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.

Research on simulation of gun muzzle flow field empowered by artificial intelligence

Artificial intelligence technology is introduced into the simulation of muzzle flow field to improve its simulation efficiency in this paper.A data-physical fusion driven framework is proposed.First,the known flow field data is used to initialize the model parameters,so that the parameters to be trained are close to the optimal value.Then physical prior knowledge is introduced into the training process so that the prediction results not only meet the known flow field information but also meet the physical conservation laws.Through two examples,it is proved that the model under the fusion driven framework can solve the strongly nonlinear flow field problems,and has stronger generalization and expansion.The proposed model is used to solve a muzzle flow field,and the safety clearance behind the barrel side is divided.It is pointed out that the shape of the safety clearance under different launch speeds is roughly the same,and the pressure disturbance in the area within 9.2 m behind the muzzle section exceeds the safety threshold,which is a dangerous area.Comparison with the CFD results shows that the calculation efficiency of the proposed model is greatly improved under the condition of the same calculation accuracy.The proposed model can quickly and accurately simulate the muzzle flow field under various launch conditions.

Influence of upstream solar wind on magnetic field distribution in the Martian nightside ionosphere

Using over eight years of Mars Atmosphere and Volatile Evolutio N(MAVEN)data,from November 2014 to May 2023,we have investigated the Martian nightside ionospheric magnetic field distribution under the influence of upstream solar wind drivers,including the interplanetary magnetic field intensity(∣BIMF∣),solar wind dynamic pressure(PS W),solar extreme ultraviolet flux(EUV),and Martian seasons(L s).Our analysis reveals pronounced correlations between magnetic field residuals and both∣BIMF∣and PS W.Correlations observed with EUV flux and Ls were weaker—notably,magnetic field residuals increased during periods of high EUV flux and at Mars perihelion.We find that the IMF penetrates to an altitude of 200 km under a wide range of upstream conditions,penetrating notably deeper under high∣BIMF∣andPSWconditions.Our analysis also indicates that EUV flux and IMF cone angle have minimal impact on IMF penetration depth.Those findings provide useful constraints on the dynamic nature of Martian atmospheric escape processes and their evolution,suggesting that historical solar wind conditions may have facilitated deeper IMF penetration and higher rates of ionospheric escape than are observed now.Moreover,by establishing criteria for magnetic‘quiet’conditions,this study offers new insights into the planet’s magnetic environment under varying solar wind influences,knowledge that should help refine models of the Martian crustal magnetic field.

Modeling of axion and electromagnetic fields interaction in particle-in-cell simulations

The axion,a theoretically well-motivated particle,has been searched for extensively via its hypothetical interactions with ordinary matter and fields.Recently,a new axion detection approach has been considered utilizing the ultra-intense electromagnetic fields produced by laser-plasma interactions.However,a detailed simulation tool has not hitherto been available to help understand the axion-coupled laser-plasma interactions in such a complex environment.In this paper,we report a custom-developed particle-in-cell(PIC) simulation method that incorporates the axion field,the electromagnetic fields,and their interactions.The axion field equation and modified Maxwell's equations are numerically solved,with the axion-induced modulation of the electromagnetic field being treated as a first-order perturbation to handle the huge orders of magnitude difference between the two types of field.The simulation is benchmarked with well-studied effects such as axion-photon conversion and the propagation of an extremely weak laser pulse in a magnetized plasma.Such an extended PIC simulation provides a powerful tool to study axions under ultra-intense electromagnetic fields in the laboratory or in astrophysical processes.

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.

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.

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.

Electric field and force characteristic of dust aerosol particles on the surface of high-voltage transmission line

High-voltage transmission lines play a crucial role in facilitating the utilization of renewable energy in regions prone to desertification. The accumulation of atmospheric particles on the surface of these lines can significantly impact corona discharge and wind-induced conductor displacement. Accurately quantifying the force exerted by particles adhering to conductor surfaces is essential for evaluating fouling conditions and making informed decisions. Therefore, this study investigates the changes in electric field intensity along branched conductors caused by various fouling layers and their resulting influence on the adhesion of dust particles. The findings indicate that as individual particle size increases, the field strength at the top of the particle gradually decreases and eventually stabilizes at approximately 49.22 k V/cm, which corresponds to a field strength approximately 1.96 times higher than that of an unpolluted transmission line. Furthermore,when particle spacing exceeds 15 times the particle size, the field strength around the transmission line gradually decreases and approaches the level observed on non-adhering surface. The electric field remains relatively stable. In a triangular arrangement of three particles, the maximum field strength at the tip of the fouling layer is approximately 1.44 times higher than that of double particles and 1.5 times higher compared to single particles. These results suggest that particles adhering to the transmission line have a greater affinity for adsorbing charged particles. Additionally, relevant numerical calculations demonstrate that in dry environments, the primary adhesion forces between particles and transmission lines follow an order of electrostatic force and van der Waals force. Specifically, at the minimum field strength, these forces are approximately74.73 times and 19.43 times stronger than the gravitational force acting on the particles.

Probing the peripheral self-generated magnetic field distribution in laser-plasma magnetic reconnection with Martin-Puplett interferometer polarimeter

Magnetic reconnection of the self-generated magnetic fields in laser-plasma interaction is an important laboratory method for modeling high-energy density astronomical and astrophysical phenomena.We use the Martin-Puplett interferometer(MPI)polarimeter to probe the peripheral magnetic fields generated in the common magnetic reconnection configuration,two separated coplanar plane targets,in laser-target interaction.We introduce a new method that can obtain polarization information from the interference pattern instead of the sinusoidal function fitting of the intensity.A bidirectional magnetic field is observed from the side view,which is consistent with the magneto-hydro-dynamical(MHD)simulation results of self-generated magnetic field reconnection.We find that the cancellation of reverse magnetic fields after averaging and integration along the observing direction could reduce the magnetic field strength by one to two orders of magnitude.It indicates that imaging resolution can significantly affect the accuracy of measured magnetic field strength.

Displacement field reconstruction in landslide physical modeling by using a terrain laser scanner e Part 1:Methodology,error analysis and validation

Laser scanning technology has been widely used in landslide aspects.However,the existing deformation analysis based on terrain laser scanners can only provide limited information,which is insufficient for understanding landslide kinematics and failure mechanisms.To overcome this limitation,this paper proposes an automated method for processing point clouds collected in landslide physical modeling.This method allows the acquisition of quantitative three-dimensional(3D)deformation field information.The results show the organized and spatially related point cloud segmentation in terms of spherical targets.The segmented point clouds can be fitted to determine the locations of all preset targets and their corresponding location changes.The proposed method has been validated based on theoretical analysis and numerical and physical tests,which indicates that it can batch-process massive data sets with high computational efficiency and good noise resistance.Compared to existing methods,this method shows a significant potential for understanding landslide kinematics and failure mechanisms and advancing the application of 3D laser scanning in geotechnical modeling.

The Formation of Oscillation Patterns Based on the Planetary Gravitational Field and Their Suitability for Earthquake Prediction

The fluctuating planetary gravitational field influences not only activities on the Sun but also on the Earth. A special correlation function describes the harmonics of these fluctuations. Groups of earthquakes form oscillation patterns that differ significantly from randomly chosen control groups. These patterns are suitable as an element of an AI for the probability of earthquakes.

Flow Field Characteristics of Multi-Trophic Artificial Reef Based on Computation Fluid Dynamics

On the basis of computational fluid dynamics,the flow field characteristics of multi-trophic artificial reefs,including the flow field distribution features of a single reef under three different velocities and the effect of spacing between reefs on flow scale and the flow state,were analyzed.Results indicate upwelling,slow flow,and eddy around a single reef.Maximum velocity,height,and volume of upwelling in front of a single reef were positively correlated with inflow velocity.The length and volume of slow flow increased with the increase in inflow velocity.Eddies were present both inside and backward,and vorticity was positively correlated with inflow velocity.Space between reefs had a minor influence on the maximum velocity and height of upwelling.With the increase in space from 0.5 L to 1.5 L(L is the reef lehgth),the length of slow flow in the front and back of the combined reefs increased slightly.When the space was 2.0 L,the length of the slow flow decreased.In four different spaces,eddies were present inside and at the back of each reef.The maximum vorticity was negatively correlated with space from 0.5 L to 1.5 L,but under 2.0 L space,the maximum vorticity was close to the vorticity of a single reef under the same inflow velocity.

The 2023 Turkey earthquake doublet: Earthquake relocation, seismic tomography, and stress field inversion

On February 6,2023,two earthquakes with magnitudes of M_(W) 7.8 and M_(W) 7.5 struck southeastern Turkey,causing significant casualties and economic losses.These seismic events occurred along the East Anatolian Fault Zone,a convergent boundary between the Arabian Plate and the Anatolian Subplate.In this study,we analyze the M_(W) 7.8 and M_(W) 7.5 earthquakes by comparing their aftershock relocations,tomographic images,and stress field inversions.The earthquakes were localized in the upper crust and exhibited steep dip angles.Furthermore,the aftershocks occurred either close to the boundaries of low and high P-wave velocity anomaly zones or within the low P-wave velocity anomaly zones.The East Anatolia Fault,associated with the M_(W) 7.8 earthquake,and the SürgüFault,related to the M_(W) 7.5 earthquake,predominantly experienced shear stress.However,their western sections experienced a combination of strike-slip and tensile stresses in addition to shear stress.The ruptures of the M_(W) 7.8 and M_(W) 7.5 earthquakes appear to have bridged a seismic gap that had seen sparse seismicity over the past 200 years prior to the 2023 Turkey earthquake sequence.

Influence of filler characteristics on particle removal in fluid catalytic cracking slurry under an alternating electric field

The characteristics of the packing material under an alternating electric field are an important factor in the removal of FCCS particles.In this study,the electric field distribution of a separation unit consisting of packed spheres under an alternating electric field is simulated,and the movement mechanism of catalyst particles is analysed.An"effective contact point"model is derived to predict the adsorption of filler contact points on catalyst particles under the alternating electric field,and the model is validated by simulations and experiments.The numerical calculation and experimental results indicate that the electrical properties of the filler spheres,the filler angleθ,and the frequency f of the alternating electric field affect the adsorption of catalyst particles.As the frequency of the electric field increases,the particle removal efficiency of the high-conductivity filler(silicon carbide)increases and then settles,and the separation efficiency of the low-conductivity filler(glass,zirconia)is not sensitive to the change in electric field frequency.

Anti-rollover Artificial Potential Field Motion Planning Method of an Autonomous Heavy Truck Optimised by Game Theory

Anti-rollover is a critical factor to consider when planning the motion of autonomous heavy trucks.This paper proposed a method for autonomous heavy trucks to generate a path that avoids collisions and minimizes rollover risk.The corresponding rollover index is deduced from a 5-DOF heavy truck dynamic model that includes longitudinal motion,lateral motion,yaw motion,sprung mass roll motion,unsprung mass roll motion,and an anti-rollover artificial potential field(APF)is proposed based on this.The motion planning method,which is based on model predictive control(MPC),combines trajectory tracking,anti-rollover APF,and the improved obstacle avoidance APF and considers the truck dynamics constraints,obstacle avoidance,and anti-rollover.Furthermore,by using game theory,the coefficients of the two APF functions are optimised,and an optimal path is planned.The effectiveness of the optimised motion planning method is demonstrated in a variety of scenarios.The results demonstrate that the optimised motion planning method can effectively and efficiently avoid collisions and prevent rollover.

Field survey and analysis on near-fault severely damaged high-speed railway bridge in 2022 M6.9 Menyuan earthquake

The 2022 M6.9 Menyuan earthquake caused severe damage to a high-speed railway bridge,which was designed for high-speed trains running at speeds of above 250 km/h and is located right next to the fault.Bridges of this type have been widely used for rapidly constructing the high-speed railway network,but few bridges have been tested by near-fault devastating earthquakes.The potential severe impact of the earthquake on the high-speed railway is not only the safety of the infrastructure,trains and passengers,but also economic loss due to interrupted railway use.Therefore,a field survey was carried out immediately after the earthquake to collect time-sensitive data.The damage to the bridge was carefully investigated,and quantitative analyses were conducted to better understand the mechanism of the bridge failure.It was found that seismic action perpendicular to the bridge’s longitudinal direction caused severe damage to the girders and rails,while none of the piers showed obvious deformation or cracking.The maximum values of transverse displacement,out-of-plane rotation and twisting angle of girders reached 212.6 cm,3.1 degrees and 19.9 degrees,respectively,causing severe damage to the bearing supports and anti-seismic retaining blocks.These observations provide a basis for improving the seismic design of high-speed railway bridges located in near-fault areas.

Bound State Description of Particles from a Quantum Field Theory of Fermions and Bosons, Compatible with Relativity

Both, the dilemma to find a quantum field theory consistent with Einstein’s law of relativity and the problem to describe existing particles as bound states of matter has been solved by calculating bound state matrix elements from a dual fermion-boson Lagrangian. In this formalism, the fermion binding energies are compensated by boson energies, indicating that particles can be generated out of the vacuum. This yields quantitative solutions for various mesons ω (0.78 GeV) - Υ (9.46 GeV) and all leptons e, μ and τ, with uncertainties in the extracted properties of less than 1‰. For transparency, a Web-page with the address htpps://h2909473.stratoserver.net has been constructed, where all calculations can be run on line and also the underlying fortran source code can be inspected.

Building a Smart Management System for the Field Training Course at the Faculty of Specific Education-Mansoura University

Field training is the backbone of the teacher-preparation process.Its importance stems from the goals that colleges of education aim to achieve,which include bridging the gap between theory and practice and aligning with contemporary educational trends during teacher training.Currently,trainee students attendance in field training is recordedmanually through signatures on attendance sheets.However,thismethod is prone to impersonation,time wastage,and misplacement.Additionally,traditional methods of evaluating trainee students are often susceptible to human errors during the evaluation and scoring processes.Field training also lacks modern technology that the supervisor can use in case of his absence from school to monitor the trainee students’implementation of the required activities and tasks.These shortcomings do not meet the needs of the digital era that universities are currently experiencing.As a result,this paper presents a smart management system for field training based on Internet of Things(IoT)and mobile technology.It includes three subsystems:attendance,monitoring,and evaluation.The attendance subsystem uses an R307 fingerprint sensor to record trainee students’attendance.The Arduino Nano microcontroller transmits attendance data to the proposed Android application via an ESP-12F Wi-Fi module,which then forwards it to the Firebase database for storage.The monitoring subsystem utilizes Global Positioning System(GPS)technology to continually track trainee students’locations,ensuring they remain at the school during training.It also enables remote communication between trainee students and supervisors via audio,video,or text by integrating video call and chat technologies.The evaluation subsystem is based on three items:an online exam,attendance,and implementation of required activities and tasks.Experimental results have demonstrated the accuracy and efficiency of the proposed management system in recording attendance,as well as in monitoring and evaluating trainee students during field traiing.

Retinal vascular morphological characteristics in diabetic retinopathy: an artificial intelligence study using a transfer learning system to analyze ultra-wide field images

AIM:To investigate the morphological characteristics of retinal vessels in patients with different severity of diabetic retinopathy(DR)and in patients with or without diabetic macular edema(DME).METHODS:The 239 eyes of DR patients and 100 eyes of healthy individuals were recruited for the study.The severity of DR patients was graded as mild,moderate and severe non-proliferative diabetic retinopathy(NPDR)according to the international clinical diabetic retinopathy(ICDR)disease severity scale classification,and retinal vascular morphology was quantitatively analyzed in ultra-wide field images using RU-net and transfer learning methods.The presence of DME was determined by optical coherence tomography(OCT),and differences in vascular morphological characteristics were compared between patients with and without DME.RESULTS:Retinal vessel segmentation using RU-net and transfer learning system had an accuracy of 99%and a Dice metric of 0.76.Compared with the healthy group,the DR group had smaller vessel angles(33.68±3.01 vs 37.78±1.60),smaller fractal dimension(Df)values(1.33±0.05 vs 1.41±0.03),less vessel density(1.12±0.44 vs 2.09±0.36)and fewer vascular branches(206.1±88.8 vs 396.5±91.3),all P<0.001.As the severity of DR increased,Df values decreased,P=0.031.No significant difference between the DME and non-DME groups were observed in vascular morphological characteristics.CONCLUSION:In this study,an artificial intelligence retinal vessel segmentation system is used with 99%accuracy,thus providing with relatively satisfactory performance in the evaluation of quantitative vascular morphology.DR patients have a tendency of vascular occlusion and dropout.The presence of DME does not compromise the integral retinal vascular pattern.

Charging Properties and Particle Dynamics of Chang’e-5 Lunar Sample in an External Electric Field

Facing the challenges of in-situ utilization of lunar regolith resources,applying an external electric field to manipulate lunar particles has become a promising method for space particle control,which mainly depends on the particle charging properties in the applied electric field.Using the surficial lunar regolith samples brought back from the Moon by the Chang’e-5 mission(CE5 LS),this work successively studied their charging properties,particle dynamics,and their collision damages to aerospace materials under the action of an external electric field in high-vacuum conditions.The results indicated that the charging pro-cess and electrostatic projection of lunar regolith particles under high-vacuum conditions were different from those under atmosphere conditions.The particle diameter range of CE5 LS used in the experiment is 27.7-139.0 lm.For electric field strength of 3-12 kV·cm^(-1),the charge obtained by CE5 LS is 4.8×10^(-15)-4.7×10^(-13) C and the charge-to-mass ratio is 1.2×10^(-5)-6.8×10^(-4) C·kg^(-1).The CE5 LS is easier to be negatively charged in an external electric field.Furthermore,significant damages were observed on the target impact surfaces,indicating severe influences of lunar regolith particles on aerospace materials.Our work contributes to a more comprehensive understanding of physical mechanisms controlling the lunar regolith shielding and utilization,and will inspire broad efforts to develop the lunar in-situ engi-neering solutions.