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The purpose of this paper is to propose a strategy for the final assembly of helicopter fuselage with weak rigidity parts and mismatched jointing butt ends.

The strategy is based on path planning methods. Compared with traditional path planning methods, the configuration-space and collision detection in the method are different. The obstacles in the configuration-space are weakly rigid and allow continuous contact with the robot. The collision detection is based on interference magnitudes, and the result is divided into no collision, weak collision and strong collision. Only strong collision is unacceptable. Then a compliant jointing path planning algorithm based on RRT is designed, combined with some improvements in search efficiency.

A series of planning results show that the efficiency of this method is higher than original RRT under the same conditions. The effectiveness of the method is verified by a series of simulations and experiments on two sets of systems.

There are few reports on the automation technology of helicopter fuselage assembly. This paper analyzes the problem and provides a solution from the perspective of path planning. This method contains a new configuration-space and collision detection method adapted to this problem and could be intuitive for the jointing of other weakly rigid parts.

The quick growth of web-based and mobile e-learning applications such as massive open online courses have created a large volume of online learning resources. Confronting such a large amount of learning data, it is important to develop effective clustering approaches for user group modeling and intelligent tutoring. The paper aims to discuss these issues.

In this paper, a minimum spanning tree based approach is proposed for clustering of online learning resources. The novel clustering approach has two main stages, namely, elimination stage and construction stage. During the elimination stage, the Euclidean distance is adopted as a metrics formula to measure density of learning resources. Resources with quite low densities are identified as outliers and therefore removed. During the construction stage, a minimum spanning tree is built by initializing the centroids according to the degree of freedom of the resources. Online learning resources are subsequently partitioned into clusters by exploiting the structure of minimum spanning tree.

Conventional clustering algorithms have a number of shortcomings such that they cannot handle online learning resources effectively. On the one hand, extant partitional clustering methods use a randomly assigned centroid for each cluster, which usually cause the problem of ineffective clustering results. On the other hand, classical density-based clustering methods are very computationally expensive and time-consuming. Experimental results indicate that the algorithm proposed outperforms the traditional clustering algorithms for online learning resources.

The effectiveness of the proposed algorithms has been validated by using several data sets. Moreover, the proposed clustering algorithm has great potential in e-learning applications. It has been demonstrated how the novel technique can be integrated in various e-learning systems. For example, the clustering technique can classify learners into groups so that homogeneous grouping can improve the effectiveness of learning. Moreover, clustering of online learning resources is valuable to decision making in terms of tutorial strategies and instructional design for intelligent tutoring. Lastly, a number of directions for future research have been identified in the study.

Resource scheduling is the study of how to effectively measure, evaluate, analyze, and dispatch resources in order to meet the demands of corresponding tasks. Aiming at the problem of resource scheduling in the private cloud environment, the purpose of this paper is to propose a resource scheduling approach from an efficiency priority point of view.

To measure the computational efficiencies for the resource nodes in a private cloud environment, the data envelopment analysis (DEA) approach is incorporated and a suitable DEA model is proposed. Then, based on the efficiency scores calculated by the proposed DEA model for the resource nodes, the 0-1 programming technique is introduced to build a simple resource scheduling model.

The proposed DEA model not only has the ability of ranking all the decision-making units into different positions but also can handle non-discretionary inputs and undesirable outputs when evaluating the resource nodes. Furthermore, the resource scheduling model can generate for the calculation tasks an optimal resource scheduling scheme that has the highest total computational efficiency.

The proposed method may also be used in studies of resource scheduling studies in the environments of public clouds and hybrid clouds.

The proposed approach can achieve the goal of resource scheduling in private cloud computing platforms by attaining the highest total computational efficiency, which is very significant in practice.

This paper uses an efficiency priority point of view to solve the problem of resource scheduling in private cloud environments.

Merger and acquisitions (M&A) is a process of restructuring two or more companies into one, a process that occurs frequently in many companies. Previous studies on M&A mainly paid attention to the potential gains from a merger, while ignored the problem of how to select the partners to merge. This paper aims to select the best partner from different candidates for a given company to merge.

Each company's historical data are used to identify each company's own production technology. With resources change, each company's new operation is restricted by its own production technology. Then, a 0–1 integer programming is proposed to select the best partner for M&A.

The banking industry involving 27 China's commercial banks is given to verify the applicability of our proposed model. The study shows the best partner selection for each bank company.

On the theoretical side, the study uses each company's own historical data to construct its own production technology to compressively reflect the production change after M&A. On the practical side, the study uses the proposed model to help the 27 commercial banks in China to select their best merger partner.

Bolted joints are the most common type of mechanical connections, and improving the anti-loosening performance of bolts for the reliable performance of mechanical and building structures is highly significant.

Because of the lack of sufficient theoretical basis for the evaluation and design of anti-loosening bolts, a quantitative evaluation model exhibiting the following two evaluation criteria for anti-loosening bolts is introduced: bolt rotation angular acceleration criterion and critical transverse load criterion. Based on the relationship among bolt tension, transverse load and bolt rotation angular acceleration, a critical transverse load calculation model is put forward, and the mechanism by which the critical transverse load increases with the increase of bolt tension is revealed.

Based on the above model, a new type of anti-loosening bolt is designed, which generates additional bolt tension when the transverse load increases, and then improves the critical transverse load of the bolt. The effectiveness of the new type of anti-loosening bolt is verified by theoretical calculations and experiments.

The proposed model and method set a preliminary theoretical foundation for the evaluation of bolt anti-loosening performance and the design of a new anti-loosening bolt.

The purpose of this study is to investigate the effect of nano ZrC particles on the mechanical and electrochemical corrosion properties of FeCrAl alloys, providing a beneficial reference basis for the development of high-performance carbide reinforced FeCrAl alloys with good mechanical and corrosion properties in the future.

Nano ZrC reinforced FeCrAl alloys were prepared by mechanical alloying and spark plasma sintering. Phases composition, tensile fractography, corrosion morphology and chemical composition of nano ZrC reinforced FeCrAl alloys were analyzed by X-ray diffraction, scanning electron microscopy and energy dispersive X-ray spectroscopy, respectively. Microhardness and tensile properties of nano ZrC reinforced FeCrAl alloys were investigated by mechanical testing machine and Vickers hardness tester. Electrochemical corrosion properties of nano ZrC reinforced FeCrAl alloys were investigated by electrochemical workstation in 3.5 wt.% NaCl solution.

The results showed that addition of nano ZrC can effectively improve the mechanical and corrosion properties. However, excessive nano ZrC could decrease the mechanical properties and reduce the corrosion resistance. In all the FeCrAl alloys, FeCrAl–0.6 wt.% ZrC alloy exhibits the optimum mechanical properties with an ultimate tensile strength, elongation and hardness of 990.7 MPa, 24.1% and 335.8 HV1, respectively, and FeCrAl–0.2 wt.% ZrC alloy has a lower corrosion potential (−0.179 V) and corrosion current density (2.099 µA/cm2) and larger pitting potential (0.497 V) than other FeCrAl–ZrC alloys, showing a better corrosion resistance.

Adding proper nano ZrC particles can effectively improve the mechanical and corrosion properties, while the excessive nano ZrC is harmful to the mechanical and corrosion properties of FeCrAl alloys, which provides an instruction to develop high-performance FeCrAl cladding materials.

This study aims to assess the pitting resistance of austenitic stainless steel welded joints fusion zone (FZ) with high density of inclusions before and after surface treatment, including potentiostatic pulse technique (PPT) and pickling.

The potentiodynamic polarization tests and critical pitting temperature tests were carried out for estimating pitting resistance. The PPT and pickling were performed as surface treatment. Scanning electron microscope (SEM) and energy dispersive spectrometer were used for characterize the microstructure and elemental distribution. Electron back-scattered diffraction (EBSD) was used to assess the portion of phases and morphology of grains.

The weld metal exhibits a higher degree of alloying compared to the base metal, and it contains d-phase and sulfur-containing inclusions. Sulfur-containing inclusions serve as initiation sites for pitting, and they diminish the pitting resistance of weld metal. Both PPT and pickling can remove sulfur-containing inclusions, but PPT causes localized dissolution of the weld metal matrix around the inclusions, while pickling does not. Because of the high density of inclusions, certain pits initiated by PPT are significantly deeper, which makes the formation of stable pitting easier. Because of the high density of inclusions, certain pits initiated by the PPT are deeper. This characteristic facilitates the progression of these initial defects into fully developed, stable pits.

Analysis of pitting initiation in shielded metal arc welding FZ with PPT and ex situ SEM tracking observation. Explanation of why the PPT surface treatment is not able to enhance the pitting resistance of stainless steel with a high inclusion density.

The purpose of this study is to investigate the intergranular corrosion (IGC) susceptibility of a nitrogen-containing austenitic stainless steel QN2109. The intergranular corrosion (IGC) susceptibility of a nitrogen-containing austenitic stainless steel QN2109 was investigated.

The double-loop electrochemical potentiodynamic reactivation (DL-EPR) tests were carried out. Scanning electron microscopy and atomic force microscopy were used to characterize the microstructure.

The optimized test condition for QN2109 was 1 M H₂SO₄ + 0.01 M NH₄SCN at 40°C. The nose temperature of the temperature–time–sensitization (TTS) curve of QN2109 plot was approximately 750°C. Moreover, the IGC susceptibility started to appear at approximately 120 min. The Cr-depletion zone of QN2109 was generated by the formation of M23C6 rather than by the addition of nitrogen. The depth–width ratio of the grain boundaries after the DL-EPR tests decreased as the aging temperature increased. The degree of Cr depletion and size of the Cr-depletion zone at the grain boundary were reflected by the degree of sensitization and depth–width ratio, respectively.

The optimized test condition for DL-EPR tests of a nitrogen-containing austenitic stainless steel QN2109 was investigated. The TTS curve of QN2109 was first plotted to avoid IGC failure. The morphology of the Cr-depletion zone was reflected by the depth–width ratio.

In the absence of previous work, this study investigates how the psychological contract (PC) influences the safety performance of construction workers in China.

The literature is first consulted to obtain a set of PC and safety performance measures that fits the specific situation of construction workers, which is then moderated by five construction experts. A questionnaire survey of 206 workers from 4 different construction sites is followed by a descriptive statistical analysis of the nature of the PC and level of the safety performance of the respondents. Finally, a regression analysis is used to ascertain the level of influence of the PS, and an analysis is made of the influence of PC on safety performance.

A set of PC and safety performance measures is identified that fits in the construction workers' specific situation. The PC of the respondents is found to be intact and well-performed, and their safety performance is maintained at a high level. Safety performance is highly influenced by the state of the PC, with the three dimensions of safety performance (safety result, safety compliance and safety participation) positively correlated with the three dimensions of the PC (normative, interpersonal and developmental).

Suggestions are made to improve safety production management and safety performance by providing adequate material and economic conditions, helping the workers establish good interpersonal relationships and realize their personal values.

This study aims to explore the critical influencing factors that lead to the site selection failure of waste-to-energy (WtE) projects in China under the influence of the “Not In My Back Yard” (NIMBY) effect, which can provide references to improve the decision-making process of similar projects in the future.

The fuzzy decision-making trial and evaluation laboratory (DEMATEL) method was used to propose an analytical framework for exploring the critical influencing factors affecting the site selection failure of WtE projects. The causal relationship between different influencing factors is finally determined on the basis of the opinions of 12 experts from universities, government departments, consulting units, planning and design units, construction units and WtE enterprises.

Results showed that six crucial factors resulted in the site selection failure of WtE projects from the NIMBY effect perspective: “Insufficient public participation,” “Near the place of residence,” “Nonstandard government decision-making processes,” “Low information disclosure,” “Destroys the surrounding environment,” and “Imperfect compensation scheme.”

Results can determine the priorities and causal relationships among the various influencing factors. The decision-making optimization suggestions can provide reference for decision- makers, thereby possibly promoting the scientific and standardization of site selection decision process.