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The stress–strain behaviors of rockfill materials in dams are significantly affected by the anisotropy and grain crushing. However, these factors are rarely considered in numerical simulations of high rockfill dams. This study intends to develop a reasonable and practical constitutive model for rockfill materials to overcome the above problems.

The effects of anisotropy and grain crushing are comprehensively considered by the spatial position of the reference state line. After the improved generalized plasticity model for rockfill materials (referred to as the PZR model) is developed and verified by laboratory tests, it is used with the finite element method to simulate the stress–strain behaviors of the Nuozhadu high core rockfill dam.

The simulated results agree well with the laboratory tests data and the situ monitoring data, verifying the reliability and practicability of the developed PZR model.

A new anisotropic state parameter is proposed to reflect the nonmonotonic variation in the strength as the major principal stress direction angle varies. This advantage is verified by the simulation of a set of conventional triaxial tests with different inclination angles of the compaction plane. 2) This is the first time that the elastoplastic model is verified by the situ monitoring data of high core rockfill dams. The numerical simulation results show that the PZR model can well reflect the stress–strain characteristics of rockfill materials in high core rockfill dams and is better than the traditional EB model.

Prior marketing and hospitality studies have largely ignored the role of corporate social responsibility (CSR) in shaping frontline employees’ customer orientation. This study aims to investigate the impacts of employee perceived CSRs on customer orientation in hotel industry.

Through an onsite data collection from 642 frontline employees of 14 hotels in China, the moderated mediation model that links frontline employees’ perceptions of internal and external CSR to person-organization fit, work engagement and customer orientation were validated with the bootstrapping procedures.

The results reveal that a higher degree of perceived internal and external CSR leads to greater customer orientation through work engagement, and these indirect effects will be stronger with comparatively higher person-organization fit levels.

By clarifying the connection between perceived CSR initiatives and customer-oriented behaviors, this study offers inspiration for hospitality managers to devise, allocate and leverage CSR investments, strategies and practices.

To the best of the authors’ knowledge, this study is the first to verify a moderated mediation model that investigates the impacts of perceived CSRs (i.e. internal vs external) on customer orientation, which not only uncovers some neglected antecedents of customer orientation but also provides a more nuanced insight into perceived CSR-customer orientation linkages.

The purpose of this paper is to develop a simple analytical model for predicting the through-thickness distribution of residual stresses in a cold spray (CS) deposit-substrate assembly.

Layer-by-layer build-up of residual stresses induced by both the peening dominant and thermal mismatch dominant CS processes, taking into account the force and moment equilibrium requirements. The proposed model has been validated with the neutron diffraction measurements, taken from the published literature for different combinations of deposit-substrate assemblies comprising Cu, Mg, Ti, Al and Al alloys.

Through a parametric study, the influence of geometrical variables (number of layers, substrate height and individual layer height) on the through-thickness residual stress distribution and magnitude are elucidated. Both the number of deposited layers and substrate height affect residual stress magnitude, whereas the individual layer height has little effect. A good agreement has been achieved between the experimentally measured stress distributions and predictions by the proposed model.

The proposed model provides a more thorough explanation of residual stress development mechanisms by the CS process along with mathematical representation. Comparing to existing analytical and finite element methods, it provides a quicker estimation of the residual stress distribution and magnitude. This paper provides comparisons and contrast of the two different residual stress mechanisms: the peening dominant and the thermal mismatch dominant. The proposed model allows parametric studies of geometric variables, and can potentially contribute to CS process optimisation aiming at residual stress control.

This paper aims to understand the influence of cylinder liner temperature on friction power loss of piston skirts and the synergistic effect of cylinder liner temperature on lubrication and heat transfer between piston skirt and cylinder liner.

A method to calculate the influence of cylinder liner temperature on piston skirt lubrication is proposed. The lubrication is calculated by considering the different temperature distribution of the cylinder liner and corresponding piston temperature calculated by a new multilayer thermal resistance model. This model uses the inner surface temperature of the cylinder liner as the starting point, and the starting temperature corresponding to different positions of the piston is calculated using the time integral average. Besides, the transient heat transfer of mixed lubrication is taken into account. Six temperature distribution schemes of cylinder liner are designed.

Six temperature distributions of cylinder liner are designed, and the maximum friction loss is reduced by 34.4% compared with the original engine. The increase in temperature in the second part of the cylinder liner will lead to an increase in friction power loss. The increase of temperature in the third part of the cylinder liner will lead to a decrease in friction power loss. The influence of temperature change in the third part of the cylinder liner on friction power loss is greater than that in the second part.

The influence of different temperature distribution of cylinder liner on the lubrication and friction of piston skirt cylinder liner connection was simulated.

The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.

The VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.

This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.

By using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

This paper aims to study the tensile performance, deformation characteristics, auxeticity and stability of different auxetic tubular structures generated by cutting method and pattern scale factor (PSF) method using validated finite element analysis.

Two types of auxetic tubular structures were designed by a coordinate transformation method and the PSF adjustment method, respectively. ABAQUS/explicit solver was used for the large deformation analysis and the displacement of key nodes was extracted to calculate Poisson’s ratio value and evaluate the deformation of tubular structures.

The random cut method was not suitable for designing auxetic tubular structures. Vertical and horizontal cut approach was suitable, but the change of the tubular diameter was lower than the tubular structures generated by the PSF adjustment method.

Simple ways to generate auxetic tubular structure, which can be made into intelligent and foldable equipment, such as annuloplasty rings, angioplasty stents and oesophageal stents. By combined with shape memory polymer, various smart tubular materials and structures with various functions can be designed, especially in medical scaffold and other medical equipment fields.

The auxetic characteristic of tubular structure designed by using random cut method has been investigated for the first time. The outcome of this study would be very useful design tubular structures with better mechanical properties.

In the academic field of business management, several potential theories were established during the last decades to explain companies' decisions, organizational behavior, consumer patterns, and internationalization, among others. As a result, businesses and scholars were able to analyze and decide based on theoretical approaches to explain the current conditions of the market. Secondary research was conducted to collect more than 36 management theories. This chapter aims to develop the most famous theories related to business applied in the international field. The novelty of this chapter relies on the compilation of recognized previous research studies from the academic literature and evidence in international business.

The purpose is to analyze and discuss the sustainable development (SD) and financing risk assessment (FRA) of resource-based industrial clusters under the Internet of Things (IoT) economy and promote the application of Machine Learning methods and intelligent optimization algorithms in FRA.

This study used the Support Vector Machine (SVM) algorithm that is analyzed together with the Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm. First, Yulin City in Shaanxi Province is selected for case analysis. Then, resource-based industrial clusters are studied, and an SD early-warning model is implemented. Then, the financing Risk Assessment Index System is established from the perspective of construction-operation-transfer. Finally, the risk assessment results of Support Vector Regression (SVR) and ACO-based SVR (ACO-SVR) are analyzed.

The results show that the overall sustainability of resource-based industrial clusters and IoT industrial clusters is good in the Yulin City of Shaanxi Province, and the early warning model of GA-based SVR (GA-SVR) has been achieved good results. Yulin City shows an excellent SD momentum in the resource-based industrial cluster, but there are still some risks. Therefore, it is necessary to promote the industrial structure of SD and improve the stability of the resource-based industrial cluster for Yulin City.

The results can provide a direction for the research on the early warning and evaluation of the SD-oriented resource-based industrial clusters and the IoT industrial clusters, promoting the application of SVM technology in the engineering field.

Psychosocial factors have received increasing attention regarding significantly influencing safety in the construction industry. This research attempts to comprehensively summarize psychosocial factors related to safety performance of construction workers. In the context of coronavirus disease 2019, some typical psychosocial factors are selected to further analyze their influence mechanism of safety performance.

First, a literature review process was conducted to identify and summarize relevant psychosocial factors. Then, considering the impact of the epidemic, hypotheses on the relationship between six selected psychosocial factors (i.e. work stress, role ambiguity, work–family conflict, autonomy, social support and interpersonal conflict) and safety performance were proposed, and a hypothetical model was developed based on job demands-resources theory. Finally, a meta-analysis was used to examine these hypotheses and the model.

The results showed these psychosocial factors indirectly influenced workers’ safety performance by impacting on their occupational psychology condition (i.e. burnout and engagement). Work stress, role ambiguity, work–family conflict and interpersonal conflict were negatively related to safety performance by promoting burnout and affecting engagement. Autonomy and social support were positively related to safety performance by improving work engagement and reducing burnout.

This research is the pioneer systematically describing the overall picture of psychosocial factors related to the safety performance of construction workers. Through deeply discussed the mechanism of psychosocial factors and safety performance, it could provide a reference for the theory and application of psychosocial factors in the field of construction safety management.

Continuous and stable tracking of the low-altitude maneuvering targets is usually difficult due to terrain occlusion and Doppler blind zone (DBZ). This paper aims to present a non-myopic scheduling method of multiple radar sensors for tracking the low-altitude maneuvering targets. In this scheduling problem, the best sensors are systematically selected to observe targets for getting the best tracking accuracy under maintaining the low intercepted probability of a multi-sensor system.

First, the sensor scheduling process is formulated within the partially observable Markov decision process framework. Second, the interacting multiple model algorithm and the cubature Kalman filter algorithm are combined to estimate the target state, and the DBZ information is applied to estimate the target state when the measurement information is missing. Then, an approximate method based on a cubature sampling strategy is put forward to calculate the future expected objective of the multi-step scheduling process. Furthermore, an improved quantum particle swarm optimization (QPSO) algorithm is presented to solve the sensor scheduling action quickly. Optimization problem, an improved QPSO algorithm is presented to solve the sensor scheduling action quickly.

Compared with the traditional scheduling methods, the proposed method can maintain higher target tracking accuracy with a low intercepted probability. And the proposed target state estimation method in DBZ has better tracking performance.

In this paper, DBZ, sensor intercepted probability and complex terrain environment are considered in sensor scheduling, which has good practical application in a complex environment.