Floor Response Spectra Research Articles

Optimal properties of hysteretic dampers to minimize peak floor accelerations in multi-story buildings subjected to earthquakes

In this study, the optimal reduction of seismic peak floor accelerations in buildings equipped with hysteretic dampers is investigated. The structures are modeled as linear elastic shear buildings, and the seismic demand is modeled as a stochastic process. The optimal properties and height-wise distribution of the hysteretic dampers are found using a pattern search optimization algorithm. The objective function is defined in terms of the stochastic non-stationary response of the structure, which is obtained using the Explicit Time Domain Method in combination with statistical linearization. Possible influence of the fundamental period of the structure, the frequency content of the excitation, and the number of stories, on the optimal properties of the hysteretic dampers are analyzed. The effects of the optimal solutions on other response quantities, such as inter-story drifts, ductility demand on the hysteretic dampers, energy dissipation, and floor response spectra, are also assessed. Findings of this study are validated by a case study that considers a real building model subjected to actual ground motion acceleration records. The main findings are: a) optimally designed hysteretic dampers are indeed effective in reducing the seismic peak floor acceleration response; and b) optimal non-uniform height-wise distributions of hysteretic dampers are essentially equal to or at most somewhat better (but not by a wide margin) than optimal uniform height-wise distributions.

A novel deep learning-based method for generating floor response spectra of building structures

Accurately and efficiently generating floor response spectra is crucial for the seismic design and analysis of nonstructural components, and seismic analysis of equipment placed on floors. In this article, a direct spectra-to-spectra method for generating floor response spectra is designed based on deep learning algorithms. The dataset was developed using the records of 102 building observation arrays in the Center for Engineering Strong Motion Data, which included 48 concrete structures, 44 steel structures and 10 masonry structures. The procedure involves training a deep learning model (FRSNet) with the ground response spectra and easily obtained structural parameters as inputs and the floor response spectra as outputs. Analysis results show that the prediction performance of the model is good on concrete structures, steel structures and masonry structures. The proposed model has sufficient accuracy, and the prediction performance is better than that of other models compared in this article. Finally, the proposed model is validated through two numerical models, a shaking table model structure and an actual structure. Convincing results confirm the accurate prediction capabilities of the proposed method.

Seismic Fragility Assessment of Equipment in Nuclear Power Plant Structures Considering Nonlinear Hysteretic Behavior of Squat Walls

Accurate seismic risk assessment of structures necessitates precise fragility analysis. This study focuses on the seismic fragility assessment of equipment in nuclear power plant structures, particularly emphasizing the influence of nonlinear hysteretic behavior exhibited by squat walls. By developing and comparing linear and nonlinear models of reactor containment and auxiliary buildings within a nuclear power plant, this research elucidates the significant impact of nonlinear behaviors on the seismic response and subsequent fragility curves of associated equipment and systems. Utilizing a lumped-mass stick model, the study efficiently captures the characteristics of squat shear walls, facilitating the calculation of floor response spectra and fragility for nuclear facility structures. The impacts of pinching and degradation, inherent characteristics of a squat wall’s hysteresis under cyclic loading, were identified as significant. These include the shift and change in amplitude of the floor response’s peak, along with amplification in high-frequency domains. Fragility assessments, informed by seismic response analysis, indicate significant variations in fragility curve parameters based on equipment location and frequency. The findings question the effectiveness of traditional response factor methods and general regression techniques in accurately addressing the complex probabilistic seismic demands of equipment, thus highlighting the importance of using direct analysis for calculating fragility in situations with significant nonlinearity.

Resilience-based seismic design for nuclear island building: An innovative hybrid passive control system

The Fukushima nuclear incident has heightened global concerns about the safety of nuclear facilities, the imperative to enhance the seismic resilience of nuclear power plants (NPPs) has become a pivotal aspect of nuclear safety. This study introduces an innovative hybrid passive control system that integrates three-dimensional (3D) base isolation technology with periodic isolation walls, aiming to bolster the seismic resilience of NPPs against very rare earthquakes. Furthermore, a complete and viable computational procedure was developed to study the nonlinear soil-structure interaction effects with high-precision wave motion analysis. Finally, the efficacy of the innovative control system to improve the seismic resilience of large-scale nuclear island buildings situated on non-rocky sites was assessed. The findings reveal that the system significantly mitigates the distribution of damage to NPPs during very rare earthquake scenarios. Compared to non-isolated NPP, the adoption of a hybrid passive control system reduces structural damage dissipation energy by 97.73 %. The system augments the effectiveness of 3D base isolation technology in reducing dynamic responses; specifically, the floor response spectra at the top position of the nuclear island building in the X, Y, and Z directions were lowered by 62.33 %, 52.03 %, and 84.12 %, respectively. Moreover, the system considerably reduces the deformation of the 3D isolation bearings. The innovative hybrid passive control system helps to enhance the seismic resilience of NPPs.

Seismic response of irregular RC buildings designed for gravity and seismic loads

Irregular reinforced concrete framed buildings are peculiar and their seismic response is difficult to predict using simplified approaches. The irregularity in structural configuration is characterized by cross-sectional area reduction of the columns along the height, in-elevation and in-plan irregular distribution of the masses, complex floor geometry or floor geometry variation along the height. This study analyses the seismic response of several four-storey buildings with different types of irregularities, namely in-elevation floor height and floor geometry variation. Additionally, responses of both seismically designed and gravity load designed structures are compared for each geometry considered. A numerical model accounting for non-linear flexural and shear response of the structure is developed, aimed at conducting non-linear incremental dynamic analyses. The results are discussed in terms of inter-storey drift, floor acceleration profiles, fragility functions and floor response spectra. A significant influence of the irregularity on floor accelerations and displacements was observed, as well as on the spectral acceleration at collapse, mainly caused by mass and stiffness variation along the height. On the other hand, no significant influence was detected on failure modes.

Estimation of consistent absolute acceleration and relative displacement floor response spectra in existing masonry-infilled reinforced concrete buildings

Estimation of consistent absolute acceleration and relative displacement floor response spectra in existing masonry-infilled reinforced concrete buildings

Study on the coupling effects between reactor coolant system and the internal structure on floor response spectrum of small modular reactor

AbstractAccording to Chinese code and US standard review plan (US SRP), when the equipment and structure satisfy certain decoupling conditions, the seismic analysis of the structure is performed using a decoupling method, where only the mass of the equipment is considered in the structure. The reactor coolant system of small modular reactor (SMR) which is integrated is different from that of PWR, and it is more likely to affect the seismic response of the supporting structure. In this paper, a decoupling model was first constructed based on the decoupling principles in the code. Then, a coupled model is built by connecting the main loop system model with the structure. The floor response spectra of the decoupling model and the coupled model are analyzed separately using ACS SASSI software to investigate the coupling effect. By the comparison of the results, the preliminary conclusions are drawn as follows: the decoupling criteria in code are met for the internal structure and reactor coolant system. For hard rock site, the coupling effect has negligible influence on the in‐structure response spectra (ISRS) for most of the structure except the reactor pit, which shows obvious change in the high‐frequency region. For soft soil site, there is no remarkable influence on the ISRS of the structure even for the reactor pit due to the filter effect of the site to the high‐frequency component in the seismic input. For the site with shear wave velocity greater than 1100 m/s, the influence of couple effect cannot be ignored.

Uncertainty parameters of the floor response spectrum in a seismically isolated structure

Uncertainty parameters of the floor response spectrum in a seismically isolated structure

Effect of Earthquake-Induced Structural Pounding on the Floor Accelerations and Floor Response Spectra of Adjacent Building Structures

The influence of earthquake-induced structural pounding among buildings is paramount in the seismic analysis and design of structures. The recognition of such a phenomenon has been growing in the last decades. The search for ways to understand and mitigate the consequences of these structural collisions in building structures is the primary goal of the investigation of earthquake-induced building pounding. This phenomenon is known for increasing the floor accelerations, mainly where pounding occurs, implying significant local damage. These collisions cause short-duration acceleration pulses that may compromise the building structure and the non-structural elements within the building’s stories. Non-structural elements supported by the structure’s floors under earthquake-induced pounding instances may present a risk to human lives and/or human activity. Hence, the influence of earthquake-induced pounding in the floor response spectra of two adjacent reinforced concrete structures with inelastic behavior is assessed by varying the number of stories and their separation distance. Pounding greatly influenced the floor acceleration spectra, increasing the spread of accelerations over a broader period range, particularly exciting low to moderate periods of vibration.

Examining random forests for predicting elastic floor response spectra involving dynamic primary-secondary structure interaction

Examining random forests for predicting elastic floor response spectra involving dynamic primary-secondary structure interaction

The influence of torsion on acceleration demands in low-rise RC buildings

AbstractThis paper presents a study of acceleration demands in low-rise reinforced concrete (RC) buildings with torsion, evaluated by quantifying peak floor accelerations (PFAs) and floor response (acceleration) spectra (FRS). The study was performed with the aim to provide simple empirical formulas to quantify the amplification effects due to torsion, which can occur in most of the existing and new RC buildings. With this goal in mind, a set of eight archetype buildings was selected, characterized by an increasing floor eccentricity obtained by moving the centre of rigidity (CR) away from the centre of mass (CM). Numerical models of the proposed set of archetype RC buildings were considered in both linear elastic and nonlinear configurations. For the latter, the properties of models were widely varied, by systematically modifying parameters of plastic hinges, in order to obtain a sample of 1000 models. Non-structural components (NSCs) were considered linear elastic in all cases. To investigate acceleration demands, a set of forty Eurocode 8 spectrum-compatible ground motion records were used as input. For linear elastic building models, it was observed that the change of demands depends on the position of the NSC (in-plan and in-height), and on the distance between CR and CM. On the other hand, for nonlinear models, additional parameters must be considered, such as the building ductility (μ) and yielding force (Vy). New regression models were proposed for quantifying the observed differences in PFAs and FRS when torsion occurs. The efficiency of the proposed models was assessed by testing the new formulas on an existing case study building, as well as on the well-known SPEAR building.

Investigation on floor response spectra of a three-story building exposed to near- and far-field earthquakes

Historical earthquakes highlighted structural collapses and non-structural component (NSC) failures. This study aims to analyze NSC behavior during near and far-field earthquakes in a three-story building by studying elastic and inelastic acceleration responses. The investigation delves into floor response spectra and analyzes how NSCs affect floor acceleration responses, aiming to understand the performance of these components. The findings from the analysis indicated that the Floor Response Spectra (FRS) consistently align peaks with elastic and inelastic modal periods. Inelastic FRS notably show reduced floor spectral accelerations compared to elastic FRS. Near-field earthquakes induce 25-30% higher floor acceleration demands in NSCs compared to far-field earthquakes. Peak Component Acceleration (PCA) values differ significantly between near and far field earthquakes, with near-field ones exhibiting notably higher values across all floors. Higher damping ratios in NSCs lead to decreased peaks in the Component Dynamic Amplification Factor (CDAF) spectrum. The inelastic model notably reduces peak values of CDAF by approximately 49.53% to 69.3% for near-field and 51.81% to 64.47% for far-field earthquakes compared to the elastic model. In summary, the examination of peak floor responses against the formulation based on building codes highlights variations, with instances where the formulation either underestimates or overestimates the peak response demands.

Seismic performance of base-isolated structures for swimming pool reactors under different foundation conditions.

The swimming pool reactor (SPR) is an innovative and environmentally friendly heating source. An SPR building was selected as the research subject, and a 3D dynamic interaction model incorporating the liquid sloshing effect was created using ANSYS software and the secondary development characteristics of user-programmable features (UPFs). Energy dissipation from scattered waves was accounted for using viscous-spring boundary elements, while the dynamic hydraulic effect was modeled via the Housner equivalent mechanical model. Considering soil-structure interaction (SSI) effects, this study examines the impact of isolation measures on the structure's seismic mitigation performance. It investigates how varying foundation conditions affect the seismic resistance of the isolated structure. Results indicate that seismic isolation ratios for acceleration, floor response spectra, displacement, and base shear diminish as site stiffness decreases. However, regarding sloshing wave height, seismic isolation amplified the height under all conditions but remained within safe limits. These findings offer valuable insights for seismic design across different SPRs.

Artificial neural network-based prediction model of elastic floor response spectra incorporating dynamic primary-secondary structure interaction

The evaluation of the Floor Response Spectrum (FRS) holds paramount significance in assessing the seismic behavior of secondary structures. Precise FRS prediction empowers engineers to make informed decisions concerning structural design, retrofitting, and safety precautions. This study aims to scrutinize the impact of dynamic interaction between primary and secondary structures on FRS. Both the elastic primary structure (PS) and elastic secondary structure (SS) employ a single-degree-of-freedom (SDOF) system. Governing motion equations for both coupled (with dynamic interaction) and uncoupled (without dynamic interaction) systems are formulated and solved numerically. The study investigates how variations in the vibration period of PS (Tp), tuning ratio (Tr), mass ratio (μ), and damping ratio (ξs) of SS influence FRS. The FRS impact remains minimal at μ = 0.001 (0.1%); however, with increasing mass ratio, PS-SS dynamic interaction significantly affects SS's spectral acceleration response. Coupled analysis is crucial only for secondary structures tuned to the primary structure's vibration period (0.8≤Tr≤1.2). This study utilizes two-layer feed-forward Artificial Neural Networks (ANNs) for FRS prediction. The Levenberg-Marquardt (LM) backpropagation (BP) algorithm trains the network using a comprehensive dataset. In summary, it is evident that the ANNs, once trained, enable accurate prediction of the FRS, exhibiting a R2 of 99%. Additionally, a design expression is formulated utilizing the ANN model and subsequently compared with the existing formulation.

Dynamic soil-structure interaction analysis for base-isolated nuclear island building based on the method of external source wave motion

Soil-structure interaction (SSI) is crucial to the dynamic response of nuclear power plants (NPPs), and should be properly considered when analysing the seismic isolation performance of base-isolated NPPs. In this study, a three-dimensional numerical simulation program is developed for the time-domain dynamic analysis of base-isolated NPPs considering SSI effects. The seismic input is realised using the method of external source wave motion, and the nonlinear behavior of isolators is fully considered. Using this program, the SSI effects of the base-isolated nuclear island building under different sites are analysed and compared, including the acceleration, displacement, and floor response spectra. The numerical results show that the SSI effects change the spectral characteristics of the actual seismic input. When the shear wave velocity of the site is relatively large, the SSI effects can increase the dynamic response of base-isolated NPPs. Additionally, the isolation performance of the base-isolated NPPs is weakened when SSI effects are considered, and with a decrease in the shear wave velocity of the site, the isolation capacity is further reduced. The influence of the SSI effects should be fully considered in the base isolation design of NPPs.

Elastic and inelastic acceleration amplification of nonstructural components characterized using recorded building responses

This paper presents a comprehensive study of the acceleration (or force) amplification behavior of building nonstructural components characterized using a large set of recorded building responses available in the Center for Engineering Strong Motion Data (CESMD) repository. The elastic acceleration amplification demands of nonstructural components are analyzed statistically and subsequently compared with the corresponding inelastic demands characterized by the constant-ductility floor response spectra. Different simplified hysteretic rules are adopted for evaluating the inelastic acceleration responses of nonstructural components. The numerical study demonstrates that the elastic acceleration amplification characteristics of the nonstructural components are highly dependent on their natural periods relative to the specific vibration modes of the supporting structures as well as their attachment locations relative to the building height. The presence of component ductility effectively reduces their seismic acceleration demands, particularly in period ranges tuned with their supporting structures. Furthermore, the hysteretic behavior of nonstructural components may moderately modify their acceleration amplification effects. Findings from this study substantiate current seismic design provisions of nonstructural components with evidence derived from building floor responses recorded during real earthquakes.

Direct floor response spectra for nonlinear nonstructural components

Direct floor response spectra for nonlinear nonstructural components

Shaking Table Testing of a Scaled Nuclear Power Plant Structure with Base Isolation

To investigate the seismic performance and isolation effect of a high-temperature gas-cooled reactor, a 1/20 scale model including a reactor, a spent-fuel plant, and a nuclear auxiliary plant was fabricated. In addition, 220 mm lead-rubber bearings were designed and produced for use in the shaking table test, which included both isolated and nonisolated conditions. Two historical earthquake records and three artificial earthquake motions were used to input the ground motion in the tests. The results demonstrated that the seismic performance of the plant was better and that the structure was in an elastic state, under a safe shutdown earthquake event. Isolation bearings were found to effectively reduce the dominate frequency of the structure. The acceleration amplification factor of the superstructure was found to be less than 1. The isolation test results showed that the peak of the floor response spectrum at the pressure vessel support was less than 0.1 g. In the nonisolation test, the peak of the floor response spectrum was greater than 1 g. In the isolation test, the relative displacement of the structure was less than 1.1 mm, which was relatively small. The structure maintained a good isolation performance and exhibited improved safety under extreme ground motion.

Utilizing Artificial Neural Networks and Random Forests to Forecast the Dynamic Amplification Factors of Non-Structural Components

Soft stories in buildings are well-known to present structural vulnerabilities during seismic events, and the failure of non-structural components (NSCs) has been evident in past earthquakes, along with structural damage. This study seeks to investigate how the presence of a soft story in a building affects the criteria for elastic floor acceleration. The soft story is assumed to be at the top, middle, and bottom levels of the structure. To comprehend the behavior of NSCs, the researchers analyze the floor response spectra (FRSs) and component acceleration amplification. Remarkably, the results reveal that the position of the soft story strongly influences the floor response spectra, with structures featuring a middle soft story showing the most significant amplification of component acceleration. In constructing the FRSs, the component dynamic amplification factors (CDAFs) play a vital role as they accurately illustrate how NSCs amplify floor vibrations. Consequently, the study delves into exploring machine learning (ML) models like artificial neural networks (ANNs) and random forest (RF) to map the intricate relationship between CDAFs, the dynamic characteristics of the building, and the behavior of NSCs. Upon comparison of the two models, the random forest model emerges as the superior method in predicting the CDAFs.

An adapted LSTM-DRRNet approach for predicting floor acceleration response spectrum

The floor response spectrum is an essential element in designing non-structural components (NSC) under earthquakes. However, most available approaches for floor response spectrum estimation involve complex modeling work, require intensive computational resources, and lack generalizability. To address these limitations, this paper proposes a novel deep-learning-based methodology to provide a generalized estimate of nonlinear floor response spectra, which is composed of a bidirectional convolutional long short-term memory network with an attention mechanism (ACN-BiLSTM) and a deep residual regression network (DRRNet). ACN-BiLSTM uses one-dimensional convolution to extract high-dimensional abstract features of ground motion spectrum in each period. The attention mechanism and multi-scale sliding time window are used to improve the network’s convergence speed and prediction accuracy. DRRNet uses deep one-dimensional convolution to build a residual shortcut connection, which delivers the proportional relationship between floor response spectrum at different heights. With the input of the ground motion acceleration spectrum and structural characteristics, the proposed method can estimate the nonlinear floor acceleration response spectrum on any floor of a building. To demonstrate its efficacy, the proposed approach is applied to a dataset that includes floor response spectra of 56 buildings subjected to 195 ground motions. The application results indicate that the proposed approach can effectively and reliably predict the nonlinear acceleration response spectrum with an accuracy of 97.29%. Such an efficient method is promising in advancing the seismic design of non-structural components.