Damage Assessment Method Research Articles

A Hybrid Deep Learning Model for Enhanced Structural Damage Detection: Integrating ResNet50, GoogLeNet, and Attention Mechanisms

Quick and accurate structural damage detection is essential for maintaining the safety and integrity of infrastructure, especially following natural disasters. Traditional methods of damage assessment, which rely on manual inspections, can be labor-intensive and subject to human error. This paper introduces a hybrid deep learning model that combines the capabilities of ResNet50 and GoogLeNet, further enhanced by a convolutional block attention module (CBAM), proposed to improve both the accuracy and performance in detecting structural damage. For training purposes, a diverse dataset of images depicting both structural damage cases and undamaged cases was used. To further enhance the robustness, data augmentation techniques were also employed. In this research, precision, recall, F1-score, and accuracy were employed to evaluate the effectiveness of the introduced hybrid deep learning model. Our findings indicate that the hybrid deep neural network introduced in this study significantly outperformed standalone architectures such as ResNet50 and GoogLeNet, making it a highly effective solution for applications in disaster response and infrastructure maintenance.

Structural response and damage assessment method for subsea pipe-in-pipe subjected to anchor impact

The pipe-in-pipe system is widely used in the development and transportation of offshore oil and gas resources. The damage caused by anchor impacts on the pipe-in-pipe system has long been a focal point and challenge in both engineering and academic fields. Numerical simulation method is employed to investigate the impact process of anchors on pipe-in-pipe systems, revealing the variation patterns of pipeline deformation response over time. The structural response of the pipe-in-pipe system to dropped anchor impacts is studied from multiple perspectives, including deformation, energy, and load transfer. The influence of pipe-in-pipe characteristic parameters, anchor characteristic parameters, centralizers, and bulkheads on the extent of impact damage is analyzed, establishing a relationship between the absorbed energy and the damage to the pipe-in-pipe. The results indicate that the impact energy primarily depends on the mass and velocity of the anchor. Energy is conserved during the impact process. It is found that even with different anchor masses and velocities, the extent of damage to the pipe-in-pipe system remains the same if the impact energy is identical. High-strength steel, large diameter, and thick-walled pipelines exhibit better resistance to impact loads. Additionally, centralizers and bulkheads mitigate the impact damage to the pipe-in-pipe system. Finally, an evaluation method for pipe-in-pipe impact damage due to dropped anchors is proposed. It is discovered that the assessment method for pipelines impacted by dropped anchors in the DNV-RP-F107 standard tends to be conservative when the impact energy is high. The findings of this study provide technical support for the integrity management of pipe-in-pipe systems.

Damage analysis and assessment of concrete T-girder bridge based on fire scene numerical reconstruction

Fire is a sporadic disaster of concrete bridges, with diverse fire environments and complex damage mechanisms. Accurately evaluating the damage situation of concrete bridges after a fire is exceedingly challenging. This study formulates a damage analysis and assessment method based on the step-by-step and progressively deepening working principle. The method relies on fire scene numerical reconstruction and encompasses key technical aspects, including bridge detection and analysis during the fire incident, fire scene numerical reconstruction, and subsequent bridge damage assessment. Building upon these principles, the study utilizes results from the detection and analysis of the concrete T-girder bridge during a fire incident to establish Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) models for the numerical reconstruction of the fire scene. These models enable the calculation of varying temperature distributions and the evolution of the bridge under fire. Compared with the parameters obtained through the ISO834 method, the numerical reconstruction approaches not only enhances the accuracy of replicating the bridge combustion process but also enables the extraction of temperature field distribution patterns within the bridge fire space and its concrete components.

Energy-based damage assessment method for masonry walls under seismic and fire loads

The evaluation of the out-of-plane (OOP) behavior for infilled walls is a critical aspect of regional seismic and fire resilience assessment. This study presents a detailed finite element (FE) model that comprehensively captures the seismic and fire behaviors of masonry walls. The FE model incorporates key factors governing the thermo-mechanical behavior of masonry walls, including temperature-dependent material properties, nonlinearities in geometry and material, block cracking and crushing, and mortar damage. Then, an energy-based damage criterion is proposed based on the principle of energy conservation, leveraging the combined mixed fracture energy and internal energy of elements. In addition, this study defines the damage levels of masonry walls under OOP loading and fire and determines corresponding damage indices using the proposed energy-based damage criterion. This criterion is further compared with a stiffness-based damage criterion. Finally, the proposed damage assessment method is employed to evaluate the damage evolution of infilled walls under seismic, fire and post-earthquake fire scenarios, and to conduct a fragility analysis. The results demonstrate a high degree of agreement between the predicted and measured damage states of masonry walls under seismic and fire loads. More severe seismic damage does not always result in diminished fire resilience. Evaluating post-earthquake fire damage requires considering the impact of displacement directions caused by earthquakes and fires.

Study on Fractal Damage of Concrete Cracks Based on U-Net

The damage degree of a reinforced concrete structure is closely related to the generation and expansion of cracks. However, the traditional damage assessment methods of reinforced concrete structures have defects, including low efficiency of crack detection, low accuracy of crack extraction, and dependence on the experience of inspectors to evaluate the damage of structures. Because of the above problems, this paper proposes a damage assessment method for concrete members combining the U-Net convolutional neural network and crack fractal features. Firstly, the collected test crack images are input into U-Net for segmenting and extracting the output cracks. The damage to the concrete structure is then classified into four empirical levels according to the damage index (DI). Subsequently, a linear regression equation is constructed between the fractal dimension (D) of the cracks and the damage index (DI) of the reinforced concrete members. The damage assessment is then performed by predicting the damage index using linear regression. The method was subsequently employed to predict the damage level of a reinforced concrete shear wall–beam combination specimen, which was then compared with the actual damage level. The results demonstrate that the damage assessment method for concrete members proposed in this study is capable of effectively identifying the damage degree of the concrete members, indicating that the method is both robust and generalizable.

The impact protection behavior of UHPC composite structure on RC columns

In order to prevent the reinforced concrete (RC) structures from being damaged under the overload impact, a new type of composite structure—ultra-high performance concrete (UHPC)–Bio-inspired honeycomb column thin-walled structure (BHTS) was designed in this paper. A scale model with a scaling factor of 1:10 was made. The experimental tests and numerical simulations of RC column and UHPC composite structure were carried out. By comparing the impact force, displacement, shear force, bending moment and energy absorption, the protective effect of the UHPC-BHTS composite structure on RC columns under lateral impact load was evaluated. Then, the failure process of RC column was analyzed, the UHPC-BHTS composite structure absorbed 76.42% of the impact kinetic energy under the higher energy input condition, the shear failure with large damage to the RC column can be converted into bending failure with small damage. At the same time, a new damage assessment method was used to evaluate the RC column. The results show that the RC column with UHPC-BHTS composite structure can effectively protects the RC column structural integrity under impact. The design and modeling methods in this research can provide a useful reference for anti-collision design in practical engineering.

Study on the Precise Evaluation of Environmental Impacts of Air Pollution in Cold Regions Using the Cost Control Method

Objective: With the acceleration of industrialization, air pollution has become a global environmental issue, particularly in cold regions where the unique climatic and geographical conditions give rise to distinctive types of air pollution and impacts. Considering the economic evaluation of environmental damage is crucial for effective pollution control policies, this study aims to provide a more precise environmental damage assessment method through the Improved Virtual Control Cost Method (IVCCM) to optimize air pollution governance strategies in cold regions. Method: This study utilizes a case study of a major company producing methanol and coal-based natural gas, where the emissions from the boiler exhaust exceeded the prescribed standards for particulate matter, sulfur dioxide, and nitrogen oxides during a specific period. By employing a segmented counting approach that accounts for downtime, precise calculations were conducted for the actual periods of excess emissions. Adjustments were made to the calculation coefficients within the Virtual Control Cost Method to more accurately reflect the ecological damage caused by air pollution. Results: The IVCCM calculations revealed that the total environmental loss caused by the company’s excessive air pollution emissions amounted to USD 1.6844 million, significantly lower than the original calculation method (USD 2.1885 million). Specifically, the environmental losses due to particulate matter, sulfur dioxide, and nitrogen oxides were USD 0.0032 million, USD 0.3600 million, and USD 1.3212 million, respectively. Conclusions: The IVCCM enables a more precise assessment and prediction of ecological environmental damage caused by air pollution in cold regions. Compared to traditional methods, it effectively reduces assessment costs, mitigates disputes arising from unclear parameter values and calculation methods, and facilitates the development of more rational environmental protection policies and measures.

Deep Learning Method for Post-earthquake Damage Assessment of Frame Structures Based on Time–Frequency Analysis and CGAN

Deep Learning Method for Post-earthquake Damage Assessment of Frame Structures Based on Time–Frequency Analysis and CGAN

Potential of Non-Contact Dynamic Response Measurements for Predicting Small Size or Hidden Damages in Highly Damped Structures.

Vibration-based structural health monitoring (SHM) is essential for evaluating structural integrity. Traditional methods using contact vibration sensors like accelerometers have limitations in accessibility, coverage, and impact on structural dynamics. Recent digital advancements offer new solutions through high-speed camera-based measurements. This study explores how camera settings (speed and resolution) influence the accuracy of dynamic response measurements for detecting small cracks in damped cantilever beams. Different beam thicknesses affect damping, altering dynamic response parameters such as frequency and amplitude, which are crucial for damage quantification. Experiments were conducted on 3D-printed Acrylonitrile Butadiene Styrene (ABS) cantilever beams with varying crack depth ratios from 0% to 60% of the beam thickness. The study utilised the Canny edge detection technique and Fast Fourier Transform to analyse vibration behaviour captured by cameras at different settings. The results show an optimal set of camera resolutions and frame rates for accurately capturing dynamic responses. Empirical models based on four image resolutions were validated against experimental data, achieving over 98% accuracy for predicting the natural frequency and around 90% for resonance amplitude. The optimal frame rate for measuring natural frequency and amplitude was found to be 2.4 times the beam's natural frequency. The findings provide a method for damage assessment by establishing a relationship between crack depth, beam thickness, and damping ratio.

Prediction of Failure Due to Fatigue of Wire Arc Additive Manufacturing-Manufactured Product

Currently, the focus of production is shifting towards the use of innovative manufacturing techniques and away from traditional methods. Additive manufacturing technologies hold great promise for creating industrial products. The industry aims to enhance the reliability of individual components and structural elements, as well as the ability to accurately anticipate component failure, particularly due to fatigue. This paper explores the possibility of predicting component failure in parts produced using the WAAM (wire arc additive manufacturing) method by employing fractal dimension analysis. Additionally, the impact of manufacturing imperfections and various heat treatment processes on the fatigue resistance of 30CrMnSi steel has been investigated. Fatigue testing of samples and actual components fabricated via the WAAM process was conducted in this study. The destruction of the examined specimens and products was predicted by evaluating the fractal dimensions of micrographs acquired at different stages of fatigue testing. It has been established that technological defects are more dangerous in terms of fatigue failure than microstructural ones. The correctly selected mode of heat treatment for metal after electric arc welding allows for a more homogeneous microstructure with a near-complete absence of microstructural defects. A comparison of the fractal dimension method with other damage assessment methods shows that it has high accuracy in predicting part failure and is less labor-intensive than other methods.

Damage assessment method of clay brick masonry load-bearing walls under intense explosions with long duration

The vulnerability of clay brick masonry load-bearing (CBML) walls under low-intensity explosions has been extensively investigated. In recent years, large-scale explosions have raised wide concerns about the destructive effect of intense explosions. Intense explosions induced by large TNT equivalent explosives usually cause severe damage to building structures within several kilometers. Although the damage of building structures under intense explosions and normal low-intensity explosions might be different, the differences have yet received any attention in previous studies. Therefore, this study numerically investigates the dynamic performance of CBML walls under intense explosions with long duration (IELD). Firstly, the numerical model is validated by reproducing experimental records. Then the verified model is utilized to investigate the dynamic response and dynamic modes of CBML walls under IELD. Based on the identified failure mechanism, the effects of several parameters such as axial compression ratio, compressive strengths of masonry materials and wall geometry on the damage degrees of CBML walls are analyzed in detail. The damage index based on the residual axial loading capacity of CBML wall is proposed for damage evaluation. The damage assessment method is established for CBML walls under IELD, which can help to evaluate the damage level of clay brick masonry structures under far-field intense explosive scenarios.

A CFD-DEM-FEM coupling method for the ice-induced fatigue damage assessment of ships in brash ice channels

Polar transport ships frequently traverse in the brash ice channel opened by icebreakers. Although the substantial ice resistance caused by direct collisions with the level ice is avoided, the hull still encounters collisions with the brash ice, leading to periodic damage and exacerbating the fatigue issues of the hull structure. To address the fatigue challenges faced by ships sailing in the brash ice channels, this paper proposes an ice-induced fatigue damage assessment method based on the CFD-DEM-FEM. Referring to the brash ice model test conducted at the Hamburg Ship Model Basin (HSVA), a discrete element ice model and a numerical brash ice tank are established using the CFD-DEM coupling method. The simulated ship-ice interaction is compared with HSVA’s experimental results to validate the reliability of the numerical brash ice tank and ice load. The ice load time history resulting from the ship-brash ice collision is applied to the hull, and the hot spot stress time history under each fatigue sub-condition is calculated using the FEM. The improved rain-flow counting method is employed to determine the stress level of the hot spot stress time history, and the S-N curve method based on the linear cumulative damage criterion is used to calculate the total fatigue damage of hot spots. Finally, the results of the proposed method are compared with those of the LR method. This study can serve as a valuable reference for the ice-induced fatigue assessment of ships navigating in brash ice channels.

Impact of local site conditions on seismic performance of free‐spanning submarine pipelines: Underwater shaking table tests and numerical simulations

AbstractLocal site conditions may pose a significant influence on the seismic responses of submarine pipelines by altering both the offshore motion propagation and soil‐structure interaction (SSI). This paper aims to provide an in‐depth understanding of the influence regularity of local site conditions on the seismic performance of free‐spanning submarine pipelines (FSSPs). For this purpose, a suite of underwater shaking table tests were performed to investigate the seismic responses of FSSP subjected to the offshore spatial motions at three site categories. Response comparison factor () is defined to quantify the structural response discrepancies caused by the seismic inputs at different sites. The test results indicate that responses of the studied model FSSP gradually increase as spatial offshore motions at softer soil sites are employed as inputs; and the values of vary with a maximum magnitude of up to 40%–60% for different response indices when the site soil changes from fine sand to clay. Subsequently, the corresponding numerical simulations are carried out to reproduce the seismic responses of the test model. The experimental and numerical results meet a good agreement, indicating that the developed numerical modeling method can accurately predict the seismic responses of FSSPs. Following this verified modeling method and using the p‐y approach to address the SSI effect, fragility surfaces of the studied FSSP are derived in terms of PGA and site parameter (shear‐wave velocity in the top 30 m of the soil profile) via probabilistic seismic demand analyses. The impact of local site conditions on the seismic performance of the FSSP is quantitatively examined by comparing the fragility curves corresponding to various . Furthermore, a fast seismic damage assessment method is proposed for efficiently evaluating the performance of FSSPs buried in various offshore soil conditions. This approach proves beneficial for designers and decision‐makers, enabling accurate estimation of seismic damage and facilitating the implementation of post‐earthquake maintenance measures for FSSPs.

Investigation of the Overall Damage Assessment Method Used for Unmanned Aerial Vehicles Subjected to Blast Waves

With the aim of investigating the assessment methodology for the overall damage effects on an unmanned aerial vehicle (UAV) subjected to a blast wave, the failure criteria for the typical UAV was formulated through an analysis of the structural strength design standards. Specifically, the shear force associated with wing failure can serve as a critical parameter for assessing the overall damage inflicted on the UAV by blast waves. According to the design load criterion of the aircraft, the shear force value corresponding to the overall failure of the typical UAV was calculated. Numerical simulations were conducted to investigate the mechanical response of UAV structures under blast wave loading generated by a 500 g explosive. Combining the critical shear force values obtained from theoretical calculations with the numerical simulation results, two distances between the explosives and the UAV that could produce different damage effects were estimated, namely 1 m and 2.5 m. Subsequently, static explosion experiments with equivalent explosive charges were performed, revealing different damage effects on a typical UAV at two specific distances. The numerical simulation results were highly consistent with the experimental observations, further validating the scientific and rational basis for using shear force as a primary parameter in assessing overall structural damage to fixed-wing UAVs.

Post-earthquake damage probability assessment of high-speed railway simply supported bridge based on traffic capacity

Railway transportation is an important channel for emergency rescue and disaster relief. Traditionally, the method of evaluating the damage degree of bridges under different seismic intensities from the perspective of structural damage cannot be directly used to judge the traffic capacity of trains on bridges after earthquakes. It is impossible to guarantee the running safety and affect the transportation of materials after the earthquake. Because the damage state of track structure directly affects the running safety of trains, this study combines the relationship between the damage of track structure and the deformation of bridge structure after earthquake, and puts forward the transverse relative displacement of girder end (TRDGE) as the damage index of train running function of railway bridge after earthquake. Then, the OpenSees-TRBF (Train-Railway-Bridge-Foundation Coupled System Dynamic Analysis Platform) co-simulation method is used to carry out the train-track-bridge coupling dynamic calculation under different seismic damage states, and the running safety analysis database under different TRDGEs is established. Then, the Particle Swarm Optimization (PSO) algorithm is used to classify the bridge damage index of traffic capacity through different target safety speeds. Based on the probabilistic seismic demand model, the exceedance probability curve of traffic capacity damage under different seismic intensities is established. Finally, based on the curve, the running safety risk domain of trains on the bridge under different seismic intensities is obtained with a confidence level of 95 %. This study proposes a post-earthquake damage assessment method for railway bridges based on the assurance of running safety probabilities, evaluating the damage degree of the bridge with the residual traffic capacity of the bridge after the earthquake. This study can be applied to assess earthquake damage on existing railway bridges and provide references for the safe speed of trains on the bridge after an earthquake.

Development of a Damage Assessment Method for the Efficient Maintenance of Aging Small- to Medium-Sized Reinforced Concrete Slab Bridge Decks

Development of a Damage Assessment Method for the Efficient Maintenance of Aging Small- to Medium-Sized Reinforced Concrete Slab Bridge Decks

Damage of special bolt structures based on multi-scale method evaluate research

Abstract During the service life of underwater bolt structures, the occurrence of fracture failures is influenced by environmental factors such as corrosion and external pressure. This study aims to evaluate the behavior of bolt structures underwater and establish reliable methods for damage assessment, which is crucial for ensuring the safe operation of underwater equipment. This article introduces the concept of multi-scale analysis, considering the influence of initial defects in materials on the structure’s performance. It explores the micro-macro crack evolution mechanism and employs surface-level methods. By utilizing the GTN-based multi-parameter damage constitutive model, the study investigates the extended behavior and stress range under various load states. The findings provide theoretical support for accurately assessing structural safety.

A Multi-Sensing IoT System for MiC Module Monitoring during Logistics and Operation Phases.

Modular integrated construction (MiC) is now widely adopted by industry and governments. However, its fragile and delicate logistics are still a concern for impeding project performance. MiC logistic operations involve rigorous multimode transportation, loading-unloading, and stacking during storage. Such processes may induce latent and intrinsic damage to the module. This damage causes safety hazards during assembly and deteriorates the module's structural health during the building use phase. Also, additional inspection and repairs before assembly cause uncertainties and can delay the whole supply chain. Therefore, continuous monitoring of the module's structural response during MiC logistics and the building use phase is vital. An IoT-based multi-sensing system is developed, integrating an accelerometer, gyroscope, and strain sensors to measure the module's structural response. The compact, portable, wireless sensing devices are designed to be easily installed on modules during the logistics and building use phases. The system is tested and calibrated to ensure its accuracy and efficiency. Then, a detailed field experiment is demonstrated to assess the damage, safety, and structural health during MiC logistic operations. The demonstrated damage assessment methods highlight the application for decision-makers to identify the module's structural condition before it arrives on site and proactively avoid any supply chain disruption. The developed sensing system is directly helpful for the industry in monitoring MiC logistics and module structural health during the use phase. The system enables the researchers to investigate and improve logistic strategies and module design by accessing detailed insights into the dynamics of MiC logistic operations.

A novel sensor placement strategy based on an enhanced damage assessment method in beam‐like structures: Saddle point criteria

A novel sensor placement strategy based on an enhanced damage assessment method in beam‐like structures: Saddle point criteria

Constraints of local stiffness adaption for reduced-order models of large-scale steel bridges

Large and complex structures, such as bridges, are subjected to a variety of environmental factors and loads over time, leading to evolving structural states. To assess their current condition and plan predictive maintenance, Digital Twins enriched with Structural Health Monitoring (SHM) data are essential. However, for large-scale structures, the creation of physics-based Digital Twins necessitates reduced-order modeling to ensure efficient adaptation to SHM data. Many of these methods for structural damage assessment rely on localized stiffness reduction to characterize discrete damage states. The Static Condensation Reduced Basis Element (SCRBE) method is a promising approach for model order reduction by decomposing the structure into parametric components. However, SCRBE's effectiveness and the accuracy of the Digital Twin depend on an appropriate partitioning of the structure into to components with reduced stiffness. This paper systematically investigates the process and the constraints of component selection for steel bridges with discrete damages, considering factors like numerics, sensor placement and complex geometries. A comprehensive analysis is conducted using a real bridge case study augmented with synthetic measurement data representing damage scenarios. The results reveal both challenges and the potential of the SCRBE method for Digital Twins. A systematic approach for component selection within the SCRBE framework is proposed, specifically tailored for real-world application scenarios. This structured methodology facilitates the efficient and adaptive development of Digital Twins for large, intricate structures, such as steel bridges.