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Construction fall-from-height accidents are not only caused by a single factor but also by the risk coupling between two or more factors. The purpose of this paper is to quantitatively analyze the risk coupling relationships between multiple factors and identify critical factors in construction fall-from-height accidents.

A cause analysis framework was established from the perspective of human, machine, material, management and environmental factors. The definition, the classification and the process of risk coupling were proposed. The data from 824 historical accident reports from 2011 to 2021 were collected on government websites. A risk coupling analysis model was constructed to quantitatively analyze the risk coupling relationships of multiple factors based on the N-K model. The results were classified using K-means clustering analysis.

The results indicated that the greater the number of causal factors involved in risk coupling, the higher the risk coupling value and the higher the risk of accidents. However, specific risk coupling combinations occurred when the number of their coupling factors was not large. Human, machine and material factors were determined to be the critical factors when risk coupling between them tended to pose a greater risk of accidents.

This study established a cause analysis framework from five aspects and constructed a theoretical model to quantitatively analyze multi-factor coupling. Several suggestions were proposed for construction units to manage accident risks more effectively by controlling the number of factors and paying more attention to critical factors coupling and management and environmental factors.

The floating ring generates elastic deformation as the film pressure for high-speed floating ring bearings (FRBs). The purpose of this study is to investigate the influence of ring elastic deformation on the performance of a hydrodynamic/hydrostatic FRB, including floating ring equilibrium and minimum film thickness.

The finite element method and finite difference method are used to solve thermohydrodynamic (THD) lubrication models, including the Reynolds equation, energy equation and temperature–viscosity equation. The deformation matrix method is applied to solve the elastic deformation equation, and then the deformation distribution, floating ring equilibrium and minimum film thickness are investigated. The maximum pressure is compared with the published article to verify the mathematical models.

The deformation value increases with the growth of shaft speed; owing to elastic deformation on the film reaction force and friction moment, the ring achieves equilibrium at a new position, and the inner eccentricity increases while the ring-shaft speed ratio declines. The minimum film thickness declines with the growth of inlet temperature, and the outer film tends to rupture considering elastic deformation at a higher temperature.

The floating ring elastic deformation is coupled with the THD lubrication equations to study ring deformation on the hydrodynamic/hydrostatic FRB lubrication mechanism. The elastic deformation of floating ring should be considered to improve analysis accuracy for FRBs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0139/

Prior investigations concerning misalignment resulting from journal deformation typically relied on predefined misaligned angles. Nevertheless, scant attention has been devoted to the determination of these misaligned angles. Furthermore, existing studies commonly treat the journal as rigid under such circumstances. Therefore, the present study aims to introduce a framework for determining misaligned angles and to compare outcomes between rigid and flexible journal configurations.

The bearing forces are considered as an external load leading to journal deformation. This deformation is calculated using the finite element method. The pressure distribution producing the bearing force is solved using the finite difference method. The mesh grids in the finite element and finite difference methods are matched for coupling calculation. By iteration, the pressure distribution of the lubricant film at the equilibrium position is determined.

Results show that the deformation-induced misalignment has a significant influence on the performance of the bearing when the journal flexibility is taken into account. The parametric study reveals that the misalignment relies on system parameters such as bearing length-diameter ratio and static load.

The investigation of this work provides a quantification method of misalignment of hydrodynamic bearings considering the elastic deformation of the journal, which assists in the design of bearing in a rotor-bearing system.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0337/

The purpose of this study is to evaluate three types of textures designed to enhance the tribological performance of static and dynamic pressure thrust bearings.

To explore the effects of different types of textures on tribological performance, the Reynolds equation is modified using lubrication theory and computational fluid dynamics methods while considering the influence of cavitation and turbulence on the physical field. In addition, the tribological performance is optimized through an improved selection algorithm based on Pareto envelope (PESA).

The results indicate that textured thrust bearings exhibit superior tribological performance compared to untextured ones. The circular texture outperforms other textures in terms of load-bearing and friction performance, with improvements of approximately 28.8% and 18.9%, respectively. In addition, the triangular texture exhibits the most significant temperature improvement, with a reduction of approximately 1.93%.

The study proposes three types of textures and evaluates the friction performance of thrust bearings by modifying the Reynolds equation. In addition, the optimal texture design is determined using an improved selection algorithm based on PESA.

This paper aims to study the influence of cylindrical texture parameters on the lubrication performance of static and dynamic pressure thrust bearings (hereinafter referred to as thrust bearings) and to optimize their lubrication performance using multiobjective optimization.

The influence of texture parameters on the lubrication performance of thrust bearings was studied based on the modified Reynolds equation. The objective functions are predicted through the BP neural network, and the texture parameters were optimized using the improved multiobjective ant lion algorithm (MOALA).

Compared with smooth surface, the introduction of texture can improve the lubrication properties. Under the optimization of the improved algorithm, when the texture diameter, depth, spacing and number are approximately 0.2 mm, 0.5 mm, 5 mm and 34, respectively, the loading capacity is increased by around 27.7% and the temperature is reduced by around 1.55°C.

This paper studies the effect of texture parameters on the lubrication properties of thrust bearings based on the modified Reynolds equation and performs multiobjective optimization through an improved MOALA.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The purpose of this paper is to solve the abrupt deterioration of lubricant performance in high-temperature conditions.

Three silver pyrazolyl methyl pyridine complexes with different morphologies were synthesized. A four-ball tribometer was used to assess the tribological characteristics as an additive for pentaerythritol oleate both independently and compound with 1-hexyl-3-methylimidazolium bis(trifluoromethane sulfonyl)imide.

The results showed that when silver complexes and ionic liquids (IL) act independently, sheet silver complex 1 and rod silver complex 2 exhibit good lubricating performance; the optimal antifriction concentration of the ILs is 0.25 Wt.%. The tribological results of the compounds additive of ILs and silver complexes indicate that the wear scar diameter of compound 1 decreased by 16.914%, the wear volume reduced by 7.44% and the lubrication effect surpassed that of the two substances individually; rod compound 2 exhibited an antagonistic effect, intensifying wear; compound 3’s lubrication effect fell between that of the two individual components.

The compound of sheet silver complexes and ILs effectively solves the agglomeration problem of micro/nano lubricant additives. When the interface fails, self-repair is completed, improving the stability and antiwear performance of the lubricating oil.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0128

This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic errors when measuring dynamic signals.

The dynamic characteristics of the force sensor are analyzed by modal analysis and negative step dynamic force calibration test, and the dynamic mathematical model of the force sensor is identified based on a generalized least squares method with a special whitening filter. Then, a compensation unit is constructed to compensate the dynamic characteristics of the force measurement system, and the compensation effect is verified based on the step and knock excitation signals.

The dynamic characteristics of the force sensor obtained by modal analysis and dynamic calibration test are consistent, and the time and frequency domain characteristics of the identified dynamic mathematical model agree well with the actual measurement results. After dynamic compensation, the dynamic characteristics of the force sensor in the frequency domain are obviously improved, and the effective operating frequency band is widened from 500 Hz to 1,560 Hz. In addition, in the time domain, the rise time of the step response signal is reduced from 0.29 ms to 0.17 ms, and the overshoot decreases from 26.6% to 9.8%.

An effective dynamic calibration and compensation method is proposed in this paper, which can be used to improve the dynamic performance of the strain-gauge-type force sensor and reduce the dynamic measurement error of the force measurement system.

The purpose of this paper is to achieve the multi-objective optimization design of novel tubular switched reluctance motor (TSRM).

First, the structure and initial dimensions of TSRM are obtained based on design criteria and requirements. Second, the sensitivity analysis rules, process and results of TSRM are performed. Third, three optimization objectives are determined by the average electromagnetic force, smoothing coefficient and copper loss ratio. The analytic hierarchy process-entropy method-a technique for order preference by similarity to an ideal solution-grey relation analysis comprehensive evaluation algorithm is used to optimize TSRM. Finally, a prototype is manufactured, a hardware platform is built and static and dynamic experimental validations are carried out.

The sensitivity analysis reveals that parameters significantly impact the performance of TSRM. The results of multi-objective optimization show that the average electromagnetic force and smoothing coefficient after optimization are better than before, and the copper loss ratio reduces slightly. The experimental and simulated results of TSRM are consistent, which verifies the accuracy of TSRM.

In this paper, only three optimization objectives are selected in the multi-objective optimization process. To improve the performance of TSRM, the heating characteristics, such as iron loss, can be considered as the optimization objective for a more comprehensive analysis of TSRM performance.

A novel motor structure is designed, combining the advantages of the TSRM and the linear motor. The established sensitivity analysis rules are scientific and suitable for the effects of various parameters on motor performance. The proposed multi-objective optimization algorithm is a comprehensive evaluation algorithm. It considers subjective weight and objective weight and fully uses the original data and the relational degree between the optimization objectives.

This study explores how chatbot gender and symbolic service recovery may improve the satisfaction of angry customers in the context of service failures. It provides a strategy for companies to deploy chatbots effectively in customer anger.

This research relies upon a systematic literature review to propose three hypotheses, and we recruit 826 participants to examine the effect of chatbot gender on angry customers through one lab study and one field study.

This research shows that female chatbots are more likely to increase the satisfaction of angry customers than male chatbots in service failure scenarios. In addition, symbolic recovery (apology vs. appreciation) moderates the effect of chatbot gender on angry customers. Specifically, male (vs. female) chatbots are more effective in increasing the satisfaction of angry customers when using the apology method, whereas female (vs. male) chatbots are more effective when using the appreciation method.

The rapid advancements in artificial intelligence technology have significantly enhanced the effectiveness of chatbots as virtual agents in the field of interactive marketing. Previous research has concluded that chatbots can reduce negative customer feedback following a service failure. However, these studies have primarily focused on the level of chatbot anthropomorphism and the design of conversational texts, rather than the gender of chatbots. Therefore, this study aims to bridge that gap by examining the effect of chatbot gender on customer feedback, specifically focusing on angry customers following service failures.