Mechanical behaviours of sandstone containing intersecting fissures under uniaxial compression

Predicting rock cracking is important for assessing the stability of underground engineering.The effects of the intersecting angle a and the distribution orientation angleβof intersecting fissures on the uniaxial compressive strength and the failure characteristics of sandstone containing intersecting fissures are investigated through laboratory experiments and two-dimensional particle flow code(PFC2D).The relationship between the mechanical properties of sandstone and the intersecting angle a and the distribution orientation angleβis analysed.Crack initiation forms and the final failure modes are then categorised and determined via empirical methods.In addition,the cracking processes of intersecting fissures with different a andβvalues are discussed.The results show that variations in the peak stress,peak strain,average modulus,and crack initiation stress of sandstone containing intersecting fissures show a“moth”shape in the space of the a-β-mechanical parameters.Two crack initiation forms are identified:inner tip cracking(usually accompanied by one outer tip cracking)and only outer tips cracking.Two failure modes are observed:(1)the main fracture planes are created at the inner tip and one outer tip,and(2)the main fracture planes are formed at the two outer tips.Two main crack evolution processes of sandstone containing intersecting fissures under uniaxial compression are found.Approaches for quickly determining the crack initiation form and the failure mode are proposed.The combination of the determination equations for the crack initiation form and the failure mode can be used to predict the crack evolution.The approach for determining the crack evolution processes is hence proposed with acceptable precision.

Intersecting Line of Conical Surface and Smoothly Blending of Two Tubes Whose Axes Are Non-Coplanar

We construct two conical surfaces which take non-coplanar lines as generatrix and rational Bezier curve as ridge-line, and prove that the intersecting line of conical surface has similar properties to Bezier curve. Then, the smoothly blending of two cylinders whose axes are non-coplanar is realized by taking intersecting line of conical surface as axes.

Groove modeling and digital simulation for intersecting structures of circular tubes based on coplanarity of vectors

In order to establish the groove model for intersecting structures of circular tubes,mathematical model of the intersecting line is established by the method of analytic geometry,and parametric equations are thus determined.The dihedral angle,groove angle and actual cutting angle for any position of the intersecting line are derived as well.In order to identify groove vectors for two pipes,a new analytical method,i.e.coplanarity of vectors,is further proposed to complete the groove model.The established model is virtually verified by programming and simulation calculation in the MATLAB environment.The results show that groove vectors of intersecting structures simulated by MATLAB are consistent with the theoretical groove model,indicating that the theoretical groove model established in this paper is accurate,and further proves that the proposed coplanarity of vectors for solving groove vectors is correct and feasible.Finally,a graphical user interface(GUI)is developed by MATLAB software to independently realize functions such as model drawing,variable calculation and data output.The research outcome provides a theoretical foundation for the actual welding of circular intersecting structures,and lays an essential basis for weld bead layout and path planning.

The Spectral Radii of Intersecting Uniform Hypergraphs

The celebrated Erdos-Ko-Rado theorem states that given n≥2k,every intersecting k-uni-n-1 form hypergraph G on n vertices has at most(n-1 k-1)edges.This paper states spectral versions of the Erd6s-_Ko--Rado theorem:let G be an intersecting k-uniform hypergraph on n vertices with n≥2k.Then,the sharp upper bounds for the spectral radius of Aα(G)and 2*(G)are presented,where Aα(G)=αD(G)+(1-α).A(G)is a convex linear combination of the degree diagonal tensor D(G)and the adjacency tensor A(G)for 0≤α<1,and Q^(*)(G)is the incidence Q-tensor,respectively.Furthermore,when n>2k,the extremal hypergraphs which attain the sharp upper bounds are characterized.The proof mainly relies on the Perron-Frobenius theorem for nonnegative tensor and the property of the maximizing connected hypergraphs.

Analytical solution for cylindrical thin shells with normally intersecting nozzles due to external moments on the ends of shells

The stress analysis based on the theory of a thin shell is carried out for cylindrical shells with normally intersecting nozzles subjected to external moment loads on the ends of shells with a large diameter ratio （ρ0≤0.8）. Instead of the Donnell shallow shell equation, the modified Morley equation, which is applicable to ρ0 （R/T）1/2（?）1, is used for the analysis of the shell with cutout. The solution in terms of displacement function for the nozzle with a nonplanar end is based on the Goldenveizer equation. The boundary forces and displacements at the intersection are all transformed from Gaussian coordinates （α, β） on the shell, or Gaussian coordinates （ζ, θ） on the nozzle into three-dimensional cylindrical coordinates （ρ, θ, z）. Their expressions on the intersecting curve are periodic functions of θ and expanded in Fourier series. Every harmonic of Fourier coefficients of boundary forces and displacements are obtained by numerical quadrature. The results obtained are in agreement

List Vertex-arboricity of Planar Graphs without Intersecting 5-cycles

The vertex-arboricity a(G)of a graph G is the minimum number of colors required for a vertex coloring of G such that no cycle is monochromatic.The list vertex-arboricity al(G)is the list-coloring version of this concept.In this paper,we prove that every planar graph G without intersecting 5-cycles has al(G)≤2.This extends a result by Raspaud and Wang[On the vertex-arboricity of planar graphs,European J.Combin.29(2008),1064-1075]that every planar graph G without 5-cycles has a(G)≤2.

MULTIPLE INTERSECTIONS OF SPACE-TIME ANISOTROPIC GAUSSIAN FIELDS

Let X={X(t)∈R^(d),t∈R^(N)}be a centered space-time anisotropic Gaussian field with indices H=(H_(1),…,H_(N))∈(0,1)~N,where the components X_(i)(i=1,…,d)of X are independent,and the canonical metric√(E(X_(i)(t)-X_(i)(s))^(2))^(1/2)(i=1,…,d)is commensurate with■for s=(s_(1),…,s_(N)),t=(t_(1),…,t_(N))∈R~N,α_(i)∈(0,1],and with the continuous functionγ(·)satisfying certain conditions.First,the upper and lower bounds of the hitting probabilities of X can be derived from the corresponding generalized Hausdorff measure and capacity,which are based on the kernel functions depending explicitly onγ(·).Furthermore,the multiple intersections of the sample paths of two independent centered space-time anisotropic Gaussian fields with different distributions are considered.Our results extend the corresponding results for anisotropic Gaussian fields to a large class of space-time anisotropic Gaussian fields.

Advancements in machine learning for material design and process optimization in the field of additive manufacturing

Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.

Wetting front migration model of ion-adsorption rare earth during the multi-hole unsaturated liquid injection

In the process of ion-adsorption rare earth ore leaching,the migration characteristics of the wetting front in multi-hole injection holes and the influence of wetting front intersection effect on the migration distance of wetting fronts are still unclear.Besides,wetting front migration distance and leaching time are usually required to optimize the leaching process.In this study,wetting front migration tests of ionadsorption rare earth ores during the multi-hole fluid injection(the spacing between injection holes was 10 cm,12 cm and 14 cm)and single-hole fluid injection were completed under the constant water head height.At the pre-intersection stage,the wetting front migration laws of ion-adsorption rare earth ores during the multi-hole fluid injection and single-hole fluid injection were identical.At the postintersection stage,the intersection accelerated the wetting front migration.By using the Darcy’s law,the intersection effect of wetting fronts during the multi-hole liquid injection was transformed into the water head height directly above the intersection.Finally,based on the Green-Ampt model,a wetting front migration model of ion-adsorption rare earth ores during the multi-hole unsaturated liquid injection was established.Error analysis results showed that the proposed model can accurately simulate the infiltration process under experimental conditions.The research results enrich the infiltration law and theory of ion-adsorption rare earth ores during the multi-hole liquid injection,and this study provides a scientific basis for optimizing the liquid injection well pattern parameters of ion-adsorption rare earth in situ leaching in the future.

The prediction of projectile-target intersection for moving tank based on adaptive robust constraint-following control and interval uncertainty analysis

To improve the hit probability of tank at high speed,a prediction method of projectile-target intersection based on adaptive robust constraint-following control and interval uncertainty analysis is proposed.The method proposed provides a novel way to predict the impact point of projectile for moving tank.First,bidirectional stability constraints and stability constraint-following error are constructed using the Udwadia-Kalaba theory,and an adaptive robust constraint-following controller is designed considering uncertainties.Second,the exterior ballistic ordinary differential equation with uncertainties is integrated into the controller,and the pointing control of stability system is extended to the impact-point control of projectile.Third,based on the interval uncertainty analysis method combining Chebyshev polynomial expansion and affine arithmetic,a prediction method of projectile-target intersection is proposed.Finally,the co-simulation experiment is performed by establishing the multi-body system dynamic model of tank and mathematical model of control system.The results demonstrate that the prediction method of projectile-target intersection based on uncertainty analysis can effectively decrease the uncertainties of system,improve the prediction accuracy,and increase the hit probability.The adaptive robust constraint-following control can effectively restrain the uncertainties caused by road excitation and model error.

Detection Algorithm of Laboratory Personnel Irregularities Based on Improved YOLOv7

Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detection accuracy and slow speed.Therefore,the current management of personnel behavior mainly relies on institutional constraints,education and training,on-site supervision,etc.,which is time-consuming and ineffective.Given the above situation,this paper proposes an improved You Only Look Once version 7(YOLOv7)to achieve the purpose of quickly detecting irregular behaviors of laboratory personnel while ensuring high detection accuracy.First,to better capture the shape features of the target,deformable convolutional networks(DCN)is used in the backbone part of the model to replace the traditional convolution to improve the detection accuracy and speed.Second,to enhance the extraction of important features and suppress useless features,this paper proposes a new convolutional block attention module_efficient channel attention(CBAM_E)for embedding the neck network to improve the model’s ability to extract features from complex scenes.Finally,to reduce the influence of angle factor and bounding box regression accuracy,this paper proposes a newα-SCYLLA intersection over union(α-SIoU)instead of the complete intersection over union(CIoU),which improves the regression accuracy while increasing the convergence speed.Comparison experiments on public and homemade datasets show that the improved algorithm outperforms the original algorithm in all evaluation indexes,with an increase of 2.92%in the precision rate,4.14%in the recall rate,0.0356 in the weighted harmonic mean,3.60%in the mAP@0.5 value,and a reduction in the number of parameters and complexity.Compared with the mainstream algorithm,the improved algorithm has higher detection accuracy,faster convergence speed,and better actual recognition effect,indicating the effectiveness of the improved algorithm in this paper and its potential for practical application in laboratory scenarios.

A Novel Foreign Object Detection Method in Transmission Lines Based on Improved YOLOv8n

The rapid pace of urban development has resulted in the widespread presence of construction equipment andincreasingly complex conditions in transmission corridors. These conditions pose a serious threat to the safeoperation of the power grid.Machine vision technology, particularly object recognition technology, has beenwidelyemployed to identify foreign objects in transmission line images. Despite its wide application, the technique faceslimitations due to the complex environmental background and other auxiliary factors. To address these challenges,this study introduces an improved YOLOv8n. The traditional stepwise convolution and pooling layers are replacedwith a spatial-depth convolution (SPD-Conv) module, aiming to improve the algorithm’s efficacy in recognizinglow-resolution and small-size objects. The algorithm’s feature extraction network is improved by using a LargeSelective Kernel (LSK) attention mechanism, which enhances the ability to extract relevant features. Additionally,the SIoU Loss function is used instead of the Complete Intersection over Union (CIoU) Loss to facilitate fasterconvergence of the algorithm. Through experimental verification, the improved YOLOv8n model achieves adetection accuracy of 88.8% on the test set. The recognition accuracy of cranes is improved by 2.9%, which isa significant enhancement compared to the unimproved algorithm. This improvement effectively enhances theaccuracy of recognizing foreign objects on transmission lines and proves the effectiveness of the new algorithm.

关于两个两点Witten-Kontsevich关联子公式等价的一个注记

We prove the equivalence between two explicit expressions for two-point Witten-Kontsevich correlators obtained by Bertola-Dubrovin-Yang and by Zograf, respectively.

A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

Static behavior of planar intersecting CFST connection in diagrid structure

Intersecting connection plays an important role in the new diagrid structural system for high-rise buildings.To investigate the static behavior of the intersecting connection of concrete-filled steel tubular(CFST)columns,a typical reduced-scale planner connection specimen is tested under monotonic axial compression.The failure modes,force mechanism and bearing capacity of intersecting CFST connections are analyzed further in the follow-up numerical simulation,considering influences of intersecting angle,elliptical plate and ring plate.Test and simulation results prove that,intersecting connection can develop fully plastic deformation and provide sufficient bearing capacity.Parametric analysis indicates that bearing capacity of planar intersecting CFST connection mainly depends on intersecting angle and thickness of elliptical plate,while the ring plate affects that little.Capacity estimation method for planar intersecting CFST connection is proposed basing on the capacity of the critical section which is located near intersecting center for a distance of steel tube radius,and the design suggestions is provided in the end of this paper.

Four-family N = 1 supersymmetric Pati-Salam models from intersecting D6-branes

We investigate the construction of four-family N= 1 supersymmetric Pati-Salam models from Type IIA T^(6)×Z_(2) Z_(2) orientifold with intersecting D6-branes. Utilizing the deterministic algorithm introduced in He W, Li T and Sun R(2021 ar Xiv: hep-th/2112.09632), we obtain 274 types of models with three rectangular tori and distinct gauge coupling relations at string scale,while 6 types of models with two rectangular tori and one tilted torus. In both cases, there exists a class of models with gauge coupling unification at string scale. In particular, for the models with two rectangular tori, one tilted torus and gauge coupling unification, the gaugino condensations are allowed, and thus supersymmetry breaking and moduli stabilization are possible for further phenomenological study.

Proactive Platooning Based on C-V2X to Relieve Congestion at a Signalized Intersection

Nowadays urban traffic congestion becomes a major issue due to the increase in vehicles that lead to more commuting time,accidents,traffic violations,and high fuel consumption.Platooning is a good way to solve traffic congestion because it drives with a smaller inter-vehicle distance than human-driving.This paper proposes proactive platooning based on C-V2X(cellular vehicle-to-everything)to relieve congestion.Proactive platooning reduces the inter-vehicle distance and increases the throughput of signalized intersections through integrating the networked control platooning and computation-centralized platooning.Model and simulation experiments of proactive platooning were conducted to verify the impact of inter-vehicle distance on platooning latency,platooning safety,and traffic throughput.Simulation results show that the optimal inter-vehicle distance under proactive platooning is less than half of human-driving at a signalized intersection.

TOA positioning algorithm of LBL system for underwater target based on PSO

For the underwater long baseline(LBL)positioning systems,the traditional distance intersection algorithm simplifies the sound speed to a constant,and calculates the underwa-ter target position parameters with a nonlinear iteration.However,due to the complex underwater environment,the sound speed changes with time and space,and then the acoustic propagation path is actually a curve,which inevitably causes some errors to the traditional distance intersection positioning algorithm.To reduce the position error caused by the uncertain underwater sound speed,a new time of arrival(TOA)intersection underwater positioning algorithm of LBL system is proposed.Firstly,combined with the vertical layered model of the underwater sound speed,an implicit positioning model of TOA intersection is constructed through the constant gradient acoustic ray tracing.And then an optimization function based on the overall TOA residual square sum is advanced to solve the position parameters for the underwater target.Moreover,the particle swarm optimization(PSO)algorithm is replaced with the tra-ditional nonlinear least square method to optimize the implicit positioning model of TOA intersection.Compared with the traditional distance intersection positioning model,the TOA intersec-tion positioning model is more suitable for the engineering practice and the optimization algorithm is more effective.Simulation results show that the proposed methods in this paper can effectively improve the positioning accuracy for the underwater target.

Local hardening and asymmetric twin growth by twin-twin interactions in a Mg alloy

In this study,the role of twin-twin interactions on the distributions of local defects(e.g.,dislocations)and stress fields in a magnesium alloy is investigated.A co-zone(1012)-(1012)tensile twin junction in a deformed Mg-3wt.%Y alloy is analyzed using transmission electron microscopy(TEM).The results show that the morphology of the impinging(1012)twin is asymmetric,and the non-interacting boundary of the recipient(1012)twin is irregular.Detailed analysis of TEM images reveals that type-II pyramidal[1213](1212)dislocations concentrate in the vicinity of the twin-twin junction site.The same<c+a>dislocations are also observed inside the interacting twin domains along with a few <a> dislocations.The<c+a>dislocations emanating from the impinging(1012)twin boundary have edge character and are extended with faults parallel to the basal plane.In contrast,the<c+a>dislocations connected to the recipient(1012)twin are predominantly screw orientation and compact.Elasto-viscoplastic fast Fourier transform based crystal plasticity calculations are performed to rationalize the observed twin morphology and local dislocation distribution.The model calculations suggest that the local stress fields generated at the junction site where the two twins meet are responsible for the experimentally observed concentration of<c+a>dislocations.The calculated stress fields are asymmetric with respect to the junction site,explaining the observed asymmetric morphology of the impinging twin.Overall,these findings show strong effects of twin-twin interactions on the distribution of dislocations as well as the evolution of the twinned microstructure and as such,can help advance understanding of twinning in Mg alloys and their effect on mechanical behavior.

Automatic Lane-Level Intersection Map Generation using Low-Channel Roadside LiDAR

A lane-level intersection map is a cornerstone in high-definition(HD) traffic network maps for autonomous driving and high-precision intelligent transportation systems applications such as traffic management and control, and traffic accident evaluation and prevention. Mapping an HD intersection is time-consuming, labor-intensive, and expensive with conventional methods. In this paper, we used a low-channel roadside light detection and range sensor(LiDAR) to automatically and dynamically generate a lane-level intersection, including the signal phases, geometry, layout, and lane directions. First, a mathematical model was proposed to describe the topology and detail of a lane-level intersection. Second, continuous and discontinuous traffic object trajectories were extracted to identify the signal phases and times. Third, the layout, geometry, and lane direction were identified using the convex hull detection algorithm for trajectories. Fourth, a sliding window algorithm was presented to detect the lane marking and extract the lane, and the virtual lane connecting the inbound and outbound of the intersection were generated using the vehicle trajectories within the intersection and considering the traffic rules. In the field experiment, the mean absolute estimation error is 2 s for signal phase and time identification. The lane marking identification Precision and Recall are96% and 94.12%, respectively. Compared with the satellite-based,MMS-based, and crowdsourcing-based lane mapping methods,the average lane location deviation is 0.2 m and the update period is less than one hour by the proposed method with low-channel roadside LiDAR.