重力方法研究越南早新生代基底效果分析(英文)

为了提高用重力方法在越南研究早新生代基底结构特点中的效率,表明作者们提出了一个综合分析地质及地球物理资料的系统方法.获得的研究结果表明:1)一个大的平均密度差是在用重力方法研究越南的早新生代基底时效率的一个基本因素;2)用多维线性相关分析来有效研究和预测越南的早新生代基底岩石的埋藏深度与密度是有可能的;3)通过利用多维线性分析预测密度以及泊松系数使我们能预测早新生代基底岩石.     

Determining the Concentration of Suspended Sediment in the Lower Đáy River (Northern Vietnam) Using MSI Sentinel 2 High Spatial Resolution Data

Izvestiya, Atmospheric and Oceanic Physics - The concentration of suspended sediment is an important parameter in assessing the quality of surface waters. Many studies have shown that reflectance...     

Prediction of Blast-induced Air Over-pressure in Open-Pit Mine: Assessment of Different Artificial Intelligence Techniques

Air over-pressure (AOp) is one of the products of blasting operations for rock fragmentation in open-pit mines. It can cause structural vibration, smash glass doors, adversely affect the surrounding environment, and even be fatal to humans. To assess its dangerous effects, seven artificial intelligence (AI) methods for predicting specific blast-induced AOp have been applied and compared in this study. The seven methods include random forest, support vector regression, Gaussian process, Bayesian additive regression trees, boosted regression trees, k-nearest neighbors, and artificial neural network (ANN). An empirical technique was also used to compare with AI models. The degree of complexity and the performance of the models were compared with each other to find the optimal model for predicting blast-induced AOp. The Deo Nai open-pit coal mine (Vietnam) was selected as a case study where 113 blasting events have been recorded. Indicators used for evaluating model performances include the root-mean-square error (RMSE), determination coefficient (R²), and mean absolute error (MAE). The results indicate that AI techniques provide better performance than the empirical method. Although the relevance of the empirical approach was acceptable (R²?=?0.930) in this study, its error (RMSE?=?7.514) is highly significant to guarantee the safety of the surrounding environment. In contrast, the AI models offer much higher accuracies. Of the seven AI models, ANN was the most dominant model based on RMSE, R², and MAE. This study demonstrated that AI techniques are excellent for predicting blast-induced AOp in open-pit mines. These techniques are useful for blasters and managers in controlling undesirable effects of blasting operations on the surrounding environment.

     

Novel Soft Computing Model for Predicting Blast-Induced Ground Vibration in Open-Pit Mines Based on Particle Swarm Optimization and XGBoost

Natural Resources Research - Blasting is a useful technique for rocks fragmentation in open-pit mines, underground mines, as well as for civil engineering work. However, the negative impacts of...     

Prediction of Blast-Induced Ground Vibration in Open-Pit Mines Using a New Technique Based on Imperialist Competitive Algorithm and M5Rules

Natural Resources Research - In this paper, blast-induced ground vibration (BIGV) was considered as the primary objective, and a new artificial intelligence system was proposed to predict BIGV with...     

A Novel Intelligent ELM-BBO Technique for Predicting Distance of Mine Blasting-Induced Flyrock

Natural Resources Research - Blasting is an economical technique for rock breaking in hard rock excavation. One of its complex undesired environmental effects is flyrock, which may result in human...     

An approach to calculating large strain accumulation for discrete element simulations of granular media

For research on granular materials, establishing a method to calculate continuum strain from particle displacements is necessary for understanding the material behaviour at macro-level and developing continuum constitutive models. Existing methods are generally based on constructing a mesh or background grid to calculate strain from particle motions. These methods offer rigorous ways to measure strain for granular materials; however, they suffer from several problems such as mesh distortion and lacking grid-to-particle strain mapping procedure, which hinders their capability of calculating strain accumulation during large deformation processes of granular media. To address this issue, this study proposes a new strain calculation method for discrete element simulations of granular materials. This method describes a particle assembly as an equivalent continuum system of material points, each of which corresponds to a particle centre and represents a continuous region with its initial volume/area presumably equal to the volume/area of Voronoi cells generated in accordance with the particle assembly configuration. Smooth Particle Hydrodynamics (SPH) interpolation functions are then employed to calculate strain for these material points. This SPH-based method does not require any mesh or background grid for computation, leading to advantages in calculating strain accumulation under large deformation. Simulations of granular materials in both uniform and heterogeneous gradations were carried out, and strain results obtained by the proposed method indicate good agreements with analytical and numerical solutions. This demonstrates its potential for strain calculations in discrete element simulations of granular materials involving large deformations and/or large displacements.     

Constraining the cosmological time variation of the fine - structure constant

The variation of the fine-structure constant α = e ² / ħc can be probed by comparing the wavelength of atomic transitions from the redshift of quasars in the Universe and laboratory over cosmological time scales t ~ 10¹⁰ yr. After a careful selection of pairs of lines, the Thong method with a derived analytical expression for the error analysis was applied to compute the α variation. We report a new constraint on the variation of the fine-structure constant based on the analysis of the C_IV, N_V, Mg_II, Al_III, and Si_IV doublet absorption lines. The weighted mean value of the variation in α derived from our analysis over the redshift range 0.4939 ≤ z ≤ 3.7 is = ( 0.09 ± 0.07)×10⁻⁵. This result is three orders of magnitude better than the results obtained by earlier analysis of the same data on the constraint on Δα/α .     

Theoretical and numerical studies of the Vishniac instability in supernova remnants

Vishniac instability has been theoretically studied in supernova remnants where it is supposed to explain the fragmentation of the interstellar medium. However its role is not fully demonstrated in these astrophysical objects. Conditions and assumptions required for the instability growth are explained in detail in the present paper. In addition the HYDRO-MUSCL hydrodynamic code has been used to simulate this instability in order to compare the numerical growth rate with the Vishniac analytical solution.     

Model development and calibration for the coupled thermal,hydraulic and mechanical phenomena of the bentonite

In the international DECOVALEX-THMC project, five research teams study the influence of thermal-hydro-mechanical (THM) coupling on the safety of a hypothetical geological repository for spent fuel. In order to improve the analyses, the teams calibrated their bentonite models with results from laboratory experiments, including swelling pressure tests, water uptake tests, thermally gradient tests, and the CEA mock-up THM experiment. This paper describes the mathematical models used by the teams, and compares the results of their calibrations with the experimental data.