, we estimated drifter tracking over seawater using machine learning and evolutionary search techniques. The parameters used for the prediction are the hourly position of the drifter, the wind velocity, and the flow velocity of each drifter position. Our prediction model [...] Read more.
In this study, we estimated drifter tracking over seawater using machine learning and evolutionary search techniques. The parameters used for the prediction are the hourly position of the drifter, the wind velocity, and the flow velocity of each drifter position. Our prediction model was constructed through cross-validation. Trajectories were affected by wind velocity and flow velocity from the starting points of drifters. Mean absolute error (MAE) and normalized cumulative Lagrangian separation (NCLS) were used to evaluate various prediction models. Radial basis function network showed the lowest MAE of 0.0556, an improvement of 35.20% over the numerical model MOHID. Long short-term memory showed the highest NCLS of 0.8762, an improvement of 6.24% over MOHID. Full article
(This article belongs to the Special Issue Applied Machine Learning)
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16 pages, 17937 KiB  
Article
Quantification of Energy-Related Parameters for Near-Fault Pulse-Like Seismic Ground Motions
by Omar AlShawa, Giulia Angelucci, Fabrizio Mollaioli and Giuseppe Quaranta
Appl. Sci. 2020, 10(21), 7578; https://doi.org/10.3390/app10217578 - 27 Oct 2020
Cited by 8 | Viewed by 2539
Abstract
An energy-based approach facilitates the explicit consideration of the damage associated with both maximum displacements and cumulative plastic deformations under earthquakes. For structural systems that can undergo pulse-like seismic ground motions close to causative faults, an energy-based approach is deemed especially appropriate with [...] Read more.
An energy-based approach facilitates the explicit consideration of the damage associated with both maximum displacements and cumulative plastic deformations under earthquakes. For structural systems that can undergo pulse-like seismic ground motions close to causative faults, an energy-based approach is deemed especially appropriate with respect to well-established force- or displacement-based strategies. In such a case, in fact, most of the damage is attributable to the dominant pulse-like component, which usually occurs into the velocity time history of the seismic ground motion, thus implying high energy levels imparted to a structural system. In order to enable the implementation of an energy-based approach in the analysis and design of structures under near-fault pulse-like seismic ground motions, this study presents a comprehensive numerical investigation about the influence of seismological parameters and hysteretic behavior on the spectra of the following energy-related parameters: inelastic absolute and relative input energy; input energy reduction factor; hysteretic energy dissipation demand; hysteretic energy reduction factor; dimensionless cumulative plastic deformation ratio. Closed-form approximations are proposed for these spectra, and the numerical values of the corresponding parameters have been also calibrated (with reference to both mean and standard deviation values) as functions of earthquake magnitude, type of hysteretic behavior (i.e., non-degrading or degrading) and ductility level. The outcomes of this study are meant to support the derivation of design spectra for the energy-based seismic design of structures under near-fault pulse-like seismic ground motions. Full article
(This article belongs to the Special Issue Effects of Near-Fault Ground Motions on Civil Infrastructure)
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21 pages, 10719 KiB  
Article
Factors That Affect Liquefaction-Induced Lateral Spreading in Large Subduction Earthquakes
by William Araujo and Christian Ledezma
Appl. Sci. 2020, 10(18), 6503; https://doi.org/10.3390/app10186503 - 18 Sep 2020
Cited by 11 | Viewed by 9396
Abstract
Liquefaction-induced lateral spreading can induce significant deformations and damage in existing structures, such as ports, bridges, and pipes. Past earthquakes have caused this phenomenon in coastal areas and rivers in many parts of the world. Current lateral spreading prediction models tend to either [...] Read more.
Liquefaction-induced lateral spreading can induce significant deformations and damage in existing structures, such as ports, bridges, and pipes. Past earthquakes have caused this phenomenon in coastal areas and rivers in many parts of the world. Current lateral spreading prediction models tend to either overestimate or underestimate the actual displacements by a factor of two or more when applied to large subduction earthquake events. The purpose of this study was to identify ground motion intensity measures and soil parameters that better correlate with observed lateral spreading under large-magnitude (Mw ≥ 7.5) subduction earthquakes that have occurred in countries like Chile, Japan, and Peru. A numerical approach was first validated against centrifuge and historical cases and then used to generate parametric models on which statistical analysis was applied. Our results show that cumulative absolute velocity (CAV), Housner intensity (HI), and sustained maximum velocity (SMV) have a reasonably good correlation with lateral spreading for the analyzed cases. Full article
(This article belongs to the Special Issue Advances in Geotechnical Engineering)
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17 pages, 7162 KiB  
Article
Angle Tracking Observer with Improved Accuracy for Resolver-to-Digital Conversion
by Haoye Qin and Zhong Wu
Symmetry 2019, 11(11), 1347; https://doi.org/10.3390/sym11111347 - 1 Nov 2019
Cited by 6 | Viewed by 7980
Abstract
A resolver is an absolute shaft sensor which outputs pair signals with ortho-symmetric amplitudes. Ideally, they are sinusoidal and cosinusoidal functions of the shaft angle. In order to demodulate angular position and velocity from resolver signals, resolver-to-digital conversion (RDC) is necessary. In software-based [...] Read more.
A resolver is an absolute shaft sensor which outputs pair signals with ortho-symmetric amplitudes. Ideally, they are sinusoidal and cosinusoidal functions of the shaft angle. In order to demodulate angular position and velocity from resolver signals, resolver-to-digital conversion (RDC) is necessary. In software-based RDC, most algorithms mainly employ a phase-locked loop (PLL)-based angle tracking observer (ATO) to form a type-II system. PLL can track the detected angle by regulating the phase error from the phase detector which depends on the feature of orthogonal symmetry in the resolver outputs. However, a type-II system will result in either steady-state errors or cumulative errors in the estimation of angular position with constant accelerations. Although type-III ATOs can suppress these errors, they are still vulnerable to high-order acceleration signals. In this paper, an improved PLL-based ATO with a compensation model is proposed. By using dynamic compensation, the proposed ATO becomes a type-IV system and can reduce position estimation errors for high-order acceleration signals. In addition, the parameters of ATO can be tuned according to the bandwidth, noise level and capability of error suppression. Simulation and experimental results demonstrate the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Symmetry in Engineering Sciences II)
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18 pages, 3884 KiB  
Article
New Equations to Evaluate Lateral Displacement Caused by Liquefaction Using the Response Surface Method
by Nima Pirhadi, Xiaowei Tang and Qing Yang
J. Mar. Sci. Eng. 2019, 7(2), 35; https://doi.org/10.3390/jmse7020035 - 4 Feb 2019
Cited by 6 | Viewed by 3921
Abstract
Few empirical and semi-empirical approaches have considered the influence of the geology, tectonic source, causative fault type, and frequency content of earthquake motion on lateral displacement caused by liquefaction (DH). This paper aims to address this gap in the literature [...] Read more.
Few empirical and semi-empirical approaches have considered the influence of the geology, tectonic source, causative fault type, and frequency content of earthquake motion on lateral displacement caused by liquefaction (DH). This paper aims to address this gap in the literature by adding an earthquake parameter of the standardized cumulative absolute velocity (CAV5) to the original dataset for analyzing. Furthermore, the complex influence of fine content in the liquefiable layer (F15) is analyzed by deriving two different equations: the first one is for the whole range of parameters, and the second one is for a limited range of F15 values under 28% in order to the F15’s critical value presented in literature. The new response surface method (RSM) approach is applied on the basis of the artificial neural network (ANN) model to develop two new equations. Moreover, to illustrate the capability and efficiency of the developed models, the results of the RSM models are examined by comparing them with an additional three available models using data from the Chi-Chi earthquake sites that were not used for developing the models in this study. In conclusion, the RSM provides a capable tool to evaluate the liquefaction phenomenon, and the results fully justify the complex effect of different values of F15. Full article
(This article belongs to the Special Issue Coastal Geohazard and Offshore Geotechnics)
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24 pages, 7478 KiB  
Article
A New Equation to Evaluate Liquefaction Triggering Using the Response Surface Method and Parametric Sensitivity Analysis
by Nima Pirhadi, Xiaowei Tang, Qing Yang and Fei Kang
Sustainability 2019, 11(1), 112; https://doi.org/10.3390/su11010112 - 26 Dec 2018
Cited by 24 | Viewed by 5361
Abstract
Liquefaction is one of the most damaging functions of earthquakes in saturated sandy soil. Therefore, clearly advancing the assessment of this phenomenon is one of the key points for the geotechnical profession for sustainable development. This study presents a new equation to evaluate [...] Read more.
Liquefaction is one of the most damaging functions of earthquakes in saturated sandy soil. Therefore, clearly advancing the assessment of this phenomenon is one of the key points for the geotechnical profession for sustainable development. This study presents a new equation to evaluate the potential of liquefaction (PL) in sandy soil. It accounts for two new earthquake parameters: standardized cumulative absolute velocity and closest distance from the site to the rupture surface (CAV5 and rrup) to the database. In the first step, an artificial neural network (ANN) model is developed. Additionally, a new response surface method (RSM) tool that shows the correlation between the input parameters and the target is applied to derive an equation. Then, the RSM equation and ANN model results are compared with those of the other available models to show their validity and capability. Finally, according the uncertainty in the considered parameters, sensitivity analysis is performed through Monte Carlo simulation (MCS) to show the effect of the parameters and their uncertainties on PL. The main advantage of this research is its consideration of the direct influence of the most important parameters, particularly earthquake characteristics, on liquefaction, thus making it possible to conduct parametric sensitivity analysis and show the direct impact of the parameters and their uncertainties on the PL. The results indicate that among the earthquake parameters, CAV5 has the highest effect on PL. Also, the RSM and ANN models predict PL with considerable accuracy. Full article
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22 pages, 13591 KiB  
Article
Shaking Maps Based on Cumulative Absolute Velocity and Arias Intensity: The Cases of the Two Strongest Earthquakes of the 2016–2017 Central Italy Seismic Sequence
by Antonio Costanzo
ISPRS Int. J. Geo-Inf. 2018, 7(7), 244; https://doi.org/10.3390/ijgi7070244 - 22 Jun 2018
Cited by 10 | Viewed by 4910
Abstract
By referring to the two strongest earthquakes of the 2016–2017 Central Italy seismic sequence, this paper presents a procedure to make shaking maps through empirical relationships between macroseismic intensity and ground-motion parameters. Hundreds of waveforms were processed to obtain instrumental ground-motion features which [...] Read more.
By referring to the two strongest earthquakes of the 2016–2017 Central Italy seismic sequence, this paper presents a procedure to make shaking maps through empirical relationships between macroseismic intensity and ground-motion parameters. Hundreds of waveforms were processed to obtain instrumental ground-motion features which could be correlated with the potential damage intensities. To take into account peak value, frequency, duration, and energy content, which all contribute to damage, cumulative absolute velocity and Arias intensity were used to quantify the features of the ground motion. Once these parameters had been calculated at the recording sites, they were interpolated through geostatistical techniques on the whole struck area. Finally, empirical relationships were used for mapping intensities, i.e., potential effects on the built environment. The results referred to both earthquake scenarios that were analyzed and were also used for assessing the influence of the spatial coverage of the instrumental network. In fact, after the first events, the Italian seismic network was subjected to the addition and thickening of sensors in the epicentral area, especially. The results obtained by models only dependent on ground-motion parameters or even on the epicentral distance were compared with the official ShakeMaps and the observed intensities for assessing their reliability. Finally, some suggestions are proposed to improve the procedure that could be used for rapidly assessing ground shaking and mapping damage potential producing useful information for non-expert audience. Full article
(This article belongs to the Special Issue Natural Hazards and Geospatial Information)
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