Search Results (8)

In recent years, with the continuous increase in coal mining depth and intensity, hydrogeological conditions in coal mines have become increasingly complex, and the risk of floor water inrush has risen significantly. To address the limitations of the global weighting pattern in traditional floor water inrush risk evaluation systems, this study, taking a coal mine in Shaanxi Province as a case, develops a local water inrush risk evaluation method based on the Monte Carlo Analytic Hierarchy Process (MAHP) combined with a circular moving window, and compares it with the water inrush coefficient method and the global evaluation method. The results demonstrate that the proposed local evaluation model achieves higher accuracy, provides a more refined delineation of high-risk zones, and shows stronger consistency with actual mining conditions. Further comparison of window radii of 100 m, 500 m, and 900 m indicates that the 500 m radius performs best in terms of spatial morphology, area proportion, and water inrush point identification rate (89.3%). Moreover, its application in Yangcheng Coal Mine further confirms that this method can accurately identify high-risk zones, thereby offering reliable scientific support for the prevention and control of coal seam floor water inrush. Full article

A key component of multi-criteria decision analysis is the estimation of criteria weights, reflecting the preference strength of different stakeholder groups related to different objectives. One common method is the Analytic Hierarchy Process (AHP). A key challenge with the AHP is the potential for inconsistency in responses, resulting in potentially unreliable preference weights. In small groups, interactions between analysts and respondents can compensate for this through reassessment of inconsistent responses. In many cases, however, stakeholders may be geographically dispersed, with online surveys being a more cost-effective means to elicit these preferences, making renegotiating with inconsistent respondents impossible. Further, the potentially large number of bivariate comparisons required using the AHP may adversely affect response rates. In this study, we test a new “modified” AHP (MAHP). The MAHP was designed to retain the key desirable features of the AHP but be more amenable to online surveys, reduce the problem of inconsistencies, and require substantially fewer comparisons. The MAHP is tested using three groups of university students through an online survey platform, along with a “traditional” AHP approach. The results indicate that the MAHP can provide statistically equivalent outcomes to the AHP but without problems arising due to inconsistencies. Full article

Most of the existing coal mine water inrush risk assessment methods are global assessment methods, which have the following problems: they ignore the difference in importance of the evaluation indicators at different locations in the study area and assign the same weight value; the area of the danger zone in the evaluation results is thus too large. The evaluation results improve the prediction accuracy by reducing the safe zone area. To address the aforementioned issues, this study employs a local analysis method based on a moving circular window, taking into account the spatial heterogeneity of criterion indicators in the decision-making process. By traversing each position of the raster with a circular moving window, the method performs local standardization and calculates local weights of indicators within the local window range. Based on the obtained maps of locally standardized evaluation criteria and local weights, a local water inrush risk assessment model is established using Geographic Information Systems (ArcGIS), considering the differences in the importance of evaluation indicators within the study area. Taking the Liangshuijing mining area as an example, both global and local evaluation models were employed to assess its water inrush risk. The evaluation results obtained from these two models were compared and validated against geological survey data and historical water inrush points. The comparative analysis between the two methods reveals that the local evaluation model demonstrates higher accuracy. It offers a more precise delineation of the distribution of water inrush risk zones, which better corresponds to the actual conditions within the mine. The localized water inrush risk assessment method proposed in this paper breaks away from the traditional approach of uniformly weighting evaluation indicators across the entire area, offering a novel method for assessing water inrush risk. Full article

Ce-doped gadolinium gallium aluminum oxide (Ce: GGAG) precursors were first prepared by the microwave-assisted homogeneous precipitation method (MAHP). Thermal gravity-differential thermal analysis (TG-DTA), X-ray diffraction (XRD), specific surface area analysis (BET) and field emission scanning electron microscopy (FE-SEM) were employed to investigate the crystal structure, phase evolution and morphologies of the Ce: GGAG precursors and powders. The influence of Ga ion concentration in the salt solution on the properties of Ce: GGAG powders was investigated. All the precursors were transformed into single-phase GGAG after being calcined at 950 °C in a furnace for 3 h. Monodispersed Ce: GGAG powders were obtained as the Ga ion concentration was lower than 0.06 mol/L. Single-phase and dense Ce: GGAG ceramics were obtained after sintering at 1600 °C in a flowing oxygen atmosphere for 10 h. Specifically, the Ce: GGAG ceramic reached its maximum density of ~6.68 g/cm³, which was close to its theoretical density of 6.70 g/cm³, and exhibited the highest optical transmittance of 65.2% at 800 nm after hot isostatic pressing sintering (HIP) as the Ga ion concentration was 0.02 mol/L. The decay time and light yield of the GGAG ceramic were 35 ns and 35,000 ± 1250 ph/MeV, respectively, suggesting that Ce: GGAG ceramics prepared using MAHP-synthesized nanopowders are promising for scintillation applications. Full article

This paper presents the application of risk analysis associated with the multicriteria decision method, through the MAHP (Monte Carlo analytic hierarchy process) technique for mining. As an example of application, the problem of choosing an access and transportation route for an underground mine is addressed. A decision can be made based on a technical, economic, and social-environmental approach. As a topic of interest for the modeling of mining projects, this work presents how the technique can qualify the decision-making process, reducing its subjectivity. It is verified that in comparison with the traditional AHP (analytic hierarchy process) method, the risk analysis allows considering the variability of weights and preferences assigned to criteria and options. In the example case, the following options are evaluated: shaft, ramp by diesel or electric truck, and conveyor belt. Full article

A combination of geographic information system (GIS) and spatial multicriteria decision making (MCDA) in mine water inrush risk evaluation is widely used, but the randomness in the process of index weight determination and the risk-coping attitude of decision makers are not considered in the decision making process. Therefore, this paper proposes a probability-based roof water inrush risk evaluation method (GIS-MCDA) by combining the Monte Carlo analytic hierarchy process (MAHP) and ordered weighted averaging (OWA) operator. This method uses MAHP to determine the weight of the evaluation indicators, reducing the randomness of the analytic hierarchy process (AHP) to determine the weight of the evaluation indicators using the OWA operator to quantify the five risk-coping attitudes of decision makers and incorporate the risk attitude of decision makers into the evaluation process. Taking the Liangshuijing Coal Mine in northern Shaanxi as an example, the application of the GIS-MCDA method showed that the method makes the risk results of roof water inrush more objective and comprehensive and reduces or avoids the risk of decision making due to human subjective tendency change. Full article

When the tunnel boring machine (TBM) construction method is used to build tunnels, if the type of TBM is not appropriate, problems, such as low construction efficiency and increased construction cost, will easily occur. Therefore, it is necessary to build a TBM selection decision-making model to guide TBM selection. In this paper, seven evaluation indexes are selected according to engineering experience and expert suggestions, and the quantitative standards of each index are unified. The modified analytic hierarchy process (MAHP) method is used to determine the weight of each evaluation index. The technique for order preference by similarity to an ideal solution (TOPSIS) method is adopted as the decision-making method of TBM selection. Finally, a TBM selection decision-making model is proposed based on the above methods. In order to verify the reliability of the TBM selection decision-making model proposed in this paper, we selected three projects for case verification and compared them with the previous TBM selection methods. The results show that the decision-making results of the method proposed in this paper are good. Additionally, the method proposed in this paper is more comprehensive and accurate than the previous methods. The model proposed in this paper can provide better suggestions for TBM selection in the project planning stage. Full article

Urban areas may be affected by multiple hazards, and integrated hazard susceptibility maps are needed for suitable site selection and planning. Furthermore, geological–geotechnical parameters, construction costs, and the spatial distribution of existing infrastructure should be taken into account for this purpose. Up-to-date land-use and land-cover (LULC) maps, as well as natural hazard susceptibility maps, can be frequently obtained from high-resolution satellite sensors. In this study, an integrated hazard susceptibility assessment was performed for a developing urban settlement (Mamak District of Ankara City, Turkey) considering landslide and flood potential. The flood susceptibility map of Ankara City was produced in a previous study using modified analytical hierarchical process (M-AHP) approach. The landslide susceptibility map was produced using the logistic regression technique in this study. Sentinel-2 images were employed for generating LULC data with the random forest classification method. Topographical derivatives obtained from a high-resolution digital elevation model and lithological parameters were employed for the production of landslide susceptibility maps. For the integrated hazard susceptibility assessment, the Mamdani fuzzy algorithm was considered, and the results are discussed in the present study. The results demonstrate that multi-hazard susceptibility assessment maps for urban planning can be obtained by combining a set of expert-based and ensemble learning methods. Full article