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The purpose of this paper is to determine (1) the relationship between microstructure and fatigue cracking behavior and (2) effect of rolling on the process of crack initiation and propagation in FeCrAl alloys.

The qualitative and quantitative fracture studies were performed using scanning electron microscopy and the non-contact optical measurement system (IFMG5).

The results show that the formation of facets, rough facets and parallel stripes in the crack initiation and early crack propagation zones are closely related to the sensitivity of crack behavior to the microstructure of the material. Besides, the rolling process has a significant influence on the small crack initiation and propagation behavior. Quantitative analysis demonstrates that the size of the stress intensity factor and plastic zone size in the rough zone is associated with the rolling process.

The findings of this study have the potential to enhance the understanding of the microstructural crack formation mechanisms in FeCrAl alloys and shed light on the impact of rolling on the long-term and ultra-long fatigue behavior of these alloys. This new knowledge is vital for improving manufacturing processes and ensuring the safety and reliability of FeCrAl alloys used in nuclear industry applications.

During the production process of steel strip, some defects may appear on the surface, that is, traditional manual inspection could not meet the requirements of low-cost and high-efficiency production. The purpose of this paper is to propose a method of feature selection based on filter methods combined with hidden Bayesian classifier for improving the efficiency of defect recognition and reduce the complexity of calculation. The method can select the optimal hybrid model for realizing the accurate classification of steel strip surface defects.

A large image feature set was initially obtained based on the discrete wavelet transform feature extraction method. Three feature selection methods (including correlation-based feature selection, consistency subset evaluator [CSE] and information gain) were then used to optimize the feature space. Parameters for the feature selection methods were based on the classification accuracy results of hidden Naive Bayes (HNB) algorithm. The selected feature subset was then applied to the traditional NB classifier and leading extended NB classifiers.

The experimental results demonstrated that the HNB model combined with feature selection approaches has better classification performance than other models of defect recognition. Among the results of this study, the proposed hybrid model of CSE + HNB is the most robust and effective and of highest classification accuracy in identifying the optimal subset of the surface defect database.

The main contribution of this paper is the development of a hybrid model combining feature selection and multi-class classification algorithms for steel strip surface inspection. The proposed hybrid model is primarily robust and effective for steel strip surface inspection.

This study aims to identify the level of sustainability consciousness among preservice teachers in China under the “Double Carbon” goal.

A sustainability consciousness questionnaire was distributed to 2,795 preservice teachers aged 17–26 years old from first-year undergraduate to third-year postgraduate students through an online questionnaire tool. The mean, standard deviation and correlation of their sustainability knowingness, attitude and behavior were analyzed using SPSS software.

First, preservice teachers scored high in sustainability knowingness, attitude and behavior. Second, across different household types, disciplines and university levels (double first-class and nondouble first-class), preservice teachers’ sustainability consciousness scores were comparable to each other. Finally, a negative correlation was found between sustainability knowingness and attitude as well as knowingness and behavior. However, the authors observed a positive correlation between sustainability attitude and behavior. Overall, the level of sustainability consciousness among Chinese preservice teachers is high and no significant differences exist between the sustainability consciousness of preservice teachers with different household types, in different disciplines and at different levels of universities. Influenced by the contextual differences of the relevant concepts in the questionnaire, there is a certain degree of structural differences in the preservice teachers’ level of sustainability consciousness across the dimensions.

This study contributes to the literature by investigating the current status of sustainability consciousness level among preservice teachers in China under the “Double Carbon” goal. The findings of this study provide universities and relevant departments with recommendations for education for sustainable development policies.

The paper aims to propose a generation approach for unstructured surface mesh to speed up mesh generation.

The paper proposes a lightweight interactive generation approach for unstructured surface mesh and presents several key technologies to support this approach.

The experimental results show that the proposed approach is feasible for unstructured meshes and it can accelerate the mesh generation process.

More geometric defects should be covered, and more convenient and efficient interactive means need to be provided.

The proposed approach and key technologies are implemented in NNW-GridStar.UG, which is the unstructured version of the mesh generation software of National Numerical Windtunnel (NNW).

This paper proposes a lightweight interactive approach for unstructured surface mesh generation, which can speed up mesh generation.

Polyethylene terephthalate (PET) as a fiber molding polymer is widely used in aerospace, electrical and electronic, clothing and other fields. The purpose of this study is to improve the thermal insulation performance of polyethylene terephthalate (PET), the SiO₂ aerogel/PET composites slices and fibers were prepared, and the effects of the SiO₂ aerogel on the morphology, structure, crystallization property and thermal conductivity of the SiO₂ aerogel/PET composites slices and their fibers were systematically investigated.

The mass ratio of purified terephthalic acid and ethylene glycol was selected as 1:1.5, which was premixed with Sb₂O₃ and the corresponding mass of SiO₂ aerogel, and SiO₂ aerogel/PET composites were prepared by direct esterification and in-situ polymerization. The SiO₂ aerogel/PET composite fibers were prepared by melt-spinning method.

The results showed that the SiO₂ aerogel was uniformly dispersed in the PET matrix. The thermal insulation coefficient of PET was significantly reduced by the addition of SiO₂ aerogel, and the thermal conductivity of the 1.0 Wt.% SiO₂ aerogel/PET composites was reduced by 75.74 mW/(m · K) compared to the pure PET. The thermal conductivity of the 0.8 Wt.% SiO₂ aerogel/PET composite fiber was reduced by 46.06% compared to the pure PET fiber. The crystallinity and flame-retardant coefficient of the SiO₂ aerogel/PET composite fibers showed an increasing trend with the addition of SiO₂ aerogel.

The SiO₂ aerogel/PET composite slices and their fibers have good thermal insulation properties and exhibit good potential for application in the field of thermal insulation, such as warm clothes. In today’s society where the energy crisis is becoming increasingly serious, improving the thermal insulation performance of PET to reduce energy loss will be of great significance to alleviate the energy crisis.

In this study, SiO₂ aerogel/PET composite slices and their fibers were prepared by an in situ polymerization process, which solved the problem of difficult dispersion of nanoparticles in the matrix and the thermal conductivity of PET significantly reduced.

This paper aims to explore the impact of enterprise niche on dual innovation performance and the moderating role of innovation openness on the relationship between enterprise niche and dual innovation performance.

This study uses the panel data of the enterprise technology patents of China's Top 100 Electronic Information Enterprises from 2009 to 2018. Multiple regression analyses were used to test the hypotheses.

Niche width has a significant positive impact on exploitative and exploratory innovation performance. Niche overlap has an inverted U-shaped effect on exploitative innovation performance and significantly positively affects exploratory innovation performance. Innovation openness negatively moderates the impact of niche width on exploitative innovation performance and positively moderates the impact of niche overlap on exploitative innovation performance.

This study provides new insights into the effects of enterprise niche on dual innovation performance by showing the moderating role of innovation openness. The study finds a strategic logic of moderate niche overlap, clarifies the innovative effect of different innovation openness modes and reveals the construction and management mechanisms of enterprise niche and innovation openness strategy.

Omnidirectional mobile platforms are still plagued by the problem of heading deviation. In four-Mecanum-wheel systems, this problem arises from the phenomena of dynamic imbalance and slip of the Mecanum wheels while driving. The purpose of this paper is to analyze the mechanism of omnidirectional motion using Mecanum wheels, with the aim of enhancing the heading precision. A proportional-integral-derivative (PID) setting control algorithm based on a radial basis function (RBF) neural network model is introduced.

In this study, the mechanism of omnidirectional motion using Mecanum wheels is analyzed, with the aim of enhancing the heading precision. A PID setting control algorithm based on an RBF neural network model is introduced. The algorithm is based on a kinematics model for an omnidirectional mobile platform and corrects the driving heading in real time. In this algorithm, the neural network RBF NN2 is used for identifying the state of the system, calculating the Jacobian information of the system and transmitting information to the neural network RBF NN1.

The network RBF NN1 calculates the deviations ?Kp, ?Ki and ?Kd to regulate the three coefficients Kp, Ki and Kd of the heading angle PID controller. This corrects the driving heading in real time, resolving the problems of low heading precision and unstable driving. The experimental data indicate that, for a externally imposed deviation in the heading angle of between 34º and ∼38°, the correction time for an omnidirectional mobile platform applying the algorithm during longitudinal driving is reduced by 1.4 s compared with the traditional PID control algorithm, while the overshoot angle is reduced by 7.4°; for lateral driving, the correction time is reduced by 1.4 s and the overshoot angle is reduced by 4.2°.

In this study, the mechanism of omnidirectional motion using Mecanum wheels is analyzed, with the aim of enhancing the heading precision. A PID setting control algorithm based on an RBF neural network model is introduced. The algorithm is based on a kinematics model for an omnidirectional mobile platform and corrects the driving heading in real time. In this algorithm, the neural network RBF NN2 is used for identifying the state of the system, calculating the Jacobian information of the system and transmitting information to the neural network RBF NN1. The method is innovative.

This paper aims to develop a new method of fuselage drag optimization that can obtain results faster than the conventional methods based on full computational fluid dynamics (CFD) calculations and can be used to improve the efficiency of preliminary design.

An efficient method for helicopter fuselage shape optimization based on surrogate-based optimization is presented. Two numerical simulation methods are applied in different stages of optimization according to their relative advantages. The fast panel method is used to calculate the sample data to save calculation time for a large number of sample points. The initial solution is obtained by combining the Kriging surrogate model and the multi-island genetic algorithm. Then, the accuracy of the solution is determined by using the infill criteria based on CFD corrections. A parametric model of the fuselage is established by several characteristic sections and guiding curves.

It is demonstrated that this method can greatly reduce the calculation time while ensuring a high accuracy in the XH-59A helicopter example. The drag coefficient of the optimized fuselage is reduced by 13.3%. Because of the use of different calculation methods for samples, this novel method reduces the total calculation time by almost fourfold compared with full CFD calculations.

To the best of the authors’ knowledge, this is the first study to provide a novel method of fuselage drag optimization by combining different numerical simulation methods. Some suggestions on fuselage shape optimization are given for the XH-59A example.

The aim of this study is to investigate the horizontal displacement effects of foundation pit excavation on adjacent metro stations and shield tunnel composite structures. It seeks to develop a theoretical calculation method capable of accurately assessing these engineering impacts, aiming to provide practical assistance for engineering applications.

This study introduces a model for shield tunnel segments incorporating rotation and misalignment, considering the constraints of metro stations. It establishes a displacement model for tunnel-station combinations during foundation pit excavation, deriving a formula for calculating station-proximal tunnel horizontal displacements. The method's accuracy is validated against field data from three engineering cases. The research also explores variations in tunnel displacement, inter-ring shear force, misalignment and rotation angle under different spatial relationships between pits, tunnels and stations.

This study models uneven deformation between stations and tunnels due to bending stiffness and shear constraints. It enhances the misalignment model with station-induced shear effects and introduces coefficients for their mutual interaction. Results show varied responses based on pit-station-tunnel positioning: minimal displacement near pit edges (coefficients around 0.1) and significant effects near pit centers (coefficients from 0.4 to 0.5). “Whip effect” from station constraints affects tunnel displacement, shear force, misalignment and rotation, with fluctuations decreasing with distance from excavation areas.

This study demonstrates significant originality and value. It introduces a novel displacement model for tunnel-station combinations considering station constraints, addressing theoretical calculations of horizontal displacement effects from foundation pit excavation on metro stations and shield tunnel structures. Through validation with field data and parameter studies, the concept of influence coefficients is proposed, offering insights into variations in structural responses under different spatial relationships. This research provides crucial technical support and decision-making guidance for optimizing designs and facilitating practical construction in similar engineering projects.

The purpose of this study is to investigate the influence of additive particle size on the anti-corrosion behaviors of polyurethane (PU) coating.

The graphite (Gr) and poly-graphite (PGr) were used as large size additive and small size additive, respectively. The immersion test and electrochemical test were used to study the corrosion behaviors.

In the immersion test, the surface of the bare steel sample was corroded uniformly. However, for the steel samples with coatings, the surfaces were corroded locally. This phenomenon showed that the coating can isolate artificial sea-water and samples and then decreased the corrosion rate. Furthermore, the most severe corrosion was observed on the sample with the Gr/PU coating compared with other anti-corrosion coatings. The results of the electrochemical measurements indicated that the corrosion rate of the sample with PGr/PU coating was approximately two times lower than that of the sample with the Gr/PU coating and the sample with PGr/PU coating was hardest to be corroded.

To have a more objective and direct recognition of the particle size effect on the coating quality.