Emerging Trends in Damage Tolerance Assessment:A Review of Smart Materials and Self-Repairable Structures

The discipline of damage tolerance assessment has experienced significant advancements due to the emergence of smart materials and self-repairable structures.This review offers a comprehensive look into both traditional and innovative methodologies employed in damage tolerance assessment.After a detailed exploration of damage tolerance concepts and their historical progression,the review juxtaposes the proven techniques of damage assessment with the cutting-edge innovations brought about by smart materials and self-repairable structures.The subsequent sections delve into the synergistic integration of smart materials with self-repairable structures,marking a pivotal stride in damage tolerance by establishing an autonomous system for immediate damage identification and self-repair.This holistic approach broadens the applicability of these technologies across diverse sectors yet brings forth unique challenges demanding further innovation and research.Additionally,the review examines future prospects that combine advanced manufacturing processes with data-centric methodologies,amplifying the capabilities of these‘intelligent’structures.The review culminates by highlighting the transformative potential of this union between smart materials and self-repairable structures,promoting a sustainable and efficient engineering paradigm.

Evaluation of excavation damaged zones(EDZs)in Horonobe Underground Research Laboratory(URL)

Excavation of underground caverns,such as mountain tunnels and energy-storage caverns,may cause the damages to the surrounding rock as a result of the stress redistribution.In this influenced zone,new cracks and discontinuities are created or propagate in the rock mass.Therefore,it is effective to measure and evaluate the acoustic emission(AE)events generated by the rocks,which is a small elastic vibration,and permeability change.The authors have developed a long-term measurement device that incorporates an optical AE(O-AE)sensor,an optical pore pressure sensor,and an optical temperature sensor in a single multi-optical measurement probe(MOP).Japan Atomic Energy Agency has been conducting R&D activities to enhance the reliability of high-level radioactive waste(HLW)deep geological disposal technology.In a high-level radioactive disposal project,one of the challenges is the development of methods for long-term monitoring of rock mass behavior.Therefore,in January 2014,the long-term measurements of the hydro-mechanical behavior of the rock mass were launched using the developed MOP in the vicinity of 350 m below the surface at the Horonobe Underground Research Center.The measurement results show that AEs occur frequently up to 1.5 m from the wall during excavation.In addition,hydraulic conductivity increased by 2e4 orders of magnitude.Elastoplastic analysis revealed that the hydraulic behavior of the rock mass affected the pore pressure fluctuations and caused micro-fractures.Based on this,a conceptual model is developed to represent the excavation damaged zone(EDZ),which contributes to the safe geological disposal of radioactive waste.

A 3D microseismic data-driven damage model for jointed rock mass under hydro-mechanical coupling conditions and its application

Rock mass is a fractured porous medium usually subjected to complex geostress and fluid pressure simultaneously.Moreover,the properties of rock mass change in time and space due to mining-induced fractures.Therefore,it is always challenging to accurately measure rock mass properties.In this study,a three-dimensional(3D)microseismic(MS)data-driven damage model for jointed rock mass under hydro-mechanical coupling conditions is proposed.It is a 3D finite element model that takes seepage,damage and stress field effects into account jointly.Multiple factors(i.e.joints,water and microseismicity)are used to optimize the rock mass mechanical parameters at different scales.The model is applied in Shirengou iron mine to study the damage evolution of rock mass and assess the crown pillar stability during the transition from open-pit to underground mining.It is found that the damage pattern is mostly controlled by the structure,water and rock mass parameters.The damage pattern is evidently different from the two-dimensional result and is more consistent with the field observations.This difference is caused by the MS-derived damage acting on the rock mass.MS data are responsible for gradually correcting the damage zone,changing the direction in which it expands,and promoting it to evolve close to reality.For the crown pillar,the proposed model yields a more trustworthy safety factor.In order to guarantee the stability of the pillar,it is suggested to take waterproof and reinforcement measures in areas with a high degree of damage.

Damage detection with image processing: a comparative study

Large structures,such as bridges,highways,etc.,need to be inspected to evaluate their actual physical and functional condition,to predict future conditions,and to help decision makers allocating maintenance and rehabilitation resources.The assessment of civil infrastructure condition is carried out through information obtained by inspection and/or monitoring operations.Traditional techniques in structural health monitoring(SHM)involve visual inspection related to inspection standards that can be time-consuming data collection,expensive,labor intensive,and dangerous.To address these limitations,machine vision-based inspection procedures have increasingly been investigated within the research community.In this context,this paper proposes and compares four different computer vision procedures to identify damage by image processing:Otsu method thresholding,Markov random fields segmentation,RGB color detection technique,and K-means clustering algorithm.The first method is based on segmentation by thresholding that returns a binary image from a grayscale image.The Markov random fields technique uses a probabilistic approach to assign labels to model the spatial dependencies in image pixels.The RGB technique uses color detection to evaluate the defect extensions.Finally,K-means algorithm is based on Euclidean distance for clustering of the images.The benefits and limitations of each technique are discussed,and the challenges of using the techniques are highlighted.To show the effectiveness of the described techniques in damage detection of civil infrastructures,a case study is presented.Results show that various types of corrosion and cracks can be detected by image processing techniques making the proposed techniques a suitable tool for the prediction of the damage evolution in civil infrastructures.

Study on Acoustic Emission Characteristics of Deformation Damage Process of Zirconia Ceramics

Zirconia ceramics have become increasingly widely used in recent years and are favored by relevant enterprises. From the traditional dental field to aerospace, parts manufacturing has been used, but there is limited research on the deformation and damage process of zirconia ceramics. This article analyzes the acoustic emission characteristics of each stage of ceramic damage from the perspective of acoustic emission, and explores its deformation process characteristics from multiple perspectives such as time domain, frequency, and EWT modal analysis. It is concluded that zirconia ceramics exhibit higher brittleness and acoustic emission strength than alumina ceramics, and when approaching the fracture, it tends to generate lower frequency acoustic emission signals.

Vehicle-Bridge Interaction Simulation and Damage Identification of a Bridge Using Responses Measured in a Passing Vehicle by Empirical Mode Decomposition Method

To prevent early bridge failures, effective Structural Health Monitoring (SHM) is vital. Vibration-based damage assessment is a powerful tool in this regard, as it relies on changes in a structure’s dynamic characteristics as it degrades. By measuring the vibration response of a bridge due to passing vehicles, this approach can identify potential structural damage. This dissertation introduces a novel technique grounded in Vehicle-Bridge Interaction (VBI) to evaluate bridge health. It aims to detect damage by analyzing the response of passing vehicles, taking into account VBI. The theoretical foundation of this method begins with representing the bridge’s superstructure using a Finite Element Model and employing a half-car dynamic model to simulate the vehicle with suspension. Two sets of motion equations, one for the bridge and one for the vehicle are generated using the Finite Element Method, mode superposition, and D’Alembert’s principle. The combined dynamics are solved using the Newmark-beta method, accounting for road surface roughness. A new approach for damage identification based on the response of passing vehicles is proposed. The response is theoretically composed of vehicle frequency, bridge natural frequency, and a pseudo-frequency component related to vehicle speed. The Empirical Mode Decomposition (EMD) method is applied to decompose the signal into its constituent parts, and damage detection relies on the Intrinsic Mode Functions (IMFs) corresponding to the vehicle speed component. This technique effectively identifies various damage scenarios considered in the study.

Monitoring and analysis of nonlinear dynamic damage of transport roadway supported by composite hard rock materials in Linglong Gold Mine

The study concentrates mainly on the development of failure process incomposite rock mass. By use of acoustic emission (AE), convergence inspection, pressure monitoring,level measurement techniques and the modem signal analysis technology, as well as scan electronmicroscopy (SEM) experiment, various aspects of nonlinear dynamic damage of composite rock masssurrounding the transport roadway in Linglong gold mine are discussed. According to the monitoringresults, the stability of the rock mass can be synthetically evaluated, and the intrinsic relationbetween the damage and the characteristic parameters of acoustic emission can be determined. Thelocation of the damage of rock mass can also be detected based on the acoustic emission couplemonitoring signals. Finally, the key factors which influence the stability of the transport roadwaysupported by composite hard rock materials are found out.

A time reversal damage imaging method for structure health monitoring using Lamb waves

This paper investigates the Lamb wave imaging method combining time reversal for health monitoring of a metallic plate structure. The temporal focusing effect of the time reversal Lamb waves is investigated theoretically. It demonstrates that the focusing effect is related to the frequency dependency of the time reversal operation. Numerical simulations are conducted to study the time reversal behaviour of Lamb wave modes under broadband and narrowband excitations. The results show that the reconstructed time reversed wave exhibits close similarity to the reversed narrowband tone burst signal validating the theoretical model. To enhance the similarity, the cycle number of the excited signal should be increased. Experiments combining finite element model are then conducted to study the imaging method in the presence of damage like hole in the plate structure. In this work, the time reversal technique is used for the recompression of Lamb wave signals. Damage imaging results with time reversal using broadband and narrowband excitations are compared to those without time reversal. It suggests that the narrowband excitation combined time reversal can locate and determine the size of structural damage more precisely, but the cycle number of the excited signal should be chosen reasonably.

Damage-Monitoring Forward Equivalent-model Construction of Rosette Eddy Current Sensors

结构损伤监测对于保证结构安全是极其重要的。针对金属螺栓连接结构中螺栓孔位置处的裂纹损伤定量监测需求,在Goldfine等人的基础之上,该文提出一种花萼状涡流传感器,构建了传感器损伤监测正向等效模型并通过搭建实验装置验证损伤监测正向等效模型准确性并进行误差分析。相对于传统的多层导电结构谐波涡流场的积分/级数解析模型,构建的损伤监测正向等效模型考虑了在高频激励下导线电流密度分布的集肤效应,并可用于互感式涡流传感器建模。实验结果表明：对测量结果经空气标定后,传感器贴于2A12-T4标准试件表面时的模型计算结果和实验结果较为吻合,第1、2和3感应通道的幅值比量模型计算结果误差随频率变化均在10%以内,第4感应通道的幅值比量模型计算结果误差随频率变化在15%以内。

Assessment and Monitoring Damage by <i>Coraebus florentinus</i>(Coleoptera: Buprestidae) in Mediterranean Oak Forests

Coraebus florentinus (Herbst) is a wood borer beetle that damages the most abundant Quercus species making up the Mediterranean forests. Damage is due to the feeding activity of the larvae which cuts the sap flow into the branch where it develops, drying it. In the last decades, the geographical range and the damage records of this species have expanded northwardly as a result of the climate global change since warmer conditions favor higher reproduction and quicker development of this species. On this paper, historical series of data after ten years evaluating damages by C. florentinus in Hornachuelos Natural Park (Southern Spain) are analyzed under the perspective of the environmental temperature increase linked to the global climate change. The assessment was done between 2007 and 2017, in two sampling plots of Mediterranean mixed-oak forests where holm and cork oaks are the predominant tree species. Results show that the infestation levels of this species at the beginning of the assessment period were higher than those described previously in the nineties and that they increased progressively during the monitoring time. The results also agree with the expansion of its distribution areas noticed in other areas of Europe. The foreseeable rising of damages of C. florentinus is discussed, at greater scale, under the perspective of future scenery of environmental warming and oaks decaying by losing fitness due to higher soil aridity.

Long Term Application of a Vehicle-Based Health Monitoring System to Short and Medium Span Bridges and Damage Detection Sensitivity

Largest portion of the bridge stock in almost any country and bridge owning organisation consists on ordinary bridges that has short or medium spans and are now deteriorating due to aging, etc. Therefore, it is becoming an important social concern to develop and put to practical use simple and efficient health monitoring systems for existing short and medium span (10 - 30 m) bridges. In this paper, one practical solution to the problem for condition assessment of short and medium span bridges was discussed. A vehicle-based measurement with a public bus as part of a public transit system (called “Bus monitoring system”) has been developed to be capable of detecting damage that may affect the structural safety of a bridge from long term vibration measurement data collected while the vehicle (bus) crossed the target bridges. This paper systematically describes how the system has been developed. The bus monitoring system aims to detect the transition from the damage acceleration period, in which the structural safety of an aged bridge declines sharply, to the deterioration period by continually monitoring the bridge of interest. To evaluate the practicality of the newly developed bus monitoring system, it has been field-tested over a period of about four years by using an in-service fixed-route bus operating on a bus route in the city of Ube, Yamaguchi Prefecture, Japan. The verification results thus obtained are also described in this paper. This study also evaluates the sensitivity of “characteristic deflection”, which is a bridge (health) condition indicator used by the bus monitoring system, in damage detection. Sensitivity of “characteristic deflection” is verified by introducing artificial damage into a bridge that has ended its service life and is awaiting removal. As the results, it will be able to make a rational long-term health monitoring system for existing short and mediumspan bridges, and then the system helps bridge administrators to establish the rational maintenance strategies.

Fatigue damage reliability analysis for Nanjing Yangtze river bridge using structural health monitoring data

To evaluate the fatigue damage reliability of critical members of the Nanjing Yangtze river bridge, according to the stress-number curve and Miner’s rule, the corresponding expressions for calculating the structural fatigue damage reliability were derived. Fatigue damage reliability analysis of some critical members of the Nanjing Yangtze river bridge was carried out by using the strain-time histories measured by the structural health monitoring system of the bridge. The corresponding stress spectra were obtained by the real-time rain-flow counting method. Results of fatigue damage were calculated respectively by the reliability method at different reliability and compared with Miner’s rule. The results show that the fatigue damage of critical members of the Nanjing Yangtze river bridge is very small due to its low live-load stress level.

A Study on Health Monitoring of Structural Damages for Two Stories Model by Using Vibration Test

Many structures in Japan were built after the war at a revival term or rapid economic growth. These structures have been reached a life in recent years and it is economically not affordable to conduct repair and reconstruct these structures only with a possibility of being damaged. This paper presents an approach to detect the structural damages for two degrees of freedom (2DOF) model. In this study, we conducted Microtremor measurement, free vibration test and vibration test. The 2DOF model was demonstrated the feasibility of using the proposed approach to damage detection of structural member.

Automatic Damage Detection and Monitoring of a Stitch Laminate System Using a Fiber Bragg Grating Strain Sensor

There are numerous aspects and questions related to the use of composite materials for primary structures in aircraft where the structural integrity is the most important factor. This is especially true if the main concerns are that the material should have good reliability and durability for the primary structural application. Composite laminates are highly sensitive to out-of-plane failure due to their low inter laminar fracture toughness. An alternate method to increase the damage resistance is through three-dimensional fibrous reinforcement such as through-the-thickness stitching with a single fiber as the thread. Recent studies have shown that the stitching of standard laminates can enhance damage tolerance to levels obtainable with toughened resin systems. However, for next-generation aircraft, material improvement alone is not enough to assure or increase the safety and reliability of the structure. Continuous damage monitoring during operation will become an important issue in aircraft safety. Embed ding fiber Bragg grating (FBG) technology into the composite structure as strain sensors could potentially solve the above problem because the FBG can be used to detect and characterize the damage before it reaches a critical stage. The model used to represent this problem is a 6 × 6 Vectran stitched carbon/ epoxy laminate under tension loading, and the real-time monitoring using the FBG strain sensors is combined with acoustic emissions that were conducted during the test. A numerical laminate theory using a rebar element and first-ply failure criterion is performed to determine the preferred area on the specimen for the placement of the FBG before manufacturing and testing. Experiments are presented to determine the damage growth that was quantified with an ultrasonic (water immersion) c-scan. In this research, the FBG successfully detected and characterized the damage in the carbon/epoxy stitch laminate caused in tension loading cases. The FBG is enhanced with acoustic emission data and can quantitatively predict the damage growth.

Distribution characteristics and the evolution law of excavation damage zone in the large-span transition section of high-speed railway tunnel based on microseismic monitoring

Purpose–The microseismic monitoring technique has great advantages on identifying the location,extent and the mechanism of damage process occurring in rock mass.This study aims to analyze distribution characteristics and the evolution law of excavation damage zone of surrounding rock based on microseismic monitoring data.Design/methodology/approach–In situ test using microseismic monitoring technique is carried out in the large-span transition tunnel of Badaling Great Wall Station of Beijing-Zhangjiakou high-speed railway.An intelligent microseismic monitoring system is built with symmetry monitoring point layout both on the mountain surface and inside the tunnel to achieve three-dimensional and all-round monitoring results.Findings–Microseismic events can be divided into high density area,medium density area and low density area according to the density distribution of microseismic events.The positions where the cumulative distribution frequencies of microseismic events are 60 and 80%are identified as the boundaries between high and medium density areas and between medium and low density areas,respectively.The high density area of microseismic events is regarded as the high excavation damage zone of surrounding rock,which is affected by the grade of surrounding rock and the span of tunnel.The prediction formulas for the depth of high excavation damage zone of surrounding rock at different tunnel positions are given considering these two parameters.The scale of the average moment magnitude parameters of microseismic events is adopted to describe the damage degree of surrounding rock.The strong positive correlation and multistage characteristics between the depth of excavation damage zone and deformation of surrounding rock are revealed.Based on the depth of high excavation damage zone of surrounding rock,the prestressed anchor cable(rod)is designed,and the safety of anchor cable(rod)design parameters is verified by the deformation results of surrounding rock.Originality/value–The research provides a new method to predict the surrounding rock damage zone of large-span tunnel and also provides a reference basis for design parameters of prestressed anchor cable(rod).

Using DNA damage to monitor water environment

DNA damage of aquatic organisms living in polluted environments can be used as a biomarker of the genotoxicity of toxic agents to organisms. This technique has been playing an important role in ecotoxi- cological study and environmental risk assessment. In this article, main types of DNA damage caused by pollut- ants in water environments were reviewed; methods of detecting DNA damage were also documented for water environmental monitoring.

Output only modal identification and structural damage detection using time frequency & wavelet techniques

The primary objective of this paper is to develop output only modal identification and structural damage detection. Identification of multi-degree of freedom （MDOF） linear time invariant （LTI） and linear time variant （LTV--due to damage） systems based on Time-frequency （TF） techniques--such as short-time Fourier transform （STFT）, empirical mode decomposition （EMD）, and wavelets--is proposed. STFT, EMD, and wavelet methods developed to date are reviewed in detail. In addition a Hilbert transform （HT） approach to determine frequency and damping is also presented. In this paper, STFT, EMD, HT and wavelet techniques are developed for decomposition of free vibration response of MDOF systems into their modal components. Once the modal components are obtained, each one is processed using Hilbert transform to obtain the modal frequency and damping ratios. In addition, the ratio of modal components at different degrees of freedom facilitate determination of mode shape. In cases with output only modal identification using ambient/random response, the random decrement technique is used to obtain free vibration response. The advantage of TF techniques is that they arc signal based; hence, can be used for output only modal identification. A three degree of freedom 1：10 scale model test structure is used to validate the proposed output only modal identification techniques based on STFT, EMD, HT, wavelets. Both measured free vibration and forced vibration （white noise） response are considered. The secondary objective of this paper is to show the relative ease with which the TF techniques can be used for modal identification and their potential for real world applications where output only identification is essential. Recorded ambient vibration data processed using techniques such as the random decrement technique can be used to obtain the free vibration response, so that further processing using TF based modal identification can be performed.

Simulation experiment of AE-based localization damage and deformation characteristic on covering rock in mined-out area

The localization damage and deformation characteristics of multiple rock in mined-out area under thick soil layer were investigated by acoustic emission （AE）-based physical similar simulation experiment and damage test combined with the AE theory on rock damage. During different mining courses, the degree of wall rock suffered from mining disturbed process in mined-out area was different, so did the AE density of initial damage and fracture. Some characteristic parameters, including large events, total events, and energy rate, presented fluctuations with temporal and spatial change and take on a certain extent statistic relation. Subsequently, the percent of damage degree was defined and divided into 4 stages, and the localization damage and deformation characteristics of surrounding rock in mined-out area and coal pillars were analyzed quantitatively.

DAMAGE DETECTION IN STRUCTURES USING MODIFIED BACK-PROPAGATION NEURAL NETWORKS

A nonparametric structural damage detection methodology based on neuralnetworks method is presented for health monitoring of structure-unknown systems. In this approachappropriate neural networks are trained by use of the modal test data from a 'healthy' structure.The trained networks which are subsequently fed with vibration measurements from the same structurein different stages have the capability of recognizing the location and the content of structuraldamage and thereby can monitor the health of the structure. A modified back-propagation neuralnetwork is proposed to solve the two practical problems encountered by the traditionalback-propagation method, i.e., slow learning progress and convergence to a false local minimum.Various training algorithms, types of the input layer and numbers of the nodes in the input layerare considered. Numerical example results from a 5-degree-of-freedom spring-mass structure andanalyses on the experimental data of an actual 5-storey-steel-frame demonstrate thatneural-networks-based method is a robust procedure and a practical tool for the detection ofstructural damage, and that the modified back-propagation algorithm could improve the computationalefficiency as well as the accuracy of detection.

EXPERIMENTAL RESEARCH ON EVALUATING STRUCTURE DAMAGE WITH PIEZOELECTRIC DYNAMIC IMPEDANCE

A dynamic impedance-based structural health monitoring technique isintroduced. According to the direct and the converse piezoelectric property of piezoelectricmaterials, the piezoceramic (PZT) can be used as an actuator and a sensor synchronously. If damageslike cracks, holes, debonding or loose connections are presented in the structure, the physicalvariations of the structure will cause the mechanical impedance modified. On the basis ofintroducing the principle and the theory, the experiment and the analysis on some damages of thestructure are studied by means of the dynamic impedance technique. On the view of experiment, kindsof structural damages are evaluated by the information of dynamic impedance in order to validate thefeasibility of the method.