Damage In Structural Components Research Articles

Comparison on seismic resilience of hybrid, isolation, and damping control reinforced concrete frame-shear wall buildings

To investigate the effectiveness of different vibration control methods in realizing seismic resilience of reinforced concrete (RC) frame-shear wall structures, four cases with different control methods were designed, including the damping control building using energy dissipation cladding panels (EDCPs) (RCFSW7-D), isolated building (RCFSW7-I), isolated building with enhanced stiffness of superstructure (RCFSW7.5-I), and hybrid control building using both EDCPs and isolation (RCFSW7-H). The critical seismic responses and resilient performance of four cases were analyzed based on the Chinese code. Maximum inter-story drift ratios (MIDRs) of RCFSW7-I, RCFSW7.5-I, and RCFSW7-H under maximum considered earthquake were 36%, 51%, and 72% lower than that of RCFSW7-D, respectively. Although the stiffness of superstructure of RCFSW7.5-I and RCFSW7-H were approximately identical, the MIDR of RCFSW7-H was 44% smaller than that of RCFSW7.5-I. Meanwhile, the maximum absolute floor accelerations (MAFAs) of three isolated structure under MCE were approximately 70% lower than that of RCFSW7-D. The seismic resilience level of RCFSW7-D was Level 1, which is dominated by the damage of structural components (SCs) controlled by MIDR and acceleration-sensitive non-structural components (ASNSCs) controlled by MAFA. The seismic resilience levels of RCFSW7-I and RCFSW7.5-I successfully increased to Level 2, leading by the effectively control of MAFA and damage of ASNSCs. However, the MIDR was not sufficiently controlled even the stiffness of superstructure was increased. In contrast, hybrid control building significantly reduced both the MIDR and MAFA through the currently utilization of seismic isolation and EDCPs, especially the MIDR and damage of SCs, leading to a seismic resilience level of Level 3.

Dynamic characteristics identification of RC beams subjected to impact damage

Structural dynamic characteristics are essential parameters for detecting structural damage. This study conducted impact and static loading tests on six reinforced concrete (RC) beams, and the plastic energy dissipation of the reinforced concrete beams under both loading conditions is be essentially consistent. The random decrement technique and Hilbert-Huang transform (RDT-HHT) combined approach is used to identify the first three mode dynamic characteristics (frequency and damping ratio) of impact-damaged reinforced concrete beams. An approach based on finite element (FE) plastic damage distribution is proposed to obtain the continuous flexural stiffness of damaged reinforced concrete beams. Both the global stiffness and Rayleigh method are used to predict the natural frequency. The results show that the first three mode frequencies of the damaged reinforced concrete beams decrease, whereas their damping ratios increase. Specifically, the first mode frequency reduction of reinforced concrete beams under impact damage is slightly lower than that under static damage, while the second and third mode frequencies exhibited a greater decrease. The increase in damping of the damaged reinforced concrete beams is mainly related to the damage extent, damage distribution, and damage location. Furthermore, the first and third mode damping ratios of reinforced concrete beams increase more significantly than the second mode damping ratio after damage, primarily because the most severe damage occurred at the location (mid-span) with the maximum curvature of the first and third mode modal shapes. Due to the more concentrated distribution and more severe local damage of impact damaged reinforced concrete beam, the increase in the first and third mode damping ratios after impact damage is more pronounced compared to static damage. The global stiffness method overestimates the frequency of damaged reinforced concrete beams. Whereas the Rayleigh method utilizes a reasonable first mode modal shape function and the continuous flexural stiffness to predict the structural frequency after damage, the first mode frequency predicts after damage with an error of less than 3%. It is recommended to consider changes in both frequency and damping to assess the extent of impact damage in structural components.

Global response of reinforced concrete framed building under varying blast load pulse shapes

Reinforced concrete buildings subjected to explosive loading and their subsequent effects have become a subject of attention in the past few years due to extensive loss of life and severe structural damage. An explosion can occur with various random pressure–time histories known as pulse shapes and these pulse-loading shapes are expected to have significant influence on the dynamic response of structures. This study investigates the response and extent of damage in reinforced concrete framed building under varying blast load pulse shapes. The research involves three major objectives as quantification of blast load and formation of varying pulse shapes, numerical modelling of reinforced concrete building (bare and masonry infilled) with application of blast loads using finite element method and global response evaluation by nonlinear time history analysis. Generally, masonry infill walls are treated as non-structural elements and often ignored in structural analysis and design. This study includes investigating the effect of masonry infill only in the in-plane direction of blast loads with varying pulse shapes. Results show significant damage particularly on the front façade due to concave and half-cycle sine shaped blast pulse shapes. At the same time, the in-plane strength and stiffness of masonry infills have significantly reduced the overall damage in structural components.

Nonlinear ultrasound to characterize dislocation-based damage in classical and rolling contact fatigue

Material damage in structural components is driven by nano- and micro-scale defects that evolve early in the component’s life. In metals, the interaction of an ultrasonic wave with these nano- and micro-structural defects, such as dislocations, precipitates, and micro-cracks, generates a second harmonic wave that is proportional to the acoustic nonlinearity parameter, which is an absolute and measurable material parameter. These defects are known to cause measurable changes in the nonlinearity parameter, which changes as the nano- and micro-structural defects evolve in the material. This talk will discuss how nonlinear ultrasound (NLU) techniques that measure the nonlinearity parameter can be used as a nondestructive evaluation tool to characterize dislocation-based damage in metals, and thus characterize early-stage damage. Our group’s recent work on using NLU to characterize different types of cyclic loading, classical fatigue and rolling contact fatigue, will be discussed. Specifically, ultrasonic measurements are related directly to materials characterizations on similar length scales to better understand the relationship between the nonlinearity parameter and the dislocation-based damage evolution.

Motorcycle Structural Fatigue Monitoring Using Smart Wheels

The paper is devoted to the measurement and to the processing of load spectra of forces and moments acting at the wheel hub of a motorcycle. Smart wheels (SWs) have been specifically developed for the scope. Throughout the paper, the extreme case of a race motorcycle is considered. Accurate load spectra were measured in two race circuits. Standardized load spectra are derived by processing measured data. A way to easily generalize the measured load spectra is proposed for the first time for motorcycles. Several loading conditions, related to the motorcycle straight line motion, cornering, curb hit and gear shift, are identified and extracted from the experimental measures. For each loading condition, by means of simple semi-analytical models (SAMs), a relationship is found between the vertical force on the wheel, the tilt angle of the motorcycle and the remaining forces and moments acting at the wheel hub. Such relationships are nothing else than the standardized load spectra. Additionally, a simple and efficient method based on smart wheels for real-time structural monitoring is proposed. Standardized load spectra prove to provide consistent results even when compared to real-time structural monitoring data. By means of the presented smart wheels, advanced lightweight motorcycle construction is enabled by derivation of standardized load spectra or real time estimation of the damage of structural components.

The influence of trampling disturbance on the fluorescence and pigment concentration of Sargassum beds (Fucales)

Direct and indirect effects on ecological processes caused by natural and anthropogenic disturbances may alter the composition and relative abundance of marine benthic communities. Trampling is a source of impact that can lead to the removal of individuals, breakage or damage of structural components and alterations of physiological performance of sessile organisms, possibly affecting the population dynamics and indirectly promoting structural changes in the entire community. To better support management strategies for coastal environments and to evaluate the anthropogenic impacts on a seaweed bed dominated by species of the genus Sargassum inhabiting the subtidal rocky shores in southeastern Brazil, we used an experimental approach to assess the physiological responses of this seaweed to trampling. We applied different intensities of trampling expected during summer vacation and throughout different periods of the year and quantified the fluorescence and pigment concentration of Sargassum beds. Changes caused by trampling are reflected in the health status of Sargassum, showing a decrease in chlorophyll a fluorescence and concentration of photosynthetic pigments depending on the site where this kind of impact occurs.

Automated crack detection in conductive smart-concrete structures using a resistor mesh model

Various nondestructive evaluation techniques are currently used to automatically detect and monitor cracks in concrete infrastructure. However, these methods often lack the scalability and cost-effectiveness over large geometries. A solution is the use of self-sensing carbon-doped cementitious materials. These self-sensing materials are capable of providing a measurable change in electrical output that can be related to their damage state. Previous work by the authors showed that a resistor mesh model could be used to track damage in structural components fabricated from electrically conductive concrete, where damage was located through the identification of high resistance value resistors in a resistor mesh model. In this work, an automated damage detection strategy that works through placing high value resistors into the previously developed resistor mesh model using a sequential Monte Carlo method is introduced. Here, high value resistors are used to mimic the internal condition of damaged cementitious specimens. The proposed automated damage detection method is experimentally validated using a mm3 reinforced cement paste plate doped with multi-walled carbon nanotubes exposed to 100 identical impact tests. Results demonstrate that the proposed Monte Carlo method is capable of detecting and localizing the most prominent damage in a structure, demonstrating that automated damage detection in smart-concrete structures is a promising strategy for real-time structural health monitoring of civil infrastructure.

Acoustic Emission Detection and Characterisation Using Networked FBG Sensors

Acoustic Emission (AE) events are often generated when a material undergoes irreversible changes to its internal structure and thus provides a basis for the detection of damage in structural components. A method for AE localisation featuring a single laser source coupled to three optical fibre Bragg grating sensors is described and experimentally demonstrated on a thin aluminium panel. The localisation algorithm analyses the time domain waveform and the corresponding frequency spectrum to determine the time of arrival and velocity of an AE signal from which its epicentre is estimated using a grid search. Experimental results are shown to demonstrate the accuracy of the method.

Основы криобиологии рака предстательной железы

The basis of cryotherapy was laid in the middle of the 19th century; today it is actively developing, minimally invasive and alternative method of prostate cancer treatment. The effectiveness of cryosurgery of the tissues depends on the quality of visualization of the process, of fast freezing and slow process of thawing, and also of repeating of the freeze-thaw cycles. The main factors that have a damaging effect on the tissue under the influence of low temperatures are: formation of intracellular and extracellular ice crystals, increase of the concentration of electrolytes and mechanical damage of structural components of cells. Studies have shown that the temperature below -40°С is lethal to cancer cells. The possibility of real-time visual control gives us the ability to control the process freezing and thawing.

Study on Dynamic Responses and Reinforcement of Reinforced Concrete Columns Subjected to Blast Loading

The terrorism and regional conflicts posed a threat to the world peace. Some terrorist explosions caused collapse of the buildings, which brought heavy tragedies to the human components. Therefore research on damage of structural components and resistance to damage have become the focus of our attention. Finite element software LS-DYNA was applied to simulating the response of reinforced concrete columns under blast loading. And analysis on dynamic response under different loading period was carried out. By studying on the stress and strain of reinforced concrete columns subjected to blast loading, the possible failure modes were obtained. In addition, the bearing capacities of concrete columns that are reinforced with carbon fiber and steel panel were analyzed, and the reinforcement effects were compared to provide reasonable reinforcement schemes for structures blast-resistant design.

Carbon nanotube coated paper sensor for damage diagnosis.

A carbon nanotube coated paper sensor has been developed for the detection of damages in structural components. Electrical resistance tomography is used to measure changes in electrical potential at various locations induced by applying a small electrical current to the sample. The spatial locations and magnitudes of multiple damages are predicted accurately with a sensitivity of 73 ppm in sensing area. The detection limit of the sensor is estimated to be 29 ppm in sensing area, which is at least 30 times better in sensitivity than previous results (0.1-0.65%) in the literature.

A Computational Nondestructive Evaluation Algorithm Combining Self-Evolving Parameterization and Multi-Objective Optimization for Quantitative Damage Characterization

A self-evolving parameterization approach for nondestructive evaluation (NDE) of damage in structural components is presented and numerically evaluated. Focused herein on problems relating to characterizing an unknown quantity of localized changes in properties, the adaptive approach utilizes the substantial solution diversity that is uniquely provided by multi-objective optimization to iteratively build up the parameterization and accurately characterize all localized property changes with the minimum dimensional parameterization. Through simulated test problems based on the characterization of damage within plates, the NDE approach with self-evolving parameterization is shown to provide an accurate and efficient process for the solution of inverse characterization problems.

An adaptive learning damage estimation method for structural health monitoring

Structural health monitoring is an important problem of interest in many civil infrastructure and aerospace applications. In the last few decades, many techniques have been investigated to address the detection, estimation, and classification of damage in structural components. One of the key challenges in the development of real-world damage identification systems, however, is variability due to changing environmental and operational conditions. Conventional statistical methods based on static modeling frameworks can prove to be inadequate in a dynamic and fast changing environment, especially when a sufficient amount of data is not available. In this paper, a novel adaptive learning structural damage estimation method is proposed in which the stochastic models are allowed to perpetually change with the time-varying conditions. The adaptive learning framework is based on the use of Dirichlet process (DP) mixture models, which provide the capability of automatically adjusting to structure within the data. Specifically, time–frequency features are extracted from periodically collected structural data (measured sensor signals), that are responses to ultrasonic excitation of the material. These are then modeled using a DP mixture model that allows for a growing, possibly infinite, number of mixture components or latent clusters. Combined with input from physically based damage growth models, the adaptively identified clusters are used in a state-space setting to effectively estimate damage states within the structure under varying external conditions. Additionally, a data selection methodology is implemented to enable judicious selection of informative measurements for maximum performance. The utility of the proposed algorithm is demonstrated by application to the estimation of fatigue-induced damage in an aluminum compact tension sample subjected to variable-amplitude cyclic loading.

α-stable distributions for better performance of ACO in detecting damage on not well spaced frequency systems

In this paper, the Ant Colony Optimization (ACO) algorithm is modified through α-stable Lévy variables and applied to the identification of incipient damage in structural components. The main feature of the proposed optimization is an improved ability, which derives from the heavy tails of the stable random variable, to escape from local minima. This aspect is relevant since the objective function used for damage detection may have many local minima which render very challenging the search of the global minimum corresponding to the damage parameter. As the optimization is performed on the structural response and does not require the extraction of modal components, the method is particularly relevant for structures with not-well spaced natural frequencies.

Assessment of multi-objective optimization for nondestructive evaluation of damage in structural components

A multi-objective optimization-based computational approach to nondestructive evaluation of damage in structural components, and more generally in solid continua, is discussed and numerically evaluated. The multi-objective approach provides a substantial improvement in the capabilities to traverse the optimization search space to minimize the measurement error and produce accurate damage estimates. Through simulated test problems based on the characterization of damage in structural steel components, including internal pipe surface geometry as well as material loss within a plate structure utilizing steady-state dynamic measurements of outer surface displacement, a multi-objective genetic algorithm optimization approach is shown to provide substantial computational improvement over single-objective strategies. The multi-objective approach consistently and efficiently produces more accurate characterization results in contrast to equivalent single-objective strategies. More importantly, the multi-objective approach is shown to exhibit consistently better tolerance to test measurement noise and measurement sparsity. Moreover, the multi-objective strategy was found to provide improved diversity in the solution estimates for ill-posed problems, which is an important step leading to insight into the necessary changes to the testing or parameterization to subsequently produce more accurate and unique solutions to such inverse characterization problems.

A multi-scale pseudo-force model in wavelet domain for identification of damage in structural components

Damage identification using wavelet-transform (WT)-processed vibration signals has been practiced over the years. In most studies, WT was used as an effective signal analysis tool to filter out noise and bring damage-incurred singularities into prominence. In spite of its proven effectiveness, such a processing is often carried out without theoretical footstones sustained by solid mechanics models, which are able to link characteristics of WT with features of damage. In the present work, a multi-scale pseudo-force model over wavelet domain was developed for vibration-based damage identification. By canvassing damage-caused local perturbance to dynamic equilibrium characteristics of a structural component, the underlying hypostasis of the model has explicit physical implication, addressing features of damage (e.g., a slot or a fine crack) and enabling a sophisticated solution to multi-scale modeling and identification of damage. In the model, WT was used as a multi-scale differential operator to acquire higher-order derivatives of equation of motion for characterizing damage of tiny dimension. The multi-scale nature brings additional benefits to enhance robustness of the detection under noisy measurement conditions. Without loss of generality, an Euler–Bernoulli beam component (EBC) was considered to facilitate understanding of the principle of the model. As proof-of-concept validation, a fine crack in an EBC was quantified using the model through numerical simulation and experiment. Satisfactory results have demonstrated the effectiveness of the model in evaluating fine damage and enhancing tolerance of the detection to measurement noise.

Integrity assessment of high pressure steam turbine casing

The assessment of creep-fatigue damage in structural components has recently become important due to economically forced needs to extend the remaining life of power plants that have been in operation for 30 – 40 years. The extension methodology determining the reliability and safety of power stations is usually based on a combination of the plant operating history data with in-service/in-situ material damage evaluation. This paper describes an application of the accumulated operational damage assessment methodology for the example of a high pressure steam turbine casing analysis.

Determination of the behaviour factor of steel moment-resisting (MR) frames by a damage accumulation approach

In most countries, seismic codes are changing, reflecting a new design philosophy based on multiple performance levels. A procedure that defines behaviour factors to reduce the elastic spectrum for different types of structures, considering all possible types of failure, is needed. The paper presents a method for the definition of the behaviour factor ( q -factor) for multi-storey steel frames, accounting for cumulative damage in structural components, by means of linear elastic time history analysis, of the Palmgren–Miner rule and of S – N (constant stress or strain range versus number of cycles to failure) curves extrapolated in the low-cycle fatigue range. This technique has been verified by a non-linear procedure that is different from the previous one, as a non-linear time history analysis with damage control has been performed instead of a linear one. The proposed approach can be useful in performance based design, since the linear procedure allows the definition of the q -factor corresponding to different level of damage or collapse prevention.

Post-earthquake loss assessment based on structural component damage inspection for residential RC buildings

There is substantial evidence showing that the seismic performance of many existing buildings may be inadequate to resist another strong earthquake. The losses from a devastating earthquake are always huge. In order to prevent damage extension and to restore the damaged community as quickly as possible, immediate post-earthquake damage assessment is always conducted through site inspection on structural components within a restricted short period of time to screen buildings that are damaged to certain levels or in danger of collapse. Without detail financial loss estimation, engineers have to face the challenge to decide whether a badly damaged building is worth retrofitting for sustainability, or needs to be demolished because existing loss estimation models are not based on the post-earthquake damage rating system. Based on some post-earthquake damage data of RC residential buildings, this paper aims to link inspected component damage level, building damage state and direct financial loss in terms of repair to replacement cost ratio. Damage of structural components are quantified by a set of damage factors and finally integrated as a building damage indicator. Building repair to replacement cost ratio and storey repair to replacement cost ratio corresponding to various damage levels of RC residential buildings have been estimated. With these statistical data, relationships of building damage indicator to repair to replacement cost ratio has been built from regression analysis.

Multi‐scale system reliability analysis of lifeline networks under earthquake hazards

AbstractRecent earthquake events evidenced that damage of structural components in a lifeline network may cause prolonged disruption of lifeline services, which eventually results in significant socio‐economic losses in the affected area. Despite recent advances in network reliability analysis, the complexity of the problem and various uncertainties still make it a challenging task to evaluate the post‐hazard performance and connectivity of lifeline networks efficiently and accurately. In order to overcome such challenges and take advantage of merits of multi‐scale analysis, this paper develops a multi‐scale system reliability analysis method by integrating a network decomposition approach with the matrix‐based system reliability (MSR) method. In addition to facilitating system reliability analysis of large‐size networks, the multi‐scale approach enables optimizing the level of computational effort on subsystems; identifying the relative importance of components and subsystems at multiple scales; and providing a collaborative risk management framework. The MSR method is uniformly applied for system reliability analyses at both the lower‐scale (for link failure) and the higher‐scale (for system connectivity) to obtain the probability of general system events, various conditional probabilities, component importance measures, statistical correlation between subsystem failures and parameter sensitivities. The proposed multi‐scale analysis method is demonstrated by its application to a gas distribution network in Shelby County of Tennessee. A parametric study is performed to determine the number of segments during the lower‐scale MSR analysis of each pipeline based on the strength of the spatial correlation of seismic intensity. It is shown that the spatial correlation should be considered at both scales for accurate reliability evaluation. The proposed multi‐scale analysis approach provides an effective framework of risk assessment and decision support for lifeline networks under earthquake hazards. Copyright © 2009 John Wiley & Sons, Ltd.