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The purpose of this paper is to develop a numerical model used for calculating the nonlinearities of large-scale hydro-pneumatic suspension (HPS) and investigating the effects of variations in flow path and operational parameter on suspension damping response.

To parameterization nonlinearities of the suspension, the author developed a two-phase flow model of a large-scale HPS based on computational fluid dynamics and volume of fluid method. Considerable effort was made to verify the nonlinearities by field measurements carried out on an off-highway mining dump truck. The investigation of effects of variations in flow path and operational parameter on damping characteristics highlights the necessity of the numerical simulation.

The two-phase flow model can represent the gas-oil interaction and simulate the suspension operational movement conveniently. Transient numerical simulation results can be used to model the nonlinearities of large-scale HPS accurately. A new phenomenon was discovered that the pressure in rebound chamber presents reduction trend during compression stroke in special cases. It has never been reported before.

Developed a two-phase flow model of a large-scale HPS, which can manage the gas-oil interaction and capture the complex flow field structure in it. The paper is the first study to model the nonlinearities of a large-scale HPS used in off-highway mining dump truck through transient numerical simulation. Compared with previous researches, such a research not only gives new insight and thorough understanding into the suspension internal fluid structure but also can give good guiding opinions to the optimal design of HPS.

Through the scientific and reasonable evaluation of the site selection of the emergency material reserve, the optimal site selection scheme is found, which provides reference for the future emergency decision-making research.

In this paper, we have chosen three primary indicators and twelve secondary indicators to construct an assessment framework for the determination of suitable locations for storing emergency material reserves. By mean of the improved entropy weight-order relationship weight determination method, the evaluation model of kullback leibler-technique for order preference by similarity to an ideal solution (KL-TOPSIS) emergency material reserve location based on relative entropy is established. On this basis, 10 regional storage sites in Beijing are selected for evaluation.

The results show that the evaluation model of the location of emergency material reserve not only respects the objective knowledge, but also considers the subjective information of the experts, which makes the ranking result of the location of the emergency material reserve more accurate and reliable.

Firstly, the modification factor is added to the calculation formula of traditional entropy weight method to complete the improvement of entropy weight method. Secondly, the order relation analysis method is used to assign subjective weights to the indicators. The principle of minimum information entropy is introduced to determine the comprehensive weight of the index. Finally, KL distance and TOPSIS method are combined to determine the relative entropy and proximity degree of alternative solutions and positive and negative ideal solutions, and the scientific and effective of the method is proved by case study.

To solve the problem of simulation evaluation with small samples, a fresh approach of grey estimation is presented based on classical statistical theory and grey system theory. The purpose of this paper is to make full use of the difference of data distribution and avoid the marginal data being ignored.

Based upon the grey distribution characteristics of small sample data, the definition about a new concept of grey relational similarity measure comes into being. At the same time, the concept of sample weight is proposed according to the grey relational similarity measure. Based on the new definition of grey weight, the grey point estimation and grey confidence interval are studied. Then the improved Bootstrap resampling is designed by uniform distribution and randomness as an important supplement of the grey estimation. In addition, the accuracy of grey bilateral and unilateral confidence intervals is introduced by using the new grey relational similarity measure approach.

The new small sample evaluation method can realize the effective expansion and enrichment of data and avoid the excessive concentration of data. This method is an organic fusion of grey estimation and improved Bootstrap method. Several examples are used to demonstrate the feasibility and validity of the proposed methods to illustrate the credibility of some simulation data, which has no need to know the probability distribution of small samples.

This research has completed the combination of grey estimation and improved Bootstrap, which makes more reasonable use of the value of different data than the unimproved method.

This study aims to identify the attitudes of Chinese residents towards tourists and tourism development. Based on periods of observation, temporary residency and several visits for more than a decade, and supplemented by data collected from 478 residents, the study examines to what extent the rural villagers identify the tourism induced changes as being an outcome of official Chinese policies. The villages, Xidi, Hongcun and Nanping, are three heritage villages in Anhui Province and represent appropriate case studies for such an examination due to their differing histories of tourism administrative procedures. Findings contribute to scholarly knowledge by putting pro-poor tourism and community participation under scrutiny in Chinese context. A change of residents’ perceptions towards tourism could potentially be consequential for tourists’ experience and the sustainability of tourism development, particularly in emerging rural destinations.

The purpose of this study is to establish a finite element (FE) model with the random distribution of the Nylon12/hydroxyapatite (PA12/HA) composite material in selective laser sintering (SLS) process for considering the material anisotropy, which aims to obtain the law of temperature and stress changes in PA12/HA sintering.

By using python script in Abaqus, the FE model is established in which the two materials are randomly distributed and are assigned to their intrinsic temperature-dependent physical parameters. Molten pool sizes at various process parameters were evaluated in terms of numerical simulation and scanning electron microscope analysis, identifying a good agreement between them. Evaluation of temperature and stress distribution under the condition of different HA contents was also conducted.

It shows that the uneven distribution and quantity of HA powder play a vital role in stress concentration and temperature increase. Additionally, the influence of HA addition on the mechanical performance of SLS-fabricated parts shows that it is conducive to improve compressive strength when the HA ratio is less than 5% because an excess of HA powder tends to bring about a certain amount of microspores resulting in a decrease in part density.

The FE model of the PA12/HA composite material with parameterized random distribution in SLS can be applied in other similar additive manufacturing technologies. It provides a feasible guideline for the numerical analysis of properties of composite materials.