Cyclic Characteristics Research Articles

The Cyclic and Episodic Transition of Strong El Niño and Implications for South American Precipitation During Their Peak and Decay Stages

ABSTRACTThe mechanisms associated with the transitions of strong El Niño (EN) events and their implications for the South American precipitation were investigated for the 1950–2023 period. Strong EN events exhibit cyclic or episodic characteristics in their transitions. Cyclic EN events are both preceded and followed by La Niña (LN) conditions, whereas episodic EN events are preceded by neutral conditions, with a more uncertain transition following. For cyclic EN, tropical Pacific mechanisms initiates and peak warming in the eastern tropical Pacific from austral winter to early summer. In contrast, for episodic EN, coupled subtropical and tropical Pacific mechanisms, respectively, initiate and peak warming in the central tropical Pacific from autumn to late summer. The Pacific Decadal Oscillation (PDO) mean state modulates EN's decay stage. During the +PDO mean state, cyclones in the eastern subtropical Pacific of both hemispheres sustain the warming of episodic EN, whereas during the −PDO mean state, anticyclones in the eastern subtropical Pacific accelerate the decay of cyclic EN, favouring its transition to an LN. These mechanisms explain why episodic EN initiates earlier, peaks later, is more intense and decays more slowly than cyclic EN. During an episodic EN summer, the strengthened atmospheric circulation maintains the Atlantic Intertropical Convergence Zone (ITCZ) north of the equator, causing persistent negative precipitation anomalies in north–northeastern South America (SA) until the following winter, while positive precipitation anomalies in southeastern SA are driven by south–southeastward moisture transport from equatorial Atlantic. Conversely, during a cyclic EN summer, negative (positive) precipitation anomalies impact north–northwestern (southeastern) SA; however, the anomalous atmospheric circulation and precipitation in SA quickly return to normal conditions in the autumn, and positive precipitation anomalies appear in northern SA in the following winter. Understanding these mechanisms is crucial for predicting EN's future changes and, consequently, their potential socio‐economic impacts globally.

Earthquake record truncation metric for nonlinear dynamic analyses of high rockfill dams

The long initial and coda waves with small amplitude are often observed in an actual earthquake record. Truncating those wavebands that contribute little to structural responses is helpful to focus on the strong shaking phase and reduce computational cost. In the paper, 157 actual earthquake records and the acceleration time windows constrained by truncation thresholds of Arias intensity serve as input ground motions. A large number of elastoplastic dynamic analyses on a 295 m-high core-wall rockfill dam (CRFD) are conducted using the generalized plasticity model and seismic wave input method. Inspired by fragility equation, the probability curves for the accuracy loss of dam response less than different limits under different truncation thresholds are established, quantifying the destructiveness of the truncated seismic acceleration time windows. Results show that the probabilities are minimally affected by peak ground acceleration (PGA); the allowable tail truncation of earthquake records is much more than the leading due to the asymmetry of seismic waveforms and the cyclic hardening characteristic of rockfill materials; the truncation metric of 0.01–98 % Arias intensity is proved to be effective and robust in accelerating dynamic analyses of rockfill dams with an accuracy loss within 5 % and an average reduction in computational workload of approximately 50 %.

Influence of steam curing on cyclic triaxial characteristics of recycled aggregate concrete: Experimental analysis and DEM simulation

The engineering application of steam-cured recycled aggregate concrete (often in a cyclic triaxial stress state) can not only improve the recycling efficiency of resources, but also accelerate the construction progress. In this paper, we adopt a combination of laboratory experiments, theoretical analysis and numerical simulation to study the cyclic triaxial characteristics of recycled aggregate concrete (RAC) under different curing regimes (20℃, 40℃, 60℃ and 80℃). The results indicate that as the steam curing temperature increases, the internal damage caused by high temperature continues to intensify, and the cyclic triaxial failure mode of RAC transitions from shear failure to compression failure, and its peak strength, dynamic elastic modulus, and dilatancy angle all show a downward trend. A linear prediction model is established based on the strong correlation between peak strength and steam curing temperature. As the loading cycles increase, the dynamic elastic modulus and dilatancy angle of RAC show exponential and linear downward trends respectively, and the decline rate increases with the increase of steam curing temperature, and the prediction models for dynamic elastic modulus and dilatancy angle are established based on quantitative relationships between variables. On the basis of experimental analysis results, a cyclic triaxial DEM model considering real recycled aggregates is established by introducing steam-cured damage indexes into the mesoscopic parameters, and its applicability in predicting cyclic triaxial mechanical properties of RAC under different curing regimes is verified. The research outcomes can save a lot of test cost and time consumption for developing steam-cured concrete with better performance, and have important theoretical guidance and practical significance for the wide application of steam-cured concrete.

The Time-Dependent Method for Probabilistic Fault Displacement Hazard Analysis (PFDHA-td)

Coseismic surface displacement can cause major damage to buildings located on faults. Therefore, it is important to quantitatively evaluate the future surface displacement of active faults. The commonly used deterministic evaluation methods often tend to overestimate surface displacement values, so researchers are working toward probabilistic fault displacement hazard analysis (PFDHA). However, the PFDHA assumes that earthquakes occur equally in time, which is not consistent with the physical mechanism of earthquake occurrence. Elastic rebound theory and paleoseismic research results show that the accumulation and release of energy in the crustal medium have cyclical characteristics. In this study, using two parameters, the strong earthquake recurrence period (TRP) and strong earthquake elapsed time (tet), of active faults, the displacements of active faults with different TRP and tet under different exceedance probabilities are obtained. The calculation results indicate that the surface displacement hazard of the weakly active and extremely weakly active faults in the Holocene does not need to be considered; for the moderately and strongly active faults in the Holocene, the surface displacement result is lower than that provided by the deterministic method. According to the importance of the project, the calculation results of the PFDHA-td method under different exceedance probabilities are selected.

Physics-Informed Neural Network Surrogate Model for Small-Sample Mistuned Bladed Disk

Mistuning in bladed disk structures disrupts their cyclic symmetry, potentially resulting in high cycle fatigue. The stochastic nature of mistuning greatly increases the computational cost of related studies. To improve computational efficiency, previous research has primarily focused on reduced-order models based on finite element methods, whereas the increasing demand for rapid computation and precise predictions has led to the emergence of data-driven approaches. These methods directly use vibration data from bladed disks, eliminating the need for building complex physical models. The accuracy of these methods is dependent on the size of the data, which, however, are often difficult to obtain. To overcome the challenge of insufficient data, this study introduces a Physics-Informed Neural Network Surrogate Model for Small-Sample Mistuned Bladed Disk (PINN-SMBD). This new method combines neural networks with the knowledge of bladed disk dynamics mainly reflected in the following three features: the integration of the governing equations of a mistuned bladed disk in the network architecture, the selection of the input and output according to the frequency independence of the response, and the data augmentation using the cyclic characteristic of bladed disks. Moreover, a dataset construction strategy is proposed that the use of datasets with high variance of mistuning can speed up model convergence and improve accuracy. Finally, a PINN-SMBD model for a dummy bladed disk is built by using only 30 samples which demonstrates remarkable accuracy.

Recursive Bayesian estimation of wind load on a monopile-supported offshore wind turbine using output-only measurements

Offshore wind turbine structures experience combined wind and wave loading during their lifetime, and the cyclic characteristics of these loads significantly impact the fatigue life of the support structure. Continuous monitoring of stress-related quantities, such as strain time histories at hotspot locations of the structure, can help to estimate the fatigue life. However, sparse measurements from the substructure necessitate using a digital twin as a tool for structural health monitoring by creating a virtual model. This virtual model relies on real-time input loads for virtual sensing and stress-related quantities prediction. However, the exact loading on these structural systems is often unknown or estimated with considerable uncertainty. This paper implements a recursive window-based Bayesian estimator for input load estimation and virtual sensing of acceleration and strain time history at unmeasured critical locations using output-only measurements. The estimator is numerically and experimentally validated in the context of input load estimation for an offshore wind turbine, and the results are compared with a traditional augmented Kalman filter and a linear regression approach for the quasi-static component of loading. The method is first demonstrated through a numerical study using a finite element model of a 6 MW offshore wind turbine, where input wind load time histories are accurately estimated. Then, the framework is applied to the real data measured from an offshore wind turbine in the North Sea. The study demonstrates the window-based Bayesian input estimator as a promising tool for the digital twinning of offshore wind turbines, demonstrating superior accuracy in input load estimations and full response predictions compared to the augmented Kalman filter and linear regression methods without the constraint of collocated measurements at input load locations.

Investigation on the cyclic buckling and plastic overstrength characteristics of steel shear links utilizing corrugated panels

This paper established and validated the finite element model (FEM) for novel steel shear links utilizing corrugated panels (CSSL), analyzed the stress and strain distributions of CSSL, and summarized the buckling characteristics and determination criteria for CSSL. Utilizing the FEM, the influence of CSSL configuration parameters on its buckling deformation capacity and plastic overstrength characteristics were analyzed. The analysis results indicated that: the decrease in the corrugated panel's sub-panel slenderness a/tw could significantly improve the buckling deformation capacity of CSSL, but had little influence on pre-buckling plastic overstrength characteristics; the decrease in sub-panel aspect ratio h/a and web aspect ratio e/h, as well as the increase in web corrugation angle θ was beneficial for the buckling deformation capacity of CSSL, but might decrease the plastic overstrength characteristics; the decrease in the equivalent links length coefficient eVp/Mp and the increase in structural steel strain-hardening value α had a slight influence on the buckling deformation capacity, but could significantly improve the plastic overstrength characteristics. Based on the analysis result, a theoretical prediction approach for the buckling deformation capacity and plastic overstrength characteristics was proposed, and the load-deformation skeleton curve model was also established, which was validated to exhibit good accuracy with compassion to experimental and finite element analysis results.

Hyperbolic Evolutionary Model for Equivalent Modulus of Sand and Characterization of Its Cyclic Hardening Properties

The cyclic hardening characteristics of soil hold significant importance for understanding its performance, and the evolution of the deformation modulus serves as a crucial indicator of the hardening properties. Deformations can be classified into elastic and plastic deformations and expressed in terms of modulus; however, their roles in the cyclic hardening process remain unclear. In this study, the elastic and plastic moduli were separated using the hyperbolic evolutionary model, which characterized the evolutionary properties of both to reflect the cyclic hardening process. A series of cyclic triaxial shear tests was conducted utilizing ISO sand and emery as test materials. A hyperbolic evolution model relating the equivalent modulus to the number of cycles was established, and the effect of various test conditions on the elastic modulus is discussed. The results indicate that: (1) the relationship between the equivalent modulus and the number of cycles is hyperbolic; and (2) the parameters k and b of the hyperbolic evolution model correspond to the elastic and plastic moduli, allowing for the separation of the evolution of both from that of the deformation modulus. The hyperbolic evolution model of the equivalent modulus proposed in this paper offers new insight into the cyclic hardening properties of sand.

A Study on the Water Management Knowledge of Traditional Villages from the Perspective of Stormwater Resilience—A Case Study of Changqi Ancient Village in Guangdong, China

With the advancement of resilience concepts, enhancing resilience capacity has become an effective approach to addressing rainwater and flooding issues. Most rural planning and construction efforts adopt urban planning models from economically developed regions, often leading to surface hardening, which subsequently causes drainage difficulties and severe surface water accumulation during the rainy season. In contrast, traditional Lingnan villages, exemplified by Guangdong’s Changqi Ancient Village, continue to function normally in flood-prone areas, suggesting that their water management knowledge merits investigation. Previous research on rainwater management in traditional Chinese villages has predominantly been qualitative, lacking scientific data support. This study employs an eco-social resilience perspective, combining field surveys and interviews with villagers, and utilizes the SWMM (Storm Water Management Model) software to conduct both qualitative and quantitative analyses of Changqi Ancient Village. The findings reveal the following: (1) The SWMM effectively quantifies rainwater and flood management in traditional villages. (2) From an ecological resilience perspective, the village’s geographical location is crucial. The topography, along with a rainwater regulation system comprising rivers, ponds, ditches, and permeable pavements, significantly influences the village’s drainage performance. (3) From a social resilience perspective, community participation is vital to the long-term stable development of traditional villages. This includes post-disaster collective fundraising by villagers for the restoration of rainwater and flood management facilities, the formulation of village regulations, and the construction and restoration of spiritual sites. (4) From an eco-social resilience perspective, the eco-social resilience system exhibits adaptive cyclical characteristics, where the geographical environment and the local economy significantly shape the ecological spatial patterns of Changqi, while positive interaction between nature and human society ensures the system’s dynamic equilibrium.

Synthesis of spherical LiFePO₄ microparticles with encapsulated carbon nanotubes for high-power lithium-ion batteries

Lithium ferrophosphate – LiFePO₄(LFP) – is one of the widely studied and used materials for lithium-ion batteries. However, one of the main drawbacks of LFP is its poor electrical conductivity. To address this issue, we propose an effective approach based on encapsulating carbon nanotubes within the volume of LFP particles in the volume of spherical LFP particles. Electrodes based on the obtained materials exhibit more aTₜᵣactive electrochemical characteristics than LFP obtained by the standard method: increased specific capacity (62 and 92 mAh g–1 at a current density of 20C for LFP and LFP/SWCNT, respectively), stability of cyclic characteristics (preservation of 98% capacity after 100 charge/discharge cycles for LFP/SWCNT and 96.5% for LFP), as well as reduced charge transfer resistance. Encapsulation of SWCNT into the structure of iron phosphate during deposition is an easy-to-implement approach to formation modified LFP-based cathodes with improved characteristics, which expands the possibilities of their practical application in high-power lithium-ion batteries.

Cyclic flow cut-off characteristics of gas-liquid two-phase flow in pipeline-riser system and prediction of its occurring condition

In offshore oil and gas fields, the prediction of gas-liquid two-phase flow pattern is of great importance for the design and operation of pipeline-riser systems. However, no special attention was put on the mechanism of periodic flow cut-off at the riser outlet, which is an inherent characteristic of certain flow patterns directly related to operation safety, in the study of flow pattern transition. In this study, differential pressure signals are used to explore the internal correlation between the flow cut-off of gas and/or liquid phase at the riser bottom and the riser outlet. The flow patterns are classified based on continuous flow or flow cut-off at the riser outlet. Then, the flow pattern transition mechanisms are studied from the view of the condition under which flow cut-off will appear. At high gas and low liquid velocities, the mechanism can be explained by a conventional theory; while at high gas and high liquid velocities, dissipation of hydrodynamic slugs becomes the major reason for flow pattern transition; and a unified model is introduced to predict the dissipation. At low gas and high liquid velocities, the condition for gas-liquid eruption can still describe the flow pattern transition, but it is modified by the slug dissipation model. At higher pressure, the lasting time of gas cut-off at the riser elbow becomes shorter, and a threshold can be set to decide whether it can be ignored. The predicted results are in good agreement with the flow pattern maps under different pipeline structures and fluid properties, and the reason why flow cut-off disappears in the experimental loop at high pressure of 10 MPa is successfully explained.

Short-Term Prediction of Origin–Destination Passenger Flow in Urban Rail Transit Systems with Multi-Source Data: A Deep Learning Method Fusing High-Dimensional Features

Short-term origin–destination (OD) passenger flow forecasting is crucial for urban rail transit enterprises aiming to optimise transportation products and increase operating income. As there are large-scale OD pairs in an urban rail transit system, OD passenger flow cannot be obtained in real time (temporal hysteresis). Additionally, the distribution characteristics are also complex. Previous studies mainly focus on passenger flow prediction at metro stations, while few methods solve the OD passenger flow prediction problems of an urban rail transit system. In view of this, we propose a novel deep learning method fusing high-dimensional features (HDF-DL) with multi-source data. The HDF-DL method is combined with three modules. The temporal module incorporates the time-varying, trend, and cyclic characteristics of OD passenger flow, while the latest OD passenger flow time sequence (within 1 h) is excluded from the time-varying characteristics. In the spatial module, the K-means and K-shape algorithms are used to classify OD pairs from multiple perspectives and capture the spatial features, reducing the difficulty of OD passenger flow predictions with large-scale and complex characteristics. Weather factors are considered in the external feature module. The HDF-DL method is tested on a large-scale metro system in China, in which eight baseline models are designed. The results show that the HDF-DL method achieves high prediction accuracy across multiple time granularities, with a mean absolute percentage error of about 10%. OD passenger flow in every departure time interval can be predicted with high and stable accuracy, effectively capturing temporal characteristics. The modular design of HDF-DL, which fuses high-dimensional features and employs appropriate neural networks for different data types, significantly reduces prediction errors and outperforms baseline models.

Synergistic enhancement of polycyclic aromatic hydrocarbon degradation by Arthrobacter sp. SZ-3 and Pseudomonas putida B6-2 under high Tween80 concentration: mechanisms and efficiency.

This study investigates the advantages of combined microbial degradation of polycyclic aromatic hydrocarbons (PAHs) in reducing the inhibitory effects of high-concentration eluents commonly used in soil washing. A microbial synergistic strategy was proposed using Arthrobacter sp. SZ-3 and Pseudomonas putida B6-2 as the key bacteria in the presence of Tween 80. The results show that in systems with Tween 80, the SZ-3 strain exhibits a strong capacity to degrade three types of PAH compounds, while the B6-2 strain follows multiple degradation pathways. Mixed bacteria achieved degradation rates 60.70% higher than single bacteria at varying concentrations of Tween 80. Additionally, the average growth rates of mixed bacteria increased by 1.17-1.37 times, aligning with the changes in the functional group. Protein activity detection within each degradation system corresponded with growth quantity and the cyclic variation characteristics of ETS enzyme activity. Notably, the ETS activity of mixed bacteria was 150% higher than that of single bacteria. At a Tween 80 concentration of 500 mg/L, the degradation rates of PAHs (Phe, Flu, Pyr) by mixed bacteria were significantly higher than those by single bacteria. The catechol 1,2-dioxygenase activity of mixed bacteria was 2.30 times higher than that of single bacteria. While Tween 80 did not alter the PAH degradation pathways, it significantly influenced the accumulation amount and duration of the characteristic intermediate product. This provides a reference for the remediation of recalcitrant pollutants under conditions involving high-concentration surfactants.

Damage Analysis of Rolling Stock Automatic Coupler under Cyclic Loads

To ensure the operational safety of the automatic couplers of a rolling stock subjected to cyclic loading, reliability and residual service life must be determined. This paper involved the prediction of the durability of the automatic coupler SA3 by analytical summation of cyclic damage. During the investigation, the cyclic characteristics and damage modes of the automatic coupler material that influence the accumulation of damage are determined. The stress and strain state assessment model was developed using a 3D finite element method for the automatic coupler housing as a geometrically complex component. A methodology was used to assess damage per load cycle that is applicable to any sequence of automatic coupler load cycles. For this purpose, the authors used low-cycle stationary load dependencies that account for quasi-static and low-cycle fatigue damage. The investigation showed that a coupler may develop a crack due to accumulated quasi-static and fatigue damage. For damage summation, the dependences of low-cycle stationary stress-controlled load accounting for low-cycle, quasi-static fatigue damage are proposed in view of the variation of the load on the automatic coupler during operation depending on the weight of the rolling stock, velocity, and railway relief. The proposed methodology is applicable to the calculation of other housings under similar loading conditions.

Study on the Cyclic Impact Mechanical Characteristics of Coal under Confining Pressure.

Coal damage accumulation and strength deterioration caused by mining-induced disturbances in deep mines are among the factors influencing the occurrence of dynamic disasters such as rock bursts. To study the mechanical deformation and failure characteristics of coal masses under both cyclic impact and confining pressure, SHPB experiments were performed to systematically analyze the behavior of coal samples under 1, 2, and 3 cycles at impact pressures of 0.25, 0.30, 0.35, 0.40, and 0.45 MPa. To study the influence of pressure and impact frequency on the dynamic mechanical failure of coal samples, a weakening effect model of coal samples under confining pressure was established, revealing the dynamic mechanical characteristics and failure mechanism of coal samples under different impact pressures and impact frequencies. The confining pressure SHPB results reveal that the number of cycles and impact pressure are inversely proportional to the peak stress and are proportional to the degree of weakening. The peak stress weakening coefficient of the coal samples under the different impact pressures ranged from 28.5 to 73.2%, and a linear weakening relationship with the number of cycles was obtained. The coal exhibited an end effect-controlled Y-shaped failure mode under both confining pressure and dynamic loading. This study provides an experimental reference for preventing the energy absorption and erosion of weak structures around rock bursts and improving the stability of supporting structures.

Experimental study on seismic performance of assembled buckling-restrained brace with low yield point steel

Based on the design concept of seismic resilience, which aims to achieve controllable damage during earthquakes and rapid post-earthquake functional recovery within the structure, an assembled buckling-restrained brace with low yield point steel (ALYBRB) was proposed. To evaluate its seismic performance, quasi-static cyclic loading tests were conducted on five ALYBRB specimens. The influence of core steel material, bolt spacing of the external restraint system, and the gap between the core and the external restraint system on the seismic performance of ALYBRBs were investigated. The results indicated that the ALYBRBs exhibited superior plastic deformation capacity, stable energy dissipation capacity, and exceptional fatigue performance, as well as significant cyclic hardening characteristics and hysteretic properties with good symmetry. The cumulative plastic deformation coefficient (CPD) of ALYBRBs with LYP100 and LYP160 steel were 2.33 times and 1.51 times greater than that with Q235 steel, respectively. The maximum equivalent viscous damping coefficients of all specimens can achieve a range of 73.0 % to 86.2 % of the theoretically maximum value. The strain hardening adjustment factors of all specimens ranged between 1.34 and 1.90. The average compression strength adjustment factor for the properly designed ALYBRB specimens was 1.12. Reducing the bolt spacing can effectively inhibit the multi-wave buckling of the core, which is conducive to the improvement of energy dissipation efficiency in ALYBRBs. ALYBRB specimen with excessive gap exhibited decreased ductility, energy dissipation efficiency, and fatigue performance, and its out-of-plane deformation mode was a combination of bending deformation in the constrained yield segment and the transition segment deformation.

Effects of Over-Sintering on Cyclic Calcination and Carbonization of Natural Limestone for CO2 Capture

To know the sustainable performance of calcium-based adsorbents is one of the important aspects to realize efficient and economical carbon capture, and to systematically study the properties of natural adsorbents is conducive to their industrialization. The cyclic calcination and carbonation characteristics of a typical natural limestone were investigated using a thermal gravimetric analyzer. Two kinds of over-sintering conditions were selected to emphatically study the cyclic separation of CO2 from limestones through prolonging the calcination time and increasing the calcination temperature. The results showed that the untimely end of the chemical reaction control stage caused by excessive sintering is the direct reason for the reduction in cyclic carbonation conversion, and the changes in surface morphology of calcined products due to pore collapse and fusion are the fundamental reasons for the reduction in cyclic carbonation conversion. The excessive sintering caused by extending the calcining time or increasing the calcining temperature has great inhibition on this cycle only; the inhibition decreases rapidly in subsequent cycles. In addition, SEM and BET–BJH tests further confirm the influence of the over-sintering phenomenon. With the further increase in cycle number, the early excessive sintering has certain stimulative effects on the subsequent carbonation reaction. It is expected to provide a reference for the subsequent research and development of natural calcium-based adsorbents.

A systematic method of long-sequence prediction of natural gas supply in IES based on spatio-temporal causal network of multi-energy

Natural gas plays an important role in the energy peak-shaving process of Integrated Energy Systems (IES). Accurate prediction of natural gas supply over longer time scales is one of the most important conditions to ensure the stability and security of IES energy supply. However, as the sequence length of the predicted time series increases, it becomes more difficult to extract valid dependencies from the data. At the same time, there are complex spatio-temporal coupling characteristics of various energy resources in the IES, which makes the construction of long sequence prediction models for natural gas supply very difficult. To solve this problem, we propose a systematic method for long-sequence prediction with natural gas supply in IES based on spatio-temporal causal network of multi-energy. First, the proposed approach uses a causal analysis algorithm to represent the complex coupled spatio-temporal relationships of multiple energy resources in an IES. Then, the natural gas time-series are decomposed through the Variational Modal Decomposition (VMD), to reveal its inherent trend and cyclical characteristics. Finally, the long-sequence prediction model is proposed by fusing the attention mechanism into Graph Convolutional Neural Network (GCN). Attentional mechanisms are introduced to obtain important long-term dependencies in the long sequence prediction process. We use a integrated energy dataset from Spain to test the validity and superiority of the method. The results show that the proposed model in this paper improves the Root Mean Square Error (RMSE) by at least 9.5% and reduces the Mean Absolute Error (MAE) by at least 14.5% compared to several baseline models.

Effects of bacterial strains on undrained cyclic behavior of bio-cemented sand considering wetting and drying cycles

The microbial-induced calcite precipitation (MICP) technique has been developed as a sustainable methodology for the improvement of the engineering characteristics of sandy soils. However, the efficiency of MICP-treated sand has not been well established in the literature considering cyclic loading under undrained conditions. Furthermore, the efficacy of different bacterial strains in enhancing the cyclic properties of MICP-treated sand has not been sufficiently documented. Moreover, the effect of wetting-drying (WD) cycles on the cyclic characteristics of MICP-treated sand is not readily available, which may contribute to the limited adoption of MICP treatment in field applications. In this study, strain-controlled consolidated undrained (CU) cyclic triaxial testing was conducted to evaluate the effects of MICP treatment on standard Ennore sand from India with two bacterial strains: Sporosarcina pasteurii and Bacillus subtilis. The treatment durations of 7 d and 14 d were considered, with an interval of 12 h between treatments. The cyclic characteristics, such as the shear modulus and damping ratio, of the MICP-treated sand with the different bacterial strains have been estimated and compared. Furthermore, the effect of WD cycles on the cyclic characteristics of MICP-treated sand has been evaluated considering 5–15 cycles and aging of samples up to three months. The findings of this study may be helpful in assessing the cyclic characteristics of MICP-treated sand, considering the influence of different bacterial strains, treatment duration, and WD cycles.

Cyclic inelastic performance evaluation of locking bolt demountable shear connectors in steel-concrete composite structures

This study extends the research on the Locking Bolt Demountable Shear Connector (LBDSC), previously introduced and extensively analysed under monotonic loading through both experimental and numerical methods. The focus here shifts towards the inelastic cyclic performance of the LBDSC, a critical aspect for applications in seismic regions. The LBDSC, designed for use in composite floors or decks, such as in-situ solid slabs, profiled deck slabs, or precast slabs in buildings and bridges, features a grout-filled steel tube bolted to the top flange of steel sections. The design incorporates a unique 'locking bolt' technique to counteract the influence of construction tolerances on undesirable initial slip behaviour, significantly facilitating the deconstruction and reuse of steel sections without the need for recycling. Following the Eurocode 4 guidelines, a series of standard push out tests were conducted to explore the LBDSC's inelastic cyclic characteristics. The experimental results confirm the LBDSC's capability for high strength, high initial stiffness, and adequate slip capacity under cyclic loading, with ductile shear failure modes observed at the bolt shank and local concrete crushing above the steel flange. The cyclic loading tests reveal a larger zone of damaged concrete compared to monotonic loading conditions, yet the monotonic and cyclic force-slip curves closely align. Based on these findings, and supported by validated finite element analyses, this paper proposes theoretical monotonic and cyclic models for LBDSC under push out loading, aimed at accurately predicting the load-slip response. These models are intended to facilitate the efficient analyses, design and numerical modelling of composite structures incorporating LBDSCs, and to support the broader adoption of LBDSCs in earthquake-prone areas, promoting sustainable steel-concrete composite construction practices.