An internal ballistic model of electromagnetic railgun based on PFN coupled with multi-physical field and experimental validation

To accelerate the practicality of electromagnetic railguns,it is necessary to use a combination of threedimensional numerical simulation and experiments to study the mechanism of bore damage.In this paper,a three-dimensional numerical model of the augmented railgun with four parallel unconventional rails is introduced to simulate the internal ballistic process and realize the multi-physics field coupling calculation of the rail gun,and a test experiment of a medium-caliber electromagnetic launcher powered by pulse formation network(PFN)is carried out.Various test methods such as spectrometer,fiber grating and high-speed camera are used to test several parameters such as muzzle initial velocity,transient magnetic field strength and stress-strain of rail.Combining the simulation results and experimental data,the damage condition of the contact surface is analyzed.

Investigating effect of coke porosity on blast furnace performance based on multi-physical fields

Reducing coke use is an effective measure to reduce carbon emission and energy consumption in the blast furnace(BF)ironmaking.Essentially,BF is a high-temperature moving bed reactor,where complex physical transformations coupled with complicated reactions occur.This makes it challenging to investigate the factors determining BF performance with the conventional method.A multi-physical field coupling mathematical model of BF was thus developed to describe its mass and heat transfer as well as its intrinsic reactions.Then,the proposed model was validated with the production data.Under coupling conditions,influences of dominating reactions on BF performance(temperature distribution,gas distribution,iron formation reaction,and direct reduction degree)were revealed.The results indicated that coke combustion,indirect reduction,and direct reduction of iron ore mainly took place nearby the shaft tuyere,cohesive zone,and dripping zone,respectively.Besides,the rate of coke solution loss reaction was increased with the rising coke porosity in the cohesive zone.Considering the effect of coke porosity on the efficiency and stability of BF,the coke porosity of 0.42 was regarded as a reasonable value.

Observation and research of deep underground multi-physical fields—Huainan–848 m deep experiment

Compared with the surface,the deep environment has the advantages of allowing“super-quiet and ultra-clean”-geophysical field observation with low vibration noise and little electromagnetic interference,which are conducive to the realization of long-term and high-precision observation of multi-physical fields,thus enabling the solution of a series of geoscience problems.In the Panyidong Coal Mine,where there are extensive underground tunnels at the depth of 848 m below sea level,we carried out the first deep-underground geophysical observations,including radioactivity,gravity,magnetic,magnetotelluric,background vibration and six-component seismic observations.We concluded from these measurements that(1)the background of deep subsurface gravity noise in the long-period frequency band less than 2 Hz is nearly two orders of magnitude weaker than that in the surface observation environment;(2)the underground electric field is obviously weaker than the surface electric field,and the relatively high frequency of the underground field,greater than 1 Hz,is more than two orders of magnitude weaker than that of the surface electric field;the east-west magnetic field underground is approximately the same as that at the surface;the relatively high-frequency north-south magnetic field underground,below 10 Hz,is at least one order of magnitude lower than that at the surface,showing that the underground has a clean electromagnetic environment;(3)in addition to the highfrequency and single-frequency noises introduced by underground human activities,the deep underground space has a significantly lower background vibration noise than the surface,which is very beneficial to the detection of weak earthquake and gravity signals;and(4)the underground roadway support system built with ferromagnetic material interferes the geomagnetic field.We also found that for deep observation in the“ultra-quiet and ultra-clean”environment,the existing geophysical equipment and observation technology have problems of poor adaptability and insufficient precision as well as data cleaning problems,such as the effective separation of the signal and noise of deep observation data.It is also urgent to interpret and comprehensively utilize these high-precision multi-physics observation data.

Effect of melt current on multi-physical field and heat flow distribution during ESR process based on model of dynamic formation of slag skin

A numerical model coupled with a multi-physical field based on dynamic formation of slag skin is established.After validation by comparing the experimental and simulation results of depth of metal pool,slag skin thickness and melt rate,it is utilized to investigate the effect of melt current on the coupled multi-physical field,slag skin thickness,metal pool depth and the heat flow distribution during electroslag remelting(ESR)Inconel 625 solidification process.The results showed that with the increase in the melt current,the velocities of ESR system and the temperature of metal pool increased,whereas the highest temperature of slag bath firstly decreased and then increased.With the increase in the melt current,the slag skin thickness,metal pool depth and melt rate increased.Furthermore,the characteristics of the heat flow distribution and the effect of melt current on the heat flow distribution were analysed.

Numerical simulation of coupling multi-physical field in electrical arc furnace for smelting titanium slag

The smelting reduction process of the ilmenite in an electric arc furnace(EAF)is a commonly used technology for producing titanium slag in the world.It has particular significance to analyze the velocity-temperature-electromagnetics multi-physical field in an EAF for improving its productivity and reducing energy consumption.A transient three-dimensional mathematical model was developed to characterize the flow,heat transfer,and electromagnetic behavior in a titanium slag EAF.For describing the electromagnetic field and its effects on velocity and temperature distribution in the furnace,magnetohydrodynamic equations and conservation equations for mass,momentum,and energy were solved simultaneously by compiling the user-defined function program.The numerical model was verified by comparing with the literature data.The results indicate that the Lorentz force is the main driving force of the velocity and temperature distribution.Moreover,the influence of input current and location of electrodes on the multi-physical field distribution was also investigated.It is found that the appropriate range of input current and diameter of pitch circle are about 30,000 A and 3000-3500 mm,respectively.The mathematical model established can characterize the multi-physical field more accu-rately than before,which can provide valuable guidance for the operation improvement and design optimization of the EAF for producing titanium slag.

Subsurface multi-physical characterization of mountain excavation and city construction in loess plateau with a fiber-optic sensing system

Mountain excavation and city construction(MECC)projects being launched in the Loess Plateau in China involve the creation of large-scale artificial land.Understanding the subsurface evolution characteristics of the artificial land is essential,yet challenging.Here,we use an improved fiber-optic monitoring system for its subsurface multi-physical characterization.The system enables us to gather spatiotemporal distribution of various parameters,including strata deformation,temperature,and moisture.Yan’an New District was selected as a case study to conduct refined in-situ monitoring through a 77 m-deep borehole and a 30 m-long trench.Findings reveal that the ground settlement involves both the deformation of the filling loess and the underlying intact loess.Notably,the filling loess exhibits a stronger creep capability compared to underlying intact loess.The deformation along the profile is unevenly distributed,with a positive correlation with soil moisture.Water accumulation has been observed at the interface between the filling loess and the underlying intact loess,leading to a significant deformation.Moreover,the temperature and moisture in the filling loess have reached a new equilibrium state,with their depths influenced by atmospheric conditions measuring at 31 m and 26 m,respectively.The refined investigation allows us to identify critical layers that matter the sustainable development of newly created urban areas,and provide improved insights into the evolution mechanisms of land creation.

Simultaneously realizing thermal andelectromagnetic cloaking by multi-physicalnull medium

Simultaneously manipulating multiple physical fields plays an important role in the increasingly complex integrated systems,aerospace equipment,biochemical productions,etc.For on-chip systems with high integration level,the precise and efficient control of the propagation of electromagnetic waves and heat fluxes simultaneously is particularly important.In this study,we propose a graphical designing method(i.e.,thermal-electromagnetic surface transformation)based on thermal-electromagnetic null medium to simultaneously control the propagation of electromagnetic waves and thermal fields according to the pre-designed paths.A thermal-electromagnetic cloak,which can create a cloaking effect on both electromagnetic waves and thermal fields simultaneously,is designed by thermal-electromagnetic surface transformation and verified by both numerical simulations and experimental measurements.The thermal-electromagnetic surface transformation proposed in this study provides a new methodology for simultaneous controlling on electromagnetic and temperature fields,and may have significant applications in improving thermal-electromagnetic compatibility problem,protecting of thermal-electromagnetic sensitive components,and improving efficiency of energy usage for complex onchip systems.

Coupled Numerical Simulation of Electromagnetic and Flow Fields in a Magnetohydrodynamic Induction Pump

Magnetohydrodynamic(MHD)induction pumps are contactless pumps able to withstand harsh environments.The rate of fluid flow through the pump directly affects the efficiency and stability of the device.To explore the influence of induction pump settings on the related delivery speed,in this study,a numerical model for coupled electromagnetic and flow field effects is introduced and used to simulate liquid metal lithium flow in the induction pump.The effects of current intensity,frequency,coil turns and coil winding size on the velocity of the working fluid are analyzed.It is shown that the first three parameters have a significant impact,while changes in the coil turns have a negligible influence.The maximum increase in working fluid velocity within the pump for the parameter combination investigated in this paper is approximately 618%.As the frequency is increased from 20 to 60 Hz,the maximum increase in the mean flow rate of the working fluid is approximately 241%.These research findings are intended to support the design and optimization of these devices.

CFD–DEM–CVD multi-physical field coupling model for simulating particle coating process in spout bed

Particle coating is a very important step in many industrial production processes as the particle coating layers may fix surfaces with unique advantages. Given the limitation and disadvantages of the existing simulation methods, a coupled CFD–DEM–CVD multi-physical field model for particle-coating simulations has been established taking into account the velocity field, temperature field, concentration field, and deposition model. In this model, gas behavior and chemical reactions are simulated in the CFD frame based on the conservation laws of mass, momentum, and energy. The particle behavior is simulated in the DEM frame based on the gas–solid interphase force model and contact force model. The deposition behavior is simulated in the CVD frame based on the particle movement–adhesion–deposition model. The coupled model can be implemented in Fluent-EDEM software with their user definition function and application programming interface. The particle coating process involving the pyrolysis of acetylene was investigated, and the effect of bed temperature and inlet gas velocity on deposition rate and coating efficiency were investigated based on the proposed model with adjustable deposition coefficients. Both the average deposition layer mass and the average deposition layer thickness were found to be proportional to the elapsed time and increased at the rate of about 1.05 × 10^-2 mg/s and 3.45 × 10^-4 mm/s, respectively, setting the inlet gas velocity to 11 m/s and bed temperature to 1680 K. A higher temperature and larger inlet gas velocity lead to a larger deposition rate, but the coating efficiency decreases because of limits imposed by the chemical reaction. At a bed temperature of 1280 K, the average deposition rate is 7.40 × 10?3 mg/s when the inlet gas velocity is set to 11 m/s, which is about double the deposition rate when the inlet gas velocity is set as 5 m/s. The proposed model can provide some guidance for the operating conditions and parameters design of the spouted bed in actual coating settings and can also be further developed as a basic model of mechanisms to integrate detailed information across multiple scales.

Multi-physical field coupling simulation of TCVI process for preparing carbon/carbon composites

To prepare Carbon/Carbon (C/C) composites with advanced performance, the thermal gradient chemical vapor infiltration (TCVI) process has been optimized by simulation. A 2D axisymmetric unstable model was built, which included convection, conduction, diffusion, densification reactions in the pores and the evolution of the porous medium. The multi-physical field coupling model was solved by finite element method (FEM) and iterative calculation. The time evolution of the fluid, temperature and preform density field were obtained by the calculation. It is indicated that convection strongly affects the temperature field. For the preform of carbon/carbon composites infiltrated for 100 h by TCVI, the radial average densities from simulation agrees well with those from experiment. The model is validated to be reliable and the simulation has capability of forecasting the process.

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.

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.

Research on heat dissipation characteristics of magnetic fluid bearings under multiple field coupling effects

This paper analyzes the sources of heat losses in magnetic fluid bearings,proposes various cou-pling relationships of physical fields,divides the coupled heat transfer surfaces while ensuring the continuity of heat flux density,and analyzes the overall heat dissipation pathways of the bearings.By changing parameters such as input current,rotor speed,and inlet oil flow rate,the study applies a multi-physics field coupling method to investigate the influence of different parameters on the temper-ature field and heat dissipation patterns of the bearings,which is then validated through experi-ments.This research provides a theoretical basis for the optimal design of magnetic fluid bearing sys-tems.

Displacement field reconstruction in landslide physical modeling by using a terrain laser scanner e Part 2:Application and large strain/displacement and water effect analysis

Deformation analysis is fundamental in geotechnical modeling.Nevertheless,there is still a lack of an effective method to obtain the deformation field under various experimental conditions.In this study,we introduce a processebased physical modeling of a pileereinforced reservoir landslide and present an improved deformation analysis involving large strains and water effects.We collect multieperiod point clouds using a terrain laser scanner and reconstruct its deformation field through a point cloud processing workflow.The results show that this method can accurately describe the landslide surface deformation at any time and area by both scalar and vector fields.The deformation fields in different profiles of the physical model and different stages of the evolutionary process provide adequate and detailed landslide information.We analyze the large strain upstream of the pile caused by the pile installation and the consequent violent deformation during the evolutionary process.Furthermore,our method effectively overcomes the challenges of identifying targets commonly encountered in geotechnical modeling where water effects are considered and targets are polluted,which facilitates the deformation analysis at the wading area in a reservoir landslide.Eventually,combining subsurface deformation as well as numerical modeling,we comprehensively analyze the kinematics and failure mechanisms of this complicated object involving landslides and pile foundations as well as water effects.This method is of great significance for any geotechnical modeling concerning large-strain analysis and water effects.

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.

Electromagnetic fields in ultra-peripheral relativistic heavy-ion collisions

Ultra-peripheral heavy-ion collisions(UPCs)offer unique opportunities to study processes under strong electromagnetic fields.In these collisions,highly charged fast-moving ions carry strong electromagnetic fields that can be effectively treated as photon fluxes.The exchange of photons can induce photonuclear and two-photon interactions and excite ions.This excitation of the ions results in Coulomb dissociation with the emission of photons,neutrons,and other particles.Additionally,the electromagnetic fields generated by the ions can be sufficiently strong to enforce mutual interactions between the two colliding ions.Consequently,the two colliding ions experience an electromagnetic force that pushes them in opposite directions,causing a back-to-back correlation in the emitted neutrons.Using a Monte Carlo simulation,we qualitatively demonstrate that the above electromagnetic effect is large enough to be observed in UPCs,which would provide a clear means to study strong electromagnetic fields and their effects.

Constructing Built-In Electric Fields with Semiconductor Junctions and Schottky Junctions Based on Mo-MXene/Mo-Metal Sulfides for Electromagnetic Response

The exploration of novel multivariate heterostructures has emerged as a pivotal strategy for developing high-performance electromagnetic wave(EMW)absorption materials.However,the loss mechanism in traditional heterostructures is relatively simple,guided by empirical observations,and is not monotonous.In this work,we presented a novel semiconductor-semiconductor-metal heterostructure sys-tem,Mo-MXene/Mo-metal sulfides(metal=Sn,Fe,Mn,Co,Ni,Zn,and Cu),including semiconductor junctions and Mott-Schottky junctions.By skillfully combining these distinct functional components(Mo-MXene,MoS_(2),metal sulfides),we can engineer a multiple heterogeneous interface with superior absorption capabilities,broad effective absorption bandwidths,and ultrathin matching thickness.The successful establishment of semiconductor-semiconductor-metal heterostructures gives rise to a built-in electric field that intensifies electron transfer,as confirmed by density functional theory,which collaborates with multiple dielectric polarization mechanisms to substantially amplify EMW absorption.We detailed a successful synthesis of a series of Mo-MXene/Mo-metal sulfides featuring both semiconductor-semiconductor and semiconductor-metal interfaces.The achievements were most pronounced in Mo-MXene/Mo-Sn sulfide,which achieved remarkable reflection loss values of-70.6 dB at a matching thickness of only 1.885 mm.Radar cross-section calculations indicate that these MXene/Mo-metal sulfides have tremendous potential in practical military stealth technology.This work marks a departure from conventional component design limitations and presents a novel pathway for the creation of advanced MXene-based composites with potent EMW absorption capabilities.

Enhancing the resolution of sparse rock property measurements using machine learning and random field theory

The travel time of rock compressional waves is an essential parameter used for estimating important rock properties,such as porosity,permeability,and lithology.Current methods,like wireline logging tests,provide broad measurements but lack finer resolution.Laboratory-based rock core measurements offer higher resolution but are resource-intensive.Conventionally,wireline logging and rock core measurements have been used independently.This study introduces a novel approach that integrates both data sources.The method leverages the detailed features from limited core data to enhance the resolution of wireline logging data.By combining machine learning with random field theory,the method allows for probabilistic predictions in regions with sparse data sampling.In this framework,12 parameters from wireline tests are used to predict trends in rock core data.The residuals are modeled using random field theory.The outcomes are high-resolution predictions that combine both the predicted trend and the probabilistic realizations of the residual.By utilizing unconditional and conditional random field theories,this method enables unconditional and conditional simulations of the underlying high-resolution rock compressional wave travel time profile and provides uncertainty estimates.This integrated approach optimizes the use of existing core and logging data.Its applicability is confirmed in an oil project in West China.