Damage State Research Articles

Experimental study and model analysis on the seismic and resilient performance of RAC precast walls with UHSB

This paper aims to investigate and compare the seismic behavior of precast resilient wall and cast-in-situ resilient wall with different shear-span ratios, and to explore the reliability of the proposed precast wall in practical engineering. For this purpose, quasi-static tests were conducted on the precast walls and cast-in-situ walls with two shear span ratios of 2.2 and 1.5. The experimental variables also involved in the presence of steel fibers, and recycled aggregate concrete (RAC) strength. The seismic responses of tested walls, including damage state, load-displacements curves, stiffness degradation, and strain development were analyzed. In addition, residual drift ratio, and damage index were used to assess the resilient performance and damage degree. The comparison results indicated that precast walls can exhibit seismic and resilient performance comparable to that of cast-in-situ walls. Ultimately, considering the weak bond performance, the model analysis was conducted based on OpenSees platform, and parameter analysis of boundary longitudinal reinforcement has been carried out.

Fatigue damage evolution behaviors and fractional fatigue mechanical model of monzogabbro under true triaxial disturbance test

The disturbance wave caused by excavation or blasting of underground surrounding rock causes fatigue degradation effect of rock and eventually leads to disasters. However, the fatigue damage characteristics and fatigue models of rock under true triaxial disturbance are scare. Therefore, a series of true triaxial disturbance tests were conducted to investigate the rock fatigue deformation, strength and damage behaviors under different conditions. The evolutions of static damage and fatigue damage are separated and investigated respectively. Fatigue deformation and damage of rock under true triaxial stress undergoes three stages: attenuation, constant velocity and acceleration stage. The crack initiation stress can be as the initial condition of the fatigue deformation; the fatigue critical stress σdc of rock entering the acceleration failure stage was proposed and explored, with increasing frequency, σdc increase slightly and with increasing σ2, σdc increase obviously. Then, a novel fractional fatigue mechanical model considering the fatigue damage and intermediate principal stress effects of rock under true triaxial disturbance was proposed. The theoretical results of the model agree well with the results of the tests. Finally, the sensitivity analysis of stresses and model parameters and the model predictions under other untesting conditions were carried out to improve the understanding and prediction level of fatigue failure in underground engineering.

An insight into annealing mechanism of graphitized structures after irradiation

Graphite components are constantly subjected to a combined actions of annealing and irradiation due to high temperatures and thermal spike caused by irradiation when reactors are operating, resulting in complex microstructures along with matching changes in the material properties and dimensions. This study investigates the evolution process of initial irradiation defects at different annealing temperatures, which is difficult to captured by experiment. The findings indicate that 923K reactor-temperature annealing can also quickly restore isolated self-interstitial atoms and small-sized point defect clusters to intralayer locations on the nanosecond scale. However, multi-interlayer penetration damages and localized point defect aggregation from high-energy irradiation can lead to the disappearance of layered structural information, which allows these damage structures to develop into interlayer dislocations during annealing process. These interlayer dislocations further exacerbate the interlayer expansion of graphite crystal and may elucidate the mechanism behind volume expansion in nuclear graphite within reactors. Fully amorphized regions can also regain a layered structure approximately when guided by residual layered structures at 2000K, while chaotic regions or disordered layered structures form in the absence of guidance. These chaotic regions significantly exacerbate the volume expansion of graphite model, which may be related to the rapid volume increase observed in nuclear graphite components at the end of reactor life. The study provides insights into the transformation of initial irradiation defects into different types of defects under different temperatures and damage states, which serve as a critical foundation for assessing the evolution of irradiation defects in nuclear graphite for reactor applications and annealing studies.

Model-free chemomechanical interfaces: History-dependent damage under transient mass diffusion

This paper presents a data-driven framework based on distance functional for chemo-mechanical cohesive interfaces to capture transient diffusion and resulting interfacial damage evolution. The framework eliminates reliance on complex constitutive models and phenomenological assumptions, especially avoiding the coupling tangent terms with a given material database. The interfacial chemical potential and its jumps are used to expand the phase space for describing the chemical states of interfaces. Subsequently, a novel chemo-mechanical distance norm, including traction-separation pair, interfacial chemical potential-concentration pair and corresponding chemical potential jump-flux pair, is presented. Momentum conservation law for interfacial tractions and mass conservation law for interfacial concentration are enforced via Lagrange multipliers. For tracking the history-dependent state of the interface damage, an internal variable, termed interface integrity, is introduced to condition the interfacial database and manage the subsets mapping strategies, following physically motivated evolution constraints. Numerical examples are conducted to investigate the efficiency and capability of the present framework. A monotonic loading test validates a good numerical convergence relative to the number of data points. Subsequent cyclic loading simulations, compared with the reference solutions, show that the algorithm is well suitable to predict the history-dependent interface damage evolution under complex loading paths. Finally, the chemo-mechanically coupled examples capture phenomena such as interfacial swelling and interface degradation induced by transient diffusion and stress-driven diffusion. The current work provides a promising tool for understanding chemo-mechanical behaviors of interfaces within heterogeneous composites.

Numerical investigation of thermal soak within engine bay using lattice Boltzmann method

A large amount of heat accumulates in the engine bay for a short time after the engine runs at high load and shuts down, that will lead to thermal damage and thermal fatigue caused by the temperature rise of some heat sensitive components. This paper uses an aero-thermal coupling approach to study the heat transfer problem in the engine bay of an SUV model under thermal soak conditions. Due to the transient characteristics of the heat transfer process, the natural transient CFD software developed based on the LBM method is used to study the engine bay heat transfer during the 400 s key-off soak process. The analysis reveals that convection and radiation are the main heat transfer modes in the early stage of hot immersion (0–120 s), and conduction only makes a significant contribution in contact with high temperature sources. The radiation and convection are the key contributors to heat transfer processes of engine bay during soak, but the efficiency of radiation heat transfer decreases with the increase of time, whereas the efficiency of convection heat transfer is not always reduced, it will increase and then decrease with the increase of time. The coupling method established can predict the thermal state in the engine bay well, and is in good agreement with the experimental results. The results show that the error in the engine coolant temperature is less than 1 °C, and the error in the temperature of the heat-sensitive components is less than 5 °C. Finally, the potential risks of thermal damage and thermal fatigue states were assessed, providing an important reference for the control design of cooling fan running time after key-off.

Hidden structural information reconstruction and seismic response analysis of high‐rise residential shear wall buildings with limited structural data

AbstractThe high‐rise residential shear wall structure is a crucial component of urban building clusters, while the limited availability of detailed structural information becomes a critical bottleneck in improving the accuracy of seismic performance assessment for high‐rise residential shear wall buildings in urban areas. Based on easily obtainable yet limited structural data at the urban scale, this paper proposes a method to address the shortcomings of existing research on reconstructing hidden structural information and enhance the accuracy of structural seismic performance assessment. It includes a physics‐constrained generative adversarial network module and a fuzzy inference system module to reconstruct the spatial arrangement of shear walls, and material strength grades within buildings, respectively. Validated against two actual buildings, the method outperforms the widely used simplified analysis method at the urban scale, achieving 85.9% accuracy in predicting damage states across various floors.

Analysis of the Effect of Road Damage Conditions on Vehicle Speed (Case Study of Road Sections in Tanjungbalai City)

Analysis of the Effect of Road Damage Conditions on Vehicle Speed (Case Study of Road Sections in Tanjungbalai City)

GRNN-based cascade ensemble model for non-destructive damage state identification: small data approach

AbstractAssessing the structural integrity of ageing structures that are affected by climate-induced stressors, challenges traditional engineering methods. The reason is that structural degradation often initiates and advances without any notable warning until visible severe damage or catastrophic failures occur. An example of this, is the conventional inspection methods for prestressed concrete bridges which fail to interpret large permanent deflections because the causes—typically tendon loss—are barely visible or measurable. In many occasions, traditional inspections fail to discern these latent defects and damage, leading to the need for expensive continuous structural health monitoring towards informed assessments to enable appropriate structural interventions. This is a capability gap that has led to fatalities and extensive losses because the operators have very little time to react. This study addresses this gap by proposing a novel machine learning approach to inform a rapid non-destructive assessment of bridge damage states based on measurable structural deflections. First, a comprehensive training dataset is assembled by simulating various plausible bridge damage scenarios associated with different degrees and patterns of tendon losses, the integrity of which is vital for the health of bridge decks. Second, a novel General Regression Neural Network (GRNN)-based cascade ensemble model, tailored for predicting three interdependent output attributes using limited datasets, is developed. The proposed cascade model is optimised by utilising the differential evolution method. Modelling and validation were conducted for a real long-span bridge. The results confirm the efficacy of the proposed model in accurately identifying bridge damage states when compared to existing methods. The model developed demonstrates exceptional prediction accuracy and reliability, underscoring its practical value in non-destructive bridge damage assessment, which can facilitate effective restoration planning.

Terahertz time-domain spectro-imaging and hyperspectral imagery to investigate a historical Longwy glazed ceramic

In this paper, we present the potential of Terahertz Time-Domain Imaging (THz-TDI) as a tool to perform non-invasive 3D analysis of an ancient enamel plate manufactured by Longwy Company in France. The THz data collected in the reflection mode were processed using noise filtering procedures and an advanced imaging approach. The results validate the capability to identify glaze layers and the thickness of ceramic materials. To characterize the nature of the pigments, we also use with X-ray images, visible near-infrared hyperspectral imaging spectroscopy, and p-XRF (portable X-ray fluorescence) to qualitatively and quantitively identify the materials used. The obtained information enables a better understanding of the decoration chromogens nature and, thus, to determine the color palette of the artists who produced such decorative object. We also establish the efficiency of a focus, Z-tracker, which enables to perform THz imaging on non-flat samples and to attenuate artifacts obtained with a short focus lens. Then, 3D images are extracted and generated, providing a real vision. We also report the evaluation of the internal damage state through the detection of fractures.

An anisotropic full-network model with damage surface for the Mullins effect in filled rubbers

The Mullins effect is a highly anisotropic damage phenomenon exhibited by filled rubbers among other soft materials. When filled rubbers are subjected to uniaxial tension, their apparent stiffness drops in the direction of stretching but is essentially unaltered in the transverse directions. However, micromechanical full-network models where Mullins softening is described at the level of individual chains often predict that uniaxial deformations induce transverse softening in addition to softening in the stretching direction. Moreover, these approaches typically require the storage of damage state variables for each chain, which is computationally expensive. Taking an alternative approach, we present a full-network model for the Mullins effect where the damage state is described by a single macroscopic damage tensor from which the damage state in each direction can be calculated. The evolution of damage is specified through damage surfaces and damage flow rules, which depend on the directions of principal stretches. The model is shown to reproduce experimental data for filled rubbers sequentially subjected to uniaxial tension in different directions. The model is also implemented in the finite element software ABAQUS as a user subroutine UMAT to illustrate the suitability of the model to simulate non-homogeneous deformation states.

Novel joint algorithm for state-of-charge estimation of rechargeable batteries based on the back propagation neural network combining ultrasonic inspection method

State of Charge (SoC) is an essential indicator for energy storage distribution in lithium-ion batteries, which prevents overcharge and over-discharge of the battery by integrating it into the Battery Management System. Common estimation approaches are Extended Kalman Filtering (EKF), Coulomb counting, open-circuit-voltage (OCV), and neural networks (NN). While these methods are able to estimate SoC more accurately, they lack real-time monitoring capability for internal and external battery damage such as air bubbles and foreign objects. This study is the first to propose a novel joint algorithm for real-time monitoring of battery SoC and health with high accuracy, integrating ultrasonic non-destructive testing (NDT). The proposed algorithm predicts the battery overcharge based on the ultrasonic signal and reveals structural changes in commercial batteries during charging/discharging. Experimental results demonstrate that ultrasonic inspection cannot only enhance the SoC estimation accuracy of the backpropagation (BP) neural network, but also detects damaged conditions of the battery.

Failure criterion and seismic fragility evaluation of isolated nuclear power plant piping system using BP neural network

The pipeline connecting the isolated nuclear island and the non-isolated turbine building is prone to significant relative displacements during intensive earthquakes. Generally, elbows closest to the isolation layer are considered to be at particularly high risk of seismic damage. The failure criterion is the critical part in determining the damage state of elbows throughout the loading cycle. Therefore, in this study, a three-tier, four-category failure criterion was firstly proposed in response to the damage patterns of elbows. A BP neural network model was subsequently developed using extensive simulation data derived from a verified numerical model, accompanied by influence analysis of the three failure indices. Finally, a fragility evaluation was conducted based on the seismic response of the piping system, and a comparison is made between the new criterion and the existing ones. The results indicate that the new failure criterion demonstrates comprehensiveness and safety, enabling a more detailed division of damage before elbow failure and providing more conservative estimates upon failure occurrence. Additionally, the study finds that under the current design of nuclear power plants, elbows across isolation layers fail to meet the requirements for safe shutdown earthquakes in certain directions. By adjusting the elbow parameters, the resistance of the elbows to damage under seismic conditions can be improved to some extent.

A methodology for evaluating damage in thin-walled cylindrical shells using bounded ultrasonic beam scattering

This paper introduces an ultrasonic detection methodology specifically designed to assess damage in thin-walled cylindrical shells, which crucially relies on the interaction between a bounded ultrasonic beam and a thin-walled cylindrical shell immersed in fluid, considering both water-filled and air-filled cavities. Initially, we derive the scattered sound field expression for a bounded ultrasonic beam obliquely striking the shell. Subsequently, through finite element simulations and experimental verification, we observe that when the incident bounded beam is emitted at the critical angles defined in this study, early damage significantly enhances the received sound pressure amplitude detected by a symmetrically positioned receiver. Notably, a mere 5 % decrease in the shell's elastic modulus leads to a notable 233.69 % increase in the area under the amplitude-frequency curve of the received sound pressure for water-filled cavities and a remarkable 642.85 % surge in area for air-filled cavities. Experimental data further validates the sensitivity of this method towards varying corrosion damage states. This approach combines the reliability of linear ultrasonic methods with the enhanced sensitivity of nonlinear ultrasonic techniques, offering a significant advancement over traditional ultrasonic detection methods for inspecting cylindrical shells. The proposed assessment method holds immense potential in providing novel insights for inspecting cylindrical shells in practical applications.

Dynamic mechanical properties and energy dissipation analysis of rubber-modified aggregate concrete based on SHPB tests

The fluctuation of the waveform curves in the Split Hopkinson Pressure Bar (SHPB) test can provide a more intuitive reflection of the material's dynamic deformation process, with different strain rates resulting in varying damage states and σ-ε curves. A Φ120×100 mm size SHPB experiment was conducted to study the dynamic mechanical properties of new rubber-modified aggregate concrete (RAC). Based on the different characteristics of waveform and σ-ε curves, combined with high-speed photography technology, the typical failure modes and dynamic compressive strength of rubber-modified aggregate concrete under different loading rates were analyzed. Furthermore, the energy dissipation capacity and mechanism of rubber-modified aggregate concrete at different stages was discussed. The reflected wave of RAC shows a "double-peak" trend of "first high and then low" instead of "first low and then high" of normal concrete due to its exceptional capacity of energy absorption and dissipation. As strain rate increases, a plateau period appears in the reflected wave before first peak. The evolution process is dominated by the energy storage mechanism until it hits the limit, then by the energy dissipation mechanism. These findings can help us design and use RAC materials under dynamic stress.

Experimental and Theoretical Investigation of Initial Irreversible Critical Damage State of Red Mudstone

Experimental and Theoretical Investigation of Initial Irreversible Critical Damage State of Red Mudstone

Comprehensive evaluation of seismic fragility in base isolated buildings enhanced with supplemental dampers considering pounding phenomenon

Base isolation is a proven technology effective in minimizing earthquake-induced damage to both the structural and non-structural elements (especially freestanding contents) of buildings. Nevertheless, it has been shown that allowing the flexible isolation layer to endure substantial demand displacements might subject the isolated structure to failure. This vulnerability arises from potential superstructure yielding due to increased deformations and reduced stiffness, such as those occurring through pounding against a moat wall during intense earthquakes. One alternative to controlling these large deformations is to use supplementary dampers at the isolation plane of the building, creating a hybrid base isolation system (HIS), which adds damping to the isolation system. In this research, the seismic performance of base isolated structures with lead-rubber bearing (LRB) are studied in conjunction with linear viscous dampers (LVD). Due to this aim, a base-isolated steel frame with 2 story X-type braces and a surrounding moat wall is modeled with two various configurations: LRB, and LRB with LVD. Fragility curves are developed for an ensemble of near-field (NF) pulse-like ground motions and for the maximum inter-story drift ratio (MIDR) as an engineering demand parameter (EDP). The incremental dynamic analysis (IDA) is conducted to calculate the damage probability of the structure by assuming different threshold values for damage states. It was found that adding viscous dampers to the isolation system balanced the behavior of the structure under near field pulse-type records; resulting in reduced isolation displacement while its adverse effects are insignificant and can be ignored. Moreover, the median spectral acceleration, namely the spectral acceleration associated to a probability of exceedance (POE) equal to 50 %, at the specific limit state, in the hybrid base isolation system is higher compared to the conventional one.

Non-magnetic metal plate classification algorithm that can ignore the damage condition

Aiming at the problem of classification and recovery of non-magnetic metals, this paper proposes a method of classification of non-magnetic metals based on eddy current detection, which takes the slope of inductance real part as the conductivity characterization parameter to measure the conductivity of non-magnetic metals, to distinguish metals. The most significant advantage of this method is that even in the face of a metal plate with a damaged surface, its classification ability still exists, and the parameter of the slope of inductance real part will monotonically change with the surface area or depth of damage, which has guiding significance for damage classification or damage assessment.

A condition-informed dynamic Bayesian network framework to support severe accident management in nuclear power plants

In the nuclear industry, Severe Accident Management Guidelines (SAMGs) are developed with the objective of providing prescriptive actions for mitigating the consequences of Nuclear Power Plant (NPP) accidents. These guidelines are defined with respect to a set of expert-based prototypical severe accident scenarios and are symptom-based, i.e., they relate to the values of specific monitored plant parameters. Expert-based SAMGs might fail to deal with non-prototypical scenarios, i.e., scenarios not considered a priori by the experts. To address this issue, in this paper we propose a methodology based on Dynamic Bayesian Networks (DBNs) to support operators decision-making for avoiding the escalation of severe accidents to non-prototypical scenarios. The methodology is based on the integration of condition monitoring data into a DBN to allow it to i) infer the current Plant Operating Condition (POC), Initiating Event (IE), and NPP safety barriers Damage State (DS), ii) predict the grace time (GT) available to carry out mitigative actions, and iii) evaluate the effectiveness of the alternative candidate mitigative actions taking into account the safety barriers estimated DS and the predicted available GT. The proposed methodology is exemplified on a Loss of Coolant Accident (LOCA) in a WWER-1000.

Experimental substantiation of the expediency of using hyperosmolar colloidal solutions for the correction of renal dysfunction in conditions of thermal skin damage

Experimental substantiation of the expediency of using hyperosmolar colloidal solutions for the correction of renal dysfunction in conditions of thermal skin damage

Collapse analysis of a masonry arch bridge using the applied element method

Masonry arch bridges constitute a fundamental part of the European transport network. Given their historical relevance and ongoing functional role, often under significantly higher load conditions than originally designed for, a reliable assessment of their load-bearing capacity is essential to understand whether they can guarantee adequate structural performance. To address this need, research efforts have focused on the development of computational methods capable of providing realistic simulations of the structural and collapse behavior of this kind of structures. In this context, the present paper aims to evaluate the application of the recently developed Applied Element Method (AEM) to masonry arch bridges, using the well-known Prestwood bridge (Staffordshire, UK) as a benchmark case study. The bridge was modeled using AEM and loaded until collapse simulating the actual conditions of the in situ test carried out in 1986. Results show consistency, in terms of bearing capacity and collapse mechanism, with the experimental data and previous studies that used other numerical approaches, proving the ability of the Applied Element Method to provide an accurate estimate of the collapse behavior of this kind of structures. AEM’s ability to represent collapse mechanisms involving large displacements, at a reduced computational cost, is especially useful for the design of alert and monitoring systems for structures in a damaged or pre-collapse state.