Stochastic modeling of spatial grain distribution in rock samples from terrigenous formations using the plurigaussian simulation method

AbstractMineral resource evaluation requires defining geological rock-type domains. The traditional simulation methods have serious limitations for applications to large numbers of domains, which have complex contact relations. Plurigaussian simulation is an effective method which can be applied, in a simple way, to any number of domains, using both local and global geological information to infer the distributions of rock types. This work not only presents the application of the plurigaussian simulation method to the Balya lead-zinc deposit, but also assesses the spatially varying rock type proportions, and accounts for uncertainties between them. These parameters are extremely important for mining deposits, since the mineralizations of interest generally occur only in certain rock types. Furthermore, being able to model the different geological rock types is vital to good mine operations, production planning, and management. The results indicate that the plurigaussian method correctly reproduces the different orientations of the individual rock types, as seen in drill holes, and the proportion of each rock type, even if this varies in space.

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Simulation of Grain Growing Process of Zinc-Aluminium Alloy under High Pressure

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.299-300.228 ◽

2011 ◽

Vol 299-300 ◽

pp. 228-232

Author(s):

Ying Dong Qu ◽

Rong De Li ◽

Yan Hua Bai ◽

Qiang Li ◽

Hong Wang Yang ◽

...

Keyword(s):

High Pressure ◽

Grain Growth ◽

Simulation Method ◽

Important Variable ◽

Solidification Time ◽

Temperature Fields ◽

Solute Diffusion ◽

Grain Distribution ◽

Simulation Results ◽

Solidification Stage

Under high pressure of more than 1GPa, the grain growing process of Zinc-Aluminium (ZA) alloy is difficult observed by experimental method, therefore numerical simulation method is used to observe grain growing process of ZA alloy. Pressure as a important variable is leading-in thermodynamic parameters of ZA alloy, then solute diffusion and redistribution model, grain nucleating and growing model are present, and dendrite growth module is applied to describe grain growth. The simulation results of grain growth process under high pressure are demonstrated: In the initially solidification stage, grains are equiaxed growing process, after 15s solidification time, dendrite arm size are not equal, the reason is there are nonhomogeneous temperature fields around grains, which make some grains appear fast growing velocity, even it can be observed that dendrite arm of different grains are meet each other at 25s solidification time. Comparing simulated microstructure with experimental microstructure under 2GPa high pressure, it shows both grain size and grain distribution are similar, proving that the grain growing process can be well observed by simulation method.

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Modeling and Simulation of Surface Topography in Single Abrasive Grain Grinding

Enhanced Heat Transfer Mechanism of Nanofluid MQL Cooling Grinding - Advances in Chemical and Materials Engineering ◽

10.4018/978-1-7998-1546-4.ch016 ◽

2020 ◽

pp. 358-380

Keyword(s):

Surface Topography ◽

Simulation Method ◽

Grinding Wheel ◽

Deformation Model ◽

Feed Speed ◽

Profile Curve ◽

Workpiece Surface ◽

Grinding Parameters ◽

Grain Distribution ◽

Surface Increase

This study establishes a kinematics model, elastic deformation model, and plastic accumulation model of a single grinding wheel, simulates the grain distribution on the surface of the common grinding wheel by using the grain vibration method, and examines the effect of different grinding parameters on the surface topography of the workpiece. Results show that the peaks and valleys on the profile curve of the workpiece surface increase, and the corresponding Ra and Rz heights decrease, as the peripheral velocity of the grinding wheel increases. The peaks and valleys on the profile curve of the workpiece surface decrease, and the corresponding Ra and Rz heights increase as the feed speed of the workpiece increases. Experiments are conducted to verify the simulation results. The results show that the simulation method can predict the surface roughness of the workpiece, which is a factor in selecting the grinding parameters.

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Incorporation of Cholesterol into Peripheral Nerve Myelin

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100094930 ◽

1972 ◽

Vol 30 ◽

pp. 334-335

Author(s):

Frank A. Rawlins

Keyword(s):

Electron Microscope ◽

Sciatic Nerve ◽

Electron Microscope Autoradiography ◽

Myelin Sheaths ◽

Microscope Autoradiography ◽

Grain Distribution ◽

Sciatic Nerves ◽

Autoradiographic Analysis ◽

Old Mice ◽

Short Times

Several speculations exist as to the site of incorporation of preformed molecules into myelin. The possibility that an autoradiographic analysis of cholesterol-1,2-H3 incorporation at very short times after injection might shed some light in the solution of that problem led to the present experiment.Cholesterol-1,2-H3 was injected intraperitoneally into 24 tenday old mice. The animals were then sacrificed at 10,20,30,40,60,90,120 and 180 min after the injection and the sciatic nerves were processed for electron microscope autoradiography. To analyze the grain distribution in the autoradiograms of cross and longitudinal sections from each sciatic nerve myelin sheaths were subdivided into three compartments named: outer 1/3, middle 1/3 and inner 1/3 compartments.It was found that twenty min. after the injection of cholesterol -1.2-H3 (Figs. 1 and 2), 55% of the total number of grains (t.n.g) found in myelin were within the outer 1/3 compartment, 9% were within the middle 1/3 and 36% within the inner 1/3 compartment

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Power of Modified Brown-Forsythe and Mixed-Model Approaches in Split-Plot Designs

Methodology ◽

10.1027/1614-2241/a000124 ◽

2017 ◽

Vol 13 (1) ◽

pp. 9-22 ◽

Cited By ~ 1

Author(s):

Pablo Livacic-Rojas ◽

Guillermo Vallejo ◽

Paula Fernández ◽

Ellián Tuero-Herrero

Keyword(s):

Repeated Measures ◽

Statistical Power ◽

Mixed Model ◽

Covariance Structure ◽

Simulation Method ◽

Future Research ◽

Repeated Measures Design ◽

Fixed And Random Effects ◽

Split Plot ◽

High Level

Abstract. Low precision of the inferences of data analyzed with univariate or multivariate models of the Analysis of Variance (ANOVA) in repeated-measures design is associated to the absence of normality distribution of data, nonspherical covariance structures and free variation of the variance and covariance, the lack of knowledge of the error structure underlying the data, and the wrong choice of covariance structure from different selectors. In this study, levels of statistical power presented the Modified Brown Forsythe (MBF) and two procedures with the Mixed-Model Approaches (the Akaike’s Criterion, the Correctly Identified Model [CIM]) are compared. The data were analyzed using Monte Carlo simulation method with the statistical package SAS 9.2, a split-plot design, and considering six manipulated variables. The results show that the procedures exhibit high statistical power levels for within and interactional effects, and moderate and low levels for the between-groups effects under the different conditions analyzed. For the latter, only the Modified Brown Forsythe shows high level of power mainly for groups with 30 cases and Unstructured (UN) and Autoregressive Heterogeneity (ARH) matrices. For this reason, we recommend using this procedure since it exhibits higher levels of power for all effects and does not require a matrix type that underlies the structure of the data. Future research needs to be done in order to compare the power with corrected selectors using single-level and multilevel designs for fixed and random effects.

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