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The purpose of this study was to validate the feasibility of the proposed microstructure-based model by comparing the simulation results with experimental data. The study also aimed to investigate the relationship between the orientation of graphite flakes and the failure behavior of the material under compressive loads as well as the effect of image size on the accuracy of stress–strain behavior predictions.

This paper presents a microstructure-based model that utilizes the finite element method (FEM) combined with representative volume elements (RVE) to simulate the hardening and failure behavior of ferrite-pearlite matrix gray cast iron under uniaxial loading conditions. The material was first analyzed using optical microscopy, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD) to identify the different phases and their characteristics. High-resolution SEM images of the undeformed material microstructure were then converted into finite element meshes using OOF2 software. The Johnson–Cook (J–C) model, along with a damage model, was employed in Abaqus FEA software to estimate the elastic and elastoplastic behavior under assumed plane stress conditions.

The findings indicate that crack initiation and propagation in gray cast iron begin at the interface between graphite particles and the pearlitic matrix, with microcrack networks extending into the metal matrix, eventually coalescing to cause material failure. The ferritic phase within the material contributes some ductility, thereby delaying crack initiation.

This study introduces a novel approach by integrating microstructural analysis with FEM and RVE techniques to accurately model the hardening and failure behavior of gray cast iron under uniaxial loading. The incorporation of high-resolution SEM images into finite element meshes, combined with the J–C model and damage assessment in Abaqus, provides a comprehensive method for predicting material performance. This approach enhances the understanding of the microstructural influences on crack initiation and propagation, offering valuable insights for improving the design and durability of gray cast iron components.

Available information for evaluating the possibility of hospitality firm failure in emerging countries is often deficient. Oversampling can compensate for this but can also yield mixed samples, which limit prediction models’ effectiveness. This research aims to provide a feasible approach to handle possible mixed information caused by oversampling.

This paper uses mixed sample modelling (MSM) when evaluating the possibility of firm failure on enlarged hospitality firms. The mixed sample is filtered out with a mixed sample index through control of the noisy parameter and outliner parameter and meta-models are used to build MSM models for hospitality firm failure prediction, with performances compared to traditional models.

The proposed models are helpful in predicting hospitality firm failure in the mixed information situation caused by oversampling, whereas MSM significantly improves the performance of traditional models. Meanwhile, only partial mixed hospitality samples matter in predicting firm failure in both rich- and poor-information situations.

This research is helpful for managers, investors, employees and customers to reduce their hospitality-related risk in the emerging Chinese market. The two-dimensional sample collection strategies, three-step prediction process and five MSM modelling principles are helpful for practice of hospitality firm failure prediction.

This research provides a means of processing mixed hospitality firm samples through the early definition and proposal of MSM, which addresses the ranking information within samples in deficient information environments and improves forecasting accuracy of traditional models. Moreover, it provides empirical evidence for the validation of sample selection and sample pairing strategy in evaluating the possibility of hospitality firm failure.

In traditional methods, a one-directional distance transformation is employed to eliminate the near-singularity in the radial direction. However, when the projection point of the source point is near the boundary of the integral element, the near-singularity in the circumferential direction still exists, resulting in large errors in the numerical results. The purpose of this paper is to propose a bi-directional distance transformation for the elimination of near-singularities in two directions arising from the irregular integral element.

The sources of the circumferential near-singularity caused by irregular sub-triangular element are analyzed in this paper. A bi-directional distance transformation based on the (a, β) transformation is proposed to eliminate the near-singularities in the two directions. The (a, β) transformation is initially introduced to separate the integral variables and streamline the implementation of subsequent transformations. In the transformed (a, β) coordinate system, a new distance transformation applied in the circumferential direction is constructed.

With the proposed method, the radial and circumferential near-singularities are eliminated using two different distance transformations, respectively. Thus, accurate calculations of the nearly singular integrals can be achieved, irrespective of the shape of the integral element.

Numerical examples are presented to calculate the nearly singular integrals of different orders over both the linear integral element and the quadratic integral element. Comparative studies demonstrate that the proposed method significantly improves the accuracy of these calculations.

This study aims to use computational fluid dynamics (CFD) to understand and quantify the overall blockage within a transonic axial flow compressor (AFC), and to develop an efficient collaborative design optimization method for compressor aerodynamic performance and stability in conjunction with a surrogate-assisted optimization technique.

A quantification method for the overall blockage is developed to integrate the effect of regional blockages on compressor aerodynamic stability and performance. A well-defined overall blockage factor combined with efficiency drives the optimizer to seek the optimum blade designs with both high efficiency and wide-range stability. An adaptive Kriging-based optimization technique is adopted to efficiently search for Pareto front solutions. Steady and unsteady numerical simulations are used for the performance and flow field analysis of the datum and optimum designs.

The proposed method not only remarkably improves the compressor efficiency but also significantly enhances the compressor operating stability with fewer CFD calls. These achievements are mainly attributed to the improvement of specific flow behaviors oriented by the objectives, including the attenuation of the shock and weakening of the tip leakage flow/shock interaction intensity.

CFD-based design optimization of AFC is inherently time-consuming, which becomes even trickier when optimizing aerodynamic stability since the stall margin relies on a complete simulation of the performance curve. The proposed method could be a good solution to the collaborative design optimization of aerodynamic performance and stability for transonic AFC.

Water-based graphite lubricants have good lubricity in the process of metal forming, especially for hot-rolling seamless pipe. Although the use of water as a working fluid system instead of conventional mineral oil has many advantages for the fuel consumption, post cleaning and a new type of lubricant, the graphite contaminated the machine and workers for its physical properties. From the global environmental protection viewpoint, it is urgent to develop a kind of benign material.

Magnesium hydroxide which has the average particle size of 10 μm was chosen as a base material without further modification and pretreatments. On the HT-1000 high-temperature tribometer, the influence of temperature and lubricant materials on the friction coefficient was studied. The tribological performance at 900^°C provided evidence under high temperature for exploring a new lubricant material.

Tap water-based brucite lubricant will open a new chapter in the industrial lubrication, effectively avoiding many unfavorable factors caused by graphite lubrication, such as conductivity, pollution and energy loss. Meanwhile, it expanded the application of brucite as flame-retardant agent, catalyst, water treatment agent and so on.

It is a new and environmental lubricant to tap water-based brucite lubricant. And specially, the preparation process of lubricant is simple and economical.

A new wire arc additive manufacturing (WAAM) process combined with gravity-driven powder feeding was developed to fabricate components of tungsten carbide (WC)-reinforced iron matrix composites. The purpose of this study was to investigate the particle transportation mechanism during deposition and determine the effects of WC particle size on the microstructure and properties of the so-fabricated component.

Thin-walled samples were deposited by the new WAAM using two WC particles of different sizes. A series of in-depth investigations were conducted to reveal the differences in the macro morphology, microstructure, tensile performance and wear properties.

The results showed that inward convection and gravity were the main factors affecting WC transportation in the molten pool. Large WC particles have higher ability than small particles to penetrate into the molten pool and survive severe dissolution. Small WC particles were more likely to be completely dissolved around the top surface, forming a thicker region of reticulate (Fe, W)₆C. Large WC particles can slow down the inward convection more, thereby leading to an increase in width and a decrease in the layer height of the weld bead. The mechanical properties and wear resistance significantly increased owing to reinforcement. Comparatively, samples with large WC particles showed inferior tensile properties owing to their higher susceptibility to cracks.

Fabricating metal matrix composites through the WAAM process is a novel concept that still requires further investigation. Apart from the self-designed gravity-driven powder feeding, the unique aspects of this study also include the revelation of the particle transportation mechanism of WC particles during deposition.

The purpose of this study is to solve the key technical problems of the practical application of electric robots. The UHV multi-split transmission line power cable operation robot is an important equipment to ensure the reliable operation of high voltage lines and is a useful exploration to realize high-quality power transmission. As the robot system platform equipment mature and operation environment gradually become more complex, the double arm coordination motion control in extreme environment becomes one of the main bottleneck for its practical in power system.

This paper summarizes the key technologies related to power cable robots, and aims at key technical indicators such as operation reliability, operation efficiency and operation quality in the robot’s practical process. The dynamic evolution mechanism of the robot’s mechanical configuration, the multi-physics information fusion algorithm in extreme environments, the robot’s autonomous positioning and its error compensation control, the robot’s robust motion control in extreme environments and the dual-arm force-position hybrid coordination control and the dynamic distribution and elimination mechanism of internal forces in the closed chain between robots and operating objects, all the research methods and solutions of the key technologies are proposed, respectively.

Finally, a new control architecture for power cable robots in the background of the Ubiquitous Power Internet of Things is proposed so as to manage the operation and maintenance of electric power systems. The above key technologies are a new exploration of the operation and maintenance management of EHV (Extra High Voltage) multi-split transmission lines which have laid a solid theoretical foundation for the power cable robot.

High voltage transmission line is the main channel of power transmission. It is an important means to improve the integration of operation and maintenance management of power system to use robot instead of manual inspection and maintenance of power line, in the promotion and application of electric robot. The authors pay attention to the practicability, and the breakthrough of key technologies of robot is the premise of the practicability of robot. In this paper, the robot operation and control in multi-task and complex scenes are studied. The research and implementation of the main key technologies, such as the dynamic evolution mechanism of robot configuration, the coupling and fusion law of multi physical fields in the extreme electric power environment, the autonomous positioning control of manipulator, the robust control of robot in the super electromagnetic field environment and the cooperative operation control of multi manipulator, are discussed.

The purpose of this paper is to study the tribological properties of a thiazole derivatives (T561), overbased alkyl benzene calcium sulfonate (T106A) compounded with T561 and overbased alkyl benzene magnesium sulfonate (T107) compounded with T561 in rapeseed oil (RSO).

A four-ball machine was used to evaluate the tribological properties of each compound and their combinations with T561 in RSO. Scanning electron microscopy, EDX and X-ray photoelectron spectroscopy were applied to analyze the tribofilm formed on the worn surfaces.

Results of tribotesting demonstrated that synergistic effects exist between the overbased sulfonates, T106A and T107, and the thiazole derivative, T561. The texts of tribofilm indicated that iron sulfide and iron oxides exist in T561 single agent lubricant film and two composite additives lubricant film, and no sulfates were detected. It suggested that the addition of alkyl benzene sulfonate did not hinder the formation of iron sulfides and iron oxides. Meanwhile, CaSO₄ (MgSO₄) and CaCO₃ (MgCO₃) were detected on the worn surface of the composite additives, which were not detected on the single agent friction surface.

A tribofilm mainly contains CaSO₄ (MgSO₄) and CaCO₃ (MgCO₃) formed on the worn surfaces, which is responsible for excellent extreme pressure and anti-wear properties of the compound agents because of their high melting point and high shear stress.

The modeling cost of the gradient-enhanced kriging (GEK) method is prohibitive for high-dimensional problems. This study aims to develop an efficient modeling strategy for the GEK method.

A two-step tuning strategy is proposed for the construction of the GEK model. First, an auxiliary kriging is built efficiently. Then, the hyperparameter of the kriging model is served as a good initial guess to that of the GEK model, and a local optimal search is further used to explore the search space of hyperparameter to guarantee the accuracy of the GEK model. In the construction of the auxiliary kriging, the maximal information coefficient is adopted to estimate the relative magnitude of the hyperparameter, which is used to transform the high-dimension maximum likelihood estimation problem into a one-dimensional optimization. The tuning problem of the auxiliary kriging becomes independent of the dimension. Therefore, the modeling efficiency can be improved significantly.

The performance of the proposed method is studied with analytic problems ranging from 10D to 50D and an 18D aerodynamic airfoil example. It is further compared with two efficient GEK modeling methods. The empirical experiments show that the proposed model can significantly improve the modeling efficiency without sacrificing accuracy compared with other efficient modeling methods.

This paper developed an efficient modeling strategy for GEK and demonstrated the effectiveness of the proposed method in modeling high-dimension problems.

The purpose of this paper is to analyze the reliability and validity of doctoral candidates’ innovative personality model.

Based on doctoral candidates’ innovative personality model, this study took the best correlation and the worst correlation into account to predict and demonstrate their innovative ability tendencies. Matlab R2016a, a program of software programming, was used to calculate the contribution degree of each personality factor of doctoral candidates to their innovative ability tendencies.

The reliability and validity of doctoral candidates’ innovative personality model based on grey target theory have been verified, and the prediction for doctoral candidates’ innovative ability tendencies can be realized on the basis of this model.

Scientific and reasonable doctoral candidates’ innovative personality model can play a good guiding role, and its research results have certain practical significance for selecting innovative doctoral candidates, ensuring the training quality of doctoral candidates and cultivating the innovative ability of doctoral candidates. It can be promoted and applied on the basis of its trial operation in Jiangsu.

With regard to the relative degree of the influence of doctoral candidates’ individual personality factors, previous researchers seldom carried out the quantitative research. In this paper, the author sought a quantitative method to describe the degree of such influence and constructed the doctoral candidates’ innovative personality model based on grey target decision making. This study took the positive and negative off-target distance into account and demonstrated the rationality and validity of doctoral candidates’ innovative personality model.