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The discrete element method (DEM) is widely used in the realistic simulation of the shapes of particles. Researchers have considered the simplification of particle shapes owing to the high computational cost of such simulation. In this regard, the modeling of calibrated particles is a major challenge owing to the simultaneous effects of particle properties. The angle-of-repose test is a standard test method used to calibrate the bulk behavior of simulated particles. In the present study, the hollow-cylinder (slump) test was modeled for the verification of discrete element simulations. In this regard, a sensitivity analysis was conducted for all effective parameters, namely the static friction, rolling friction, restitution coefficient, sphericity, roundness, particle size distribution, and number of ballast particles. The results indicate that the rolling friction, roundness, number of particles, and size of particles are the most important parameters in the determination of the angle of repose (AOR). For particles in the range of ballast (20–60 mm), the effect of the number of particles on the angle of repose is reduced when the number is greater than 426. Additionally, it is concluded that angular particles can be replaced with sub-angular particles (R ≈ 0.2–0.45) with a higher rolling friction coefficient (μr > 0.14).

Polymers are frequently used for a variety of applications in industry. One relevant field is plastic tubing. As plastic tubes are manufactured from thermoplastic material through hot-extrusion their dimensional accuracy is only moderate. Wherever high accuracy on tube diameters and roundness are required, the conventional production techniques reach their limits and more complex technologies are needed. Known approaches from metal machining are deep hole drilling and internal broaching. However, machining processes with chip removal on polymeric materials are not so common. Therefore, the authors studied cutting operations of polypropylene experimentally. Based on their findings they designed and built an internal broach for the machining of polypropylene tubes. Finally, the authors tested their developed broaching tool in a relevant industrial environment. The tool not only fulfills the dimensional machining requirements but also solves the present chip evacuation problem in a unique way. It enables free cutting through the whole operation and creates continuous straight chips with no need for chip breakers. Consequently, the timely cleaning step, required in traditional broaching, can be eliminated, which reduces the lead time significantly. Furthermore, the set of materials allows dry broaching. Coolant is not necessary. This leads to less waste, a cleaner production line, and avoids damage through aggressive liquids. Lastly, their design ensures that no loss of dimension occurs when resharpening the tool.

Plasma Arc Drilling (PAD) is well known non-conventional process extensively used to assemble the complex part profiles for different materials. The dimensional accuracy and surface quality like roundness, kerf tape, and heat-affected zone of PAD are precarious factors for specific applications, especially in aerospace and manufacturing industries. In present investigation has studied the influence of plasma arc drilling parameters for evaluating the quality characteristics of roundness on Ti–6Al–4 V alloy. The experimental runs were designed by the Taguchi method. The optimal PAD parameters such as arc current of 160 amp, speed of 1500 m/min, and stand-off distance of 1 mm are determined. The confirm test exhibits better agreement with the predicted values.

In any research work, the role of preliminary experimentation to decide the range of various input parameters can never be overlooked. To commence the main experimentation a range of these parameters is selected on the basis of preliminary experiments and an in-depth literature review. The Peak Current (Ip) is considered to be the most predominant input parameter affecting the cryogenically assisted electric discharge machining (CEDM) process. In this paper, the effects of varying the peak current have been evaluated in terms of Material Removal Rate (MRR), Tool Wear Rate (TWR), Surface Roughness (SR), Aspect Ratio (AR) and Out of Roundness and the range of the peak current to be kept during CEDM of AISI D2 has been focused. The electrolytic copper has been used as tool electrode. After conducting the experiments and with the support of literature, it is proposed to keep the range of peak current from 4 A to 12 A, under given machining conditions. The Scanning electron microscope (SEM) analysis of machined workpiece were also performed and CEDM was found to be better than EDM.

This paper evaluates the dimensional accuracy of industrial X-ray computed tomography (CT) measurements as a function of the geometric magnification (Mg) used for CT scanning. Two plates of square-shaped geometry with 28 drilled holes, one made of aluminum (48 mm × 48 mm × 8 mm) and a second one made of steel (6 mm × 6 mm × 1 mm), are used as measuring workpieces to test fourteen different magnification axis positions in a metrology-grade X-ray CT system. In addition to measuring the diameter and roundness of each hole, distance measurements between the holes are evaluated—both as uni-directional (center-to-center) and bi-directional (point-to-point or edge-to-edge) lengths. The variance of CT dimensional measurements, with respect to reference data obtained from tactile coordinate measurement machines (CMMs), is studied. It is found that the measurement deviations for uni-directional distances are approximately independent of Mg and mostly within a ±4 μm range. In contrast, for measurements of diameter, roundness, and bi-directional lengths, the deviations between CT and CMM data extend outside the ±4 μm limits and strongly depend on Mg (which is a variable inversely proportional to the voxel size of CT scan, VX). More specifically, decreasing Mg or, equivalently, increasing VX, generally leads to larger deviations in the dimensional data. To include the magnification dependence on the estimations of CT measurement deviations, based on the experimental data presented throughout this paper, the authors propose that the maximum error of CT length measurements can be expressed as E m a x = ( A + X / B + L / K ) μm, with A , B , and K being constant factors (determined for a particular CT measuring setup), L the dimension of the measuring length (in mm), and X the magnification axis position of the CT scanner (also in mm). Whereas the term “ L / K ” considers error influences from the size of the sample, the term “ X / B ” accounts for influences from magnification (and voxel size) selections during CT measurement.

With the development of MEMS technologies, research on MEMS gas sensor has emerged recently, and micro hotplate (MHP) is designed to provide suitable temperature for MEMS gas sensor. Heat properties of MHP profoundly influences the sensing properties of MEMS gas sensor. With the tendency of down-sizing in MEMS gas sensors, traditional temperature measurements such as contact measure and infrared temperature detection are no longer available due to relatively low resolution. In this work we used finite element analysis (FEA) to realize cost- and time-saving heat property evaluations for MEMS gas sensor with different MHP structures, and two indexes were introduced to describe heat properties of MHPs, such as area factor Q to describe area of isotherm and roundness of isotherm %R to evaluate isotherm shape. It is found that silicon oxide and silicon nitride suspension structures have different tendency in heat properties. The size of working area has important impacts on the heat properties of the MHP, and MHP with different working area may be applied in different applications. For instance, larger MHP with 1643 μm2/K area factor Q is suitable for noble metal catalytic gas sensing application, which requires uniform temperature distribution, and smaller MHP, which could reach 609 °C peak temperature at 30 mW power-consumption, is applied to IoT applications with battery power supply. Furthermore, some special characteristics of the heat distribution of MHP are found with adjusting the width of suspension beams. This work provides guidance on how to design proper sensing material shapes to utilize the performance of MHP and reduce heat loss.

We present single-and dual-frequency antennas based on the shorted helical slot in hepatic microwave ablation. The single-frequency antenna is designed by lathing a helical slot on shorted traditional semi-rigid coaxial cable, which is expected to be operated at the frequency of 2450 MHz, and the dual-frequency antenna is designed with the combination of an annular slot and a helical slot, which can be operated at 915 and 2450 MHz. We use full-wave electromagnetic simulation and transient thermal simulation to analyze the performance of proposed ablation antennas. Both proposed antennas are fabricated, and used in ex vivo ablation experiments at different frequencies with a power level of 23 W for 2 or 5 minutes. We observe that proposed single-frequency antenna with helical slot has more concentrated specific absorption rate (SAR) pattern than those antennas with conventional slots does at 2450 MHz, and the dual-frequency one has the capability to control the roundness of ablation zone from 0.34 to 0.63, under the different combination of frequencies and operation times. Proposed microwave ablation antennas are expected to lead to a potential solution of curing the liver cancers with various characteristic.

With the progression of technology, demands of super alloys have been increased dramatically. One such super alloy is Inconel-718. Although, it is having an extensive application in aerospace industries, steam power plants and oil and gas refineries due to possession of some stringent properties like hot hardness, resistance to wear, high strength. Possession of these rigorous characteristics makes it hard to finish this alloy with the conventional finishing processes almost impossible. So the present work focuses on the predominant role in Industries by giving an edge on surface finishing with more precision and accuracy. To establish the process experimental setup and magnetic tool have been created for chemical assisted magnetic abrasive finishing process to inspect the enhancement in internal roundness of Inconel-718 cylinder. The processing unit has been installed on the lathe machine. Experiments have been performed on Inconel-718 cylinders with 5.7 mm in thickness, 155 mm in length. The experiments have been planned by means of Response surface methodology. Results of the experiments have been analysed with the help of analysis of variance. It has been found that with the operating parameters having specified values like duration of processing-80 mins, Pole work gap-4 mm, and abrasive weight percentage-30%, size of abrasive particle- 40 µm and concentration of Etchant- 700 gm/litre internal roundness improvement percentage for Inconel 718 cylinder is achieved as 42.86%.

Fabrication of microperforated panel (MPP) using an additive manufacturing (AM) process produced imperfect perforations with an irregular shape, inconsistent size, and rough inner surface (due to burr formation). This imperfect hole condition leads to a significant deviation between measured and modeled acoustic properties. This study aims to introduce the resistance end correction factor ( α ) for quantifying this deviation. The MPP model’s current development excludes the irregular and inconsistent holes from the actual MPP. The improved resistance end correction factor ( α ) is determined based on the actual MPP samples. The MPP’s acoustic properties fabricated using AM process (3D Printing – PolyJet technology) are measured. The improved resistance end correction factor ( α ) is presented in surface plots for different geometrical parameters, perforation diameter ( d ), plate thickness ( t ), and perforation ratio ( σ ). The interpolation method is used to predict the “ α ” value based on the surface plot. The improved relative acoustic resistance value for the actual MPP sample with imperfect perforation condition (with recorded lowest hole roundness value at 0.207) is calculated using the predicted “ α ” value. Comparative results showed that the improved relative acoustic resistance determined based on the interpolated “ α ” agreed well with the experimental measurement results. The correlation coefficient for each comparison varied from 0.885 to 0.987. This finding is better than comparing calculated relative acoustic resistance values by using Maa’s theory and other MPP models with different proposed resistance end correction factors ( α ). Therefore, the proposed technique can reflect the imperfect perforation condition in actual MPP samples.

In this study, discrete element method (DEM) simulations of a biaxial test were used to examine the effect of particle roundness on the mechanical behavior of sands at both the macro and micro scales. First, a stack of microcomputed tomography images were binarized, segmented, and labeled using advanced image processing and analysis techniques. Second, a spherical harmonic (SH) analysis, which involves a complete set of orthogonal functions, was implemented to rebuild the natural particle shape. Then, five templates of virtual particles were built in a DEM simulation, four of which were obtained from SH degrees of 3, 8, 12, and 15, and one template was an elementary sphere. A flexible membrane was numerically generated to allow the material to deform freely under a prescribed confining stress. Finally, the effect of particle roundness on the mechanical properties of granular materials was investigated and discussed. Two shear bands were found to intersect, forming an X shape in both the rotation and displacement fields. Moreover, a lower particle roundness results in higher deviatoric stress and stronger dilation in the volumetric change. A decrease in particle roundness leads to less rotation of particles despite a higher displacement value. In addition, a larger SH degree leads to smaller normalized contact forces of the particles. This implies that decreasing the roundness results in higher anisotropy of the contact forces.

The reliable modelling of irregular grain shapes and generating realistic particle packs still remain urgent problems limiting the application of the particle-based numerical techniques in many industries dealing with granular materials. An effective computational approach for generating irregular three-dimensional (3D) grains by dynamic agglomeration of a large number of movable and interacting particles is proposed. The constructed grains are then randomly packed within an arbitrary-shaped container. The molecular dynamics-based concept is used for producing the grains with realistically complex configurations and adjustable shape morphology. The identical molecular dynamics technique coupled with the full six-degree-of-freedom rigid-body dynamics of the agglomerates is applied for grain packing. A database of 3D models of unduplicated irregular particles has been created. Several examples are considered to demonstrate the computational efficiency and controllability of the presented algorithms. The numerically reconstructed packings qualitatively and quantitatively satisfy the desirable properties of the real one in terms of the morphological features, void ratio, size distribution, and generally accepted shape characteristics of the grains (such as aspect ratio, sphericity, roundness, and roughness). Not only statistical, but also physical correspondence is established through the numerical reproduction of the angle of repose tests. An experimental verification of the model is performed.

In this study, three-probe error separation was developed with three chromatic confocal displacement sensors for roundness measurement. Here, the harmonic suppression is discussed first to set suitable orientation angles among three sensors. Monte Carlo simulation is utilized to test the error separation and optimize the orientation angles and off-axial distance. The experimental setup is established using chromatic confocal sensors with a precise rotary platform. The experimental results show that the measured roundness with an orientation-angle combination of (0°, 90.1°, and 178.6°) is much better than that of another nonoptimal selection (0°, 90.4°, and 177.4°). The roundness error is only 0.7% between the proposed measurement system and an expensive ultraprecision roundness meter. Furthermore, it is proven that the eccentricity distance should be decreased as small as possible to improve the measurement accuracy. In sum, this paper proposes a feasible method for roundness measurement with reliable simulations, easily integrated sensors, and an ordinary precision rotary platform.

This paper aims to study the influence of particle shape on the shear strength of superellipsoidal particles by Discrete Element Method (DEM) simulations of triaxial tests in 3D. A total of forty-nine types of equiaxed superellipsoidal particles from three evolution paths have been created. The definition of effective porosity has been proposed. Our findings show that both the particle sphericity and roundness affect the shear strength of the superellipsoidal particle system. Under the mutual impact of initial porosity and particle shape, the simulation results of shear strength and volumetric strains present a trend of initially decreasing and subsequently increasing. The microstructure evolution of superellipsoidal particles during the shearing process is observed microscopically. The anisotropy of fabric reveals the mechanism of effective porosity and sphericity influencing the macroscopic shear strength at the particle scale.

It has been well established that critical state behavior of granular soils is controlled by their intrinsic properties. The critical state behavior is quantified by strength parameter M, as well as slope λ and intercept Г of the critical state line. The recent advance of image-based particle shape characterizations allows for reliably and rapidly determining particle roundness and sphericity of a statistically significant large number of particles, which enables systematical investigation of influences of intrinsic properties on criterial state parameters of sands. The computational geometry technique is used to analyze images of seven sands collected in this study to determine their roundness and sphericity. Drained triaxial tests are performed on these seven sands to determine their critical state parameters. This database is further augmented by experimental data of another 71 sands from published geotechnical engineering sources. Influences of image-based sphericity, roundness, gradation, and mean particle size on the critical state parameters are analyzed, leading to observations that angular sands with low roundness exhibit larger M, λ, and Г values, while the remaining parameters have no perceptible effects. Therefore, the roundness is used to develop predictive models for M, λ, and Г values. The effectiveness and accuracy of the predicted models are validated by 78 sands. The predictive models provide insights into relationships between microparticle level properties and macro-critical state mechanical behavior of sands and enable researchers and practitioners to rapidly estimate critical state parameters of sands without performing laboratory tests.

Roundness has an important role in terms of dividing the load equally, determining component life, determining adjustment conditions, determining rotation accuracy, and facilitating lubrication. To measure the roundness required a tool that can perform measurements with precision. With a roundness measuring instrument that has an automatic motion control system it will be able to produce more efficient data retrieval and higher accuracy than previous research. The control system in this tool is a system that regulates the automatic movement of the roundness gauge. Where the function of this automatic motion control system is to measure the test object using a chuck as a clamp, the indicator dial is directed by the X and Y axes to the data collection point on the test object which is connected to the driving motor. Axis Y moves in translation to direct the indicator dial on the "arm" to the pick-up point which moves automatically depending on the selected data collection mode, then the indicator dial starts taking measurement data until the measurement data retrieval is complete, then the motor moves from top to bottom, to perform reversible data retrieval. Stepper motor on the chuck will also move. There are 2 mode in this machine, it is mode 1, where the resulting data is in the form of a "ring" and for mode 2, the resulting data is “spiral”. It was found that the translational speed of the screw shaft in the vertical movement is 0.025 m/s and the horizontal linear speed is 0.026 m/s.

The dressing regime parameters in the process of grinding are the most important enabling factors that need to be determined. In this study, the influence of dressing regime parameters (the rough dressing depth, the dressing feed rate, the fine dressing depth, rough dressing times, fine dressing times, none-feeding dressing times) on roundness tolerance for external grinding of SKD11 steel is introduced. The Taguchi technique in designing the experiment and analyzing of variance (ANOVA) have been applied to define the influence of dressing regime parameters on the roundness tolerance. The results show that the impact level of fine dressing times (nf), none-feeding dressing times (n0), fine dressing depth (af), rough dressing times (nr), rough dressing depth (ar), dressing feed rate (Sd), and errors on roundness tolerance (Rt) are 62.88%, 19.70%, 9.85%, 3.79%, 1.52%, 1.52% and 0.76% respectively. Finally, by analyzing experimental results, optimized dressing parameters with fine dressing times (nf) of 3, none-feeding dressing times (no) of 3, fine dressing depth (af) of 0.01 mm, rough dressing times (nr) of 3, rough dressing depth (ar) of 0.03 mm and dressing feed rate (Sd) of 1.0 m/min have been determined, that allow getting the best roundness tolerance.

The multi-scale characteristics of particle morphology, including the overall form, local roundness and surface roughness, affect the critical state behavior of sands and should be considered in modern critical state-based continuum constitutive modeling. Despite extensive experimental and numerical studies, no consensus has been reached as to how particle morphology may quantitatively dictate the critical state response of sands. This study presents a numerical investigation based on discrete element method (DEM) in an attempt to address this outstanding issue. Five DEM samples of uniformly graded sands consisting of realistic shape clumps and ideal spheres of different mass proportions are prepared and subjected to conventional drained and undrained triaxial compression under different initial void ratios and stress states. A 3D overall regularity (OR) index is adopted to quantify both the overall form and local roundness characteristics of these assemblies. It is shown that this shape parameter OR may effectively help to elucidate the correlation between mechanical properties, especially the critical state behavior of sand and particle shape, and has a great potential for incorporation into the framework of anisotropic critical state theory for constitutive modeling of sand behavior. The study helps to advance our cross-scale understanding of microscopic grain-scale morphology information in relation to macroscopic soil behavior.

In the process of tobacco silk making, how to better improve the quality of stem and leaf separation has become an issue of concern. His research mainly discusses the data collected from tobacco leaf images based on computer vision sensors. In LM (Levenberg-Marquarelt) as a training function, the algorithm uses threshing effect samples for training and learning. This paper is aimed at extracting the shape characteristic parameters of tobacco leaves and obtains the shape parameters of the length, width, area, circumference, and roundness of the tobacco leaves. In this paper, boundary tracking is used to obtain the coordinate and direction information of the tobacco leaf boundary pixels in the image, which provides a basis for obtaining the subsequent extraction of tobacco leaf characteristic parameters. In the tobacco leaf grading system, the tobacco leaf feature parameter extraction module displays the geometric characteristics of tobacco leaf, such as length, width, area, aspect ratio, rectangularity, and color characteristic, hue H , saturation S , A channel, and B channel in detail through the computer vision sensor. Finally, the subjective and objective combination weighting method is used to combine and weight the indicators of the threshing effect of the first-level threshing machine, which not only considers the quantity of information provided by the indicators but also takes into account the subjective view of the experts, which increases the weight of the indicators, accuracy, and scientificity. The approximation accuracy of the training samples of the threshing effect prediction model based on the BP neural network LM algorithm is 99.495%, the approximation accuracy of the validation set is 96.535%, and the approximation accuracy of the test set is 98.392%. This research will greatly improve production efficiency and meet the enterprise’s requirements for high efficiency and low cost.

In this paper, the centerless finishing process of bearing cylindrical roller made of AISI 52100 steel using free abrasives and soft pad was investigated by the Taguchi method in the experiments and simulation, with the aim of improving the roundness. The rounding and material removal process was simulated based on the improved model. The test runs of experiments and simulation were designed according to a standard orthogonal array in which four factors included loading force, abrasives concentration, particle size, and error, and each factor had three levels, as well as the total number of parameter combinations was nine. The signal-to-noise (S/N) ratio was applied in experimental data processing, representing both the average (mean) and the variation (scatter). According to the analysis of variance (ANOVA) by S/N ratio, it is indicated that the loading force makes the largest contributions respectively accounting for 72% in roundness and 54% in material removal rate (MRR), the abrasive concentration almost has no contribution in roundness but has one accounting for 24% in MRR, and the particle size has contributions respectively accounting for 21% in roundness and 13% in MRR. Through the analysis of level average response, the optimal parameter combination was chosen as loading force of 60 N, abrasives concentration of 10 wt%, and particle size of 127 μm. In the centerless finishing experiments under the optimal conditions, the roundness was improved from an initial 0.71 to a final 0.32 μm after 12 min of processing at the MRR of 0.44 μm/min.

In the manufacturing sector, the section that has attained the most demand is metal forming. Most traditional methods in the manufacturing industry are not flexible, thus opted for the single point incremental forming (SPIF) method. However, it encompasses a geometric deviation issue. The prediction of geometric deviation and optimal parameter selection is more tedious in the existing works. In order to trounce these issues, this paper proposes a modified adaptive neuro-fuzzy inferences system (MANFIS)-centred geometric deviation prediction and enhanced squirrel search algorithm (ESSA)-centred optimal parameter selection for SPIF in AA2024-O aluminium alloy sheets. The proposed methodology encompasses '3' sections. Initially, the SPIF designing is performed in which truncated cone shape is chosen and inputted into Computer-Aided Designs/Computer-Aided Manufacturing software. Next, the designed shape is constructed and coordinate-measuring machines gauges the geometric metrics. Therefore, to envisage the geometric deviations, the measured geometric values are rendered as the input to the MANFIS. If the deviation is presented, then the ESSA algorithm chooses the optimal initial parameters, and that selected parameters are suggested to the SPIF design. The minimum roundness deviation together with the position deviation is fixed as the Fitness Function in ESSA. The AA2024-O aluminium alloy sheet is taken for the experimental investigation. In addition, the proposed method's performance is contrasted with prevailing methods centred on statistical metrics and MSE, which exhibits that the proposed methods outweigh the prevailing methods. A better result is attained by the proposed works when analogized to the existent methods by obtaining values of 97.90%, 96.78%, 95.84%, 96.23%, and 0.017% for accuracy, precision, recall, F-measure along with mean error.

The issues of estimating the error of coordinate measurements of the shape characteristics of geometric elements of products depending on the number of control points, taking into account a given confidence probability, are considered. Analytical models are proposed for estimating the error based on a priori data, similar to estimating uncertainty by type B. The correspondence of model and experimental results is verified by the Monte Carlo method using a specially developed program in VBA and the library functions of the Statistical Analysis package of the Microsoft Excel program. Such a characteristic of the shape of the part as roundness is investigated. The influence of the parameters of regular structures associated with the features of the technological processes of manufacturing the part on the parameters of the distribution function of the coordinates of the control points is revealed. Fourier analysis is used to identify and quantify regular structures on the surface of the part. The sources of error that have a significant impact on the results of measurements of the shape characteristics of geometric elements of products are given. Based on the results of statistical calculations, the dependence of the measurement error of the shape characteristics on the number of control points is analyzed, the scope of application of analytical formulas for estimating the error of single measurements for a given confidence probability is determined. The article is intended for specialists in the field of practical coordinate metrology and related fields.

An omnidirectional wireless local area network (WLAN) loop-slot antenna with common-mode current (CMC) suppression is proposed in this communication. First, based on the analysis of the equivalent model of odd–even mode, the feeding coaxial line is led out at the voltage-zero point of the loop-slot element, which suppresses the CMC over the full band. Second, through the theory of array, three loop-slot elements form an array to obtain omnidirectional radiation. Finally, the physical size is reduced by loading Stubs T in the slot. The roundness of the radiation pattern is modified by the Stubs T and the chamfering edge of the antenna. A prototype of the proposed antenna was fabricated and measured. The measured results show that the antenna achieves $\vert \text{S}_{11}\vert dB in bands of 2.15–2.65 and 4.85–5.92 GHz. In addition, the roundness is 0.95 dB at 2.4 GHz, 1.84 dB at 5.2 GHz, and 2.43 dB at 5.8 GHz. The antenna effectively suppresses the CMC to keep a favorable roundness over a wide band, showing its potential in WLAN communication systems.

The erosion of soluble rock and transformation of groundwater result in the high geometrical irregularity of cavities in nature. The purpose of this paper is to quantitatively describe the shape of irregular cavities using Fourier transform analysis. Firstly, multi-level characterization indexes of the 2D section of cavities have been proposed, considering the high shape irregularity of cavities. The first level indexes include Shape Factor (SF), Aspect Ratio (AR) and Sphere Like (SL). The second level indexes consist of Angularity Factor (AF) and Convexity Factor (CF). The third level indexes are Roundness Factor (RF). Then, the geometric contour of cavity was transformed into a 2D waveform, with an equal-angle points sampling of the cavity boundary. The geometric boundary of irregular cavity was segmented and transformed from discrete time domain to frequency domain based on discrete Fourier transform (DFT). Furthermore, we proposed Fourier shape descriptor, which was found to control the cavity shape. The relationship between Fourier shape descriptors in different sequences and multi-level characterization indexes was determined using designed and irregular nature cavities as sample data. The results demonstrated that the Fourier shape descriptors​ D 2 , D 3 and D 8 mainly control multi-level characterization indexes including the overall shape, the irregularity and the roughness of the cavity boundary, respectively. Finally, the 3D characterization method of cavity shape was further proposed based on averaging the 2D sections, which hence offers a possible way to further quantitatively study the mechanical properties of surrounding rockmass effected by the irregular shape of cavities.

Made available in DSpace on 2022-04-29T08:31:52Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 The grinding of interrupted geometries, such as keyways, holes, lubrication channels and crankshafts, bearings, helical drills, sharpening, and gear hobbing process for pre-toothing, presents technical difficulties such as decrease in surface quality and an increase in costs, when compared to continuous grinding process. This work aims to study further findings about interrupted cylindrical grinding process of AISI 4340 steel, with the application of resinoid aluminum oxide grinding wheel and conventional application of MWF. In a novel and innovative way, this work analyzed the wheel wear cost at 3 different feed rates (0.25, 0.50, and 0.75 mm/min) for continuous workpieces and interrupted workpieces with 2, 6, and 12 grooves. In addition, surface roughness, roundness deviation, grinding power, tangential force, microstructural analysis, diametrical wear, and G ratio were also evaluated. In conclusion to the results obtained, the average values of surface roughness Ra and Rz increased with the severity of the process (feed rate and number of grooves). For feed rates varying from 0.25 to 0.75 mm/min, mean values of 0.51 to 1.10 μm (Ra) and 4.52 to 10.99 μm (Rz) were obtained for the condition with 12 interruptions, indicating an increase in the order of 75 to 114% compared to without interrupted workpiece. The quick wear of the wheel, obtained for an average diametrical wheel wear of 5.79 μm for workpiece with 12 interruptions in 0.75 mm/min, produced higher surface roughness values. Variations of more than 80% in roundness deviation were obtained during grinding at feed rates of 0.75 mm/min due to mechanical shocks during material removal process, being observed in force variations from 50 to 700 N. The cost analysis of grinding wheel wear showed the waste of abrasive material for grinding process with interrupted geometries. For all tests, the tool cost for low feed rate (0.25 mm/min) did not suffer great variations. For feed rates of 0.50 and 0.75 mm/min, the cost of tool wear was higher. The condition with the highest percentage increase in cost was recorded for grinding process with workpiece of 12 grooves and feed rate of 0.75 mm/min, generating an increase of up to 1720% in the tool cost. Converting into monetary values, the wheel cost is of $ 12.62 per 1000-piece batch. Department of Control and Industrial Process Federal Institute of Paraná Jacarezinho Campus Department of Mechanical Engineering São Paulo State University “Júlio de Mesquita Filho” Bauru Campus Department of Mechanical Engineering São Paulo State University “Júlio de Mesquita Filho” Bauru Campus

To verify if indirect radiographic signs of first metatarsal pronation, determined by the head round sign, correspond to weight-bearing computed tomography (WBCT) measurements. In this case–control retrospective study, we analyzed 26 hallux valgus (HV) feet and 20 controls through conventional radiograph (CR) and WBCT images. Two blinded orthopaedic foot and ankle surgeons performed the measurements. Pronation classification (head roundness), head diameter (HD), traditional HV angles, arthritis, sesamoid positioning, and first metatarsal rotation angle (MRA) (alpha angle) were evaluated. Comparisons were performed by Student’s T-test and a multivariate regression was executed. P-values less than 0.05 were considered significant. Mean values were higher in HV patients than controls when evaluating MRA (11.51 [9.42–13.60] to 4.23 [1.84–6.62], 95%CI), HD (22.35 [21.52–23.18] to 21.01 [20.07–21.96]), and sesamoid rotation angle (SRA) (26.72 [24.09–29.34] to 4.56 [1.63–7.50]). The MRA had a low influence in head roundness classification (R2: 0.15). Changes in the pronation classification were explained chiefly by the sesamoid station (SS) (R2: 0.37), where stations 4 to 7 were found to be strong predictors of roundness classifications 2 and 3. Indirect signs of metatarsal pronation, determined by the head round sign, correlate weakly with the alpha angle measured in WBCT. The presence of arthritis and sesamoids displacement might modify the perception of first head roundness. The influence of MRA in the classification was low, where SS from 4 to 7 was strong predictors of a higher pronation classification.

In this work we describe the production of spherical polymer particles from thermoplastic polymers. A simple method is developed to transform rough powders into spherical particles. The polymer particles are molten in heated oil whereafter interfacial tension driven reduction of curvature and shape retraction induce a transformation to the equilibrium spherical shape. The sphericity of the particles is validated by determining the aspect ratio, roundness, as well as circularity. Furthermore, batches of narrow particle size distribution are attained by sieving on different mesh sizes. The effects of the material characteristics and processing conditions are investigated and rationalized based on the governing physical processes and their scaling relations. As a result, the processing conditions can a priori be tailored depending on the material characteristics. The versatility of the method is confirmed by generating spherical particles from various thermoplastic polymers including PS, LDPE, PP, PA12 and PA12 filled with carbon nanotubes.

The physical and mechanical properties of the material to be processed are fundamental and continue to be a challenge for researchers to design a machine appropriately. Studies of the soybean engineering properties have not been widely highlighted and reviewed. This makes researchers and engineers of soybean processing machines still have to search through experimentation or read deeply through scientific papers before applying it. Therefore, this paper presents highlights and reviews of studies related to the measurement and modelling of soybean engineering properties. The objective is to study methodologies uses and identify future research directions to get a result in more accuracy. Several papers are searched from various search engines for scientific articles that are available online. Some keywords and a combination of keywords used in the search process are “physical properties”, “mechanical properties”, “soybean grains” and “moisture-dependent”. The results show that ten scientific papers are strictly related to the measurement and modelling of the engineering properties of soybean. In general, the documents found were in the period 1993 to 2012. The research paper investigated the engineering properties of soybean in the moisture content ranges from 6.7% (d.b.) to 49.7% (d.b.). The widely studied physical properties are diameter, surface area, roundness, the weight of 1000 soybeans, bulk density, and true density associated with moisture content. Mechanical parameters investigated include friction coefficient, angle of repose, terminal velocity, angle of internal friction, rupture force, and rupture energy. On the one hand, some of the engineering properties of soybeans that have not yet been discovered are thermal, optical, and aerodynamic properties. On the other hand, the effect of soaking and blanching on changes in the engineering properties of soybean (physical, mechanical, thermal, optical, and aerodynamic) has not been done in-depth. Besides that, most of the soybean processing agro-industry requires engineering properties of soybean to be able to design their machines more precisely. One of the agro-industries that need data on the study results of the nature of engineering with these treatments is the tofu processing industry.

The Roundness Tester Machine is a tool used to take measurements that are shown to check the Roundness of an object or to find out whether an object is really round or not when viewed carefully using a measuring instrument. DFM (Design for Manufacturing) is a method for reducing production costs by estimating production costs through reducing component costs, assembly costs, and other production supporting costs based on design submission data without reducing product quality. AHP (Analytical Hierarchy Process) method was chosen as a method to determine the optimal Vertical Roundness Tester Machine design based on a questionnaire given to the expert, to choose the best alternative decision. The questionnaire was created to get priority customer needs which was then used for the initial design. The next stage is selecting the optimal design using AHP which involves experts based on indicators of a product. The highest indicator value obtained on the Vertical Roundness Tester Machine is the accuracy indicator with a value of 48.52%. Then in choosing the optimal design in the DFM analysis, namely in alternative 3, where alternative 3 is the design with the lowest cost so as to minimize the cost of making a Vertical Roundness Tester Machine. The manufacturing cost for alternative design 3 is Rp. 4,173,000.

In this paper, a mechanical model of axial and circumferential bidirectional deformation has been developed by considering two factors: roller shape and radial reduction. Since the calibration of the roundness and that of the straightness of pipes are currently separate processes, the established mechanical models are based on a single direction. However, the established bidirectional mechanical model can describe not only the stress-strain distribution of the pipe in deformation to determine the position of the stress concentration but also the deformation curve of the pipe in different directions. As a result, it can serve as a theoretical basis for setting process parameters and optimizing roller shape. A large thin-walled pipe of Al6063 is modeled and then numerically simulated with FEM software of ABAQUS, and the results are compared with the model. Then, the process is fabricated and tested experimentally. The results are compared with the mechanical and numerical models. The distribution of equivalent stress and equivalent strain obtained by the model has a good match with the simulation results, and the maximum relative error is not more than 25%. The axial and circumferential deformation curve calculated by the mechanical model coincides well with the simulation and experimental results, and the maximum error is not greater than 3.0 mm. Obviously, both the experiment and the simulation have verified a superior validity of the model.

In this study, several artificial neural network (ANN) models were developed with the help of microstructural characteristics to predict uniaxial compressive strength (UCS) and elastic modulus (E) of migmatites. To this end, 51 migmatite samples were prepared and for each sample some microstructural characteristics along with UCS and E were determined. A semi-automatic technique was implemented to quantify twenty microstructural characteristics including mineral size (area, perimeter, equivalent circular diameter, minimum Feret diameter, maximum Feret diameter), mineral shape (aspect ratio, orientation, compactness, roundness, rectangularity, solidity, convexity, concavity, form factor), fabric coefficients (index of interlocking, index of grain size homogeneity), mineral contents (quartz content, feldspar content), and mineralogical indices (saturation index, and coloration index) based on digital imaging of representative parts of thin sections of samples. Area, orientation, concavity, index of interlocking, feldspar content and saturation index were chosen as inputs of the prediction models. Here, 6, 10 and 10 ANN models were developed with 5, 4 and 3 inputs, respectively, using these microstructural characteristics. Bayesian regularization was employed for training the models to improve the generalization capacity of the models. From these models, the model with orientation, index of interlocking and feldspar content as inputs was selected for producing prediction charts. For this model, mean squared error and correlation coefficient were obtained as 0.0148 and 0.854 for training data, and 0.0143 and 0.860 for test data, respectively. The proposed models and prediction charts in this study can show high prediction capability, given that they are used for similar types of rocks.

In contrast to a macroscopic solid, the color and spectroscopic properties of gold nanoparticles change with size. Here, we propose a teaching platform for high school students (hereafter defined as students, attending secondary school in Europe, preparatory high schools in the US, or any educational institution of a comparable level) that explains the relationship between the perceived color of colloidal solutions and their physicochemical properties. For this aim, an open-source code, based on Mie theory and colorimetry, was developed to link the perceived colors to the plasmonic effects. Moreover, a set of such nanoparticles, varied in diameter, was created to support the theoretical description. The employed seed-mediated synthesis approach provides sufficient spherical roundness that is crucial for color matching. The proposed teaching platform is available online and can be linked to an outreach activity or practical laboratory course. Furthermore, we illustrate the linkage of nanoscience concepts to real-world examples (e.g., stained church glass), which can be used for promoting the potential of nanotechnology in other fields, including electronics, optics, and biomedicine adding to the interdisciplinarity of the teaching platform.

Pellets formulation with natural gums. The formulation of an enzyme as well as pH dependant pellets containing natural gums such as Mornings oleifera gum Lam. (MOG) and Cyamopsis tetragonolobus gum Taub. (CTG) were used for enzyme dependant release and further coating is provided to shows colon-specific delivery. Extrusion and spheronization techniques were used for the preparation of pellets. Pellets of budesonide evaluated for various properties such as flow behavior, physical properties such as sphericity, roundness, aspect ratio, hardness, and friability also investigated in vitro and in vivo targeting in rabbit. Preparation of pellets was done by using extrusion and spheronization method with the use of optimized concentration of gums those were 7.5% and 10% for CTG and MOG respectively and proportion of solvent mixture of water and Isopropyl alcohol in the ratio of 80:20. Pellets of budesonide evaluated for various properties includes flow behavior, physical properties such as sphericity, roundness, aspect ratio, hardness, and friability and found that all properties as per official limit also in vitro release study found that release of uncoated pellets in a sustained manner in 0.1N HCl for 2h due to swelling of natural gum, therefore further step of the coating was done in fluidized bed coater to prevent the release of drug in the upper part of GIT and after coating found that In vitro release of drug at the colonic environment and it confirmed with in vivo investigation in rabbit with X-ray examination of targeting and found that pellets reach at colonic part without disintegration. The use of natural gums for preparation of pellets in optimized concentration and wetting agent produce a formulation with all required chemical and physical properties and it gives effective in vitro release and also shows In vivo targeting in rabbit and due to use of natural gum for preparation of pellets also reduce some problems of metabolism of synthetic excipients.

Turning is one of the most used metal removal operations in the industry. It can remove material faster, giving reasonably good surface quality apart from geometrical requirements. Conformity of geometry is one of the most significant requirements of turned components to perform their intended functions. Apart from dimensional requirements, the important geometrical necessities are Circularity, Straightness, Cylindricity, Perpendicularity, etc. Since they have a direct influence on the functioning of the components, the effect of the cutting parameters on them has greater significance. In this paper experiments are carried out to examine the effect of turning parameters such as cutting speed, feed rate, and depth of cut on responses like; straightness, roundness, surface roughness, and material removal rate during turning of AISI 4340 steel. Analysis of Variance (ANOVA) is performed and the influence of parameters on each response is studied. The optimal values of parameters obtained from the study are further confirmed by conducting experiments.

The article presents a study of the characteristics of experimental samples with a chrome coating: the straightness and ovality of the inner surface of the cylinder, as well as the hardness and thickness of the chrome coating. The chrome coating is obtained on a previously developed installation for applying chrome coating on the inner surfaces of hydraulic cylinders of hydraulic drives with hydrostatic guides. The measurement of the geometric characteristics of the internal surface of the samples was carried out, the values ​​of deviations from roundness and deviations from straightness were obtained. A study of the chrome coating was carried out, for this we cut out sectors from the samples, carried out their sample preparation, measured the hardness and took pictures under a microscope, measured the hardness and thickness of the chrome coating. The obtained measurement results: deviation from roundness, deviation from straightness, coating hardness, coating thickness - correspond to the specified technical requirements, the proposed construction of the installation for applying chrome coating to the inner surfaces and the electrolyte composition, selected earlier, are applicable for chrome plating of the inner surfaces.

Taking the raceway roundness error into account, mechanical characteristics of cross roller bearings (CRBs) were investigated. A static analysis model of CRBs considering the raceway roundness error was established. Based on this model, the rotational accuracy and load distribution of CRBs under constraints of geometry and external loads were derived. The fatigue life of CRBs with roundness error was calculated by applying Palmgren-Miner linear cumulative damage theory. The influence of inner and outer raceway roundness error on the performance of the CRBs, such as rotational accuracy, load distribution, and fatigue life, was studied through the analysis of examples. The results indicate that the influence of roundness error on the rotating inner raceway is more significant than that of roundness error on the nonrotating outer raceway. The roundness error on the rotating inner raceway always degrades the performance of CRBs. However, a proper roundness error on the nonrotating outer raceway can reduce the loads acting on the rollers and thus improve the fatigue life of CRBs. The effect of the roundness error amplitude on the bearing performance is ordinal, whereas the effect of the roundness order on the bearing performance is not in order.

Metallurgical coke is an important raw material for blast furnaces. Specifically, temperature and CO2 significantly affect its metallurgical behavior. In this study, the influence of temperature and CO2 on the high-temperature behavior of three metallurgical coke samples, used in blast furnaces of different volumes, was investigated. The carbon structure and pore structure of the coke samples were analyzed. The results indicated that as the temperature increased from 1100 to 1500 °C, the weight loss ratio increased 10-fold and the drum strength decreased to approximately 80% in Ar. Under a CO2 atmosphere, as the temperature increased from 1100 to 1300 °C, the reactivity index increased from 20 to 70%, and the strength after reaction exhibited the lowest value of 40% at 1250 °C. When the temperature increased from 1100 to 1500 °C, the stacking height of the layer structure Lc of the coke samples increased to ∼5.5 nm. Under the influence of CO2 and temperature, the Lc of the coke samples increased to approximately 4 nm between 1100 and 1300 °C. Furthermore, CO2 slightly affected the carbon structure. The changes in pores under the influence of CO2 and temperature were greater than those under the influence of temperature between 1100 and 1300 °C. Typically, the strength of coke is high when the pore number, roundness, and porosity are low. The strength and microstructure parameters of the coke samples were correlated via multiple regression. The results of the multiple regression showed that the carbon structure and pore number had the highest impact on coke strength, followed by roundness and porosity.

Grain morphology has significant impacts on the mechanical behaviors of granular materials. However, its influences on grain breakage are still poorly understood due to the complexity of morphological characterization. This work employs the machine learning (ML) approach to reveal the impacts of grain morphology on grain crushing strength. A database consisting of 400 high-resolution rock grains was collected by 3D scanning. The morphology of each grain is characterized using 24 global shape descriptors and the local roundness at the contact zone. Based on hierarchical clustering, eight descriptors are selected as input features to the ML model. Grain instability is also quantified and used in the training of the ML model. To eliminate the influence of material properties and size effects on grain breakage, we perform the combined finite and discrete element method simulation of the single grain crushing test to get the crushing strength, which is used as the output of the ML model. Among the five ML regression algorithms used, XGBoost has more outstanding prediction accuracy and generalization ability. Each feature's influence on crushing strength is then analyzed using permutation feature importance and SHapley Additive exPlanations (SHAP) value. The feature importance ranking indicates that grain instability has the most significant impact on the crushing strength. The SHAP value demonstrates that flat, rounded, and convex grains have higher resistance to compression. The local roundness at the contact points also affects the crushing strength, in which higher local roundness corresponds to larger crushing strength. The results revealed by ML are in agreement with previous qualitative studies. The interpretable ML may shed new light on the investigation of the complex granular materials.

This paper presents a novel computational-geometry-based approach to generating random packing of complex-shaped 3D particles with quantitatively controlled sizes and shapes for discrete modeling of granular materials. The proposed method consists of the following five essential steps: (1) partitioning of the packing domain into a prescribed number of random polyhedrons with desired sizes and form-scale shapes using the constrained Voronoi tessellation; (2) extraction of key points from the edges and facets of each polyhedron; (3) construction of a freeform curve network in each polyhedron based on Bezier curve fitting; (4) generation of solid particles with smooth, convex surfaces using the biharmonic-based surface interpolation of the constructed network; and (5) creation of concavity by superimposing spherical harmonic-based random noise. To ensure that the obtained shape descriptors (e.g., the elongation, flatness, roundness and convexity ratio) match the hypothesized values, an inverse Monte Carlo algorithm is employed to iteratively fine-tune the control parameters during particle generation. The ability of the proposed approach to generate granular particles with the desired geometric properties and packing is demonstrated through several examples. This study paves a viable pathway for realistic modeling of granular media pertaining to various engineering and industrial processes.

High-order and low-order wheel out-of-roundness (OOR) often occur on metro train wheels, which can intensify the wheel–rail dynamic interaction. A vehicle–track rigid-flexible coupled dynamics model is built through combining the dynamics software SIMPACK with the finite element software ANSYS, which is validated by field vibration measurement results of vehicle and track. Two adjacent vehicles with two two-axle bogies for each one are considered in the model. The wheel–rail interactions caused by high-order and low-order wheel OOR are investigated. The influence of the wheel–rail interaction caused by wheel OOR on one wheelset on wheel–rail interactions at other 7 wheelsets is explored. The results show that the wheel OOR can excite the first bending vibration of the wheelset and the P2 resonance at a normal operating speed, which can result in a considerable increase of the wheel–rail dynamic interaction and wheelset vibration. The wheel–rail dynamic interaction can be transmitted from the polygonised wheelset to another wheelset of the same bogie through the rail. However, the transmission is negligible from the path of the bogie. The amplitude of wheel OOR has no effect on the transmission ratio of wheel–rail dynamic interaction, but the vertical stiffness and damping coefficient of fasteners greatly influence the transmission. The two wheelsets on the same bogie should be re-profiled simultaneously if the radial run-out for one wheelset exceeds the limit and for the other does not. The effects of vibration transmission between wheelsets and track flexibility need to be taken into account in a model for predicting the development of wheel OOR.

Improving roundness of a local silica sand was conducted by abrasion using a laboratory ball mill having a diameter of about 156 mm with steel milling balls of 2800 g. Abrasion was conducted at a fixed speed of 30 rpm; with various sand loadings of 150, 200, and 250 g; and milling time of 60, 105, and 120 min. Roundness was evaluated based on Wadell equation and topography of particle surface was measured by using a new practical method consisting of a build-in camera in mobile phone and common image processing application. Results of measurement using this new proposed method had been confirmed with roundness reported from two service laboratories. The abrasion could increase the roundness of Sidrap sand from 0.20 to an average of 0.31, while the measured roundness of Ottawa standard sand was about 0.46. Three types of mortar were prepared from Sidrap sands before and after abrasion, as well as Ottawa sand. Compressive strengths of mortar after aging of 28 days were 345, 375, and 333 MPa respectively.

Crankshaft is a core part of automobile engine to bear impact load and transmit power. Precision grinding is the most important machining method to achieve high precision of crankshaft main journal. Although many scholars have established various simulation models in the field of cylindrical grinding, it is difficult to carry out effective quantitative simulation for a given crankshaft main journal grinding system. Aiming at the shortcomings of the existing models, a double-rotor dynamic model is proposed, which considers the interaction between the grinding wheel and the main journal, and iterative algorithm is adopted to simulate material removal and roundness change in the grinding process of the main journal. The normal force between grinding wheel and the main journal is defined in detail in the algorithm, which is closer to the actual grinding process. For a given crankshaft grinding system, different grinding strategies of the main journal are quantitatively simulated by using the model. The proposed model and algorithm are validated by experiments, which can provide a basic model for the further study of the crankshaft cylindrical grinding system.

The process of mining filling, when the slurry is transported to the goaf by the filling pipeline, is very important to find the location and size of the caking in the filling pipeline in time for the safe and stable operation of the mine filling pipeline. It is an important research work to detect different flow patterns after two-dimensional section reconstruction in closed filling pipeline based on ECT (electrical capacitance tomography) visualization method. Slurry flow in pipeline is regarded as a two-phase flow, and the multishape distribution was reconstructed into images by ECT and intelligently recognized by broad learning system (BLS) algorithm. BLS is a feedforward neural network with few optimization parameters and fast training speed. In this paper, three features of two-phase sample images, the number of regional blocks, the roundness of regional blocks, and barycenter of regional blocks, are combined with network structure of BLS to recognize different flow patterns. Through the simulation, the recognition accuracy of two-phase fillback image is more than 99%. This conclusion indicates the effectiveness of BLS to predict different two-phase flow patterns; it also provides a new solution for the pattern recognition of the flow pattern in the mining filling pipeline.

The field emission scanning electron microscopy coupled with energy dispersive X-ray spectrometry (FESEM-EDX) was employed for morphological characterization and elemental microanalysis of individual particles. Size distribution of analyzed particles were found between 0.2 and 1.0 μm which displayed a bimodal distribution in the q-Acc range (0.25–0.50 μm and 0.50–1.0 μm). Soot particles, Tar balls (TBs) and dust particles were classified on the basis of SEM images and elemental composition. Shape descriptor parameters such as circularity (Circularity: 0.62–0.72) and aspect ratio (AR: 1.50–1.88), inferring that particles were not perfectly spherical and not elongated in any uniform direction. Besides, the values of sphericity varied from 0.10 to 2.88 (mean: 1.22) thereby suggesting deviation of the shape (from spherical to non-spherical) in micro-environments. Decreasing trend of roundness and increasing trend of AR with increasing DAeq (Area equivalent diameter) suggest that particles with higher DAeq are more elongated in nature. The value of roundness (RN) varies from 0.18 to 0.98 (mean 0.68) suggesting particle shape varies from nearly perfectly spherical to irregular shape. Furthermore, particles were found to be more spherical in HIG than MIG and LIG which points towards more soot and TBs. The elements such as Si, Mg, Ca and fewer amounts of Al, Fe and K were observed in PM1.0-0.5. While Fe, K, Mg were found in PM0.50-0.25 μm size having crustal origin.

Image editing is an effective solution to adapt contents for different applications. In this paper, we present a roundness-preserving warping model for stereoscopic image editing, in which energy constraints from image quality energy, aesthetics energy and depth adaptation energy are involved in the framework to solve the optimization. Specifically, to preserve object roundness during warping, the relationship between object’s shape and disparity is established and is applied for depth adaptation. Different from the existing stereoscopic image editing methods, the main innovations of our method are to achieve a tradeoff in balancing information loss and reducing semantic distortion while providing a novel death adaptation model for recomposition and retargeting applications. Experimental results demonstrate the effectiveness of our method in enhancing the aesthetics of stereoscopic images.

In this paper, the centerless finishing process using free abrasives and soft pad was developed and applied in fine machining the bearing cylindrical roller of AISI 52100 steel on self-made machine, improving roundness and its deviation on roller’s circular profile. A novel modeling and simulation method of material removal and rounding process for cylindrical workpiece was proposed in three-body abrasive wear pattern, combining geometry, kinematics, elastic contact, and single grain’s micro-cutting. The equivalent elastic modulus of roller and pad in contact is a key parameter for simulation, and its value was obtained through loading experiment and data processing. The finishing simulation and experiments were carried out under different loading forces. Their diameter’s results are in good agreement, and roundness’s results are in considerable agreement with error of less than 7%, demonstrating the validity of modeling and simulation method. Through data processing and analysis, it is indicated that the roundness is improved obviously; but with a slight material removal rate, the effect of loading force on roundness is greater than that of material removal. The reasons for above results are analyzed and discussed, taking into account three-body elastic contact, contact area and depth, and number of abrasive grains in finishing region.

In the present study, the effect of electromagnetic stirring parameters, including stirring time, pouring temperature and stirring frequency, on the morphology of the AM60 alloys was investigated using Taguchi-based grey relational analysis (TGRA). Each parameter of the process was analyzed at three levels. To accommodate all parameters, an orthogonal array L9 based on the Taguchi approach was used. The optimum parameters were chosen, using different microstructural responses such as shape factor, roundness, average grain size, average grain density and average aspect ratio. The optimal processing parameters were found to be 240 s, 30 Hz and 610 °C for stirring time, stirring frequency and pouring temperature, respectively. Results showed that the shape factor, roundness and average grain density were improved by 33%, 12.8% and 5.5%, respectively. Moreover, the average grain size and the aspect ratio decreased compared to those related to the preliminary set of experimental parameters, which represents the refining of the primary α-Mg phases. In addition, optimal experiment shows a dramatic improvement in tensile strength, uniform elongation and hardness compared to the initial conditions. Besides, the overall grey relational grade was compared to an initial set of experimental parameters, showing an improvement of 64%.

High product quality is one of key demands of customers in the field of manufacturing such as computer numerical control (CNC) machining. Quality monitoring and prediction is of great importance to assure high-quality or zero defect production. In this work, we consider roughness parameter Ra, profile deviation Pt and roundness deviation RONt of the machined products by a lathe. Intrinsically, these three parameters are much related to the machine spindle parameters of preload, temperature, and rotations per minute (RPMs), while in this paper, spindle vibration and cutting force are taken as inputs and used to predict the three quality parameters. Power spectral density (PSD) based feature extraction, the method to generate compact and well-correlated features, is proposed in details in this paper. Using the efficient features, neural network based machine learning technique turns out to be able to result in high prediction accuracy with R2 score of 0.92 for roughness, 0.86 for profile, and 0.95 for roundness.

For workpieces with discontinuous surface characteristics such as shafts with keyways, obtaining continuous and valid measurement data is essential for assessing machining quality. In this paper, a Bayesian approach based on prior knowledge is proposed to evaluate the geometric characteristics of the discontinuous surface. Effective measurement data for discontinues surface is supplemented by accurate Bayesian parameter estimation. By using the supplemented data, the dimensional error and roundness error can be calculated. Using the in-process measurement method, the process progress can be adjusted in time according to the error value to realize the fusion control of dimension and roundness. Experimental investigations for machining multi-keyway shaft are carried out based on the proposed method. The results show that grinding workpieces with discontinuous surface by using the in-process measurement method based on Bayesian theory can significantly improve product quality and efficiency.

Fertilizer sphericity is an important assessment index of appearance quality that affects the fertilization effect. A fertilizer sphericity measuring device based on machine vision was designed aimed at low precision and heavy workload of manual fertilizer measurement, and high cost and complicated operation of high precision measuring instruments. A fertilizer sphericity measuring method based on equatorial and meridian circles was proposed. The device works in an intermittent static acquisition mode to simultaneously obtain both top and side images of a single fertilizer. First, the method performs gamma correction on the top and side images of the single fertilizer, and uses the Canny operator to detect the edge of the image to obtain the equatorial and meridian circular contour images of the fertilizer. Second, based on the fertilizer equatorial and meridian circular contour, the Least Squares Circle method was used to evaluate the roundness of the single fertilizer. Finally, the average roundness value of the equatorial and meridian circles was used as the final sphericity value of the fertilizer. The sphericity measurement test was carried out on the same batch of compound, organic and biological fertilizers by using the sphericity measuring device. The fertilizer sphericity data were obtained by different measurement and evaluation methods. The variation coefficient was used to evaluate the difference in fertilizer sphericity measured by different sphericity measurement and evaluation methods. The results show that among the different measurement and evaluation methods, the coefficient of variation of fertilizer sphericity measured by the equatorial and meridian circle method was the smallest, and the coefficient of variation of sphericity measured by the Least Squares Circle method was the smallest and accurate. This study shows that the sphericity measuring device and method can accurately measure the fertilizer sphericity, and has a significant potential to facilitate fertilizer production and quality inspection.

The article considers the main factors influencing the magnitude and nature of the change in friction torque in rotating pairs and shows the influence of deviations of the shape of holes on its magnitude. The scheme of laboratory installation used in experiment for measurement of the friction torque is resulted. Statistical estimates of the values of deviations of the shape of ring samples and their influence on the change of friction torque under dry friction conditions are given. The nature and types of wear of the rotating element of the pair are determined.