Computer vision-aided DEM study on the compaction characteristics of graded subgrade filler considering realistic coarse particle shapes

The compaction quality of subgrade filler strongly affects subgrade settlement.The main objective of this research is to analyze the macro-and micro-mechanical compaction characteristics of subgrade filler based on the real shape of coarse particles.First,an improved Viola-Jones algorithm is employed to establish a digitalized 2D particle database for coarse particle shape evaluation and discrete modeling purposes of subgrade filler.Shape indexes of 2D subgrade filler are then computed and statistically analyzed.Finally,numerical simulations are performed to quantitatively investigate the effects of the aspect ratio(AR)and interparticle friction coefficient(μ)on the macro-and micro-mechanical compaction characteristics of subgrade filler based on the discrete element method(DEM).The results show that with the increasing AR,the coarse particles are narrower,leading to the increasing movement of fine particles during compaction,which indicates that it is difficult for slender coarse particles to inhibit the migration of fine particles.Moreover,the average displacement of particles is strongly influenced by the AR,indicating that their occlusion under power relies on particle shapes.The dis-placement and velocity of fine particles are much greater than those of the coarse particles,which shows that compaction is primarily a migration of fine particles.Under the cyclic load,the interparticle friction coefficientμhas little effect on the internal structure of the sample;under the quasi-static loads,however,the increase inμwill lead to a significant increase in the porosity of the sample.This study could not only provide a novel approach to investigate the compaction mechanism but also establish a new theoretical basis for the evaluation of intelligent subgrade compaction.

Analyzing Thermal Stratification and Nanoparticle Shapes Influence on an EMHD Ternary Nanofluid Flow amidst Two Spinning Disks

The present study examines the thermal distribution of ternary nanofluid flow amid two spinning disks influenced by electric and magnetic fields. Keeping in view the shape of the particles, the electrically conducting ternary nanofluid is analyzed with variable thermophysical features. Three types of nanoparticles namely Copper, Aluminum Oxide, and Graphene with spherical, cylindrical, and platelet shapes are taken respectively and are immersed in a (50-50)% ratio of water and ethylene glycol mixture which acts as a base fluid. The anticipated problem is addressed by employing a reliable and user-friendly numerical bvp4c built-in collocation scheme. This solution is then showcased through illustrations and tables. Strengthening the radiation results in an enhanced heat transfer rate. Radial and azimuthal velocities once rotation of disks is enhanced. The key findings provide a strong theoretical background in photovoltaic cells, solar collectors, radiators, solar water heaters, and many other applications.

改进Alpha Shapes和快速凸壳算法的SVM故障诊断

现有的基于凸壳的支持向量机(SVM)算法处理机械装备产生的大规模原始数据时间太长。针对这一问题,通过结合轮廓提取算法(Alpha Shapes)和快速凸壳算法,提出一种结合改进快速凸壳算法的SVM用于故障诊断研究。该融合算法利用改进简化的Alpha Shapes算法提取点集的边界数据点,作为改进的快速凸壳算法的对象,减少凸壳算法递归的工作量。实验结果表明:该算法平均只提取了数据集0.26%的数据点,且计算的时间也相应降低。最后实验同样表明该算法的性能优于单一的SVM算法。

3shape Trios 3口内扫描和传统硅橡胶在牙体缺损修复中的失败原因分析

目的分析并比较3shape Trios 3口内扫描和传统硅橡胶在牙体缺损修复中的失败原因,为临床取模以及口内扫描仪性能改善提供参考依据。方法回顾性分析2021年1月至2023年10月实施口腔固定修复治疗并返工的200例患者为研究对象,以取模方式将其分为口扫组(n=97)和硅橡胶组(n=103)。口扫组给予3shape Trios 3口内扫描,硅橡胶组给予传统硅橡胶。比较两组在牙体缺损修复中的失败原因。结果两组的牙体缺损修复失败分布情况比较,差异具有统计学意义(P<0.05);口扫组中,龈下缺损修复失败占比高于龈上(P<0.05)。两组的龈下缺损修复失败原因比较,差异具有统计学意义(P<0.05)。结论相较于传统硅橡胶,3shape Trios 3口内扫描在龈上缺损修复中更有优势,但在龈下缺损修复中,硅橡胶应用效果更佳。

Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature

The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

Numerical simulation on the impact characteristics between rockfalls of different shapes and gravel cushions

The shape of rockfalls significantly affects the performance of the impact cushion,which is manifested by the difference in the impact force and the penetration depth of the rockfall during the collision.In this study,we built the collision numerical model between rockfalls and cushions based on the results from previous studies,and simulated the collision process of rockfalls with four different shapes(cylindrical,cuboid,spherical,and cubic)and different cushions.Essential parameters when rockfalls impact cushions are calculated,including the maximum impact forces on the surface and bottom of the cushions and the maximum penetration depth of the rockfall.The results showed that the maximum impact force on the surface and the bottom of the cushions varies with the rockfall shapes.The maximum impact force on the cushion surface caused by cylindrical rockfall is the smallest,followed by the cuboid rockfall,the cube rockfall,and the spherical rockfall.The maximum impact force at the cushion bottom also follows this trend.However,the penetration depth of cuboid rockfall is the smallest,followed by the cylindrical rockfall,the cubic rockfall,and the spherical rockfall.The results of this study provide more extensive theoretical support for rockfall disaster prevention using gravel cushions.

Effect of Different Raft Shapes on Hydrodynamic Characteristics of the Attenuator-Type Wave Energy Converter

A numerical simulation method based on CFD has been established to simulate the fully coupled motion for an atten-uator-type wave energy converter(WEC).Based on this method,a detailed parametric analysis has been conducted to investigate the design of the rafts.The effects of different parameters(wave parameters,structural parameters and PTO parameters)on the hydrodynamic characteristics of the attenuator-type WEC were studied in detail.The results show that in terms of wave parameters,there is an optimal wave period,which makes the relative pitching angle amplitude of the WEC reach the maximum,and the increase of wave height is conducive to the relative pitching angle amplitude of wave energy.Under different wave conditions,the relative pitch angle of the parallelogram raft device is the maximum.In terms of structural parameters,the parallelogram attenuator-type device has the optimal values in different relative directions,different distances and different apex angle,which makes the relative motion amplitude of the device reach the maximum,and the spacing and the apex angle have influence on the motion frequency of the device,while the relative direction has almost no influence on it.In terms of PTO parameters,there is an optimal damping coefficient,which makes the power generation efficiency of the WEC reach the maximum.The research results provide a valuable reference for future research and design of the attenuator-type WEC.

Optimizing Solar Drying: A Critical Review of Shapes, Orientation, and Future Prospects for Hybrid Solar Dryers

This comprehensive review focuses on the performance of solar dryers, with a specific emphasis on their structural shape and orientation. Researchers have extensively examined these design parameters, often employing Computational Fluid Dynamics (CFD) to assess thermal attributes and predict temperature distribution, airflow patterns, and temperature profiles within the structures. Geographical location significantly influences solar dryer shape preferences, with the parabolic shape finding favor in tropical regions for its superior solar radiation capture and storm resistance, while even-span and Quonset shapes are popular elsewhere. Solar dryer orientation is another crucial factor, with east-west alignment consistently proving optimal due to its ability to maximize year-round solar radiation absorption and, consequently, enhance drying efficiency. Economic considerations, however, fall beyond the scope of this review, which predominantly focuses on thermal aspects. This investigation reveals diverse global preferences for solar dryer shapes and orientation, highlighting the necessity of considering geographical factors in design choices. While CFD and shape/orientation dynamics have provided valuable insights, there remains room for future research to expand into transient state simulations under various conditions, contributing to a more comprehensive understanding of solar dryer performance. Such insights promise to promote sustainable and efficient drying processes, benefitting agricultural and drying applications across the globe.

Effects of tube cross-sectional shapes on flow pattern, liquid film and heat transfer of n-pentane across tube bundles

The heat transfer of hydrocarbon refrigerant across tube bundles have been widely used in refrigeration.Three-dimensional simulation model using volume of fluid(VOF) was presented to study the effects of tube shapes on flow pattern, film thickness and heat transfer of n-pentane across tube bundles, including circle, ellipse-shaped, egg-shaped and cam-shaped tube bundles. Simulation results agree well with experimental data in the literature. The liquid film thickness of sheet flow and heat transfer for different tube shapes were obtained numerically. The flow pattern transition occurs lower vapor quality for ellipse-shaped tube than other tube shapes. For sheet flow, the liquid film on circle tube and ellipseshaped tube is symmetrically distributed along the circumferential direction. However, the liquid film on egg-shaped tube at circumferential angles(θ) = 15°–60° is thicker than θ = 135°–165°. The liquid film on cam tube at θ = 15°–60° is slightly thinner than θ = 135°–165°. The liquid film thickness varies from thinner to thicker for ellipse-shaped, cam-shaped, egg-shape and circle within θ = 15°–60°. The effect of tube shape is insignificant on thin liquid film thickness. Ellipse-shaped tube has largest heat transfer coefficient for sheet flow. In practical engineering, the tube shape could be designed as ellipse to promote heat transfer.

Robust Symmetry Prediction with Multi-Modal Feature Fusion for Partial Shapes

In geometry processing,symmetry research benefits from global geo-metric features of complete shapes,but the shape of an object captured in real-world applications is often incomplete due to the limited sensor resolution,single viewpoint,and occlusion.Different from the existing works predicting symmetry from the complete shape,we propose a learning approach for symmetry predic-tion based on a single RGB-D image.Instead of directly predicting the symmetry from incomplete shapes,our method consists of two modules,i.e.,the multi-mod-al feature fusion module and the detection-by-reconstruction module.Firstly,we build a channel-transformer network(CTN)to extract cross-fusion features from the RGB-D as the multi-modal feature fusion module,which helps us aggregate features from the color and the depth separately.Then,our self-reconstruction net-work based on a 3D variational auto-encoder(3D-VAE)takes the global geo-metric features as input,followed by a prediction symmetry network to detect the symmetry.Our experiments are conducted on three public datasets:ShapeNet,YCB,and ScanNet,we demonstrate that our method can produce reliable and accurate results.

基于alpha shapes算法的相邻航带点云重叠区提取

相邻航带点云重叠区提取是实现点云配准工作的前提,本文利用alpha shapes算法原理,并结合K-D树快速查找的优势完成航带点云的轮廓边界提取,最后根据PCL中多边形滤波器提取点云边界包含区域,完成相邻航带点云重叠区提取工作。本文试验首先根据简易点云完成初步试验,总结参数的设置情况,最后根据实际作业情况采用两组不同区域相邻航带点云进一步完成对该算法有效性进行验证,结果表明该方法原理简单,设置参数少,对数据边界提取有较强的鲁棒性,且重叠区输出结果可靠。

Multiresolution method for bending of plates with complex shapes

A high-accuracy multiresolution method is proposed to solve mechanics problems subject to complex shapes or irregular domains.To realize this method,we design a new wavelet basis function,by which we construct a fifth-order numerical scheme for the approximation of multi-dimensional functions and their multiple integrals defined in complex domains.In the solution of differential equations,various derivatives of the unknown function are denoted as new functions.Then,the integral relations between these functions are applied in terms of wavelet approximation of multiple integrals.Therefore,the original equation with derivatives of various orders can be converted to a system of algebraic equations with discrete nodal values of the highest-order derivative.During the application of the proposed method,boundary conditions can be automatically included in the integration operations,and relevant matrices can be assured to exhibit perfect sparse patterns.As examples,we consider several second-order mathematics problems defined on regular and irregular domains and the fourth-order bending problems of plates with various shapes.By comparing the solutions obtained by the proposed method with the exact solutions,the new multiresolution method is found to have a convergence rate of fifth order.The solution accuracy of this method with only a few hundreds of nodes can be much higher than that of the finite element method(FEM)with tens of thousands of elements.In addition,because the accuracy order for direct approximation of a function using the proposed basis function is also fifth order,we may conclude that the accuracy of the proposed method is almost independent of the equation order and domain complexity.

基于改进Alpha Shape算法的点云数据岛屿边界提取

针对机载LiDAR点云的岛屿岸线提取过程复杂、附属岛屿岸线难以提取等问题,提出一种基于改进Alpha Shape算法的点云数据岛屿边界提取方法。首先利用布料模拟滤波算法剔除非岛屿点云数据,通过欧式聚类进行不同岛屿的提取,再将岛屿点云数据投影至二维平面,并根据岛屿点云构建格网。在此基础上使用自适应Alpha Shape算法,对提取出的岛屿点云进行边界提取,即可得到岛屿的岸线轮廓。选取新西兰的玛提尤/萨姆斯岛作为研究区域,并将本文算法与Alpha Shape算法进行对比,结果表明:本文算法提取岛屿边界点云的精准度为97.78%,可以准确地提取岛屿岸线,为海岛规划提供参考。

J-shaped association between dietary thiamine intake and the risk of cognitive decline in cognitively healthy,older Chinese individuals

Background The prospective association of dietary thiamine intake with the risk of cognitive decline among the general older adults remains uncertain.Aims To investigate the association between dietary thiamine intake and cognitive decline in cognitively healthy,older Chinese individuals.Methods The study included a total of 3106 participants capable of completing repeated cognitive function tests.Dietary nutrient intake information was collected through 3-day dietary recalls and using a 3-day food-weighed method to assess cooking oil and condiment consumption.Cognitive decline was defined as the 5-year decline rate in global or composite cognitive scores based on a subset of items from the Telephone Interview for Cognitive Status-modified.Results The median follow-up duration was 5.9 years.There was a J-shaped relationship between dietary thiamine intake and the 5-year decline rate in global and composite cognitive scores,with an inflection point of 0.68 mg/day(95%confidence interval(Cl):0.56 to 0.80)and a minimal risk at 0.60-1.00 mg/day of dietary thiamine intake.Before the inflection point,thiamine intake was not significantly associated with cognitive decline.Beyond the inflection point,each unit increase in thiamine intake(mg/day)was associated with a significant decrease of 4.24(95%Cl:2.22 to 6.27)points in the global score and 0.49(95%Cl:0.23 to 0.76)standard units in the composite score within 5 years.A stronger positive association between thiamine intake and cognitive decline was observed in those with hypertension,obesity and those who were non-smokers(all p<0.05).Conclusions This study revealed a J-shaped association between dietary thiamine intake and cognitive decline in cognitively healthy,older Chinese individuals,with an inflection point at 0.68 mg/day and a minimal risk at 0.60-1.00 mg/day of dietary thiamine intake.

Shape and diffusion instabilities of two non-spherical gas bubbles under ultrasonic conditions

Ultrasonic cavitation involves dynamic oscillation processes induced by small bubbles in a liquid under the influence of ultrasonic waves. This study focuses on the investigation of shape and diffusion instabilities of two bubbles formed during cavitation. The derived equations for two non-spherical gas bubbles, based on perturbation theory and the Bernoulli equation, enable the analysis of their shape instability. Numerical simulations, utilizing the modified Keller–Miksis equation,are performed to examine the shape and diffusion instabilities. Three types of shape instabilities, namely, Rayleigh–Taylor,Rebound, and parametric instabilities, are observed. The results highlight the influence of initial radius, distance, and perturbation parameter on the shape and diffusion instabilities, as evidenced by the R_0–P_a phase diagram and the variation pattern of the equilibrium curve. This research contributes to the understanding of multiple bubble instability characteristics, which has important theoretical implications for future research in the field. Specifically, it underscores the significance of initial bubble parameters, driving pressure, and relative gas concentration in determining the shape and diffusive equilibrium instabilities of non-spherical bubbles.

Effect of granular shape on radial segregation in a two-dimensional drum

Granular segregation is widely observed in nature and industry.Most research has focused on segregation caused by differences in the size and density of spherical grains.However,due to the fact that grains typically have different shapes,the focus is shifting towards shape segregation.In this study,experiments are conducted by mixing cubic and spherical grains.The results indicate that spherical grains gather at the center and cubic grains are distributed around them,and the degree of segregation is low.Through experiments,a structured analysis of local regions is conducted to explain the inability to form stable segregation patterns with obviously different geometric shapes.Further,through simulations,the reasons for the central and peripheral distributions are explained by comparing velocities and the number of collisions of the grains in the flow layer.

Auxin-brassinosteroid crosstalk:Regulating rice plant architecture and grain shape

Rice(Oryza sativa)plant architecture and grain shape,which determine grain quality and yield,are modulatedby auxin and brassinosteroid via regulation of cell elongation and proliferation.We review the signaltransduction of these hormones and the crosstalk between their signals on the regulation of rice plantarchitecture and grain shape.

The interaction between a shaped charge jet and a single moving plate

Reactive armour is a very efficient add-on armour against shaped charge threats.Explosive reactive armour consists of one or several plates that are accelerated by an explosive.Similar but less violent acceleration of plates can also be achieved in a completely inert reactive armour.To be efficient against elongated jets,the motion of the plates needs to be inclined against the jet such that a sliding contact between the jet and the plates is established.This sliding contact causes a deflection and thinning of the jet.Under certain circumstances,the contact will become unstable,leading to severe disturbances on the jet.These disturbances will drastically reduce the jet penetration performance and it is therefore of interest to study the conditions that leads to an unstable contact.Previous studies on the interaction between shaped charge jets and flyer plates have shown that it is mainly the forward moving plate in an explosive reactive armour that is effective in disturbing the jet.This is usually attributed to the higher plate-to-jet mass flux ratio involved in the collision of the forward moving plate compared to the backward moving plate.For slow moving plates,as occurs in inert reactive armour,the difference in mass flux for the forward and backward moving plate is much lesser,and it is therefore of interest to study if other factors than the mass flux influences on the protection capability.In this work,experiments have been performed where a plate is accelerated along its length,interacting with a shaped charge jet that is fired at an oblique angle to the plate’s normal,either against or along the plate’s velocity.The arrangement corresponds to a jet interacting with a flyer plate from a reactive armour,with the exception that the collision velocity is the same for both types of obliquities in these experiments.The experiments show that disturbances on the jet are different in the two cases even though the collision velocities are the same.Numerical simulations of the interaction support the observation.The difference is attributed to the character of the contact pressure in the interaction region.For a backward moving plate,the maximum contact pressure is obtained at the beginning of the interaction zone and the contact pressure is therefore higher upstream than downstream of the jet while the opposite is true for a forward moving plate.A negative interface pressure gradient with respect to the jet motion results in a more stable flow than a positive,which means that the jet-plate contact is more stable for a backward moving plate than for a forward moving plate.A forward moving plate is thus more effective in disturbing the jet than a backward moving plate,not only because of the higher jet to plate mass flux ratio but also because of the character of the contact with the jet.

Study on the tunnel shape and soil-lining interaction influencing the lining behavior under seismic loading

The response of tunnels subjected to seismic loading is a complex mechanism and depends not only on the seismic nature but also on tunnel structure and surrounding soil properties.The individual behavior of circular,rectangular,and sub-rectangular tunnels subjected to seismic loadings has already been studied in the literature.In the present research,two case scenarios of circular,rectangular tunnels and four sub-rectangular shaped tunnels,with similar cross-section areas,were adopted to perform a comprehensive numerical investigation.The purpose of the study was to determine the mechanical behavior of tunnels of different shapes,depending upon seismic conditions.Analyses were performed by considering the influence of soil-lining interaction,soil parameters,and lining thickness,as well as lining rigidity.Computations were performed for no-slip and full-slip conditions.The results indicate that the tunnel shape design is of great importance when regarding the mechanical behavior of the surrounding soil.This concerns no-slip as well as full-slip soil-lining interaction,especially when the lining is subjected to seismic loading.Moreover,it is shown that changes in incremental bending moments for circular,rectangular and sub-rectangular tunnels that depend upon the soil-lining interaction conditions differ significantly.

A Deep Learning Approach to Shape Optimization Problems for Flexoelectric Materials Using the Isogeometric Finite Element Method

A new approach for flexoelectricmaterial shape optimization is proposed in this study.In this work,a proxymodel based on artificial neural network(ANN)is used to solve the parameter optimization and shape optimization problems.To improve the fitting ability of the neural network,we use the idea of pre-training to determine the structure of the neural network and combine different optimizers for training.The isogeometric analysis-finite element method(IGA-FEM)is used to discretize the flexural theoretical formulas and obtain samples,which helps ANN to build a proxy model from the model shape to the target value.The effectiveness of the proposed method is verified through two numerical examples of parameter optimization and one numerical example of shape optimization.