Structural Response Research Articles

Freeze–Thaw Response of Permeability and Absorption Channel Structure and Moisture Distribution in Different Coal Ranks

Freeze–Thaw Response of Permeability and Absorption Channel Structure and Moisture Distribution in Different Coal Ranks

The Social Justice Engagement Scale: Development and Validation on Professional and Student Counselors and Counseling Psychologists from the U.S

Objective The Social Justice Engagement Scale (SJES) is a newly developed instrument that assesses a counselor’s prior behavior in social justice activities. Method The first study (N = 249, 80% female, 68% White) examined the internal structure and item response process of the SJES. The second study (N = 219, 79% female, 53% White) examined confirmatory evidence of the factor structure, and discriminatory and convergent validity. The third study (N = 160, 75% female, 47% White) replicated the internal structure and examined evidence of the concurrent validity of the SJES. Results Exploratory and confirmatory factor analyses supported a one-factor, 19-item measure. A graded response model supported the scale of measurement. The SJES demonstrated discriminant and divergent validity evidence. The SJES was the only significant independent variable in an experimental test of concurrent validity. Conclusions The SJES offers a promising new scale distinct from prior social justice instruments.

Study on secondary collapse of the bottom frame masonry structure in semi-ruined state based on FEM–FDEM

The bottom frame masonry structure (BFMS) in a semi-ruined state is vulnerable to secondary collapse under strong aftershocks, posing a significant risk to rescuers during post-earthquake operations. Therefore, investigating the mechanisms and characteristics of secondary collapse of BFMS in a semi-ruined state (BFMS-SR) under aftershocks is critical. This paper proposes a numerical modeling framework for BFMS under mainshock-aftershock conditions, utilizing a combination of the finite element method (FEM) and the finite discrete element method (FDEM). The validation demonstrates that FEM–FDEM can effectively reproduce the transition of BFMS from an intact state to a semi-ruined state, ultimately leading to a secondary collapse state. Subsequently, the mechanisms and structural response characteristics of BFMS-SR under aftershocks are analyzed. The secondary collapse of the BFMS-SR under aftershocks is primarily governed by column hinge development. Furthermore, according to the time-history curve of absolute vertical velocity, the secondary collapse of BFMS-SR exhibits four distinct stages: stabilization, structural response development, secondary collapse, and post-collapse. The end of the stabilization phase is proposed as the early-warning threshold for secondary collapse of BFMS-SR under aftershocks, aiding in post-earthquake rescue operations.

The Dynamic Soil–Foundation–Structure Interaction Problem in the Time Domain Using a Discrete Element Model

This study investigates the influence of the soil–structure interaction (SSI) on the seismic performance of structures, focusing on the effects of foundation size, soil type, and superstructure height. While the importance of SSI is well recognized, its impact on structural behavior under seismic loads remains uncertain, particularly in terms of whether it reduces or amplifies structural demands. A simplified dynamic model, incorporating both the mechanical behavior of the soil and structural responses, is developed and validated to analyze these effects. Using a discrete element approach and the 1940 El Centro earthquake for validation, the study quantitatively compares the response of soil-interacting structures to those with fixed bases. The numerical results show that larger foundation blocks (20 m × 20 m and 30 m × 30 m) increase the seismic response values across all soil types, causing the structure to behave more like a fixed-base system. In contrast, reducing the foundation size to 10 m × 10 m increases the flexibility of structures, particularly buildings built on soft soils, which affects the displacement and acceleration response spectra. Softer soils also increase natural vibration periods and extend the plateau region in regard to spectral acceleration. This study further finds that foundation thickness has a minimal impact on spectral displacement, but structures on soft soils show more than a 15% reduction in spectral displacement (SD) compared to those on hard soils, indicating a dampening effect. Additionally, increasing the building height from 7 to 21 m results in a more than 20% decrease in SD for superstructures with natural vibration periods exceeding 2.4 s, while taller buildings with longer natural vibration periods exhibit opposite trends. Structures built on soft soils experience larger foundation-level displacements, absorbing more seismic energy and reducing earthquake accelerations, which mitigates structural damage. These results highlight the importance of considering SSI effects in seismic design scenarios to achieve more accurate performance predictions.

A multi-scale uncertainty analysis method based on the Hermite–Chebyshev polynomials for dynamic responses of FRP composite structures with hybrid uncertainties

Multi-scale hybrid uncertainties in material properties of FRP composites stemming from their manufacturing processes present significant challenges for dynamic analysis and reliability assessment. This paper proposes a multi-scale uncertainty surrogate model based on Hermite–Chebyshev polynomials. The relationship between micro- and macro-scale material properties is established using the Mori–Tanaka method. To demonstrate the efficacy of the proposed method, case studies are conducted on both a FRP wide-flange I-beam structure and a FRP truss bridge. Results indicate that this method accurately determines the probability density functions and cumulative distribution functions of natural frequencies and mode shapes. Notably, the method efficiently computes the upper and lower bounds of dynamic failure probability of FRP truss bridge with high numerical efficiency.

The Effect of Protective Barriers on the Dynamic Response of Underground Structures

Engineers have dedicated considerable attention over the past ten years to studying the influences of dynamic loads caused by both intentional and unintentional events on infrastructures. As a result, determining how buried structures react to explosions and enhancing their security against blast loads have become crucial subjects in defensive engineering. To achieve this goal, constructing a protective barrier, which is known as a blast wall, in front of structures can be an effective measure. This research focused on examining the impact of a protective barrier on the response of a box-shaped tunnel located in Kobe, Japan, using a comprehensive numerical approach. The results revealed that incorporating a barrier with widths of either 1 m or 2 m resulted in a significant reduction in peak pressure. Specifically, the use of a 1 m wide barrier resulted in a 77% decrease, while a 2 m wide barrier achieved an even greater reduction of 84%. Additionally, it was observed that minimizing the distance between the barrier and the explosion point, as well as increasing the width of the barrier, resulted in reduced peak pressure throughout all sections of the tunnel.

Design Principle and Regulation Strategy of Noble Metal‐Based Materials for Practical Proton Exchange Membrane Water Electrolyzer

AbstractGreen hydrogen holds immense promise in combating climate change and building a sustainable future. Owing to its high power‐to‐gas conversion efficiency, compact structure, and fast response, the proton exchange membrane water electrolyzer (PEMWE) stands out as the most viable option for the widespread production of green hydrogen. However, the harsh operating conditions of PEMWE make it heavily dependent on noble metal‐based catalysts (NMCs) and incur high operational and maintenance costs, which hinder its extensive adoption. Hence, it is imperative to improve the performance and lifespan of NMCs and develop advanced components to reduce the overall costs of integrating PEMWE technology into practical applications. In light of this, the fundamental design principles of NMCs employed in acidic water electrolysis are summarized, as well as recent advancements in compositional and structural engineering to enhance intrinsic activity and active site density. Moreover, recent innovations in stack components of practical PEMWE and their impact on cost‐benefit and lifespan are presented. Finally, the current challenges are examined, and potential solutions for optimizing NMCs and PEMWE in electrocatalytic hydrogen production are discussed.

Multi-fidelity enhanced few-shot time series prediction model for structural dynamics analysis

These days, deep learning (DL) techniques are regarded as an effective substitution of refined finite element models to conduct structural dynamics analysis. Nevertheless, the efficacy of DL methods overwhelmingly depends on the quality and quantity of the data. Since high-fidelity (HF) data are accurate enough but usually time-consuming and costly, while low-fidelity (LF) data are low-cost and efficient but inaccurate, the DL models cannot efficiently and accurately achieve prediction of structural dynamic response solely using either HF or LF data. Under this circumstance, a multi-fidelity enhanced few-shot time series prediction approach is proposed that can significantly promote the efficiency of structural dynamics analysis. Moreover, the K-shape clustering method is utilized to select representative training sample to lessen the need for HF data, further improving efficiency of structural dynamics analysis. For validating the accuracy and efficiency of this method, a case study about the prediction for seismic response on a reinforced concrete frame is conducted, wherein fiber element models are utilized to generate accurate but limited HF seismic response data, while multi-degree of freedom models are utilized to develop a larger LF response database. Eventually, diverse vital factors impacting the performance of the proposed method are also investigated. The results demonstrate that the proposed method can efficiently implement structural dynamics analysis without compromising precision.

Fire behavior of composite steel truss bridge girders: numerical investigation and design strategies

Fire pose more severe threat to steel truss bridge girders as compared to common steel plate and box bridge girders. To deeply clarify failure mechanism of fire exposed steel truss bridge girders, this paper presents an investigation on fire performance of composite steel truss bridge girders simultaneously subjected to structural loadings and hydrocarbon fires. A numerical model, developed using the computer program ANSYS, is validated dependent on fire test to trace fire behavior of a typical through-type composite steel truss bridge girders under different hydrocarbon fire exposure conditions. The analysis is applied to evaluate influence of potential fire exposure scenarios occurred in bridge structures, including fire exposure lanes on bridge deck and fire exposure length beneath bridge, on temperature and structural response in steel truss bridge girders. The results shows that fire exposure lanes on bridge decks and fire exposure length beneath bridge has a significant influence on fire performance of steel truss bridge girders. Fire exposure on all lanes and side lanes can cut down fire resistance highly as compared to fire exposure on mid-lanes. The composite steel truss bridge girders exhibit special multi-hinge failure modes when fire exposure under bridge. Further, the composite steel truss bridge girders exposed to side-lane fire exhibit significant transverse torsional deformation. The established failure criteria dependent on structural deflection limit states, chord deformation and strength can be applied to evaluate fire resistance of actual composite steel truss bridge girders under realistic fire exposure scenarios. Limiting the minimum clearance of passage on bridge deck and increasing fire protection measures in upper portion of trusses can effectively improve fire resistance of through-type composite steel truss bridge girders. Some predominant design strategies closely related to oil tanker trucks traversing composite steel truss bridge girders are proposed to minimize probability of fire incidents on bridge and keep integrity of structure in the case of fire to the maximum extent possible.

A boundary enforcement method for the truncated ship structure model during underwater contact explosion experiments

Conducting model experiments is an effective approach for investigating structural damage of ship cabin structures induced by underwater contact explosions. However, large-scale cabin model experiments often encounter challenges in establishing practical constraints, resulting in disparities in boundary constraints between the experimental model and the intact ship model. To overcome this, the present work proposes a novel method for enforcing boundary conditions that involves extending the boundaries of the experimental model, securing the model boundaries with clamps and the rigid wall, and simulating the underwater environment using the temporary water tank. Based on this method, an experiment of a broadside cabin of large ships subjected to underwater contact explosion was conducted, and results are reproduced through the Arbitrary Lagrange-Euler (ALE) method. Subsequently, the explosive load characteristics of the boundary enforcement model are further analyzed, followed by a discussion of the impact of boundary constraints on structural response, thereby validating the effectiveness of the boundary enforcement method.

Kohonen Mapping of the Space of Vibration Parameters of an Intact and Damaged Wheel Rim Structure

The research presented in this paper takes another step towards developing methods for automatic condition verification to detect structural damage to vehicle wheel rims. This study presents the utilisation of vibration spectra via Fast Fourier Transform (FFT) and a neural network’s learning capabilities for evaluating structural damage. Amplitude and time cycles of acceleration were analyzed as the structural response. These cycles underwent FFT analysis, leading to the identification of four diagnostic symptoms described by 20 features of the diagnostic signal, which in turn defined a condition vector. In the subsequent stage, the amplitude and frequency cycles served as input data for the neural network, and based on them, self-organizing maps (SOM) were generated. From these maps, a condition vector was defined for each of the four positions of the rim. Therefore, the technical condition of the wheel rim was determined based on the variance in condition parameter features, using reference frequencies of vibration spectra and SOM visualisations. The outcome of this work is a unique synergetic diagnostic system with innovative features, identifying the condition of a wheel rim through vibration and acoustic analysis along with neural network techniques in the form of Kohonen maps.

Dynamic strength criterion of concrete utilizing dynamic coordinates

AbstractThe effects of strain rate on the strength of concrete should be considered when analyzing the dynamic responses of concrete structures subjected to earthquakes or explosions. This paper shows that the effect of strain rate on strength characteristics can be attributed to an increase in cohesion. Notably, the effects of friction, hydrostatic pressure, and intermediate principal stress tend to remain rate‐independent under the appropriate reference system. Consequently, a dynamic coordinate system is established to account for the effects of strain rate on isotropic tensile strength. In this dynamic coordinate system, the strength envelopes for concrete closely resemble those in quasi‐static conditions under varying strain rates, as defined in the unified strength criterion. Using this proposed dynamic strength criterion, this paper explores the dynamic characteristics of different stress paths, including uniaxial, biaxial, and triaxial compression and tension. The predictions, both in terms of tendencies and magnitudes, are consistent with test results. The proposed method enables the extension of most strength criteria to dynamic scenarios by introducing two additional parameters with clear physical interpretations. This advancement enhances the current understanding of dynamic strength characteristics and provides a theoretical foundation for dynamic response analysis.

A Cepstrum-Informed neural network for Vibration-Based structural damage assessment

Data-driven methods for vibration-based Structural Health Monitoring (SHM) have gained significant popularity for their straightforward modeling process and real-time tracking capabilities. However, developing complex models such as deep neural networks can pose challenges, including limited interpretability and substantial computational demands, due to the large number of parameters and deep layer stacking. This study introduces a novel Cepstrum-Informed Attention-Based Network (CIABN) developed to model power cepstral coefficients of structural acceleration responses, guided by cepstrum-based physical properties to facilitate efficient structural damage assessment. The CIABN integrates three key components: a unique input–output mapping based on weighted cepstral coefficients, a novel cepstral positional encoding mechanism, and a multi-head self-attention mechanism. The unique input–output mapping enables appreciable model generalization in overall structural characteristics, with the weighted cepstral coefficients serving as informative and compact data for efficient neural network modeling. The developed cepstral positional encoding scientifically guides the model to capture the coefficient indices, and the underlying trend of cepstral coefficients primarily governed by overall structural characteristics. The multi-head attention mechanism enables computationally efficient parallel analysis of interdependencies among coefficients, facilitating the development of a lightweight network. The effectiveness and superiority of the method have been validated using both simulated and experimental structural data.

A rapid estimation method for the probability of wind-induced first plastic displacement of SDOF systems based on the Slepian model

The conventional method based on the Slepian model for estimating the probability distribution of the first plastic displacement of an ideal elastic-plastic oscillator (EPO) is only applicable for zero-mean white noise loads. This study proposes an improved method applicable to wind loads with non-zero mean and non-white noise characteristics for structures whose resonant response dominates the fluctuating wind-induced response. The original EPO's symmetric constitutive model under non-zero mean loads is modified to be equivalent to an asymmetric constitutive model under zero mean loads; thus, a SDOF system subjected to non-zero mean loads is transformed into a SDOF system under zero mean loads. When the resonant response dominates the fluctuating wind-induced response, the fluctuating wind-induced response can be approximated as a narrow-band stochastic process, the extreme values following a Rayleigh distribution, and the probability distribution of the local maximum displacement of the associated linear oscillator (ALO) can be directly obtained, making the Slepian model-based method applicable for non-white noise loads. A case study is performed to validate the accuracy of the proposed improved method, and the results demonstrate that the improved method proposed in this study can significantly enhance computational efficiency. The accuracy of the improved method is independent of the load characteristics but rather depends on the narrowband characteristics of the structural response. When the narrowband characteristics of the structural response are prominent, the improved method exhibits high accuracy.

Optical response of WSe2-based vertical tunneling junction

Layered materials have attracted significant interest because of their unique properties. Van der Waals heterostructures based on transition-metal dichalcogenides have been extensively studied because of potential optoelectronic applications. We investigate the optical response of a light-emitting tunneling structure based on a WSe2 monolayer as an active emission material using the photoluminescence (PL) and electroluminescence (EL) experiments performed at low temperature of 5 K. We found that the application of the bias voltage allows us to change both a sign and a value of free carriers concentrations. Consequently, we address the several excitonic complexes emerging in PL spectra under applied bias voltage. The EL signal was also detected and ascribed to the emission in a high-carrier-concentration regime. The results show that the excitation mechanisms in the PL and EL are different, resulting in various emissions in both types of experimental techniques.

Lost data reconstruction for structural health monitoring by parallel mixed Transformer-CNN network

Transformer-based and convolutional neural network-based deep learning methods have been extensively utilized to reconstruct lost data for structural health monitoring. However, the lack of inductive bias in Transformer and the fixed receptive fields of convolutional neural network (CNN) limit their local and global modeling capabilities, respectively. The traditional method of combining the two in series creates a sequential relationship and interdependence, negatively impacting reconstruction accuracy. To address this problem, this paper proposes a novel parallel mixed Transformer-CNN network. By parallel connecting the shifted window transformer and densely connected convolutional block, both can process structural vibration responses simultaneously and independently, leveraging the locality of convolution to address the inductive bias of Transformer. Experiments on real acceleration data from the Canton Tower validate its effectiveness. Compared with models using only Transformer or CNN, the reconstruction errors are reduced by 56% and 17%, respectively. The modal parameters extracted from the reconstructed data are highly consistent with those from the true data, and our model has good robustness to lost rates and noise.

Numerical investigation of pre-flawed FGM tubes repaired with different composite jackets under sequential gaseous detonation loading

Investigation on the structural response of pre-flawed functionally graded material (FGM) cylindrical tubes submitted to sequential detonation loading is the main contribution of this study. Analyses are made for repaired and unrepaired tubes using three different composite patch (CP) geometric shapes: full cylindrical, semi-cylindrical, and circular. The effect of non-homogeneous FGM materials (ceramic-to-aluminum, aluminum-to-ceramic, and steel-to-ceramic) and CPs on the stress field in the tube is studied using three-dimensional finite element (FE) models. The FE analyses are conducted for two distinct categories of detonation loading: low- and high-pressure detonations. This approach helps to enhance the understanding of how material gradation influences stress distribution and damage assessment in tubes subjected to these specific loading conditions. The FE analyses revealed that both forward and reflective waves coming from detonation load significantly contribute to crack propagation by elevating stresses near crack tips. The application of CPs, made of boron/epoxy material, effectively mitigated stress concentrations across all FGMs, with full cylindrical CPs providing the best results. Delamination was observed in CPs with two composite layers under high-pressure loading, particularly in aluminum-to-ceramic FGM.

Controlled dynamic response of a novel auxetic sandwich structure: A tunable tetrachiral core with dual-FG nanocomposite skin

Controlled dynamic response of a novel auxetic sandwich structure: A tunable tetrachiral core with dual-FG nanocomposite skin

Femtosecond Laser Introduced Cantilever Beam on Optical Fiber for Vibration Sensing

An all-fiber vibration sensor based on the Fabry-Perot interferometer (FPI) is proposed and experimentally evaluated in this study. The sensor is fabricated by introducing a Fabry-Perot cavity to the single-mode fiber using femtosecond laser ablation. The cavity and the tail act together as a cantilever beam, which can be used as a vibration receiver. When mechanical vibrations are applied, the cavity length of the Fabry-Perot interferometer changes accordingly, altering the interference fringes. Due to the low moment of inertia of the fiber optic cantilever beam, the sensor can achieve broadband frequency responses and high vibration sensitivity without an external vibration receiver structure. The frequency range of sensor detection is 70 Hz–110 kHz, and the sensitivity of the sensor is 60 mV/V. The sensor’s signal-to-noise ratio (SNR) can reach 56 dB. The influence of the sensor parameters (cavity depth and fiber tail length) on the sensing performance are also investigated in this study. The sensor has the advantages of compact structure, high sensitivity, and wideband frequency response, which could be a promising candidate for vibration sensing.

Small intestine structural and functional responses to environmental heavy metal stress in tree sparrow Passer montanus nestlings.

Tree sparrow nestlings predominantly consume protein-rich insect larvae, making them vulnerable to environmental heavy metal contamination through the food web, potentially affecting their growth. Understanding the effects of heavy metals on the structure and function of the small intestine, the principal organ responsible for protein digestion and absorption, is therefore crucial. This study investigated tree sparrow nestlings at three developmental stages (3, 6, and 12days old) in Liujiaxia (LJX), a comparatively unpolluted area, and Baiyin (BY), a heavy metal polluted area, to elucidate the factors and mechanisms by which heavy metals affect nutrient absorption. We compared heavy metal accumulation levels, structural integrity, and protein digestion and absorption functions of the duodenum, jejunum, and ileum. The increase of fluctuating asymmetry and decrease in body condition in tree sparrow nestlings were found to be associated with environmental heavy metal accumulation in the small intestine. Structural impairments of villi and crypts were observed in the duodenum and jejunum of tree sparrow nestlings at 3-, 6-, and 12-day-old in the polluted site BY. Conversely, structures related to the ileum were elevated, and the small intestine of nestlings at all stages exhibited abnormally elevated protein digestibility but diminished absorption of amino acids. However, there was no significant difference in small peptide absorption. These findings indicate that environmental heavy metal pollution impacts the structure of the small intestine in tree sparrow nestlings through the food chain and further affects their digestion and absorption function of proteins.