Damage Assessment Method Research Articles

Post-disaster building damage assessment based on improved U-Net

When a severe natural disaster occurs, the extraction of post-disaster building damage information is one of the methods to quickly obtain disaster information. The increasingly mature high-resolution remote sensing technology provides a solid foundation for obtaining information about building damage. To address the issues with inaccurate building positioning in existing building damage assessment methods, as well as poor classification due to similar minor and major damage characteristics in building damage classification. Based on U-Net, we designed a two-stage building damage assessment network. The first stage is an independent U-Net focused on building segmentation, followed by a Siamese U-Net focused on building damage classification. The Extra Skip Connection and Asymmetric Convolution Block were used for enhancing the network's ability to segment buildings on different scales; Shuffle Attention directed the network's attention to the correlation of buildings before and after the disaster. The xBD dataset was used for training and testing in the study, and the overall performance was evaluated using a balanced F-score (F1). The improved network had an F1 of 0.8741 for localization and F1 of 0.7536 for classification. When compared to other methods, it achieved better overall performance for building damage assessment and was able to generalize to multiple disasters.

Response spectrum method for fatigue damage assessment of mechanical systems

In this paper, a new response spectrum method is proposed for high-cycle fatigue damage assessment of a linear multi-degree-of-freedom system subjected to random base acceleration. Mode damage response can be accessed by separating the modal participation factor and stress mode from the contribution of a mode to the total damage, assessed by the Single Moment method. The fatigue damage response spectrum is defined as the family of curves formed by the mode damage response with the variation of the frequency and modal damping ratio, which is irrelevant to the spatial characteristics of the load and structure. Three calculation formats of the response spectrum method are formed by considering different cross-correlation hypotheses of each mode (i.e. the Complete Quadratic Combination format, the Square Root of the Sum of Squares format, and the Modified Square Root of the Sum of Squares format). The proposed method has higher computational efficiency than other frequency-domain methods because of avoiding the calculation of power spectral density function and spectral moment of stress responses. The spatial and frequency information of the structure are decoupled from each other in the implementation, which can effectively reduce the computational cost of reanalysis. Compared to the result of the Dirlik method (self-compiled program and MSC.Patran/Nastran) and the Single Moment method, the correctness and efficiency of the proposed method are verified, and the influences of the material and load spectrum form on the response spectrum method are investigated.

Damage Assessment Method of Reinforcement Concrete Building By Fuzzy Theory

As reinforcement concrete building is composition material which reinforcement bar and concrete work together, effect factors concerned with its damage are countlessly much and interrelationship between them is also very complex and indefiniteness. Until now many researches about the damage assessment of a building has been performed but the problem accounting correctly damage of the reinforcement concrete building by connecting several of damage factors has not yet been solved. In research a method accounting damage of reinforcement concrete building in the fuzzy integral way in consideration of fuzzy property existing in the damage assessment system of it has been newly suggested.

Coda Wave Interferometry for Monitoring Bridges with Embedded Ultrasonic Transducers – Lessons Learned at the Gänstorbrücke Bridge Ulm, Germany

Ultrasonic Coda Wave interferometry has the potential to detect minute changes in scattering materials like concrete. By permanently installing ultrasonic transducers in concrete, DFG Research unit CoDA aims to develop methods for concrete damage assessment in Germany's ageing infrastructure. To test the methods developed in simulations and laboratory experiments on a large scale, we have implemented several ultrasonic transducers, both embedded and externally attached at the Gänstorbrücke Ulm, one of Germany's most monitored road bridges. Since fall 2020 we are monitoring parts of the centre of the Bridge, as well as an abutment, and compare the results to the commercial monitoring system. All data is recorded with a self-made data collection device, the so-called W-Box, and analyzed with different coda wave-based algorithms to detect signal and volumetric velocity changes for several transducer combinations. The long-term measurements show that the influence of temperature changes on strains and therefore ultrasound velocity changes calculated with coda waves can be monitored. Maps of velocity change show that parts of the bridge react differently to environmental heating or cooling which indicates material property differences comparing those areas. The capabilities and limitations of the coda wave-based monitoring system are tested in a controlled experiment. Static loading using a truck with varying load at several positions allows the calibration of the system to improve the detectability of possibly damaging loads and changes induced by this loading versus the influence of the environment.

Landslide Assessment Using Sentinel-I SAR-C Interferometry Technique

Landslides might remain unknown or unnoticed for a long time in various remote areas due to the unavailability of optical images caused by cloud persistence, which creates difficulties for civil protection rescue operations, and disaster management as well. Rapid crisis response for humanitarian and reconstruction operations in the affected area after such dangerous landslides is necessary. Thus, a rapid detection map is necessary to detect the affected area with damage grade and level for further investigation and human safety protocols. To detect landslide incidents, the unprecedented availability of Sentinel-1 SAR-C band images provides new solutions and better safety reports. In this study, we performed an efficient evaluation of Sentinel-1 SAR C band images before and after landslide incidents. This study provides a comprehensive evaluation based on the advanced space-borne remote sensing technology aiming at SAR products for rapid damage detection and analysis with respect to the interferometric coherence and intensity correlation. We presented the results of a pilot study on the Rudraprayag Uttarakhand massive landslide incident, which includes the different types, sizes, slope expositions, and human safety aspects. Our study and outcomes represent an updated method, which provides a solution for critical terrain rescue operations and an upgraded geomatics map that provides subsidence data with historical data with topographical statistics. Finally, an outlook into the Sentinel-1 SAR-C analysis demonstrates probable solutions to certain constraints, enabling global applicability of the proposed damage assessment methods with the improved accuracy from 50 to 60 % for the obtained temporal resolution datasets.

A cost-benefit analysis of sensor quality and spatial density for rapid regional post-event seismic damage assessment: Application to Istanbul

A quantitative evaluation of the influence of sensor quality and spatial density on the results of rapid regional seismic damage evaluations of buildings can provide an important reference for the deployment of a strong-motion network. However, the influence of sensor quality and spatial density on seismic damage assessment is still unclear. Therefore, a cost-benefit analysis framework of sensor quality and spatial density for rapid regional post-event seismic damage assessment is proposed. In this framework, a simulation method for sensor-recorded ground motions and an interpolation-based ground motion field refinement method are used to consider the influence of the quality and density of the sensor network. The accuracies of seismic damage assessments with different sensor layout schemes were compared using the time-history analysis-based regional seismic damage assessment method, through which the influence of sensor quality and spatial density on the seismic damage assessment can be quantitatively evaluated. Finally, the Zeytinburnu district of Istanbul was selected as an example for illustrating the proposed framework. The main conclusions are as follows: (1) the spatial density of the sensors used is more significant for improving the accuracy of a seismic damage assessment than the quality of the sensors used; (2) the influence of population density can be considered using the proposed framework; and (3) the proposed framework can quantitatively consider the influence of sensor quality and spatial density on the rapid regional seismic damage assessment of buildings, which provides an important reference for the deployment of a strong-motion network for a given budget.

Fast damage assessment of seismic-damaged structures based on response deduction and energy dissipation ratio

Considering the difference of cumulative deformation energy between the elastic-plastic state and the ideal elastic state, a structural damage assessment method based on the generalized elastic–plastic energy dissipation ratio (GEPEDR) is proposed. To solve the problem that the actual structure dynamic response in the ideal elastic state is difficult to predict, a method to deduce the dynamic response in the ideal elastic state according to Kalman filter is proposed. Based on the above research, the overall damage and interlayer damage assessment methods of seismic-damaged structures are presented. The nonlinear finite element analysis of reinforced concrete (RC) frame structures and the shaking table test of the 12-story RC frame structure are taken as examples for verification. The results show that the GEPEDR method can realize damage assessment based on only seismic signals and structural responses and reveal the dynamic evolution process of structural overall damage and the distribution of weak story.

Optimal Domain Scale for Stochastic Urban Flood Damage Assessment Considering Triple Spatial Uncertainties

AbstractAs a key factor in the flood damage assessment process, the damage ratio is defined as the ratio of the potential damage value to the total risk assets at a certain inundation depth. Spatial variability of flood‐bearing elements caused spatial heterogeneity, local correlation and neighborhood non‐stationarity to the damage ratio. Thus, it is challenging to scientifically and rationally measure the damage ratio. In this study, a modeling framework of stochastic flood damage assessment functions was established to measure triple uncertainties. First, based on the maximum likelihood estimation method, migration data of the flood damage ratio were constructed as the beta distribution by heterogeneous multi‐attribute analogy. Then, the Markov chain Monte Carlo method, combined with a variant sliding window method, is used for sampling to generate spatially distributed samples. In addition, three risk factors were integrated grid by grid to assess flood damage. By taking the Jinshui District of Zhengzhou City in China as an example, economic losses during the 1%, 2%, 5% and 10% annual exceedance probability (AEP) floods were assessed, respectively. The results show that the economic losses showed a significant increasing trend with AEP. The optimal domain scales for industrial, commercial, residential and public service land uses were 19, 14, 25 and 32 m, respectively, and also varied with different AEP floods. The model was effectively verified by simulating and comparing historical data of the “7·20” flood event in Zhengzhou, China. This study aims to provide feasible ideas for uncertainty research of damage assessment methods.

Stochastic harmonic function-based traffic load simulation method for fatigue damage assessment of concrete bridges

A novel simulation method of the compound Poisson process based on the stochastic harmonic function (SHF) is proposed to represent the stochastic traffic load process, so that the fatigue damage of concrete bridges under traffic loading can be efficiently and accurately evaluated. To start with, the fundamental theory of simulation of the compound Poisson process via SHF is elucidated in detail with the application of the inverse transformation principle. Afterwards, the stochastic traffic load modelled by the compound Poisson process is reproduced by utilizing the SHF-based simulation method. Simultaneously, the Monte Carlo simulation (MCS) method is applied to simulate the traffic load, aiming to verify the superiority of the SHF-based method. By introducing a micro–meso stochastic fatigue damage constitutive model of concrete, integrated with the SHF-based simulation method of traffic load, the theoretical framework of estimating fatigue damage of concrete bridges under stochastic traffic loading is established. Finally, the fatigue damage assessment of a concrete bridge in practical engineering is implemented to validate the feasibility and advantage of the proposed SHF-based traffic load simulation method.

A comparative review of time- and frequency-domain methods for fatigue damage assessment

In this paper, a comparative review between time- and frequency-domain methods for fatigue damage assessment is performed. The principal steps of a fatigue study are described in detail: Material Characterization, Definition of the Reference Parameter, Treatment of Loading History, Cycle Counting Algorithm and Damage Model. Furthermore, for each of them the main differences found between the advances made in the time- and frequency-domains are highlighted. As a conclusion, this comparative literature review allows us to identify some important lights and shadows in both approaches: several efforts have been made in the development of advanced material characterization models in S-N field in the time-domain methods, either deterministic or probabilistic, but in the frequency-domain methods only the linear Basquin model is currently used. Also the ongoing discussion about the reference parameter in material characterization (stress, strain, energy, etc.) is not present in the frequency-domain methods, which are mainly based on the stress range. Contrarily, the frequency-domain methods show an advanced treatment of the rainflow histogram with different proposed statistical distributions together with theoretical and analytical relationships between the power spectral density and the expected fatigue damage, leading to a simpler and easier methodology to be applied for fatigue damage assessment than those based on time-domain.

High velocity impact on generic CFRP blade specimen: baseline free method for impact localisation and damage assessment on complex structures

Nowadays components made of unidirectional composite materials are largely diffused in many engineering fields, such as automotive, railways, marine and aerospace. Main drawback of this class of materials lies in their low out-of-plane properties making them very sensible to impulsive loads such as impact events. After a collision with an external object, composites structures could be affected by damage, sometimes not visible from visual inspections (barely visible damage) hence with detrimental consequences on structure resistance and strength. Therefore, it is fundamental in terms of safety to continuously assess the healthy state of structures during their life and determine whether an impact event has occurred and if it caused damage or not. This work proposes a baseline free methodology to determine the coordinates of very high velocity impact on complex structures and evaluate if damage has occurred during the impact by only acquiring signal during the impact event. The technique overcomes the common limitations of previous technique presented in literature, i.e. a priori knowledge of mechanical properties, vibration response analysis, wave propagation direction dependency, sensor locations. The routine developed is based first on the estimation of the power of the acoustic emission generated by impact events, at sensors location, then the power information through the entire structure is reconstructed exploiting radial basis function network. The actual impact estimation is finally obtained using a weighted method. Furthermore, damage assessment is conducted with a novel method based on Hilbert–Huang transform and mode decomposition. Experimental tests were performed on a generic carbon fibre reinforced polymers blade specimen with a complex stacking sequence and embedded sensors. Two test configurations at different velocities were considered: one at 90 m s−1 and one at 190 m s−1. Before and afterwards the actual impact tests, the blade was excited as well with a modal hammer (pre and post impact). The results from the impact analysis highlighted the validity and reliability of the proposed method, with a high level of accuracy in terms of impact localisation estimation, and qualitative integrity state was effectively evaluated.

Study of water-conducting fractured zone development law and assessment method in longwall mining of shallow coal seam

Starting from the source of mining, scientific understanding of surface damage law and assessment method in longwall mining of shallow coal seam is conducive to solving the problems of geological hazards and deterioration of the ecological environment, and promoting the coordinated development of efficient coal mining and environmental protection. Based on numerical simulation and theoretical analysis, the surface damage process and spatiotemporal evolution of fracture field are discussed. The influencing factors and assessment method of surface damage are clarified. The results show that surface damage undergone the immediate roof caving stage, the fracture and instability stage of main roof, the spatial amplification stage of separation layer, the instability stage of surface damage control layer and the mining damage stability stage. Under the critical extraction condition, the cracks above the goaf are divided into the crack area outside the cut, the crack area inside the cut, the re-compaction area in the middle goaf, the crack area behind the longwall face, and the crack area in front of the longwall face. The overburden reaches critical failure ahead of surface critical mining. The sensitivity of loose layer thickness to surface subsidence coefficient is greater than that of mining thickness to surface subsidence coefficient. Surface damage control should be adjusted to local conditions, and finally realize zoning treatment and zoning repair. Through the three-step method of "longwall face rapid advancing method, local grouting reinforcement overburden method and zoning treatment ground fissures method", the surface damage control of 12,401 longwall face is realized. This research provides theoretical guidance and application value for surface ecological restoration in similar mining area.

ASSESSMENT OF BUILDINGS AND ELECTRICAL FACILITIES DAMAGED BY FLOOD AND EARTHQUAKE FROM SATELLITE IMAGERY

Abstract. Natural disasters cause considerable losses to people’s lives and property. Satellite images can provide crucial information of the affected areas for the first time, conducive to relieving the people in disaster and reducing the economic loss. However, the traditional satellite image analysis method based on manual processing drains workforce and material resources, which slowed the government’s response to the disaster. Aiming at the natural disasters like floods and earthquakes that often happen in the south of China, we propose a dual-stage damage assessment method based on LEDNet and ResNet. Our method detects the changes between the satellite images captured before and after a disaster of the same area, segments the buildings, and evaluates the damage level of affected buildings. In addition, we calculate influence maps based on the damage scale to the building and estimate the damage situation for electrical facilities. We used images related to earthquakes and floods in the xBD dataset to train the network model. Moreover, qualitative and quantitative evaluations demonstrated that our method has higher accuracy than the xBD baseline.

Advanced Damage Assessment Method for Bacterial Leaf Blight Disease in Rice by Integrating Remote Sensing Data for Agricultural Insurance

This study aimed to develop a new method for assessing damage to rice plants by pests and diseases using remote sensing data to enable greater efficiency and accuracy for payment of indemnity in the agricultural insurance system of Indonesia, formally operationalized in 2016. The relationships between bacterial leaf blight (BLB) damage ratio in rice crops evaluated by pest observers using the current visual inspection method and the reflectance of each observation band of RapidEye and Sentinel 2, normalized difference vegetation index (NDVI), green NDVI (GNDVI), and red edge multiplied by the green band index (RGI) were studied. The results showed a positive relationship between BLB damage intensity and reflectance of visible wavelength bands, and a particularly strong positive correlation between the red band and BLB damage intensity. The BLB damage intensity can be evaluated based on pixels and paddy parcels. Time series analysis was conducted using Sentinel-2 data acquired during different plant growth periods such as heading, flowering, ripening, maturity, and harvesting. The results showed a strong correlation between the BLB damage intensity and reflectance of the red edge band at the rice heading and flowering stages; the correlation of BLB damage intensity with the reflectance of the visible range became stronger as the rice plant approached the harvesting stage. This study clearly demonstrated that BLB symptoms can be successfully detected and evaluated approximately one or one and a half months before the harvesting period using remote sensing data. We propose that the BLB damage intensity, currently assessed by pest observers through visual inspection methods, can be calculated from satellite data, suggesting that the satellite sensor could play a role similar to the human eye.

A Two-Stage Seismic Damage Assessment Method for Small, Dense, and Imbalanced Buildings in Remote Sensing Images

Large-scale optical sensing and precise, rapid assessment of seismic building damage in urban communities are increasingly demanded in disaster prevention and reduction. The common method is to train a convolutional neural network (CNN) in a pixel-level semantic segmentation approach and does not fully consider the characteristics of the assessment objectives. This study developed a machine-learning-derived two-stage method for post-earthquake building location and damage assessment considering the data characteristics of satellite remote sensing (SRS) optical images with dense distribution, small size, and imbalanced numbers. It included a modified You Only Look Once (YOLOv4) object detection module and a support vector machine (SVM) based classification module. In the primary step, the multiscale features were successfully extracted and fused from SRS images of densely distributed buildings by optimizing the YOLOv4 model toward the network structures, training hyperparameters, and anchor boxes. The fusion improved multi-channel features, optimization of network structure and hyperparameters have significantly enhanced the average location accuracy of post-earthquake buildings. Thereafter, three statistics (i.e., the angular second moment, dissimilarity, and inverse difference moment) were further discovered to effectively extract the characteristic value for earthquake damage from located buildings in SRS optical images based on the gray level co-occurrence matrix. They were used as the texture features to distinguish damage intensities of buildings, using the SVM model. The investigated dataset included 386 pre- and post-earthquake SRS optical images of the 2017 Mexico City earthquake, with a resolution of 1024 × 1024 pixels. Results show that the average location accuracy of post-earthquake buildings exceeds 95.7% and that the binary classification accuracy for damage assessment reaches 97.1%. The proposed two-stage method was validated by its extremely high precision in respect of densely distributed small buildings, indicating the promising potential of computer vision in large-scale disaster prevention and reduction using SRS datasets.

Experimental study and numerical simulation of all‐steel buckling‐restrained brace with distributed inspection windows

SummaryThis paper presents a novel all‐steel seismic‐resistant, buckling‐restrained brace (BRB) which can be easily detached from its steel core for post‐seismic inspections. This allows inspectors to quickly determine if the BRB needs to be replaced to reduce the impact of seismic aftershocks. The weld toes of brace stiffeners were specially smoothed to reduce the residual stress and stress concentration, thereby improving the low‐cycle fatigue performance of the brace. Two identical restraining units were connected by high‐strength bolts. A small air gap was provided by annular gaskets between the core and the restraining system to allow for lateral expansion of the core plate under compression. Five specimens were tested under different cyclic loading protocols to investigate the performance. The hysteretic behavior, compression strength adjustment factor, equivalent viscous damping ratio, failure modes, and deformation of the restraining system were analyzed. The multi‐wave buckling deformation of the core was studied in detail to provide a basis for the accurate calculation of the number of contact points. Finite element analyses were performed to compare the response with test results, which proved the structure of the novel BRB to be reasonable except for the compression strength adjustment factor of some specimens, which was greater than 1.3. A damage assessment method was proposed to evaluate the working status of the newly designed BRB after an earthquake.

Damage Assessment of Reinforced Concrete Structures: A Review

Damage may be assessed using several damage indices with values associated with different structural damage states. The usefulness of a variety of current response-based damage indices in seismic damage assessment is addressed and critically assessed. A novel rational damage assessment method is provided, which measures the structure’s physical reaction characteristics. A practical method based on various analyses is given to evaluate the damaged structures in earthquakes of different intensities. This paper provides an overview of previous research works on the damage assessment of the reinforced concrete structures. This study may be helpful for easy understanding about the damage assessment of reinforced concrete structures and reduce the impacts of disaster and surrounding structures.

Damage Assessment of Reinforced Concrete Structures: A Review

Damage may be assessed using several damage indices with values associated with different structural damage states. The usefulness of a variety of current response-based damage indices in seismic damage assessment is addressed and critically assessed. A novel rational damage assessment method is provided, which measures the structure’s physical reaction characteristics. A practical method based on various analyses is given to evaluate the damaged structures in earthquakes of different intensities. This paper provides an overview of previous research works on the damage assessment of the reinforced concrete structures. This study may be helpful for easy understanding about the damage assessment of reinforced concrete structures and reduce the impacts of disaster and surrounding structures.

Accountable outsourcing data storage atop blockchain

Outsourcing data integrity auditing enables users to efficiently check whether their cloud data are stored intactly without retrieving them. However, a problem arises that how to hold the storage server accountable when the auditing results show that the data has been lost or tampered with. In this paper, we propose a blockchain-based accountable data outsourcing storage protocol, which enables users to obtain fine-grained compensation based on the damage of data. We provide an accurate and verifiable damage assessment method to achieve quantitative compensation. Specifically, the damage is assessed by the server and verified by smart contract. Furthermore, our protocol ensures the fairness of participants by deposit mechanism and smart contract. If any participant behaves dishonestly, it cannot obtain any benefit or even be punished. To reduce user’s overhead, we propose a new provable data possession scheme, PDP in short, supporting outsourcing the calculation of tags. Moreover, we provide a detailed security proof for the proposed protocol as well. Finally, we evaluate the time cost of off-chain functions and the gas cost of on-chain operations for our protocol, which demonstrates that it is practical and suitable in reality.

Multicategory damage detection and safety assessment of post‐earthquake reinforced concrete structures using deep learning

AbstractEarthquake damage investigation is critical to post‐earthquake structural recovery and reconstruction. In this study, a method of assessing the component failure mode and damage level was established based on object detection and recognition. A quantitative structural damage level assessment method was developed based on the type and extent of damage to the components. A You Only Look Once v4 (YOLOv4) network was used to detect multicategory damage (fine crack, wide crack, concrete spalling, exposed rebar and buckled rebar). Depthwise separable convolution was introduced into YOLOv4 to decrease the computation cost without reducing accuracy. Finally, the damage detection method and assessment method were integrated within a graphical user interface (GUI) to facilitate the post‐earthquake reinforced concrete (RC) structural damage assessment. The test results by GUI indicate that the improved object network can get accurate detection results, and the preliminary safety assessment method can judge the damage level and failure mode. The present study shows high potential for estimating the seismic damage states of RC structures.