A Comprehensive Failure Risk Assessment Method of Machining Center Component Based on Topology Analysis

The risk assessment of the failure mode of the traditional machining center component rarely considers the topological characteristics of the system and the influence of propagation risks, which makes the failure risk assessment results biased. Therefore, this paper proposes a comprehensive failure risk assessment method of a machining center component based on topology analysis. On the basis of failure mode and cause analysis, considering the correlation of failure modes, Analytic Network Process (ANP) is used to calculate the influence degree of failure modes, and it is combined with component failure mode frequency ratio and failure rate function to calculate independent failure risk. The ANP model of the machining center is transformed into a topological model, and the centrality measurement of network theory is used to analyze the topology of the machining center. The weight of the topological structure index is measured by subjective and objective weighting methods, and then the importance degree of the machining center component is calculated. In this paper, the coupling degree function is introduced to calculate the importance of the connection edge, which is combined with the failure probability to calculate the failure propagation influence degree, and the component propagation failure risk is calculated based on this. Finally, the independent failure risk and the propagation failure risk of the component are integrated to realize the failure risk assessment of the component. Taking a certain type of machining center as an example to illustrate the application, compared with the traditional assessment method, the effectiveness and advancement of the method proposed in this paper have been verified.

Studying joint influence of a number of factors on borehole cleaning

Studying the behavior of cuttings transport under various conditions using experimental observations and computational fluid dynamics is the main method for analyzing the influence of cuttings, fluid and operating parameters on well cleaning. Despite the existing abundant models and recommendations of researchers, still there are problems with the accuracy of determining the cuttings layer height, critical velocity and other key parameters, which complicates the task of effective solution of the problem of borehole cleaning. The purpose of the study is to analyze the models obtained via the organization of a full factorial experiment and variance analysis to identify the influence of such factors as viscosity and flow rate of the drilling fluid in the annular space and the inclination angle of the well on the degree of cuttings transport. The studies of the kind are carried out using special devices called flow loops. Experimental data were taken from literature sources. To organize a full factorial experiment, the data of the dependent variable were combined into a combinational square, which simplified the coding of factor values. After setting the full factorial experiment, the models were obtained that made it possible to assess the contribution of the studied factors to the process of destruction product removal within the intervals determined while setting the research tasks. The obtained models allowed to determine the influence degree of each of the factors on the process under investigation. The results of the succeeding analysis of variance confirmed the indicated degree of influence and determined the rank of each of the factors in percentage.

Analyzing Multiscale Spatial Relationships between the House Price and Visual Environment Factors

House price is closely associated with the development of the national economy and people’s daily life. Understanding the spatial distribution characteristics and influencing factors of the house price is of great practical significance. Although a lot of attention has been paid to modeling the house price from structure and location attributes, limited work has considered the impact of visual attributes. Intuitively, a better visual environment may raise the surrounding house price. When aggregating multiple factors that influence house price, the multiscale geographically weighted regression (MGWR) provides a suitable solution. Specifically, the MGWR assigns each factor a bandwidth to model the spatial heterogeneity, e.g., a factor may have different influences at different places. In this paper, we introduce the visual environment factors into the MGWR method. In detail, we extract ten visual elements, e.g., sky, vegetation, road, from the Baidu street view (BSV) images, using a deep learning framework. We further define six visual environment factors to investigate their influence on house price. Based on the data from two representative Chinese cities, i.e., Beijing and Chongqing, we reveal the influence degree and spatial scale difference of six visual indexes on the house price in two cities. Results show that: (1) the influence intensity of our proposed six visual environment factors on the house price in different regions of the city can be identified, and the green view index (GVI) is the most important visual environmental factor; and (2) the influence of these view indexes changes significantly or even reversely depends on different areas.

A Fast Diagnosis Method of Escalator Reversal Faults Based on Dynamic Information and Multiattribute Decision-Making

There are many reasons for escalator reversal failure, and the reasons are distributed in different locations. It is difficult to locate the specific location of the fault in the actual fault troubleshooting. At the same time, the information related to the failure is not used in the troubleshooting, so there is a problem of inefficient troubleshooting. To this end, this paper proposes a multiattribute decision-making method that integrates dynamic information and gives the optimal troubleshooting order to improve the efficiency of the troubleshooting. First of all, according to the structure of the escalator components, the escalator reversal fault tree is established. Secondly, a static decision matrix is established by comprehensively considering the failure probability, search cost, and influence degree of the bottom event of the fault tree. Finally, the influence matrix of information on each attribute is given by the dynamic information obtained in troubleshooting, the static decision fusion influence matrix determines the dynamic decision matrix, the dynamic decision matrix is weighted and normalized, and the Technique for Order Preference by Similarity to Ideal Solution is used to determine the optimal troubleshooting order. Taking the reversal failure of a certain type of escalators as an example, the method of multiattribute decision-making of fusion dynamic information is used to shorten the troubleshooting time, improve the efficiency of troubleshooting, and verify the effectiveness of this method.

Construction and Empirical Analysis of Citizens' Water Literacy Evaluation Index System: A Structural Equation Model

This study draws on the existing water literacy evaluation system and the weight of each indicator to construct a three-dimensional theoretical analysis framework of water knowledge, water attitude, and water behaviour. Based on the constructed evaluation index system, research hypotheses were proposed, questionnaires designed, and areas of Beijing, Zhengzhou, Hechi, Qingtongxia selected for investigation. According to the constructed structural equation model of citizen water literacy, the influence degree of the influence factors of citizen water literacy evaluation on the path is discussed. The coefficient of the influence degree of each factor on water literacy is obtained. The research results show that: 1) water knowledge has a positive and significant influence on water attitude; 2) water attitude has a positive and significant impact on water behaviour; 3) water behaviour has a positive and significant impact on water literacy. 4) The following two hypotheses, that water knowledge has a positive and significant effect on water behaviour, and water attitude has a positive and significant effect on water literacy, are shown not to hold. The research conclusions can provide a theoretical basis for the water sector to formulate relevant policies to improve water literacy.

Effect of Process Parameters on the Microstructure and Mechanical Properties of Bars from Al-Cu-Mg Alloy Processed by Multipass Radial-Shear Rolling

The study of microstructure and mechanical properties formation of A2024 alloy obtained by the multipass radial-shear rolling (RSR) method is discussed in this article. FEM simulation was carried out that made it possible to evaluate the influence degree of rolling temperature-velocity parameters on the strain state of material. It has been found the increase in rotary velocity of rolls significantly influences on the deformation heating of bar after RSR (predominantly in its surface layer). The combination of rolling temperature-velocity conditions at selection of deformation regime has complex effect on structure and properties formation. The analysis of sizes and distribution of phase particles has shown that the rolling at lower temperatures allowed to increase the mechanical strength due to the more intensive refinement of undissolved Fe-containing phase. The gradual decrease in the rolling temperature in each pass makes possible to achieve the high strength (UTS~430 MPa and YS~255 MPa) while maintaining the ductility level ~15%, that are comparable to ones obtained at some severe plastic deformation (SPD) methods.

Analysis on the Influencing Factors of Methane Emission from Wetlands

Methane research has attracted much attention of the scientific community, not only in that its contribution to global warming is second only to carbon dioxide, but also because the value-added potential of single molecule methane is 15-30 times that of carbon dioxide. As a unique ecosystem, wetland is the “source” of methane (CH4), which is an important greenhouse gas in the atmosphere. Methane emission from wetlands is the result of the combined effects of methane production, transport and oxidation processes, in which methane production is the prerequisite for methane emission. This paper studied the effects of different factors on methane production in wetlands, including methanogens and methanotrophs, substrate, temperature, soil water, pH, and vegetation, in order to find out the main factors that affect methane emission from wetlands and their influence degree so that could provide some reference for the estimation and prediction of global greenhouse effect.

Process fluid as a technological system element of vibro-impact parts processing

Vibro-impact processing refers to finishing processing methods, which largely determine the operational part properties. It is shown that the parameter optimization of the vibro-impact processing is a very promising area of improving the part quality and reducing their manufacturing cost.One of the most important technological system elements is the process fluid. As a result of the priory information analysis, factors that determine the parameters of the vibro-impact processing were identified.Because of theoretical studies, the process fluid parameters and flushing mode influence degree on the process parameters and treated part quality indicators was determined. The process fluid is presented as a set of unit volumes that form an elastically deformable matrix. The necessary list of initial data for determining the maximum allowable process fluid amount in the mass load volume has been identified.The dependence for determining the minimum required process fluid volume is presented. A complex parameter that characterizes the change in the load mass volume in one oscillations cycle, together with the working chamber oscillation frequency and the process fluid fluidity, which determine both the fluid flow process nature (turbulent) and the flow rate inside the load mass is proposed. Based on the complex parameter, the load mass flushing speed is determined. It is shown that at this stage, the numerical value of the parameter can only be determined experimentally. Its theoretical definition is a promising area of further research.

Effect of external thermal insulation layer on the Chinese solar greenhouse microclimate

In order to optimize the heat preservation capacity of Chinese solar greenhouse (CSG) and further reduce energy consumption, we clarified the mechanism of the external thermal insulation layer that affects the microclimate environment of CSG. The most suitable external insulation layer thickness (EILT) of the solar greenhouse envelope structure in high latitude and cold region has been indicated. A three-dimensional mathematical model was developed based on computational fluid dynamics and verified using experimental measurement. The temperature variations, heat variations and economic benefit were analysed. The results indicated that covering the outer surface of the enclosures with a thermal insulation layer could effectively increase the greenhouse temperature by 1.2–4.0°C. The influence degree of the external thermal insulation layer on the greenhouse microclimate was as follows: sidewall (SW) > north wall (NW) > north roof (NR). In high-dimensional and cold areas, covering the outer surface of all enclosures with insulation layer as the suitable solution could raise the greenhouse air temperature maximally. The suitable EILT of each maintenance structure was obtained as follows: NW 80 mm, SW 80 mm, NR 100 mm.

Study and Analysis on the Influence Degree of Particle Settlement Factors in Pipe Transportation of Backfill Slurry

In this study, we developed a pipeline transport model to investigate the influence of particle sedimentation factors on slurry transportation through pipelines. The particle tracking module of the software was used to simulate the transport process, and the influences on the sedimentation rate were analyzed considering the slurry concentration, particle size, and flow velocity. The established model exhibited small calculation errors. In addition, the results revealed that the proposed model is reliable for calculating the degree of influence of various factors on particle sedimentation. The effect of the particle sedimentation rate on the pipeline slurry was explored considering the particle size, slurry concentration, and flow velocity. The sedimentation rate was positively related to particle size and adversely related to the slurry concentration and flow velocity. Indeed, study on the sedimentation rate requires considering a reasonable range of particle sizes, preparing a slurry with an appropriate concentration, and adjusting an appropriate flow velocity. Numerical simulations were performed using the filling data as the background for a sample mining area. The experimental results showed optimal slurry concentration and particle size of 60% and 25.25 µm, respectively.