Soft rock is one of the common geological conditions in coal mine underground water reservoir engineering.The cross-scale correlation analysis of water erosion soft lithology deterioration is very important for the sa...Soft rock is one of the common geological conditions in coal mine underground water reservoir engineering.The cross-scale correlation analysis of water erosion soft lithology deterioration is very important for the safety and stability of coal mine underground reservoir(CMUR)engineering.To address the issues of grain crowding and segmentation difficulties in cross-scale corelation analysis,as well as the limitations of traditional etching methods,this study proposes an image grain segmentation method based on deep learning algorithms,utilizing scanning electron microscopy and image process-ing techniques.The method successfully segments crowded grains and eliminates the interference from misplaced particles.In addition,indoor uniaxial compression tests were conducted to obtain the mechanical properties of sandstone samples with different water content.By quantitatively characterizing the macroscopic and microscopic deterioration degree of red sandstone samples with different water contents,the relationship between the strength changes of rock samples and the pet-rographic parameters such as grain size and grain shape is analyzed,and the influence law of soft lithology deterioration in CMUR engineering is revealed.The results indicate:(1)Water significantly weakens the mechanical properties and stability of soft rock.With increasing water content,the strength of sandstone samples continuously decreases,and the failure mode transitions from brittle to ductile failure.(2)The deterioration of micro-micro structures is the main cause of the decrease in mechanical properties of water-eroded soft rock.Grain size,grain area,and aspect ratio are negatively correlated with water content,indicating that hydrophilic minerals in soft rock dissolve under the action of water,leading to rock damage.(3)Grain size,area,and aspect ratio can serve as significant indicators for quantifying the strength changes of water-eroded soft rock.The research findings can be applied to stability assessment and disaster prevention in CMUR engineering.展开更多
Accurate calculations of strongly correlated materials remain a formidable challenge in condensed matter physics,particularly due to the computational demand of conventional methods.This paper presents an efficient so...Accurate calculations of strongly correlated materials remain a formidable challenge in condensed matter physics,particularly due to the computational demand of conventional methods.This paper presents an efficient solver for dynamical mean field theory using configuration interaction(CI).The method is shown to have improved efficiency compared to traditional,exact diagonalization approaches.Hence,it provides an accessible,open-source alternative that can be executed on standard laptop computers or on supercomputers.The solver is demonstrated on cerium in theγ,αandϵphases.An analysis of how the electronic structure of Ce evolves as function of lattice compression is made.It is argued that the electronic structure evolves from a localized nature of the 4f shell in γ-Ce to an essentially itinerant nature of the 4f shell of ϵ-Ce.The transition between these two phases,as function of compression,can hence be seen as a Mott transition.However,this transition is intercepted by the strongly correlatedα-phase of elemental Ce,for which the 4f shell forms a Kondo singlet.展开更多
基金supported by the National Natural Science Foundation of China(51774196,52304093)China Postdoctoral Science Foundation(2023M741968)Shandong Provincial Natural Science Foundation(ZR2023ME086).
文摘Soft rock is one of the common geological conditions in coal mine underground water reservoir engineering.The cross-scale correlation analysis of water erosion soft lithology deterioration is very important for the safety and stability of coal mine underground reservoir(CMUR)engineering.To address the issues of grain crowding and segmentation difficulties in cross-scale corelation analysis,as well as the limitations of traditional etching methods,this study proposes an image grain segmentation method based on deep learning algorithms,utilizing scanning electron microscopy and image process-ing techniques.The method successfully segments crowded grains and eliminates the interference from misplaced particles.In addition,indoor uniaxial compression tests were conducted to obtain the mechanical properties of sandstone samples with different water content.By quantitatively characterizing the macroscopic and microscopic deterioration degree of red sandstone samples with different water contents,the relationship between the strength changes of rock samples and the pet-rographic parameters such as grain size and grain shape is analyzed,and the influence law of soft lithology deterioration in CMUR engineering is revealed.The results indicate:(1)Water significantly weakens the mechanical properties and stability of soft rock.With increasing water content,the strength of sandstone samples continuously decreases,and the failure mode transitions from brittle to ductile failure.(2)The deterioration of micro-micro structures is the main cause of the decrease in mechanical properties of water-eroded soft rock.Grain size,grain area,and aspect ratio are negatively correlated with water content,indicating that hydrophilic minerals in soft rock dissolve under the action of water,leading to rock damage.(3)Grain size,area,and aspect ratio can serve as significant indicators for quantifying the strength changes of water-eroded soft rock.The research findings can be applied to stability assessment and disaster prevention in CMUR engineering.
基金support from the Wallenberg Initiative Materials Science for Sustainability (WISE) funded by the Knut and Alice Wallenberg Foun- dation (KAW) and the European Research Council through the ERC Synergy Grant 854843-FASTCORRO.E. also acknowledges support from STandUPP, eSSENCE, the Swedish Research Council (VR) and the Knut and Alice Wallenberg Foundation (KAW- Scholar program)NL-ECO: Netherlands Initiative for Energy-Efficient Computing (with project number NWA. 1389.20.140) of the NWA research program.
文摘Accurate calculations of strongly correlated materials remain a formidable challenge in condensed matter physics,particularly due to the computational demand of conventional methods.This paper presents an efficient solver for dynamical mean field theory using configuration interaction(CI).The method is shown to have improved efficiency compared to traditional,exact diagonalization approaches.Hence,it provides an accessible,open-source alternative that can be executed on standard laptop computers or on supercomputers.The solver is demonstrated on cerium in theγ,αandϵphases.An analysis of how the electronic structure of Ce evolves as function of lattice compression is made.It is argued that the electronic structure evolves from a localized nature of the 4f shell in γ-Ce to an essentially itinerant nature of the 4f shell of ϵ-Ce.The transition between these two phases,as function of compression,can hence be seen as a Mott transition.However,this transition is intercepted by the strongly correlatedα-phase of elemental Ce,for which the 4f shell forms a Kondo singlet.
