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1 – 10 of 574Jingxiao Shu, Yao Lu and Yan Liang
To understand the seismic behavior of reinforced concrete (RC) beams confined by corroded stirrups, low-reversed cyclic loading tests were carried out on seven RC beam specimens…
Abstract
Purpose
To understand the seismic behavior of reinforced concrete (RC) beams confined by corroded stirrups, low-reversed cyclic loading tests were carried out on seven RC beam specimens with different stirrup corrosion levels and stirrup ratios to investigate their mechanical characteristics.
Design/methodology/approach
The failure mode, hysteresis behavior, skeleton curves, ductility, stiffness degradation and energy dissipation behavior of RC specimens are compared and discussed. The experimental results showed that the restraint of concrete provided by corroded stirrups is reduced, which leads to a decline in seismic performance.
Findings
For the specimens with the same ratios of stirrup, as the corrosion level increased, the load-carrying capacity, stiffness, plastic deformation capacity and energy-dissipation capacity dropped significantly. Compared with the uncorroded specimen, the failure modes of specimens with high corrosion level changed from ductile bending failure to brittle failure. For the specimens with the same levels of corrosion, the higher the stirrup ratio was, the stronger the restraint effect of the stirrups on the concrete, and the seismic behavior of the specimens was obviously improved.
Originality/value
In this paper, a total of seven full-size RC beam specimens at joints with different stirrup corrosion levels and stirrup ratios were designed and constructed to explore the influences of corrosion levels and stirrup ratios of stirrups on the seismic performances. The failure modes, strain of reinforcement, hysteretic curves, skeleton curves, stiffness degradation and ductility factor of RC specimens are compared and discussed.
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Chang Liu, Shiwu Yang, Yixuan Yang, Hefei Cao and Shanghe Liu
In the continuous development of high-speed railways, ensuring the safety of the operation control system is crucial. Electromagnetic interference (EMI) faults in signaling…
Abstract
Purpose
In the continuous development of high-speed railways, ensuring the safety of the operation control system is crucial. Electromagnetic interference (EMI) faults in signaling equipment may cause transportation interruptions, delays and even threaten the safety of train operations. Exploring the impact of disturbances on signaling equipment and establishing evaluation methods for the correlation between EMI and safety is urgently needed.
Design/methodology/approach
This paper elaborates on the necessity and significance of studying the impact of EMI as an unavoidable and widespread risk factor in the external environment of high-speed railway operations and continuous development. The current status of research methods and achievements from the perspectives of standard systems, reliability analysis and safety assessment are examined layer by layer. Additionally, it provides prospects for innovative ideas for exploring the quantitative correlation between EMI and signaling safety.
Findings
Despite certain innovative achievements in both domestic and international standard systems and related research for ensuring and evaluating railway signaling safety, there’s a lack of quantitative and strategic research on the degradation of safety performance in signaling equipment due to EMI. A quantitative correlation between EMI and safety has yet to be established. On this basis, this paper proposes considerations for research methods pertaining to the correlation between EMI and safety.
Originality/value
This paper overviews a series of methods and outcomes derived from domestic and international studies regarding railway signaling safety, encompassing standard systems, reliability analysis and safety assessment. Recognizing the necessity for quantitatively describing and predicting the impact of EMI on high-speed railway signaling safety, an innovative approach using risk assessment techniques as a bridge to establish the correlation between EMI and signaling safety is proposed.
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Zejian Huang, Yihua Cao and Yanyang Wang
The sandy environment is one of the typical environments in which helicopters operate. Air-sand two-phase flow in sandy environments may be an important factor affecting flight…
Abstract
Purpose
The sandy environment is one of the typical environments in which helicopters operate. Air-sand two-phase flow in sandy environments may be an important factor affecting flight safety. Taking a typical example, this paper aims to investigate the aerodynamic and rotor trim characteristics of the UH-60 helicopter in sandy environments.
Design/methodology/approach
A computational study is conducted to simulate the air-sand flow over airfoils based on the Euler–Lagrange framework. The simulation uses the S-A turbulence model and the two-way momentum coupling methodology. Additionally, the trim characteristics of the UH-60 rotor are calculated based on the isolated rotor trim algorithm.
Findings
The simulation results show that air-sand flow significantly affects the aerodynamic characteristics of the SC1095 airfoil and the SC1094R8 airfoil. The presence of sand particles leads to a decrease in lift and an increase in drag. The calculation results of the UH-60 helicopter rotor indicate that the thrust decreases and the torque increases in the sandy environment. To maintain a steady forward flight in sandy environments, it is necessary to increase the collective pitch and the longitudinal cyclic pitch.
Originality/value
In this paper, the aerodynamic characteristics of airfoils and the trim characteristics in the air-sand flow of the UH-60 helicopter are discussed, which might be a new view to analyse the impact of sandy environments on helicopter safety and manoeuvring.
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Rolling element bearings (REBs) are commonly used in rotating machinery such as pumps, motors, fans and other machineries. The REBs deteriorate over life cycle time. To know the…
Abstract
Purpose
Rolling element bearings (REBs) are commonly used in rotating machinery such as pumps, motors, fans and other machineries. The REBs deteriorate over life cycle time. To know the amount of deteriorate at any time, this paper aims to present a prognostics approach based on integrating optimize health indicator (OHI) and machine learning algorithm.
Design/methodology/approach
Proposed optimum prediction model would be used to evaluate the remaining useful life (RUL) of REBs. Initially, signal raw data are preprocessing through mother wavelet transform; after that, the primary fault features are extracted. Further, these features process to elevate the clarity of features using the random forest algorithm. Based on variable importance of features, the best representation of fault features is selected. Optimize the selected feature by adjusting weight vector using optimization techniques such as genetic algorithm (GA), sequential quadratic optimization (SQO) and multiobjective optimization (MOO). New OHIs are determined and apply to train the network. Finally, optimum predictive models are developed by integrating OHI and artificial neural network (ANN), K-mean clustering (KMC) (i.e. OHI–GA–ANN, OHI–SQO–ANN, OHI–MOO–ANN, OHI–GA–KMC, OHI–SQO–KMC and OHI–MOO–KMC).
Findings
Optimum prediction models performance are recorded and compared with the actual value. Finally, based on error term values best optimum prediction model is proposed for evaluation of RUL of REBs.
Originality/value
Proposed OHI–GA–KMC model is compared in terms of error values with previously published work. RUL predicted by OHI–GA–KMC model is smaller, giving the advantage of this method.
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Gang Yu, Zhiqiang Li, Ruochen Zeng, Yucong Jin, Min Hu and Vijayan Sugumaran
Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due…
Abstract
Purpose
Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.
Design/methodology/approach
Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.
Findings
The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.
Originality/value
This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.
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Meng Jiang, Yang Liu, Ke Li, Zhen Pan, Quan Sun, Yongzhe Xu and Yuan Tao
The purpose of this paper is to study the reliability of sintered nano-silver joints on bare copper substrates during high-temperature storage (HTS).
Abstract
Purpose
The purpose of this paper is to study the reliability of sintered nano-silver joints on bare copper substrates during high-temperature storage (HTS).
Design/methodology/approach
In this study, HTS at 250 °C was carried out to investigate the reliability of nano-silver sintered joints. Combining the evolution of the microstructure and shear strength of the joints, the degradation mechanisms of joints performance were characterized.
Findings
The results indicated that the degradation of the shear properties of sintered nano-silver joints on copper substrates was attributed to copper oxidation at the silver/copper interface and interdiffusion of interfacial elements. The joints decreased by approximately 57.4% compared to the original joints after aging for 500 h. In addition, severe coarsening of the silver structure was also an important cause for joints failure during HTS.
Originality/value
This paper provides a comparison of quantitative and mechanistic evaluation of sintered silver joints on bare copper substrates during HTS, which is of great importance in promoting the development of sintered silver technology.
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Bingbing Qi, Lijun Xu and Xiaogang Liu
The purpose of this paper is to exploit the multiple-Toeplitz matrices reconstruction method combined with quadratic spatial smoothing processing to improve the…
Abstract
Purpose
The purpose of this paper is to exploit the multiple-Toeplitz matrices reconstruction method combined with quadratic spatial smoothing processing to improve the direction-of-arrival (DOA) estimation performance of coherent signals at low signal-to-noise ratio (SNRs).
Design/methodology/approach
An improved multiple-Toeplitz matrices reconstruction method is proposed via quadratic spatial smoothing processing. Our proposed method takes advantage of the available information contained in the auto-covariance matrices of individual Toeplitz matrices and the cross-covariance matrices of different Toeplitz matrices, which results in a higher noise suppression ability.
Findings
Theoretical analysis and simulation results show that, compared with the existing Toeplitz matrix processing methods, the proposed method improves the DOA estimation performance in cases with a low SNR. Especially for the cases with a low SNR and small snapshot number as well as with closely spaced sources, the proposed method can achieve much better performance on estimation accuracy and resolution probability.
Research limitations/implications
The study investigates the possibility of reusing pre-existing designs for the DOA estimation of the coherent signals. The proposed technique enables achieve good estimation performance at low SNRs.
Practical implications
The paper includes implications for the DOA problem at low SNRs in communication systems.
Originality/value
The proposed method proved to be useful for the DOA estimation at low SNR.
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Keywords
Yuan Li, Yanzhi Xia, Min Li, Jinchi Liu, Miao Yu and Yutian Li
In this paper the aim is that Aramid/alginate blended nonwoven fabrics were prepared, and the flame retardancy of the blended nonwoven fabrics was studied by thermogravimetric…
Abstract
Purpose
In this paper the aim is that Aramid/alginate blended nonwoven fabrics were prepared, and the flame retardancy of the blended nonwoven fabrics was studied by thermogravimetric analysis, vertical flame test, limiting oxygen index (LOI) and cone calorimeter test.
Design/methodology/approach
The advantages of different fibers can be combined by blending, and the defects may be remedied. The study investigates whether incorporating alginate fibers into aramid fibers can enhance the flame retardancy and reduce the smoke production of prepared aramid/alginate blended nonwoven fabrics.
Findings
Thermogravimetric analysis indicated that alginate fibers could effectively inhibit the combustion performance of aramid fibers at a higher temperature zone, leaving more residual chars for heat isolation. And vertical flame test, LOI and cone calorimeter test testified that the incorporation of alginate fibers improved the flame retardancy and fire behaviors. When the ratio of alginate fibers for aramid/alginate blended nonwoven fabrics reached 80%, the incorporation of alginate fibers could notably decreased peak-heat release rate (54%), total heat release (THR) (29%), peak-smoke production rate (93%) and total smoke production (86%). What is more, the lower smoke production rate and lower THR of the blends vastly reduced the risk of secondary injury in fires.
Originality/value
This study proposes to inhibit the flue gas release of aramid fiber and enhance the flame retardant by mixing with alginate fiber, and proposes that alginate fiber can be used as a biological smoke inhibitor, as well as a flame retardant for aramid fiber.
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Classification of remote sensing images (RSI) is a challenging task in computer vision. Recently, researchers have proposed a variety of creative methods for automatic recognition…
Abstract
Purpose
Classification of remote sensing images (RSI) is a challenging task in computer vision. Recently, researchers have proposed a variety of creative methods for automatic recognition of RSI, and feature fusion is a research hotspot for its great potential to boost performance. However, RSI has a unique imaging condition and cluttered scenes with complicated backgrounds. This larger difference from nature images has made the previous feature fusion methods present insignificant performance improvements.
Design/methodology/approach
This work proposed a two-convolutional neural network (CNN) fusion method named main and branch CNN fusion network (MBC-Net) as an improved solution for classifying RSI. In detail, the MBC-Net employs an EfficientNet-B3 as its main CNN stream and an EfficientNet-B0 as a branch, named MC-B3 and BC-B0, respectively. In particular, MBC-Net includes a long-range derivation (LRD) module, which is specially designed to learn the dependence of different features. Meanwhile, MBC-Net also uses some unique ideas to tackle the problems coming from the two-CNN fusion and the inherent nature of RSI.
Findings
Extensive experiments on three RSI sets prove that MBC-Net outperforms the other 38 state-of-the-art (STOA) methods published from 2020 to 2023, with a noticeable increase in overall accuracy (OA) values. MBC-Net not only presents a 0.7% increased OA value on the most confusing NWPU set but also has 62% fewer parameters compared to the leading approach that ranks first in the literature.
Originality/value
MBC-Net is a more effective and efficient feature fusion approach compared to other STOA methods in the literature. Given the visualizations of grad class activation mapping (Grad-CAM), it reveals that MBC-Net can learn the long-range dependence of features that a single CNN cannot. Based on the tendency stochastic neighbor embedding (t-SNE) results, it demonstrates that the feature representation of MBC-Net is more effective than other methods. In addition, the ablation tests indicate that MBC-Net is effective and efficient for fusing features from two CNNs.
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Wenjun Wang, Luting Shen, Yinsong Si, Islam MD Zahidul, Azim Abdullaev and Yubing Dong
Sodium alginate (Na-Alg) is a natural polysaccharide with a rich and renewable production that is widely used in the food, pharmaceutical and daily necessities industries, among…
Abstract
Purpose
Sodium alginate (Na-Alg) is a natural polysaccharide with a rich and renewable production that is widely used in the food, pharmaceutical and daily necessities industries, among other fields. The purpose of this study is to obtain a green and degradable shape memory material, calcium alginate (Ca-Alg) film was prepared and the mechanical properties, the shape memory effect of the film were investigated and confirmed.
Design/methodology/approach
The Ca-Alg films were prepared by Na-Alg, calcium chloride (CaCl2) solution, and flow extension method. Dissolve sodium alginate powder, remove bubbles, pour into petri dish, dry at 60°C, add calcium chloride solution cross-linking and finally dry naturally. The effect of CaCl2 solution concentration on the mechanical properties of the films were investigated and discussed by universal tensile tester. The shape memory behavior and degradation performance of thin films were verified and studied by the fold-deploy shape memory test and soil embedding method, respectively.
Findings
The Ca-Alg films exhibited good mechanical and shape memory properties, with a 72.2% shape memory fixity ratio and a 92.3% shape memory recovery ratio, respectively. For a period of 120 days, the film treated with a 6 wt% CaCl2 solution degraded at a rate of approximately 53%.
Research limitations/implications
Shape memory polymers (SMPs) as intelligent materials are an important research direction for the development of modern high-tech materials. On the other hand, plastic pollution is a major problem today; as a result, preparing green degradable SMPs is essential.
Originality/value
This study synthesized transparent and degradable shape memory Ca-Alg films using Na-Alg and CaCl2 solution and the flow extension method.
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