Particle Discontinuous Deformation Analysis of Static and Dynamic Crack Propagation in Brittle Material

Crack propagation in brittle material is not only crucial for structural safety evaluation,but also has a wideranging impact on material design,damage assessment,resource extraction,and scientific research.A thorough investigation into the behavior of crack propagation contributes to a better understanding and control of the properties of brittle materials,thereby enhancing the reliability and safety of both materials and structures.As an implicit discrete elementmethod,the Discontinuous Deformation Analysis(DDA)has gained significant attention for its developments and applications in recent years.Among these developments,the particle DDA equipped with the bonded particle model is a powerful tool for predicting the whole process of material from continuity to failure.The primary objective of this research is to develop and utilize the particle DDAtomodel and understand the complex behavior of cracks in brittle materials under both static and dynamic loadings.The particle DDA is applied to several classical crack propagation problems,including the crack branching,compact tensile test,Kalthoff impact experiment,and tensile test of a rectangular plate with a hole.The evolutions of cracks under various stress or geometrical conditions are carefully investigated.The simulated results are compared with the experiments and other numerical results.It is found that the crack propagation patterns,including crack branching and the formation of secondary cracks,can be well reproduced.The results show that the particle DDA is a qualified method for crack propagation problems,providing valuable insights into the fracture mechanism of brittle materials.

Analysis of a landfill cover without geomembrane using varied particle sizes of recycled concrete

Previous studies have demonstrated the effectiveness of a novel three-layer landfill cover system constructed with recycled concrete aggregates(RCAs)without geomembrane in both laboratory and field.However,no systematic investigation has been carried out to optimize the combination of the particle sizes for fine-grained RCAs(FRC)and coarse-grained RCAs(CRC)that can be used for the three-layer landfill cover system.The aim of this paper is to assist engineers in designing the three-layer landfill cover system under a rainfall of 100-year return period in humid climate conditions using an easily controlled soil parameter D10 of RCAs.The numerical study reveals that when D10 of FRC increases from 0.05 mm to 0.16 mm,its saturated permeability increases by 10 times.As a result,a larger amount of rainwater infiltrates into the cover system,causing a higher lateral diversion in both the top FRC and middle CRC layers.No further changes in the lateral diversion are observed when the D10 value of FRC is larger than 0.16 mm.Both the particle sizes of FRC and CRC layers are shown to have a minor influence on the percolation under the extreme rainfall event.This implies that the selection of particle sizes for the FRC and CRC layers can be based on the availability of materials.Although it is well known that the bottom layer of the cover system should be constructed with very fine-grained soils if possible,this study provides an upper limit to the particle size that can be used in the bottom layer(D10 not larger than 0.02 mm).With this limit,the three-layer system can still minimize the water percolation to meet the design criterion(30 mm/yr)even under a 100-year return period of rainfall in humid climates.

An image segmentation method of pulverized coal for particle size analysis

An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of pulverized coal,which is greatly influenced by the particle size and shape distribution acquired by image segmentation.However,the agglomeration effect of fine powders and the edge effect of granular images caused by scanning electron microscopy greatly affect the precision of particle image segmentation.In this study,we propose a novel image segmentation method derived from mask regional convolutional neural network based on deep learning for recognizing fine coal powders.Firstly,an atrous convolution is introduced into our network to learn the image feature of multi-sized powders,which can reduce the missing segmentation of small-sized agglomerated particles.Then,a new mask loss function combing focal loss and dice coefficient is used to overcome the false segmentation caused by the edge effect.The final comparative experimental results show that our method achieves the best results of 94.43%and 91.44%on AP50 and AP75 respectively among the comparison algorithms.In addition,in order to provide an effective method for particle size analysis of coal particles,we study the particle size distribution of coal powders based on the proposed image segmentation method and obtain a good curve relationship between cumulative mass fraction and particle size.

Extended wet sieving method for determination of complete particle size distribution of general soils

The traditional standard wet sieving method uses steel sieves with aperture?0.063 mm and can only determine the particle size distribution(PSD)of gravel and sand in general soil.This paper extends the traditional method and presents an extended wet sieving method.The extended method uses both the steel sieves and the nylon filter cloth sieves.The apertures of the cloth sieves are smaller than 0.063 mm and equal 0.048 mm,0.038 mm,0.014 mm,0.012 mm,0.0063 mm,0.004 mm,0.003 mm,0.002 mm,and 0.001 mm,respectively.The extended method uses five steps to separate the general soil into many material sub-groups of gravel,sand,silt and clay with known particle size ranges.The complete PSD of the general soil is then calculated from the dry masses of the individual material sub-groups.The extended method is demonstrated with a general soil of completely decomposed granite(CDG)in Hong Kong,China.The silt and clay materials with different particle size ranges are further examined,checked and verified using stereomicroscopic observation,physical and chemical property tests.The results further confirm the correctness of the extended wet sieving method.

Particle size characterization and sources of sediments in the Uzhumqin sand dunes

Sediment constitutes the fundamental basis for forming and evolving aeolian geomorphology.The characteristics of sediment particle size offer insights into the development and evolution of sandy terrain,making their study critical to understanding aeolian geomorphology and sand control.In this study,we combined high-density collection of surface sediments in the Uzhumqin sand dunes and GIS spatial analysis to analyze the particle size parameters and changes in the spatial distribution of surface sediments in this region.In addition,we used an end-member analysis to identify the potential sources of the sediments.The results showed that surface sediments in the Uzhumqin sand dunes had distinct spatial distributions.Medium and coarse grain sands dominated the sediments in the dunes,and the mean grain size and the sorting coefficient generally increased along the prevailing wind direction,with high values in individual areas related to factors such as material sources and vegetation cover.Skewness was strongly influenced by factors such as landform change and human activity,and spatial variability became more complex.Kurtosis and the soil fractal dimension showed generally decreasing trends along the prevailing wind direction.With dune fixation,the contents of clay and powder particles in the soil increased;the mean particle size,the sorting coefficient,and the fractal dimension of the soil gradually increased,and the skewness and kurtosis gradually decreased.The end-member analysis results indicated the existence of five end-members(EM)in the dune sediments.EM 1 was a mixed component of wind-deposited fine sands and nearby fluvial sediments.EM 2 was the main component of sediments in the study area and was the result of sorting lake sediments by wind action and by the local topography.EM 3 may be a product of river flood deposition.EM 4 and EM 5 had coarser grain sizes.EM 4 was a lake-phase sediment product influenced by topographic and vegetation cover factors,and EM 5 was primarily a river and lake sediment product modified by weathering.The sediment particle size results from the study area indicate that the sediment in the sandy region is generally coarse due to multiple factors,including topography,climate,hydrology,and human activity.Sandy material in the study area originated from nearby,with very little sand being transported from long distances.

Pelleting and particle size reduction of corn increase net energy and digestibility of fiber,protein,and fat in corn-soybean meal diets fed to group-housed pigs

Background Reduction of the particle size of corn increases energy digestibility and concentrations of digestible and metabolizable energy.Pelleting may also reduce particle size of grain,but it is not known if there are interactions between particle size reduction and pelleting.The objective of this experiment was to test the hypothesis that particle size reduction and pelleting,separately or in combination,increase N balance,apparent total tract digestibility(ATTD)of fiber and fat,and net energy(NE)in corn-soybean meal diets fed to group-housed pigs.Methods Six corn-soybean meal-based diets were used in a 3×2 factorial design with 3 particle sizes of corn(i.e.,700,500,or 300μm)and 2 diet forms(i.e.,meal or pelleted).Pigs were allowed ad libitum access to feed and water.Twenty-four castrated male pigs(initial weight:29.52 kg;standard diviation:1.40)were allotted to the 6 diets using a 6×6 Latin square design with 6 calorimeter chambers(i.e.,4 pigs/chamber)and 6 periods.Oxygen consumption and CO_(2)and CH_(4)productions were measured during fed and fasting states and fecal and urine samples were collected.Results Regardless of particle size of corn,the ATTD of gross energy(GE),N,and acid-hydrolyzed ether extract(AEE),and the concentration of NE were greater(P<0.05)in pelleted diets than in meal diets.Regardless of diet form,the ATTD of GE,N,and AEE,and the concentration of NE were increased(linear;P<0.05)by reducing the particle size of corn,but the increase was greater in meal diets than in pelleted diets(interaction;P<0.05).Conclusions Both pelleting and reduction of corn particle size increased nutrient digestibility and NE,but increases were greater in meal diets than in pelleted diets.

High-Volume Mineral Admixtures Cement: The Effects of Particle Size Distribution

The effects of high-volume slag-fly ash cement with different particle sizes on hydration degree,microstructure and mechanical properties were systematically studied,by means of laser particle size(DLS),X-ray diffraction (XRD),comprehensive thermal analysis (TG-DTA),scanning electron microscopy(SEM) and mechanical properties tests.The results show that suitable particle size distribution of cementitious material has significantly promoting effects on hydration reaction rate and mechanical properties.Compared with slag without further grinding,the slag after ball milling for 4 h has an obvious improvement in reactivity,which also provides a faster hydration rate and higher compressive strength for the cementitious material.When the slag milled for 1 and 4 h is mixed at a mass ratio of 2:1 (i e,slag with D_(50) of 7.4μm and average size of 9.9μm,and slag with D_(50) value of 2.6μm and average size of 5.3μm),and a certain amount of fly ash is added in,the most obvious improvement of compressive strength of cement is achieved.

Optical Modeling of Sea Salt Aerosols Using in situ Measured Size Distributions and the Impact of Larger Size Particles

Sea salt aerosols play a critical role in regulating the global climate through their interactions with solar radiation.The size distribution of these particles is crucial in determining their bulk optical properties.In this study,we analyzed in situ measured size distributions of sea salt aerosols from four field campaigns and used multi-mode lognormal size distributions to fit the data.We employed super-spheroids and coated super-spheroids to account for the particles’non-sphericity,inhomogeneity,and hysteresis effect during the deliquescence and crystallization processes.To compute the singlescattering properties of sea salt aerosols,we used the state-of-the-art invariant imbedding T-matrix method,which allows us to obtain accurate optical properties for sea salt aerosols with a maximum volume-equivalent diameter of 12μm at a wavelength of 532 nm.Our results demonstrated that the particle models developed in this study were successful in replicating both the measured depolarization and lidar ratios at various relative humidity(RH)levels.Importantly,we observed that large-size particles with diameters larger than 4μm had a substantial impact on the optical properties of sea salt aerosols,which has not been accounted for in previous studies.Specifically,excluding particles with diameters larger than 4μm led to underestimating the scattering and backscattering coefficients by 27%−38%and 43%−60%,respectively,for the ACE-Asia field campaign.Additionally,the depolarization ratios were underestimated by 0.15 within the 50%−70%RH range.These findings emphasize the necessity of considering large particle sizes for optical modeling of sea salt aerosols.

Threshold friction velocity influenced by soil particle size within the Columbia Plateau, northwestern United States

Wind erosion is a geomorphic process in arid and semi-arid areas and has substantial implications for regional climate and desertification.In the Columbia Plateau of northwestern United States,the emissions from fine particles of loessial soils often contribute to the exceedance of inhalable particulate matter(PM)with an aerodynamic diameter of 10μm or less(PM10)according to the air quality standards.However,little is known about the threshold friction velocity(TFV)for particles of different sizes that comprise these soils.In this study,soil samples of two representative soil types(Warden sandy loam and Ritzville silt loam)collected from the Columbia Plateau were sieved to seven particle size fractions,and an experiment was then conducted to determine the relationship between TFV and particle size fraction.The results revealed that soil particle size significantly affected the initiation of soil movement and TFV;TFV ranged 0.304-0.844 and 0.249-0.739 m/s for different particle size fractions of Ritzville silt loam and Warden sandy loam,respectively.PM10 and total suspended particulates(TSP)emissions from a bed of 63-90μm soil particles were markedly higher for Warden sandy loam than for Ritzville silt loam.Together with the lower TFV of Warden sandy loam,dust emissions from fine particles(<100μm in diameter)of Warden sandy loam thus may be a main contributor to dust in the region's atmosphere,since the PM10 emissions from the soil erosion surfaces and its ensuing suspension within the atmosphere constitute an essential process of soil erosion in the Columbia Plateau.Developing and implementing strategic land management practices on sandy loam soils is therefore necessary to control dust emissions in the Columbia Plateau.

Particle size spatial distribution in landslide dams

The particle composition and spatial distribution of landslide-induced dam bodies are critical geotechnical parameters for studying the hazards of dam-break floods.However,current research often neglects the influence of the initial particle composition and spatial distribution of the landslide on the particle composition and spatial distribution of the landslide dam.This study investigated the impact of initial particle size distribution,volume,and sliding length on the energy and velocity changes of characteristic particles during the sliding process and the spatial distribution of particle sizes in the landslide dam body.Numerical simulations and physical models were employed to examine the effects of sequential gradient arrangements(where particle sizes decrease from top to bottom)and four other different initial particle arrangements on the energy and velocity changes of particles and the spatial distribution of particle sizes in the dam body.The study reveals the characteristics of translational and rotational energy of different particles and the laws of mechanical energy conversion,obtaining the spatial distribution patterns of particle sizes in landslide-induced dams.The results show that under the sequential gradient arrangement,the energy dissipation of the landslide movement is lower,with larger particles mainly distributed at the distal end and smaller particles at the proximal end of the landslide dam.In contrast,under the reverse gradient arrangement,the energy dissipation of the landslide movement is higher,and the distribution pattern of the dam particles is opposite to that of the sequential gradient arrangement.For the other arrangement modes,the spatial distribution of dam particles falls between the aforementioned two.There is a positive correlation between particle size and translational kinetic energy within the particle flow during the landslide process,and rotational motion increases energy dissipation.Under constant slope conditions,sliding length does not affect the movement pattern of the particle flow or the spatial distribution of particles in the dam body.The findings of this study provide a scientific basis for the accurate simulation and prediction of dam-break flood processes.

Microfluidic preparation of surfactant-free ultrafine DAAF with tunable particle size for insensitive initiator explosives

High purity and ultrafine DAAF(u-DAAF)is an emerging insensitive charge in initiators.Although there are many ways to obtain u-DAAF,developing a preparation method with stable operation,accurate control,good quality consistency,equipment miniaturization,and minimum manpower is an inevitable requirement to adapt to the current social technology development trend.Here reported is the microfluidic preparation of u-DAAF with tunable particle size by a passive swirling microreactor.Under the guidance of recrystallization growth kinetics and mixing behavior of fluids in the swirling microreactor,the key parameters(liquid flow rate,explosive concentration and crystallization temperature)were screened and optimized through screening experiments.Under the condition that no surfactant is added and only experimental parameters are controlled,the particle size of recrystallized DAAF can be adjusted from 98 nm to 785 nm,and the corresponding specific surface area is 8.45 m^(2)·g^(-1)to 1.33 m^(2)·g^(-1).In addition,the preparation method has good batch stability,high yield(90.8%-92.6%)and high purity(99.0%-99.4%),indicating a high practical application potential.Electric explosion derived flyer initiation tests demonstrate that the u-DAAF shows an initiation sensitivity much lower than that of the raw DAAF,and comparable to that of the refined DAAF by conventional spraying crystallization method.This study provides an efficient method to fabricate u-DAAF with narrow particle size distribution and high reproducibility as well as a theoretical reference for fabrication of other ultrafine explosives.

Effects of temperature, particle size, and air humidity on sensibility of typical high-energetic explosives

The production and utilization of high-energetic explosives often pose a range of safety hazards,with sensitivity being a key factor in evaluating these risks.To investigate how temperature,particle size,and air humidity affect the responsiveness of commonly used high-energetic explosives,a series of BAM(Bundesanstalt für Materialforschung und-prüfung)impact and friction sensitivity tests were carried out to determine the critical impact energy and critical load pressure of four representative high-energetic explosives(RDX,HMX,PETN and CL-20)under different temperatures,particle sizes,and air humidity conditions.The experimental findings facilitated an examination of temperature and particle size affecting the sensitivity of high-energetic explosives,along with an assessment of the influence of air humidity on sensitivity testing.The results clearly indicate that high-energetic explosives display a substantial decline in critical reaction energy when subjected to micrometre-sized particles and an air humidity level of 45%at a temperature of 90℃.Furthermore,it was noted that the critical reaction energy of high-energetic explosives diminishes with an increase in temperature within 25℃−90℃.In the same vein,as the particle sizes of high-energetic explosives increase,so does the critical reaction energy for micrometre-sized particles.High air humidity significantly affects the sensitivity testing of high-energetic explosives,emphasizing the importance of refraining from conducting sensitivity tests in such conditions.

Quantum Particle Swarm Optimization with Deep Learning-Based Arabic Tweets Sentiment Analysis

Sentiment Analysis(SA),a Machine Learning(ML)technique,is often applied in the literature.The SA technique is specifically applied to the data collected from social media sites.The research studies conducted earlier upon the SA of the tweets were mostly aimed at automating the feature extraction process.In this background,the current study introduces a novel method called Quantum Particle Swarm Optimization with Deep Learning-Based Sentiment Analysis on Arabic Tweets(QPSODL-SAAT).The presented QPSODL-SAAT model determines and classifies the sentiments of the tweets written in Arabic.Initially,the data pre-processing is performed to convert the raw tweets into a useful format.Then,the word2vec model is applied to generate the feature vectors.The Bidirectional Gated Recurrent Unit(BiGRU)classifier is utilized to identify and classify the sentiments.Finally,the QPSO algorithm is exploited for the optimal finetuning of the hyperparameters involved in the BiGRU model.The proposed QPSODL-SAAT model was experimentally validated using the standard datasets.An extensive comparative analysis was conducted,and the proposed model achieved a maximum accuracy of 98.35%.The outcomes confirmed the supremacy of the proposed QPSODL-SAAT model over the rest of the approaches,such as the Surface Features(SF),Generic Embeddings(GE),Arabic Sentiment Embeddings constructed using the Hybrid(ASEH)model and the Bidirectional Encoder Representations from Transformers(BERT)model.

CPSO: Chaotic Particle Swarm Optimization for Cluster Analysis

Background:To solve the cluster analysis better,we propose a new method based on the chaotic particle swarm optimization(CPSO)algorithm.Methods:In order to enhance the performance in clustering,we propose a novel method based on CPSO.We first evaluate the clustering performance of this model using the variance ratio criterion(VRC)as the evaluation metric.The effectiveness of the CPSO algorithm is compared with that of the traditional particle swarm optimization(PSO)algorithm.The CPSO aims to improve the VRC value while avoiding local optimal solutions.The simulated dataset is set at three levels of overlapping:non-overlapping,partial overlapping,and severe overlapping.Finally,we compare CPSO with two other methods.Results:By observing the comparative results,our proposed CPSO method performs outstandingly.In the conditions of non-overlapping,partial overlapping,and severe overlapping,our method has the best VRC values of 1683.2,620.5,and 275.6,respectively.The mean VRC values in these three cases are 1683.2,617.8,and 222.6.Conclusion:The CPSO performed better than other methods for cluster analysis problems.CPSO is effective for cluster analysis.

Stability of the Dividing Distribution Function Method for ParticleSize Distribution Analysis in Small Angle X－Ray Scattering

The Dividing Distribution Function (DDF) method is one of the methods by which the particle size distribution of ultrafine powder can be evaluated from its small angle X-ray scattering data. In this paper, the stability of the solution obtained from DDF method has been investigated through optimizing the coefficient matrix, introducing a damping factor and a least square treatment. All calculations were accomplished with a microcomputer. It was shown that the average deviations of the size distribution obtained are not larger than the assigned random errors to the scattering intensities as long as the corresponding requirements are satisfied.

Sampling Surface Particle Size Distributions and Stability Analysis of Deep Channel in the Pearl River Estuary

Particle size distributions （PSDs） of bottom sediments in a coastal zone are generally multimodal due to the complexity of the dynamic environment. In this paper, bottom sediments along the deep channel of the Pearl River Estuary （PRE） are used to understand the multimodal PSDs＇ characteristics and the corresponding depositional environment. The results of curve-fitting analysis indicate that the near-bottom sediments in the deep channel generally have a bimodal distribution with a fine component and a relatively coarse component. The particle size distribution of bimodal sediment samples can be expressed as the sum of two lognormal functions and the parameters for each component can be determined. At each station of the PRE, the fine component makes up less volume of the sediments and is relatively poorly sorted. The relatively coarse component, which is the major component of the sediments, is even more poorly sorted. The interrelations between the dynamics and particle size of the bottom sediment in the deep channel of the PRE have also been investigated by the field measurement and simulated data. The critical shear velocity and the shear velocity are calculated to study the stability of the deep channel. The results indicate that the critical shear velocity has a similar distribution over large part of the deep channel due to the similar particle size distribution of sediments. Based on a comparison between the critical shear velocities derived from sedimentary parameters and the shear velocities obtained by tidal currents, it is likely that the depositional area is mainly distributed in the northern part of the channel, while the southern part of the deep channel has to face higher erosion risk.

3D characterization and analysis of pore structure of packed ore particle beds based on computed tomography images

Methods and procedures of three-dimensional （3D） characterization of the pore structure features in the packed ore particle bed are focused. X-ray computed tomography was applied to deriving the cross-sectional images of specimens with single particle size of 1-2, 2-3, 3-4, 4-5, 5-6, 6-7, 7-8, 8-9, 9-10 ram. Based on the in-house developed 3D image analysis programs using Matlab, the volume porosity, pore size distribution and degree of connectivity were calculated and analyzed in detail. The results indicate that the volume porosity, the mean diameter of pores and the effective pore size （d50） increase with the increasing of particle size. Lognormal distribution or Gauss distribution is mostly suitable to model the pore size distribution. The degree of connectivity investigated on the basis of cluster-labeling algorithm also increases with increasing the particle size approximately.

Analysis on the Distribution Characteristics of Atmospheric Aerosol Particles in Hebei Area in the Cloudy Day Condition

By using the probe data of two sorties airplane in the middle and southern parts of Hebei Province in 2007 spring,the characteristics of atmospheric aerosol particles concentration and size distribution in the area in the cloudy day situation were analyzed.The results showed that the overall trend of aerosol particles concentration in the weather systems which included the south branch trough and North China low vortex was the decrease as the height increased.However,if the cirrostratus was in the high altitude,it increased as the height increased.In the bottom of inversion layer,there existed the obvious accumulation of aerosol and cloud droplet.Affected by the complex weather systems,the aerosol particle size distribution presented the multi-peak type for the disturbance of updraft or turbulence.

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.

Analysis of Correlation between Concentration of Atmospheric Particulates and Humidity Based on the Aerodynamic Particle Sizer

The TSI-3321 APS was used to measure concentration of atmospheric particulates in Ranjiaba region of Yubei District in Chongqing City during March 21- 29,2014,and the temporal variations in the hourly average mass and number concentration and median particle diameter of PM10 and PM2.5 as well as their correlation with relative humidity were analyzed. The results showed that the three indicators of PM10 and PM2.5 except for the mass concentration correlated with relative humidity,of which the correlation between the mass median particle diameter and relative humidity was the best. The correlation coefficient R^2 between the mass median particle diameter of PM10（ PM2.5） and relative humidity was up to 0. 943（ 0. 832）. Therefore,relative humidity and pressure are key impact factors of indicators of particles.