Drilling-based measuring method for the c-φ parameter of rock and its field application

The technology of drilling tests makes it possible to obtain the strength parameter of rock accurately in situ. In this paper, a new rock cutting analysis model that considers the influence of the rock crushing zone(RCZ) is built. The formula for an ultimate cutting force is established based on the limit equilibrium principle. The relationship between digital drilling parameters(DDP) and the c-φ parameter(DDP-cφ formula, where c refers to the cohesion and φ refers to the internal friction angle) is derived, and the response of drilling parameters and cutting ratio to the strength parameters is analyzed. The drillingbased measuring method for the c-φ parameter of rock is constructed. The laboratory verification test is then completed, and the difference in results between the drilling test and the compression test is less than 6%. On this basis, in-situ rock drilling tests in a traffic tunnel and a coal mine roadway are carried out, and the strength parameters of the surrounding rock are effectively tested. The average difference ratio of the results is less than 11%, which verifies the effectiveness of the proposed method for obtaining the strength parameters based on digital drilling. This study provides methodological support for field testing of rock strength parameters.

ST-LSTM-SA:A New Ocean Sound Velocity Field Prediction Model Based on Deep Learning

The scarcity of in-situ ocean observations poses a challenge for real-time information acquisition in the ocean.Among the crucial hydroacoustic environmental parameters,ocean sound velocity exhibits significant spatial and temporal variability and it is highly relevant to oceanic research.In this study,we propose a new data-driven approach,leveraging deep learning techniques,for the prediction of sound velocity fields(SVFs).Our novel spatiotemporal prediction model,STLSTM-SA,combines Spatiotemporal Long Short-Term Memory(ST-LSTM) with a self-attention mechanism to enable accurate and real-time prediction of SVFs.To circumvent the limited amount of observational data,we employ transfer learning by first training the model using reanalysis datasets,followed by fine-tuning it using in-situ analysis data to obtain the final prediction model.By utilizing the historical 12-month SVFs as input,our model predicts the SVFs for the subsequent three months.We compare the performance of five models:Artificial Neural Networks(ANN),Long ShortTerm Memory(LSTM),Convolutional LSTM(ConvLSTM),ST-LSTM,and our proposed ST-LSTM-SA model in a test experiment spanning 2019 to 2022.Our results demonstrate that the ST-LSTM-SA model significantly improves the prediction accuracy and stability of sound velocity in both temporal and spatial dimensions.The ST-LSTM-SA model not only accurately predicts the ocean sound velocity field(SVF),but also provides valuable insights for spatiotemporal prediction of other oceanic environmental variables.

Field test of high-power microwave-assisted mechanical excavation for deep hard iron ore

Microwave-assisted mechanical excavation has great application prospects in mines and tunnels,but there are few field experiments on microwave-assisted rock breaking.This paper takes the Sishanling iron mine as the research object and adopts the self-developed high-power microwave-induced fracturing test system for hard rock to conduct field experiments of microwave-induced fracturing of iron ore.The heating and reflection evolution characteristics of ore under different microwave parameters(antenna type,power,and working distance)were studied,and the optimal microwave parameters were obtained.Subsequently,the ore was irradiated with the optimal microwave parameters,and the cracking effect of the ore under the action of the high-power open microwave was analyzed.The results show that the reflection coefficient(standing wave ratio)can be rapidly(<5 s)and automatically adjusted below the preset threshold value(1.6)as microwave irradiation is performed.When using a right-angle horn antenna with a working distance of 5 cm,the effect of automatic reflection adjustment reaches the best among other antenna types and working distances.When the working distance is the same,the average temperature of the irradiation surface and the area of the high-temperature area under the action of the two antennas(right-angled and equal-angled horn antenna)are basically the same and decrease with the increase of working distance.The optimal microwave parameters are:a right-angle horn antenna with a working distance of 5 cm.Subsequently,in further experiments,the optimal parameters were used to irradiate for 20 s and 40 s at a microwave power of 60 kW,respectively.The surface damage extended 38 cm×30 cm and 53 cm×30 cm,respectively,and the damage extended to a depth of about 50 cm.The drilling speed was increased by 56.2%and 66.5%,respectively,compared to the case when microwaves were not used.

Reactor field reconstruction from sparse and movable sensors using Voronoi tessellation-assisted convolutional neural networks

The aging of operational reactors leads to increased mechanical vibrations in the reactor interior.The vibration of the incore sensors near their nominal locations is a new problem for neutronic field reconstruction.Current field-reconstruction methods fail to handle spatially moving sensors.In this study,we propose a Voronoi tessellation technique in combination with convolutional neural networks to handle this challenge.Observations from movable in-core sensors were projected onto the same global field structure using Voronoi tessellation,holding the magnitude and location information of the sensors.General convolutional neural networks were used to learn maps from observations to the global field.The proposed method reconstructed multi-physics fields(including fast flux,thermal flux,and power rate)using observations from a single field(such as thermal flux).Numerical tests based on the IAEA benchmark demonstrated the potential of the proposed method in practical engineering applications,particularly within an amplitude of 5 cm around the nominal locations,which led to average relative errors below 5% and 10% in the L_(2) and L_(∞)norms,respectively.

Strong coupling and catenary field enhancement in the hybrid plasmonic metamaterial cavity and TMDC monolayers

Strong coupling between resonantly matched surface plasmons of metals and excitons of quantum emitters results in the formation of new plasmon-exciton hybridized energy states.In plasmon-exciton strong coupling,plasmonic nanocavities play a significant role due to their ability to confine light in an ultrasmall volume.Additionally,two-dimensional transition metal dichalcogenides(TMDCs) have a significant exciton binding energy and remain stable at ambient conditions,making them an excellent alternative for investigating light-matter interactions.As a result,strong plasmon-exciton coupling has been reported by introducing a single metallic cavity.However,single nanoparticles have lower spatial confinement of electromagnetic fields and limited tunability to match the excitonic resonance.Here,we introduce the concept of catenary-shaped optical fields induced by plasmonic metamaterial cavities to scale the strength of plasmon-exciton coupling.The demonstrated plasmon modes of metallic metamaterial cavities offer high confinement and tunability and can match with the excitons of TMDCs to exhibit a strong coupling regime by tuning either the size of the cavity gap or thickness.The calculated Rabi splitting of Au-MoSe_2 and Au-WSe_2 heterostructures strongly depends on the catenary-like field enhancement induced by the Au cavity,resulting in room-temperature Rabi splitting ranging between 77.86 and 320 me V.These plasmonic metamaterial cavities can pave the way for manipulating excitons in TMDCs and operating active nanophotonic devices at ambient temperature.

A new electric field mill array with each of the mill’s rotor controlled precisely by a GPS module:Equipment and initial results

We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning discharges.It is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple locations.For multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed instruments.Currently,there is no such EFM with specified speed and phase control performance of the rotary part.Thus,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS module.Five EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test observation.Here we describe the design and a simple calibration method for our new EFM array.Data analysis method based on the assumption of a simple monopole charge structure is also summarized.For validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF bands.Initial results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.

Numerical simulation of melt flow and temperature field during DC casting 2024 aluminium alloy under different casting conditions

Casting speed,casting temperature and secondary cooling water flow rate are the main process parameters affecting the DC casting process.These parameters significantly influence the flow and temperature fields during casting,which are crucial for the quality of the ingot and can determine the success or failure of the casting operation.Numerical simulation,with the advantages of low cost,rapid execution,and visualized results,is an important method to study and optimize the DC casting process.In the present work,a simulation model of DC casting 2024 aluminum alloy was established,and the reliability of the model was verified.Then,the influence of casting parameters on flow field and temperature field was studied in detail by numerical simulation method.Results show that with the increase of casting speed,the melt flow becomes faster,the depths of slurry zone and mushy zone increase,and the variation of slurry zone depth is greater than that of mushy zone.With an increase in casting temperature,the melt flow rate increases,the depth of the slurry zone becomes shallower,and the depth of the mushy zone experiences only minor changes.The simulation results further indicate that the increase of the flow rate of the secondary cooling water slightly reduces the depths of both slurry and mushy zone.

Strong field ionization of molecules on the surface of nanosystems

Besides the diverse investigations on the interactions between intense laser fields and molecular systems,extensive research has been recently dedicated to exploring the response of nanosystems excited by well-tailored femtosecond laser fields.Due to the fact that nanostructures hold peculiar effects when illuminated by laser pulses,the underlying mechanisms and the corresponding potential applications can make significant improvements in both fundamental research and development of novel techniques.In this review,we provide a summarization of the strong field ionization occurring on the surface of nanosystems.The molecules attached to the nanoparticle surface perform as the precursor in the ionization and excitation of the whole nanosystem,the fundamental processes of which are yet to be discovered.We discuss the influence on nanoparticle constituents,geometric shapes and sizes,as well as the specific waveforms of the excitation laser fields.The intriguing characteristics observed in surface ion emission reflect how enhanced near field affects the localized ionizations and nanoplasma expansions,thereby paving the way for further precision controls on the light-and-matter interactions in the extreme spatial temporal levels.

Variational Reconstruction and Simulation Experiments of Sea Surface Wind Field for Ocean Data Buoy

The sea surface wind field is an important physical parameter in oceanography and meteorology.With the continuous refinement of numerical weather prediction,air-sea interface materials,energy exchange,and other studies,three-dimensional(3D)wind field distribution at local locations on the sea surface must be measured accurately.The current in-situ observation of sea surface wind parameters is mainly achieved through the installation of wind sensors on ocean data buoys.However,the results obtained from this single-point measurement method cannot reflect wind field distribution in a vertical direction above the sea surface.Thus,the present paper proposes a theoretical framework for the optimal inversion of the 3D wind field structure variation in the area where the buoy is located.The variation analysis method is first used to reconstruct the wind field distribution at different heights of the buoy,after which theoretical analysis verification and numerical simulation experiments are conducted.The results indicate that the use of variational methods to reconstruct 3D wind fields is significantly effective in eliminating disturbance errors in observations,which also verifies the correctness of the theoretical analysis of this method.The findings of this article can provide a reference for the layout optimization design of wind measuring instruments in buoy observation systems and also provide theoretical guidance for the design of new observation buoys in the future.

A booming field of large animal model research

Animal models are integral to the study of fundamental biological processes and the etiology of human diseases.Small animal models,especially those involving mice,have yielded abundant and significant insights,greatly enhancing our understanding of biological phenomena and disease mechanisms.

Optimization of magnetic field design for Hall thrusters based on a genetic algorithm

Magnetic field design is essential for the operation of Hall thrusters.This study focuses on utilizing a genetic algorithm to optimize the magnetic field configuration of SPT70.A 2D hybrid PIC-DSMC and channel-wall erosion model are employed to analyze the plume divergence angle and wall erosion rate,while a Farady probe measurement and laser profilometry system are set up to verify the simulation results.The results demonstrate that the genetic algorithm contributes to reducing the divergence angle of the thruster plumes and alleviating the impact of high-energy particles on the discharge channel wall,reducing the erosion by 5.5%and 2.7%,respectively.Further analysis indicates that the change from a divergent magnetic field to a convergent magnetic field,combined with the upstream shift of the ionization region,contributes to the improving the operation of the Hall thruster.

Spin Resolved Zero-Line Modes in Minimally Twisted Bilayer Graphene from Exchange Field and Gate Voltage

The reliance on spin-orbit coupling or strong magnetic fields has always posed significant challenges for the mass production and even laboratory realization of most topological materials. Valley-based topological zero-line modes have attracted widespread attention due to their substantial advantage of being initially realizable with just an external electric field. However, the uncontrollable nature of electrode alignment and precise fabrication has greatly hindered the advancement in this field. By utilizing minimally twisted bilayer graphene and introducing exchange fields from magnetic substrates, we successfully realize a spin-resolved, electrode-free topological zeroline mode. Further integration of electrodes that do not require alignment considerations significantly enhances the tunability of the system's band structure. Our approach offers a promising new support for the dazzling potential of topological zero-line mode in the realm of low-energy-consumption electronics.

Superposition of dual electric fields in covalent organic frameworks for efficient photocatalytic hydrogen evolution

Covalent organic frameworks(COFs)are promising materials for converting solar energy into green hydrogen.However,limited charge separation and transport in COFs impede their application in the photocatalytic hydrogen evolution reaction(HER).In this study,the intrinsically tunable inter-nal bond electric field(IBEF)at the imine bonds of COFs was manipulated to cooperate with the internal molecular electric field(IMEF)induced by the donor-acceptor(D-A)structure for an effi-cient HER.The aligned orientation of IBEF and IMEF resulted in a remarkable H_(2)evolution rate of 57.3 mmol·g^(-1)·h^(-1)on TNCA,which was approximately 520 times higher than that of TCNA(0.11 mmol·g^(-1)·h^(-1))with the opposing electric field orientation.The superposition of the dual electric fields enables the IBEF to function as an accelerating field for electron transfer,kinetically facilitat-ing the migration of photogenerated electrons from D to A.Furthermore,theoretical calculations indicate that the inhomogeneous charge distribution at the C and N atoms in TNCA not only pro-vides a strong driving force for carrier transfer but also effectively hinders the return of free elec-trons to the valence band,improving the utilization of photoelectrons.This strategy of fabricating dual electric fields in COFs offers a novel approach to designing photocatalysts for clean energy synthesis.

Imaging a force field via an optically levitated nanoparticle array

Levitated optomechanical systems represent an excellent candidate platform for force and acceleration sensing.We propose a force-sensing protocol utilizing an optically levitated nanoparticle array.In our scheme,N nanoparticles are trapped in an optical cavity using holographic optical tweezers.An external laser drives the cavity,exciting N cavity modes interacting simultaneously with the N nanoparticles.The optomechanical interaction encodes the information of the force acting on each nanoparticle onto the intracavity photons,which can be detected directly at the output ports of the cavity.Consequently,our protocol enables real-time imaging of a force field.

Simulation of the SMILE Soft X-ray Imager response to a southward interplanetary magnetic field turning

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)Soft X-ray Imager(SXI)will shine a spotlight on magnetopause dynamics during magnetic reconnection.We simulate an event with a southward interplanetary magnetic field turning and produce SXI count maps with a 5-minute integration time.By making assumptions about the magnetopause shape,we find the magnetopause standoff distance from the count maps and compare it with the one obtained directly from the magnetohydrodynamic(MHD)simulation.The root mean square deviations between the reconstructed and MHD standoff distances do not exceed 0.2 RE(Earth radius)and the maximal difference equals 0.24 RE during the 25-minute interval around the southward turning.

Petrology and Structural Characterization of Post-Neoproterozoic Dolerites from the Kimberlite Fields in the Kéniéba Region (Western Mali)

Post-Neoproterozoic dolerites from the Kéniéba region (Western Mali) are often associated with kimberlites. The rarity of kimberlite outcrops led to the study of doleritic rocks, spatially associated with them. The petrographic and lithogeochemical study showed that the dolerites of the Kéniéba kimberlitic fields are of tholeiitic nature and of the E-MORB (Enriched-Mid Ocean Ridge Basalt) type. This reflects an enrichment over time, compared to the Birimian dolerites of the volcano-sedimentary greenstone belt of Toumodi, in central C?te d’Ivoire. Furthermore, these dolerites are enriched in SiO2, TiO2, Zr and poor in Fe2O3, MgO. These dolerites would have formed in a late to post-orogenic intracontinental context during the breakup of Gondwana. Structurally, Kéniéba dolerites are often associated with kimberlite pipes, fractures and large deep structures identified using aeromagnetic images. Taking into account the fact that kimberlites do not outcrop in the Kéniéba region, the geochemical study coupled with the interpretation of aeromagnetic data proved to be very useful for the search for pipes.

A solution method for decomposing vector fields in Hamilton energy

Hamilton energy,which reflects the energy variation of systems,is one of the crucial instruments used to analyze the characteristics of dynamical systems.Here we propose a method to deduce Hamilton energy based on the existing systems.This derivation process consists of three steps:step 1,decomposing the vector field;step 2,solving the Hamilton energy function;and step 3,verifying uniqueness.In order to easily choose an appropriate decomposition method,we propose a classification criterion based on the form of system state variables,i.e.,type-I vector fields that can be directly decomposed and type-II vector fields decomposed via exterior differentiation.Moreover,exterior differentiation is used to represent the curl of low-high dimension vector fields in the process of decomposition.Finally,we exemplify the Hamilton energy function of six classical systems and analyze the relationship between Hamilton energy and dynamic behavior.This solution provides a new approach for deducing the Hamilton energy function,especially in high-dimensional systems.

Revolutionizing plasmonic platform via magnetic field-assisted confined ultrafast laser deposition of high-density,uniform,and ultrafine nanoparticle arrays

The remarkable capabilities of 2D plasmonic surfaces in controlling optical waves havegarnered significant attention.However,the challenge of large-scale manufacturing of uniform,well-aligned,and tunable plasmonic surfaces has hindered their industrialization.To address this,we present a groundbreaking tunable plasmonic platform design achieved throughmagnetic field(MF)assisted ultrafast laser direct deposition in air.Through precise control of metal nanoparticles(NPs),with cobalt(Co)serving as the model material,employing an MF,and fine-tuning ultrafast laser parameters,we have effectively converted coarse and non-uniform NPs into densely packed,uniform,and ultrafine NPs(~3 nm).This revolutionary advancement results in the creation of customizable plasmonic‘hot spots,’which play a pivotal role insurface-enhanced Raman spectroscopy(SERS)sensors.The profound impact of this designable plasmonic platform lies in its close association with plasmonic resonance and energyenhancement.When the plasmonic nanostructures resonate with incident light,they generate intense local electromagnetic fields,thus vastly increasing the Raman scattering signal.This enhancement leads to an outstanding 2–18 fold boost in SERS performance and unparalleled sensing sensitivity down to 10^(-10)M.Notably,the plasmonic platform also demonstratesrobustness,retaining its sensing capability even after undergoing 50 cycles of rinsing andre-loading of chemicals.Moreover,this work adheres to green manufacturing standards,making it an efficient and environmentally friendly method for customizing plasmonic‘hot spots’inSERS devices.Our study not only achieves the formation of high-density,uniform,and ultrafine NP arrays on a tunable plasmonic platform but also showcases the profound relation betweenplasmonic resonance and energy enhancement.The outstanding results observed in SERS sensors further emphasize the immense potential of this technology for energy-relatedapplications,including photocatalysis,photovoltaics,and clean water,propelling us closer to a sustainable and cleaner future.

Effect of Artificial Electric Field Surface by Wave-Driven Triboelectricity on Anti-Bioadhesion for Riser Protection

Biofouling has been a persistent problem in marine riser system, resulting in energy waste and equipment damage. Inthis study, a kind of water wave-driven contact-mode flexible triboelectric nanogeneration has been prepared byusing graphene-doped PDMS as dielectric friction material. When the graphene content is 2%, the average outputvoltage can reach 46 V under the contact frequency 10 Hz. The flexible triboelectric nanogeneration encapsulationmodule is impinged by water waves to generate alternating microelectric field on the riser surface and destroy theadhesion conditions of microorganisms during the biofilm stage. In the biofouling experiments at different stages, thebiofouling area of the platymonas subcordiformis has been reduced by 53%, 62% and 61%. It provides a new ideafor effective treatment of biofouling of mussels, oysters and barnacles attached to risers.

Phase-field lattice-Boltzmann study on fully coupled thermal-solute-convection dendrite growth of Al-Cu alloy

Dendrite growth is a complex liquid-solid phase transition process involving multiple physical factors.A phase-field lattice-Boltzmann method was developed to simulate the two-and three-dimension dendrite growth of Al-Cu alloy.The effect of fully coupled thermal-solute-convection interaction on the dendrite growth was investigated by incorporating a parallel-adaptive mesh refinement algorithm into the numerical model.By accurately reproducing the latent heat release,solute diffusion and convective transport behaviors at the liquidsolid interface,the interaction mechanism among thermal-solute-convection transport as well as their coupling effects on the dendrite growth dynamics were discussed.The simulation results show that the release of latent heat slows down the dendrite growth rate,and both natural and forced convection disrupt the symmetrical growth of dendrites.Their combination makes the growth of dendrites more complex,capturing important physical aspects such as recalescence,dendrite tip splitting,dendrite tilting,dendrite remelting,and solute plume in the simulation case.Based on the robustness and powerful ability of the numerical model,the formation mechanisms of these physical aspects were revealed.