Effects of seepage pressure on the mechanical behaviors and microstructure of sandstone

Surrounding rocks of underground engineering are subjected to long-term seepage pressure,which can deteriorate the mechanical properties and cause serious disasters.In order to understand the impact of seepage pressure on the mechanical property of sandstone,uniaxial compression tests,P-wave velocity measurements,and nuclear magnetic resonance(NMR)tests were conducted on saturated sandstone samples with varied seepage pressures(i.e.0 MPa,3 MPa,4 MPa,5 MPa,6 MPa,7 MPa).The results demonstrate that the mechanical parameters(uniaxial compressive strength,peak strain,elastic modulus,and brittleness index),total energy,elastic strain energy,as well as elastic strain energy ratio,decrease with increasing seepage pressure,while the dissipation energy and dissipation energy ratio increase.Moreover,as seepage pressure increases,the micro-pores gradually transform into meso-pores and macro-pores.This increases the cumulative porosity of sandstone and decreases P-wave velocity.The numerical results indicate that as seepage pressure rises,the number of tensile cracks increases progressively,the angle range of microcracks is basically from 50-120to 80-100,and as a result,the failure mode transforms to the tensile-shear mixed failure mode.Finally,the effects of seepage pressure on mechanical properties were discussed.The results show that decrease in the effective stress and cohesion under the action of seepage pressure could lead to deterioration of strength behaviors of sandstone.

Numerical Simulation of Slurry Diffusion in Fractured Rocks Considering a Time-Varying Viscosity

To analyze the effects of a time-varying viscosity on the penetration length of grouting,in this study cement slur-ries with varying water-cement ratios have been investigated using the Bingham’sfluidflow equation and a dis-crete element method.Afluid-solid coupling numerical model has been introduced accordingly,and its accuracy has been validated through comparison of theoretical and numerical solutions.For different fracture forms(a single fracture,a branch fracture,and a fracture network),the influence of the time-varying viscosity on the slurry length range has been investigated,considering the change in the fracture aperture.The results show that under different fracture forms and the same grouting process conditions,the influence of the time-varying viscosity on the seepage length is 0.350 m.

Experimental and numerical investigation on failure characteristics and mechanism of coal with different water contents

Water injection, as a widely used technique to prevent coal burst, can restrain the fractured coal seam and released the energy storage. In this study, laboratory tests were frstly carried out on standard coal specimens with fve diferent water contents (i.e., 0%, 0.6%, 1.08%, 1.5%, 2.0%, and 2.3%). The failure mode, fragment size, and energy distribution characteristics of coal specimens were investigated. Experimental results show that strength, elastic strain energy, dissipated energy, brittleness index, as well as impact energy index decrease with increasing water content. Besides, the failure mode transitions gradually from splitting ejection to tensile-shear mixed failure mode as water content increases, and average fragment size shows positively related to water content. Moreover, scanning electron microscope tests results indicate that water in coal sample mainly causes the mineral softening and defects increase. Furthermore, a numerical model containing roadway excavation was established considering the water on coal burst prevention. Modelling results revealed that water injection can reduce degree of coal burst and ejection velocity of coal blocks, while it will raise up the depth of crack zone and surface displacement of roadway. Combined with laboratory tests and numerical results, the micro mechanism, energy mechanism, and engineering signifcance of water injection on coal burst prevention were fnally analyzed.

Seismic Attenuation and Velocity Dispersion to Discriminate Gas Hydrates and Free Gas Zone, Makran Offshore, Pakistan

Gas hydrates gained a remarkable attention as an unconventional energy resource recently. In order to interpret gas hydrates (part of fluid) and free gas saturated zone accurately, it is essential to implement new technique related to seismic attenuation and velocity dispersion. P wave attenuation and velocity dispersion in porous media made promising imprints for exploration of gas hydrates. The most prominent phenomenon for attenuation and velocity dispersion in porous media is wave induced fluid flow in which wave inhomogeneities are larger than pore size but smaller than wavelength. Numerical simulation technique is applied to analyze frequency dependent velocity dispersion and attenuation in gas hydrates and free gas layer in Makran offshore of Pakistan. Homogeneous and patchy distribution patterns of gas hydrates and free gas within pore spaces of host sediments at lower and higher frequency regime are considered. It is noted that the attenuation and velocity dispersion increase with the increase in gas hydrates saturation. The maximum attenuation is observed at 66% saturation of gas hydrates in the area under investigation. However, in case of water and gas mixture the maximum attenuation and velocity dispersion occur at low gas saturation (~15%). Therefore, based on our numerical simulation, velocity dispersion and attenuation can be used as seismic attributes to differentiate various gas saturations and gas hydrates saturation for Makran offshore area of Pakistan.

石墨烯包覆天然球形石墨作为锂离子电池的负极材料,是否需要乙炔黑导电剂?

我们通过包覆炭化的方法制备得到了石墨烯包覆的天然球形石墨(G/SG)材料,并使用扫描电子显微镜、X射线衍射仪以及多种电化学测试手段考察了不同石墨烯含量的复合材料的形貌结构及电化学性能。我们发现,在不添加乙炔黑(AB)的情况下,G/SG复合材料表现出较高的首次库伦效率,很好的循环稳定性和高倍率性能。当石墨烯包覆量为1%时,材料50次循环后的可逆容量可与添加10%AB的天然石墨电极(SG)等同;当石墨烯包覆量为2.5%时,材料的比容量完全高于添加10%AB的石墨电极。材料电化学性能的改善归因于石墨烯的包覆。一方面,石墨烯的柔软可变性可以保证天然石墨颗粒在充放电过程中的结构完整性,从而有效改善材料的循环稳定性;另一方面,石墨烯的存在提高了电极的导电性,促进更好导电网络的形成。因此,石墨烯包覆天然球形石墨材料中,石墨烯不仅是活性物质,也发挥导电剂的作用。当添加5%的乙炔黑时,在50 mA·g^(-1)电流循环50次后,5%G/SG电极的可逆容量从381.1 mAh·g^(-1)提高到404.5 mAh·g^(-1),在1 A·g^(-1)电流时可逆容量从82.5 mAh·g^(-1)提高到101.9 mAh·g^(-1),这表明G/SG电极仍然需要乙炔黑导电剂。乙炔黑颗粒填充在复合材料的空隙中,通过点接触的形式连接到G/SG颗粒,与石墨烯协同作用形成了更加有效的导电网络。尽管石墨烯包覆和乙炔黑添加对天然石墨电极具有积极的影响,例如增加了天然石墨电极的导电性和储锂性能(包括可逆容量,倍率性能和循环性能),但随着石墨烯或乙炔黑的增加,电极密度通常会降低。因此,在实际应用中应考虑石墨负极材料的质量和体积容量的平衡。这些结果对天然石墨的进一步商业应用具有重要意义。我们的工作为天然石墨电极在锂电池中的电化学行为提供了一种新的认识,并且有助于制备更高性能的负极材料。

A real-time prediction method for tunnel boring machine cutter-head torque using bidirectional long short-term memory networks optimized by multi-algorithm

Based on data from the Jilin Water Diversion Tunnels from the Songhua River(China),an improved and real-time prediction method optimized by multi-algorithm for tunnel boring machine(TBM)cutter-head torque is presented.Firstly,a function excluding invalid and abnormal data is established to distinguish TBM operating state,and a feature selection method based on the SelectKBest algorithm is proposed.Accordingly,ten features that are most closely related to the cutter-head torque are selected as input variables,which,in descending order of influence,include the sum of motor torque,cutter-head power,sum of motor power,sum of motor current,advance rate,cutter-head pressure,total thrust force,penetration rate,cutter-head rotational velocity,and field penetration index.Secondly,a real-time cutterhead torque prediction model’s structure is developed,based on the bidirectional long short-term memory(BLSTM)network integrating the dropout algorithm to prevent overfitting.Then,an algorithm to optimize hyperparameters of model based on Bayesian and cross-validation is proposed.Early stopping and checkpoint algorithms are integrated to optimize the training process.Finally,a BLSTMbased real-time cutter-head torque prediction model is developed,which fully utilizes the previous time-series tunneling information.The mean absolute percentage error(MAPE)of the model in the verification section is 7.3%,implying that the presented model is suitable for real-time cutter-head torque prediction.Furthermore,an incremental learning method based on the above base model is introduced to improve the adaptability of the model during the TBM tunneling.Comparison of the prediction performance between the base and incremental learning models in the same tunneling section shows that:(1)the MAPE of the predicted results of the BLSTM-based real-time cutter-head torque prediction model remains below 10%,and both the coefficient of determination(R^(2))and correlation coefficient(r)between measured and predicted values exceed 0.95;and(2)the incremental learning method is suitable for realtime cutter-head torque prediction and can effectively improve the prediction accuracy and generalization capacity of the model during the excavation process.

On the Development of an Effective Pressure Driving System for Ultra-Low Permeability Reservoirs

Given its relevance to the exploitation of ultra-low permeability reservoirs,which account for a substantial proportion of the world’s exploited and still unexploited reserves,in the present study the development of an adequate water injection system is considered.Due to the poor properties and weak seepage capacity of these reservoirs,the water injection pressure typically increases continuously during water flooding.In this research,the impact on such a process of factors as permeability,row spacing,and pressure gradient is evaluated experimentally using a high-pressure large-scale outcrop model.On this basis,a comprehensive evaluation coefficient is introduced able to account for the effective driving pressure.

Gentianine protects hippocampal neurons in a rat model of recurrent febrile convulsion

Gentianine has been shown to have a protective effect on hippocampal CA1 neurons in rats subjected to recurrent febrile convulsion（FC）.The present study sought to explore the possible mechanism of gentianine by intraperitoneally injecting gentianine into rats with warm water-induced FC.The results revealed that neuronal organelle injury was slightly ameliorated in the hippocampal CA1 region.The level of glutamate was decreased,but the level of γ-aminobutyric acid was increased,as detected by ninhydrin staining.In addition,glutamate acid decarboxylase expression in hippocampal CA1 was increased,as determined by immunohistochemistry.The results demonstrated that gentianine can ameliorate FC-induced neuronal injury by enhancing glutamate acid decarboxylase activity,decreasing glutamate levels and increasing γ-aminobutyric acid levels.

Experimental and theoretical insights into copper phthalocyanine-based covalent organic frameworks for highly efficien radioactive iodine capture

Exploring efficient materials for capturing radioactive iodine in nuclear waste is of great significance for the progress of nuclear energy as well as the protection of ecological environment.Covalent organic frameworks(COFs)have emerged as promising adsorbents because of their predesignable and functionalizable skeleton structures.However,it remains a grand challenge to achieve large scale preparation of COFs.In this work,we developed a mild and efficient microwave irradiation method instead of the traditional solvothermal method to prepare copper phthalocyanine-based covalent organic frameworks(Cu_(x)Pc-COFs)within only 15 min.The nitrogen-rich 1,2,4,5-tetracarbonitrilebenzene(TCNB)was selected as the solely organic ligand to construct copper phthalocyanine-based 2D conjugated COFs.The resultant Cu_(x)Pc-COFs exhibited excellent iodine enrichment with 2.99 g/g for volatile iodine and 492.27 mg/g for iodine-cyclohexane solution,respectively,outperforming that of many porous materials.As indicated by spectroscopic analysis and DFT calculations,this impressive adsorption performance can be attributed to the charge transfer arising from nitrogen-rich phthalocyanine structures and electron-richπ-conjugated systems with iodine molecules.Moreover,the strong electrostatic interaction between Cu(Ⅱ)on chelate centers and polyiodide anions(I_(x)^(-))also play an important role in the firmly trapping radioactive iodine.Therefore,this study provides a facile and intelligent approach to implement metal-based COFs for the remediation of toxic radioactive iodine.

High-Temperature and Low-Frequency Acoustic Energy Absorption by a Novel Porous Metamaterial Structure

In this paper,we propose a novel porous metamaterial structure with an improved acoustic energy absorption performance at high-temperature and in the low-frequency range.In the proposed novel porous metamaterial structure,a porous material matrix containing periodically perforated cylindrical holes arranged in a triangular lattice pattern is applied,and additional interlayers of another porous material are introduced around these perforations.The theoretical model is established by adopting the double porosity theory for the interlayer and the cylindrical hole which form an equivalent inclusion and then applying the homogenization method to the porous metamaterial structure formed by the equivalent inclusion and the porous matrix.The temperature-dependent air and material parameters are considered in the extended theoretical model,which is validated by the finite element results obtained by COMSOL Multiphysics.The acoustic or sound energy absorption performance can be improved remarkably at very low frequencies and high temperature.Furthermore,the underlying acoustic energy absorption mechanism inside the unit-cell is investigated by analyzing the distribution of the time-averaged acoustic power dissipation density and the energy dissipation ratio of each constituent porous material.The results reveal that regardless of the temperature,the acoustic energy is mostly dissipated in the porous material with a lower airflow resistivity,while the acoustic energy dissipated in the porous material with a higher airflow resistivity also becomes considerable in the high-frequency range.The novel porous metamaterial structure proposed in this paper can be efficiently utilized to improve the acoustic energy absorption performance at high temperature.

Computational cytometer based on magnetically modulated coherent imaging and deep learning

Detecting rare cells within blood has numerous applications in disease diagnostics.Existing rare cell detection techniques are typically hindered by their high cost and low throughput.Here,we present a computational cytometer based on magnetically modulated lensless speckle imaging,which introduces oscillatory motion to the magneticbead-conjugated rare cells of interest through a periodic magnetic force and uses lensless time-resolved holographic speckle imaging to rapidly detect the target cells in three dimensions(3D).In addition to using cell-specific antibodies to magnetically label target cells,detection specificity is further enhanced through a deep-learning-based classifier that is based on a densely connected pseudo-3D convolutional neural network(P3D CNN),which automatically detects rare cells of interest based on their spatio-temporal features under a controlled magnetic force.To demonstrate the performance of this technique,we built a high-throughput,compact and cost-effective prototype for detecting MCF7 cancer cells spiked in whole blood samples.Through serial dilution experiments,we quantified the limit of detection(LoD)as 10 cells per millilitre of whole blood,which could be further improved through multiplexing parallel imaging channels within the same instrument.This compact,cost-effective and high-throughput computational cytometer can potentially be used for rare cell detection and quantification in bodily fluids for a variety of biomedical applications.

Orderly Porous Covalent Organic Frameworks-based Materials:Superior Adsorbents for Pollutants Removal from Aqueous Solutions

Covalent organic frameworks(COFs)are a new type of crystalline porous polymers known for chemical stability,excellent structural regularity,robust framework,and inherent porosity,making them promising materials for capturing various types of pollutants from aqueous solutions.This review thoroughly presents the recent progress and advances of COFs and COF-based materials as superior adsorbents for the efficient removal of toxic heavy metal ions,radionuclides,and organic pollutants.Information about the interaction mechanisms between various pollutants and COF-based materials are summarized from the macroscopic and microscopic standpoints,including batch experiments,theoretical calculations,and advanced spectroscopy analysis.The adsorption properties of various COF-based materials are assessed and compared with other widely used adsorbents.Several commonly used strategies to enhance COF-based materials’adsorption performance and the relationship between structural property and sorption ability are also discussed.Finally,a summary and perspective on the opportunities and challenges of COFs and COF-based materials are proposed to provide some inspiring information on designing and fabricating COFs and COF-based materials for environmental pollution management.