Impact of Pollutant Concentration and Particle Deposition on the Radiative Flow of Casson-Micropolar Fluid between Parallel Plates

Assessing the behaviour and concentration of waste pollutants deposited between two parallel plates is essential for effective environmental management.Determining the effectiveness of treatment methods in reducing pollution scales is made easier by analysing waste discharge concentrations.The waste discharge concentration analysis is useful for assessing how effectively wastewater treatment techniques reduce pollution levels.This study aims to explore the Casson micropolar fluid flow through two parallel plates with the influence of pollutant concentration and thermophoretic particle deposition.To explore the mass and heat transport features,thermophoretic particle deposition and thermal radiation are considered.The governing equations are transformed into ordinary differential equations with the help of suitable similarity transformations.The Runge-Kutta-Fehlberg’s fourthfifth order technique and shooting procedure are used to solve the reduced set of equations and boundary conditions.The integration of a neural network model based on the Levenberg-Marquardt algorithm serves to improve the accuracy of predictions and optimize the analysis of parameters.Graphical outcomes are displayed to analyze the characteristics of the relevant dimensionless parameters in the current problem.Results reveal that concentration upsurges as the micropolar parameter increases.The concentration reduces with an upsurge in the thermophoretic parameter.An upsurge in the external pollutant source variation and the local pollutant external source parameters enhances mass transport.The surface drag force declines for improved values of porosity and micropolar parameters.

Comparison of debris flow susceptibility assessment methods:support vector machine,particle swarm optimization,and feature selection techniques

The selection of important factors in machine learning-based susceptibility assessments is crucial to obtain reliable susceptibility results.In this study,metaheuristic optimization and feature selection techniques were applied to identify the most important input parameters for mapping debris flow susceptibility in the southern mountain area of Chengde City in Hebei Province,China,by using machine learning algorithms.In total,133 historical debris flow records and 16 related factors were selected.The support vector machine(SVM)was first used as the base classifier,and then a hybrid model was introduced by a two-step process.First,the particle swarm optimization(PSO)algorithm was employed to select the SVM model hyperparameters.Second,two feature selection algorithms,namely principal component analysis(PCA)and PSO,were integrated into the PSO-based SVM model,which generated the PCA-PSO-SVM and FS-PSO-SVM models,respectively.Three statistical metrics(accuracy,recall,and specificity)and the area under the receiver operating characteristic curve(AUC)were employed to evaluate and validate the performance of the models.The results indicated that the feature selection-based models exhibited the best performance,followed by the PSO-based SVM and SVM models.Moreover,the performance of the FS-PSO-SVM model was better than that of the PCA-PSO-SVM model,showing the highest AUC,accuracy,recall,and specificity values in both the training and testing processes.It was found that the selection of optimal features is crucial to improving the reliability of debris flow susceptibility assessment results.Moreover,the PSO algorithm was found to be not only an effective tool for hyperparameter optimization,but also a useful feature selection algorithm to improve prediction accuracies of debris flow susceptibility by using machine learning algorithms.The high and very high debris flow susceptibility zone appropriately covers 38.01%of the study area,where debris flow may occur under intensive human activities and heavy rainfall events.

Quickly obtaining densely dispersed coherent particles in steel matrix and its related mechanical property

Densely distributed coherent nanoparticles(DCN)in steel matrix can enhance the work-hardening ability and ductility of steel simultaneously.All the routes to this end can be generally classified into the liquid-solid route and the solid-solid route.However,the formation of DCN structures in steel requires long processes and complex steps.So far,obtaining steel with coherent particle enhancement in a short time remains a bottleneck,and some necessary steps remain unavoidable.Here,we show a high-efficiency liquid-phase refining process reinforced by a dynamic magnetic field.Ti-Y-Mn-O particles had an average size of around(3.53±1.21)nm and can be obtained in just around 180 s.These small nanoparticles were coherent with the matrix,implying no accumulated dislocations between the particles and the steel matrix.Our findings have a potential application for improving material machining capacity,creep resistance,and radiation resistance.

Performance characteristics of the airlift pump under vertical solid-water-gas flow conditions for conveying centimetric-sized coal particles

In this study,the installation of an airlift pump with inner diameter of 102 mm and length of 5.64 m was utilized to consider the conveying process of non-spherical coal particles with density of 1340 kg/m3 and graining 25-44.5 mm.The test results revealed that the magnitude of increase in the solid transport rate due to the changes in the three tested parameters between compressed air velocity,submergence ratio,and feeding coal possibility was not the same,which are stand in range of 20%,75%,and 40%,respectively.Hence,creating the optimal airlift pump performance is highly dependent on submergence ratio.More importantly,we measured the solid volume fraction using the method of one-way valves in order to minimize the disadvantages of conventional devices,such as fast speed camera and conductivity ring sensor.The results confirmed that the volume fraction of the solid phase in the transfer process was always less than 12%.To validate present experimental data,the existing empirical correlations together with the theoretical equations related to the multiphase flow was used.The overall agreement between the theory and experimental solid delivery results was particularly good instead of the first stage of conveying process.This drawback can be corrected by omitting the role of friction and shear stress at low air income velocity.It was also found that the model developed by Kalenik failed to predict the performance of our airlift operation in terms of the mass flow rate of the coal particles.

Extending homogeneous fluidization flow regime of Geldart-A particles by exerting axial uniform and steady magnetic field

The homogeneous/particulate fluidization flow regime is particularly suitable for handling the various gas–solid contact processes encountered in the chemical and energy industry.This work aimed to extend such a regime of Geldart-A particles by exerting the axial uniform and steady magnetic field.Under the action of the magnetic field,the overall homogeneous fluidization regime of Geldart-A magnetizable particles became composed of two parts:inherent homogeneous fluidization and newly-created magnetic stabilization.Since the former remained almost unchanged whereas the latter became broader as the magnetic field intensity increased,the overall homogeneous fluidization regime could be extended remarkably.As for Geldart-A nonmagnetizable particles,certain amount of magnetizable particles had to be premixed to transmit the magnetic stabilization.Among others,the mere addition of magnetizable particles could broaden the homogeneous fluidization regime.The added content of magnetizable particles had an optimal value with smaller/lighter ones working better.The added magnetizable particles might raise the ratio between the interparticle force and the particle gravity.After the magnetic field was exerted,the homogeneous fluidization regime was further expanded due to the formation of magnetic stabilization flow regime.The more the added magnetizable particles,the better the magnetic performance and the broader the overall homogeneous fluidization regime.Smaller/lighter magnetizable particles were preferred to maximize the magnetic performance and extend the overall homogeneous fluidization regime.This phenomenon could be ascribed to that the added magnetizable particles themselves became more Geldart-A than-B type as their density or size decreased.

A flexible multiscale algorithm based on an improved smoothed particle hydrodynamics method for complex viscoelastic flows

Viscoelastic flows play an important role in numerous engineering fields,and the multiscale algorithms for simulating viscoelastic flows have received significant attention in order to deepen our understanding of the nonlinear dynamic behaviors of viscoelastic fluids.However,traditional grid-based multiscale methods are confined to simple viscoelastic flows with short relaxation time,and there is a lack of uniform multiscale scheme available for coupling different solvers in the simulations of viscoelastic fluids.In this paper,a universal multiscale method coupling an improved smoothed particle hydrodynamics(SPH)and multiscale universal interface(MUI)library is presented for viscoelastic flows.The proposed multiscale method builds on an improved SPH method and leverages the MUI library to facilitate the exchange of information among different solvers in the overlapping domain.We test the capability and flexibility of the presented multiscale method to deal with complex viscoelastic flows by solving different multiscale problems of viscoelastic flows.In the first example,the simulation of a viscoelastic Poiseuille flow is carried out by two coupled improved SPH methods with different spatial resolutions.The effects of exchanging different physical quantities on the numerical results in both the upper and lower domains are also investigated as well as the absolute errors in the overlapping domain.In the second example,the complex Wannier flow with different Weissenberg numbers is further simulated by two improved SPH methods and coupling the improved SPH method and the dissipative particle dynamics(DPD)method.The numerical results show that the physical quantities for viscoelastic flows obtained by the presented multiscale method are in consistence with those obtained by a single solver in the overlapping domain.Moreover,transferring different physical quantities has an important effect on the numerical results.

Artificial intelligence-motivated in-situ imaging for visualization investigation of submicron particles deposition in electric-flow coupled fields

This study delves into the intricate deposition dynamics of submicron particles within electric-flow coupled fields,underscoring the unique challenges posed by their minuscule size,aggregation tendencies,and biological reactivity.Employing an operando investigation system that synergizes microfluidic technology with advanced micro-visualization techniques within a lab-on-a-chip framework enables a meticulous examination of the dynamic deposition phenomena.The incorporation of object detection and deep learning methodologies in image processing streamlines the automatic identification and swift extraction of crucial data,effectively tackling the complexities associated with capturing and mitigating these hazardous particles.Combined with the analysis of the growth behavior of particle chain under different applied voltages,it established that a linear relationship exists between the applied voltage and θ.And there is a negative correlation between the average particle chain length and electric field strength at the collection electrode surface(4.2×10^(5)to 1.6×10^(6)V·m^(-1)).The morphology of the deposited particle agglomerate at different electric field strengths is proposed:dendritic agglomerate,long chain agglomerate,and short chain agglomerate.

THE GLOBAL EXISTENCE AND UNIQUENESS OF SMOOTH SOLUTIONS TO A FLUID-PARTICLE INTERACTION MODEL IN THE FLOWING REGIME

This paper is concerned with the Cauchy problem for a 3D fluid-particle interaction model in the so-called flowing regime inℝ3.Under the smallness assumption on both the external potential and the initial perturbation of the stationary solution in some Sobolev spaces,the existence and uniqueness of global smooth solutions in H3 of the system are established by using the careful energy method.

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.

Numerical investigation on MHD Jeffery-Hamel nanofluid flow with different nanoparticles using fuzzy extension of generalized dual parametric homotopy algorithm

This study considers an MHD Jeffery-Hamel nanofluid flow with distinct nanoparticles such as copper,Al_(2)O_(3)and SiO_(2)between two rigid non-parallel plane walls with the fuzzy extension of the generalized dual parametric homotopy algorithm.The nanofluids have been formulated to enhance the thermophysical characteristics of fluids,including thermal diffusivity,conductivity,convective heat transfer coefficients and viscosity.Due to the presence of distinct nanofluids,a change in the value of volume fraction occurs that influences the velocity profiles of the flow.The short value of nanoparticles volume fraction is considered an uncertain parameter and represented in a triangular fuzzy number range among[0.0,0.1,0.2].A novel generalized dual parametric homotopy algorithm with fuzzy extension is used here to study the fuzzy velocities at various channel positions.Finally,the effectiveness of the proposed approach has been demonstrated through a comparison with the available results in the crisp case.

In vivo fluorescence flow cytometry reveals that the nanoparticle tumor vaccine OVA@HA-PEI effectively clears circulating tumor cells

Tumor vaccine therapy offers significant advantages over conventional treatments,including reduced toxic side effects.However,it currently functions primarily as an adjuvant treatment modality in clinical oncology due to limitations in tumor antigen selection and delivery methods.Tumor vaccines often fail to elicit a sufficiently robust immune response against progressive tumors,thereby limiting their clinical efficacy.In this study,we developed a nanoparticle-based tumor vaccine,OVA@HA-PEI,utilizing ovalbumin(OVA)as the presenting antigen and hyaluronic acid(HA)and polyethyleneimine(PEI)as adjuvants and carriers.This formulation significantly enhanced the proliferation of immune cells and cytokines,such as CD3,CD8,interferon-,and tumor necrosis factor-,in vivo,effectively activating an immune response against B16–F10 tumors.In vivofluorescenceflow cytometry(IVFC)has already become an effective method for monitoring circulating tumor cells(CTCs)due to its direct,noninvasive,and long-term detection capabilities.Our study utilized a laboratory-constructed IVFC system to monitor the immune processes induced by the OVA@HA-PEI tumor vaccine and an anti-programmed death-1(PD-1)antibody.The results demonstrated that the combined treatment of OVA@HA-PEI and anti-PD-1 antibody significantly improved the survival time of mice compared to anti-PD-1 antibody treatment alone.Additionally,this combination therapy substantially reduced the number of CTCs in vivo,increased the clearance rate of CTCs by the immune system,and slowed tumor progression.Thesefindings greatly enhance the clinical application prospects of IVFC and tumor vaccines.

In Vivo Studies and Flow Cytometric Investigation on Anticancer Potential of Selenium Nanoparticles Synthesized via Aqueous Extract of Clerodendron phlomidis

Nowadays,doctors and nutritionists recommend individuals incorporate selenium-rich foods such as nuts,cereals,and mushrooms into their regular diet to maintain fitness and overall health.Selenium nanoparticles(SeNPs)exhibit strong chemopreventive capabilities.The anticipations for SeNPs with enhanced and tunable bioactive activities have led to a keen interest in phytofabrication.In this study,the aqueous extract of Clerodendron phlomidis plant leaves was utilized for the synthesis of SeNPs.In traditional Indian medicine,this plant extract is recognized as a significant anti-diabetic agent.The flavonoids tetrahydroxylflavone,7-hydroxyflavanone,and 6,4’-dimethyl-7-acetoxy-scutellarein present in this plant leaf extract demonstrate excellent anticancer activity.These secondary metabolites exhibit the ability to reduce sodium selenite into SeNPs.At a concentration of 13μg/mL,the synthesized SeNPs effectively inhibited the proliferation of the HepG2 cell line.The results suggest that the SeNPs possess promising anti-cancer potential against liver cancer and can be considered as a therapeutic agent for liver cancer treatment.Additionally,the cell cycle arrest induced by SeNPs was further confirmed by the fluorescence-activated cell sorting(FACS)method,indicating that SeNPs could efficiently differentiate cancer cells from normal cells.Notably,it showed a significant improvement in diethylnitrosamine(DEN)-induced Swiss Wistar rat groups.This scientific investigation highlights the high anti-cancer potential of SeNPs,positioning them as a promising therapeutic agent for liver cancer treatment.

Size dependent flow behaviors of particles in hydrocyclone based on multiphase simulation

To investigate the flow behaviors of different size particles in hydrocyclone,a designed process was numerically simulated by the transient solver,where the quartz particles possessing a size distribution were injected into a 100 mm diameter hydrocyclone with the steady water field and air core inside.A lab experimental work has validated the chosen models in simulation by comparing the classification efficiency results.The simulated process shows that the 25 μm quartz particles,close to the cut size,need much more time than the finer and coarser particles to reach the steady flow rate on the outlets of hydrocyclone.For the particles in the inner swirl,with the quartz size increasing from 5 to 25 μm,the particles take more time to enter the vortex finder.The 25 μm quartz particles move outward in the radial direction when they go up to the vortex finder,which is contrary to the quartz particles of 5 μm and 15 μm as they are closely surrounding the air core.The studies reveal that the flow behaviors of particles inside the hydrocyclone depend on the particle size.

Expressway traffic flow prediction using chaos cloud particle swarm algorithm and PPPR model

Aiming at the real-time fluctuation and nonlinear characteristics of the expressway short-term traffic flow forecasting the parameter projection pursuit regression PPPR model is applied to forecast the expressway traffic flow where the orthogonal Hermite polynomial is used to fit the ridge functions and the least square method is employed to determine the polynomial weight coefficient c.In order to efficiently optimize the projection direction a and the number M of ridge functions of the PPPR model the chaos cloud particle swarm optimization CCPSO algorithm is applied to optimize the parameters. The CCPSO-PPPR hybrid optimization model for expressway short-term traffic flow forecasting is established in which the CCPSO algorithm is used to optimize the optimal projection direction a in the inner layer while the number M of ridge functions is optimized in the outer layer.Traffic volume weather factors and travel date of the previous several time intervals of the road section are taken as the input influencing factors. Example forecasting and model comparison results indicate that the proposed model can obtain a better forecasting effect and its absolute error is controlled within [-6,6] which can meet the application requirements of expressway traffic flow forecasting.

基于3dmax Particle Flow系统的矿的虚拟效果实现

以煤为矿的代表,在对煤的视觉特性进行分析的基础上,基于3dmax Particle Flow系统建立了采掘系统中采煤机和提升运输系统中的带式输送机工作过程中煤的模型,采用3dmax自身的渲染器渲染出了该过程的动画,该方法可用于简便真实的展示煤等矿的效果及相关机械的工作原理。

浅谈3ds Max中Thinking Particles和Particle Flow的区别

Thinking Particles和Particle Flow是3ds Max中两大粒子系统,是动画师制作动画特效的两大利器,本文分别介绍了Thinking Particles和Particle Flow两个粒子系统的优缺点,并且从两个不同的方面讲述了两者的区别。

Particle Flow制作龙卷风的原理研究

3DsMax中的ParticleFlow粒子流系统是很多大型影片中特效制作的主要工具，它的出现给影视制作带来了无限的生命力，本文通过利用ParticleFlow粒子流系统制作龙卷风探讨PF粒子流的设置及“力”的应用。

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.

Particle Flow与粒子特效

3dsMax中的ParticleFlow是基于事件驱动(Event-driven)的新一代粒子特效系统,使用的是图表、示意图的工作方式,灵活性非常高。文章从一个简单易行的ParticleFlow入门例子介绍ParticleFlow与粒子特效。

Particle Flow制作“钟声敲响春节好”

本文着重介绍了3dsMax内嵌的粒子系统Particle Flow(简称PF)的强大功能,并结合案例简要展示了其操作方法与制作粒子运动的技术要点。