Stiffness Reduction Factor Research Articles

Comparative Analysis of Measurement Points for Structural Damage Identification in Free-Free Aluminium Beam using Response Surface Methodology and FRF Curvature

This research paper presents a comprehensive comparative analysis of measurement points for structural damage identification in free-free aluminium beams using Response Surface Methodology (RSM) and Frequency Response Function (FRF) curvature. The primary objective is to determine the optimal measurement points for establishing a relationship between the input parameters and response features, thus forming a surrogate model. The investigation focuses on analyzing the influence of the number of measurement points on RSM's capability to identify structural damage. Three distinct Design of Experiment (DOE) techniques are explored: central composite design (CCD), Box-Behnken design (BBD), and D-optimal design, each incorporating different numbers of measurement points (10 elements, 15 elements, and 20 elements). The study's results highlight BBD's strong capability in detecting damage with fewer measurement points, while CCD design accurately identifies damage in finer measurement points. The findings reveal a clear trend: as the number of measurement points increases, the model becomes more refined, yielding higher stiffness reduction factor (SRF) values. The results underscore the significance of selecting an appropriate number of measurement points to enhance RSM's efficiency in identifying structural damage, thereby optimizing damage identification processes. This study contributes valuable insights into the selection of measurement points for effective structural damage identification, offering practical implications for engineering applications.

Wind-related structural stiffness and stiffness reduction factors

One of the most important parts of a building is its columns. When columns are destroyed, it can lead to the destruction of other structures or be the major cause of the destruction of the whole structure. Building stiffness is a very important factor when looking at how structures behave because it affects how buildings vibrate and, by extension, how much horizontal wind they can handle. It is possible to be more specific about how to plan high-rise buildings that are subject to wind loads by looking at how buildings behave when their structural stiffness decreases. The objective of the study is to investigate through the effects if reinforced concrete buildings reduce stiffness and how that changes how wind affects the structure. The author of this study looks at how reinforced concrete high-rise buildings behave. The results will be used to look at changes in the horizontal displacements and internal forces in buildings so that project design suggestions can be made.

Damage inference and residual capacity assessment for an E-Defense 2018 ten-story RC test structure

This paper presents an enhanced vision-based, post-earthquake performance assessment framework for RC building structures. This framework incorporates a damage inference method that can estimate the stiffness and strength reduction factors of components in stories without damage inspection based on the inter-story drift. The framework was validated by the application to the full-scale shaking table test of an E-Defense 2018 ten-story RC structure. The vision-based damage detection method effectively detected multicategory seismic damage on the component surfaces, and the damage states estimated by the vision-based method were consistent with the results estimated by the measured plastic hinge rotation. The proposed inter-story drift-based damage inference method reasonably estimated the reduction factors of components in the stories without damage photos. The numerical model updated by the reduction factors of damaged components provided accurate estimates of the fundamental vibrational frequencies after different levels of seismic shaking, and the drift-based inference method significantly improved the results compared with the trivial linear interpolation method. The residual capacity curves provided by pushover analysis of the updated model using the reduction factors as per FEMA 306 & Chiu et al. reasonably captured the hysteretic responses of the structure.

Experimental investigation of the damage characteristics and seismic response of moment-resisting bolted column base joints for precast concrete frames

Although several studies have been carried out on the development of bolted dry joints for precast concrete structures, damage assessment and seismic performance of bolted dry joints for column base joints under the different axial compression ratios have been rarely studied. In this study, six half-scale reinforced concrete columns, half of them were bolted connected and others were monotonically connected to the foundation, are subjected to combined cyclic lateral load and static axial compression load. The tests were carried out under three axial compression ratios: 0.10, 0.20, and 0.30. The seismic performances, including failure modes, lateral load-displacement responses, displacement ductilities, energy dissipation capacities, stiffness degradation behaviors, and moment-curvature responses, were evaluated and compared. The influence of axial compression ratio and reinforcement details on the seismic performance, plastic hinge characteristics, and damage assessment of specimens was also investigated in detail. The experiment results show that the increase of axial compression ratio from 0.1 to 0.3 increased the lateral load capacity, secant stiffness, and plastic hinge length while reducing the ductility. The efficiency of current formulations to predict plastic hinge length for the determination of plastic hinge length of specimens was also compared. Proposed damage descriptions for different performance levels (or damage states) were summarized and observed damage states correlated with drift ratio demands. Some modifications to the Park and Ang damage index for each damage state were proposed and stiffness reduction factors for the damage states were comparatively investigated. In addition, the displacement-based seismic capacities of this novel RC column base connection are presented in detail.

Wind-Related Structural Stiffness and Stiffness Reduction Factors

One of the most important parts of a building is its columns. When columns are destroyed, it can lead to the destruction of other structures or be the major cause of the destruction of the whole structure. Building stiffness is a very important factor when looking at how structures behave because it affects how buildings vibrate and, by extension, how much horizontal wind they can handle. It is possible to be more specific about how to plan high-rise buildings that are subject to wind loads by looking at how buildings behave when their structural stiffness decreases. The objective of the study is to investigate through the effects if reinforced concrete buildings reduce stiffness and how that changes how wind affects the structure. The author of this study looks at how reinforced concrete high-rise buildings behave. The results will be used to look at changes in the horizontal displacements and internal forces in buildings so that project design suggestions can be made.

Estimation of effective rigidity in reinforced concrete structures through modal identification tests and sclerometry

It is currently known that the structural elements of a building can crack due to structural failures under service loads, due to frequent low-intensity earthquakes or during the first moments of a severe earthquake, which could result in cracked sections when the action of the earthquake occurs. of maximum intensity, for such considerations, the Peruvian norm of seismic analysis does not contemplate cracked sections for seismic analysis. The purpose of this study was to estimate the effective stiffness factors of 4 reinforced concrete buildings. The research has a quantitative approach of non-experimental design, the sample is made up of 4 reinforced concrete buildings in the city of Juliaca, to which sclerometry and modal identification tests were carried out with X16 - 1D sensors to obtain compressive strength. and natural periods of field vibration respectively. Numerical models were obtained with their real concrete resistance considering the existing partitions, to which stiffness reduction factors will be applied using international codes and iterations to approximate their natural periods to the natural periods obtained by modal identification. The results show that there is a difference in natural periods of vibration between the numerical model with real resistances considering the effects of the partitioning and those obtained with modal identification tests in a range of 5 % to 30 %, which shows that the fundamental period field vibration is greater than projected.

Simplified Method for Nonlinear Seismic Response Analysis of Corroded Pile-Supported Wharf

Fiber-based finite element analysis (FB-FEA) has been widely recognized for its ability to reproduce experimental results and is also a reliable method for evaluating the nonlinear seismic response of pile-supported wharves (PSWs). Design practice often employs frame analysis (FA) due to its easy implementation. To precisely reproduce the nonlinear seismic response of PSW using FA, it is necessary to configure mechanical properties such as the hinge property correctly. However, it is unclear whether the hinge properties proposed in previous studies can be applied to PSWs with spun piles. In this study, a novel FA method was developed to investigate the nonlinear seismic response of PSWs with corroded spun piles considering PC bar area reduction, deteriorated material properties, the bending stiffness reduction factor, and the moment–curvature relationship of the spun pile. The nonlinear seismic response of corroded PSWs was determined by performing pushover analysis using three methods: FA using the method of the previous study (FA-1), the proposed FA method (FA-2), and FB-FEA. As regards PSW foundations, vertical pile and batter pile configurations were considered. The pushover analysis results were compared in terms of several parameters, such as the natural period, plastic hinge formation, and load capacity of the corroded PSWs. The FA-2 results agreed very well with the FB-FEA results, while the FA-1 results were less precise with respect to the natural periods and load capacities of corroded PSWs. The results indicated that the bending stiffness reduction factor, moment–curvature relationship, and axial load–bending moment (P–M) capacity of the corroded spun piles should be appropriately defined. Corrosion had greater negative impacts on the compressive axial load and bending moment capacities of the spun pile than on its tensile axial load capacity.

The Reduction Factor of Pultrude Glass Fibre-Reinforced Polyester Composite Cross-Arm: A Comparative Study on Mathematical Modelling for Life-Span Prediction.

This paper presents an experimental and numerical investigation of pultruded composite glass fibre-reinforced polymer (pGFRP) cross-arms subjected to flexural creep behaviour to assess their performance and sustainability in composite cross-arm structure applications. The primary objective of this study was to investigate the failure creep behaviour of pGFRP cross-arms with different stacking sequences. Specifically, the study aimed to understand the variations in strain rate exhibited during different stages of the creep process. Therefore, this study emphasizes a simplified approach within the experiment, numerical analysis, and mathematical modelling of three different pGFRP composites to estimate the stiffness reduction factors that determine the prediction of failure. The findings show that Findley's power law and the Burger model projected very different strains and diverged noticeably outside the testing period. Findley's model estimated a minimal increase in total strain over 50 years, while the Burger model anticipated PS-1 and PS-2 composites would fail within about 11 and 33 years, respectively. The Burger model's forecasts might be more reasonable due to the harsh environment the cross-arms are expected to withstand. The endurance and long-term performance of composite materials used in overhead power transmission lines may be predicted mathematically, and this insight into material property factors can help with design and maintenance.

Analysis of Corneal Biomechanical Properties in Different Keratotopographic Patterns of Keratoconus.

To analyze the frequency of main keratotopographic patterns at the 1st, 2nd, and 3rd stages of keratoconus and investigate corneal biomechanical properties across different patterns. The study comprised two stages. The first stage was computational-experimental, where we utilized COMSOL Multiphysics® software (COMSOL AB, Stockholm, Sweden) to mathematically model corneal mechanical behavior under intraocular pressure and pulsed air jet action in both normal and keratoconic conditions. The second stage was the clinical phase, during which we retrospectively analyzed the examination results of both healthy subjects and patients with keratoconus. In total, the study included 256 eyes (256 subjects). Among them, 174 eyes (174 healthy individuals) had normal corneas with different refractions, and 82 eyes (82 individuals) had stages 1, 2, and 3 of keratoconus based on Amsler-Krumeich classification. The keratotopographic characteristics of the participants were assessed using Sirius (Schwind, Germany) and Pentacam AXL (OCULUS Optikgeräte GmbH, Germany) keratotomographs, while the corneal biomechanical properties were studied using noncontact tonometry with the Corvis ST device (OCULUS Optikgeräte GmbH, Germany). The study focused on evaluating corneal stiffness index values in the central optical zone under various keratotopographic patterns. In addition, it compared the elastic coefficient values c1, c2, and c3 for the model of hyperelastic behavior of corneal material outside the keratoconus zone. Furthermore, the study examined the values of reduced stiffness zone characteristics, including the stiffness reduction factor ψmax, effective radius Rk, and the ratio of maximum and minimum strain intensity in keratoconus of different stages. The mean age of the patients in the study was 30.16 ± 8.31 years, with 166 men and 90 women participating. The study revealed typical keratotopographic patterns in the examined keratoconus stages, as well as their occurrence frequency. In the 1st stage of keratoconus, the pattern of asymmetric astigmatism was noted more frequently (in 75% of cases). In the 2nd stage, the pattern with an ectasia zone in the lower cornea was observed in 80% of cases, and in the 3rd stage, a centrally located keratotopographic ectasia pattern was found in 42% of cases. Comparative analysis showed that the greatest decrease in stiffness parameter (SpA1) and stress-strain index occurred in the central pattern (by 64% and 46%, respectively), while the least decrease was observed in local corneal radius reduction in the lower cornea (by 42% and 33%, respectively). The decrease in strength properties in keratoconus occurs in a local area, the size and degree of which are determined by the disease stage. The indicated biomechanical parameters are consistent regardless of the shape and localization of keratotopographic patterns but are relevant to diagnostic specifications using the Corvis ST pneumotonometer, which assesses corneal properties in the apical zone.

Structural modal identification and damage detection with incomplete data utilized by genetic algorithm optimization

This research presented a procedure to automatically identify the modal characteristics of structures to detect and quantify any localized damage of structures in frequency domain. This process uses the acceleration frequency response of the selected degree of freedoms, some natural frequency of the damaged structure and mode shapes of the undamaged Finite Element (FE) model to identify the structural stiffness of the damaged structure containing the damping ratio. The incomplete data in the unmeasured degree of freedom will be updated using a genetic optimization algorithm. The accuracy and efficiency of the proposed method have been tested on a 25 elements truss subjected to a harmonic load with sweep frequency. Optimization results demonstrated that the proposed method is capable of precisely identifying the modal characteristics and stiffness reduction factor of the damaged structure using genetic optimization algorithm along with 5% noise in the input force and response of the system in all studied cases.

EESD special issue: AI and data‐driven methods in earthquake engineering – (Part 1)

EESD special issue: AI and data‐driven methods in earthquake engineering – (Part 1)

Application of Machine Learning to predict the mechanical properties of high strength steel at elevated temperatures based on the chemical composition

This paper presents the results obtained using Machine Learning (ML) algorithms to predict the mechanical properties, including ultimate tensile strength, yield strength, 0.2% proof strength and elastic modulus, of high strength steel plate material at elevated temperatures. High strength steels are increasingly used in several areas of construction offering efficient structural solutions with a high strength-to-weight ratio. Safe fire design of these structures relies heavily on accurate prediction of mechanical properties of the material with temperature. The data on elevated temperature mechanical properties collected from the literature experimental tests show a high degree of scatter, implying that they are influenced significantly by various factors, most notably the testing method, manufacturing process and chemical composition. However, the current methods for predicting the mechanical properties of high strength steels at elevated temperatures by using ‘reduction factors’ as adopted by the structural design codes do not consider these effects and may lead to inaccurate predictions. To overcome these deficiencies, a ML-based prediction method that uses temperature and chemical composition as input parameters is developed in this paper. Deep Neural Networks are trained and validated on the basis of elevated temperature material data collated from the literature test programmes. The analysis of the results show that the trained algorithm gives an excellent correlation coefficient with very small error value in predicting the strength and stiffness reduction factors of HSS.

Strength Evaluation of End-Plate Connections Using Stiffness Reduction Factor

Strength Evaluation of End-Plate Connections Using Stiffness Reduction Factor

Horizontal Bearing Capacity and Reliability of Piles in Coastal Soft Soil Considering the Time-Varying Characteristics

In order to study the influence of the creep of soft soil and the corrosion damage of reinforced concrete on the horizontal bearing behavior of piles, the novel p-y curve model was established considering the time-varying characteristics of soil parameters. The attenuation law of the bending stiffness of reinforced concrete piles under chloride erosion was analyzed by introducing the bending stiffness reduction factor. The limit state function of pile reliability analysis was then established considering the time-varying characteristics. The reliability index of a pile under horizontal displacement failure mode was obtained using the quadratic response surface method. Finally, the sensitivity analysis of random variables (cohesion, internal friction angle, concrete cover, and chloride concentration) on the time-varying reliability of a pile under horizontal displacement failure mode was carried out. The influence of the distribution types of soil parameters on the time-varying reliability was considered. The results show that the load-bearing characteristics of the horizontally loaded pile are impacted significantly by the time-varying characteristics of the soil. The maximum horizontal displacement of the pile increases nonlinearly with the increase in service time. When the horizontal displacement failure mode occurs, the variability in the internal friction angle has a significant impact on the reliability of the pile. The reliability index decreases nonlinearly with an increase in service time. When the soil parameters obey the extreme value type I distribution, the corresponding reliability index is greater than that of log-normal distribution and normal distribution.

Numerical study of the seismic retrofitting of masonry‐Infilled RC frames with openings using TRM

AbstractThe seismic retrofitting of existing masonry‐infilled reinforced‐concrete (RC) frame buildings is one major challenge of earthquake risk mitigation. In this paper, the use of promising novel alternative composite material, namely textile reinforced mortar (TRM) for seismic retrofitting masonry‐infilled RC frames with central openings is examined numerically, to the best knowledge of the authors, for the first time ever. This is achieved by performing a parametric study on a validated 2D numerical model of a three‐story masonry‐infilled RC frame with and without TRM considering different size of central openings. This parametric study aims to examine (i) the influence of central openings on the lateral response of masonry‐infilled RC frames subjected to cyclic loading and (ii) the lateral response of the three‐story masonry‐infilled RC frame with central openings retrofitted with TRM under cyclic loading. From the results obtained in this study, it was concluded that TRM contributes to increase the lateral capacity, stiffness, and the dissipated energy of infilled frames with openings and at the same time provides a more ductile behavior by delaying the strength and the stiffness degradation of infilled frames due to openings and further by delaying or even preventing brittle failures that occur on infilled frames due to the presence of the opening. New stiffness reduction factors for infilled frames with openings, and for TRM‐retrofitted infilled frames with openings are also proposed, which can be used with an equivalent compression strut model and with a tension tie‐model as an everyday practice tool for simulating infilled frames with central openings along the diagonal of the infill wall with and without TRM. A numerical sensitivity analysis is also performed aiming to investigate the influence of (i) the TRM reinforcement ratio and (ii) the type of mortar used for binding the textile reinforcement on the lateral response of the three‐story masonry‐infilled RC frame retrofitted with TRM subjected to cyclic loading. This study showed that by increasing the reinforcement ratio, or by using high‐strength mortars for binding the textile reinforcement, the lateral capacity of infilled frames is increased leading to a more ductile behavior, but this increase is not proportional to the increase of the reinforcement ratio or to the increase of the mechanical properties of the mortar.

Durability life prediction and horizontal bearing characteristics of CFRP composite piles in marine environments

In this paper, the durability life and horizontal bearing characteristics of carbon fiber reinforced polymers (CFRP) composite piles in marine environments are studied. The durability life of CFRP composite piles is divided into the initial corrosion stage of reinforcement and the crack propagation stage of concrete protection layer. The chloride diffusion model and Monte Carlo simulation method are used to predict the initial corrosion time of CFRP composite piles. Based on the thick-walled cylinder theory, the critical corrosion depth of the reinforced steel corresponding to the cracking of concrete protective layer is deduced. The durability life prediction model of crack propagation stage is established. The flexural stiffness reduction factor of CFRP composite piles with different replacement ratios is obtained by conducting the model pile bending tests. The attenuation law of bending stiffness and horizontal bearing characteristics of CFRP composite piles in marine environments are analyzed. The results show that the higher the replacement ratio of CFRP bar, the slower the reduction rate of flexural stiffness of CFRP composite pile is. Under the same buried depth, the pile bending moment and shear force of CFRP composite piles decrease with the increase of CFRP reinforcement replacement ratio. The horizontal displacement of CFRP composite piles increases with the increase of CFRP reinforcement replacement ratio.

MODELING OF SKELETON CURVES AND EVALUATION OF DEFORMATION CAPACITY OF EWECS COLUMNS

In this research, static loading test of Engineering Wood Encased Concrete-Steel (EWECS) columns with different steel depth has been conducted. From the results, it was confirmed that deterioration in capacity during large deformation, and the concrete failed in shear. Flexural strength could be estimated by the generalized superposed strength theory and shear strength could be estimated by the simplified equation given in the Standard for Structural Calculation for Steel Reinforced Concrete Structures. In addition, an evaluation equation for stiffness reduction factor at yield point in the skeleton curve and ultimate deformation have been proposed based on test results.

Stiffness Reduction Factor for Slender Concrete Column Reinforced with Fiber-Reinforced Polymer Bars

First Name is required invalid characters Last Name is required invalid characters Email Address is required Invalid Email Address Invalid Email Address

Deep learning‐based evaluation for mechanical property degradation of seismically damaged RC columns

AbstractThe evaluation of mechanical property degradation (i.e., stiffness and strength degradation) for seismically damaged reinforced concrete (RC) components is a critical step in the post‐earthquake assessment of the residual seismic capacity of buildings. In this study, a novel approach based on deep learning (DL) was proposed to evaluate the stiffness and strength degradation of RC columns according to visible seismic damage. A database was constructed by linking the test photos of RC column specimens with the loading points on the hysteretic curves, from which the stiffness and strength reduction factors (λK and λQ, respectively) were analyzed. Two novel convolutional network (CNN) modules were designed to enable feature extraction and integration of seismic damage with a reduced number of parameters, and multitask learning was introduced to enable adaptive feature fusion for stiffness and strength degradation individually. A deep convolutional network (DCNN) was therefore proposed to model the correlation between visible seismic damage and mechanical property degradation of flexural‐dominated RC columns, which can integrate visual characteristics and spatial topologies of visible damage to estimate λK and λQ. The application to two test specimens validated the preferable accuracy and robustness of the proposed DL‐based approach, and demonstrated its high potential for use in post‐earthquake performance assessment of buildings.

Solution to the problem of bridge structure damage identification by a response surface method and an imperialist competitive algorithm

To increase the efficiency of structural damage identification (SDI) methods and timeously and accurately detect initial structural damage, this research develops an SDI method based on a response surface method (RSM) and an imperialist competitive algorithm (ICA). At first, a Latin hypercube design method is used for experimental design and selection of sample points based on RSM. Then, a high-order response surface surrogate model for the target frequency response and stiffness reduction factor is established. Finally, analysis of variance is performed to assess the overall goodness-of-fit and prediction accuracy of the established model. Then the results obtained are combined with structural dynamic response data to construct objective functions; furthermore, the optimal solution of parameter vector in the objective function is solved based on the ICA. Then damage positioning and quantification can be achieved according to location and degree of change in each parameter; finally, the RSM-ICA-based SDI method proposed is applied to damage identification of high-dimensional damaged simply-supported beam models. To verify the effectiveness of the proposed method, the damage identification results are compared with the results obtained from traditional optimization algorithms. The results indicate that: average errors in the structural stiffness parameters and natural frequency that are identified by the proposed method are 6.104% and 0.134% respectively. The RSM-ICA-based SDI method can more accurately identify the location and degree of damages with more significantly increased identification efficiency and better precision compared to traditional algorithms. This approach provides a novel means of solving SDI problems.