scholarly journals OPTIMIZATION OF PRESS-FIT PROCESSES

2021 ◽  
Vol 55 (2) ◽  
pp. 207-212
Author(s):  
Gašper Gantar ◽  
Peter Göncz ◽  
Miha Kovačič
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Input Parameter ◽  
Research Work ◽  
Rejection Rate ◽  
The Core ◽  
Press Fit ◽  
Stage Of Development ◽  
Fe Simulations ◽  
The Press

The press-fit process is an efficient, low-cost method for joining parts. The parts that must be joined interfere with each other’s occupation of space; therefore, contact dimensions and their tolerances influence the quality of the assembly. The traditional method for the selection of contact dimensions and their tolerances is based on engineering experience. The idea of the research work presented in this paper is to optimize the press-fit process at an early stage of development process, involving prediction and optimization of the joining force and consequently the prediction and minimization of the rejection rate. Accordingly, several finite-element (FE) simulations of the press-fit process for predicting the joining forces were conducted, considering input-parameter variations (material properties: yield stress, hardening exponent; geometry: shaft diameter, guide diameter of the core, functional diameter of the core; friction coefficient). Based on FE simulations and 47 different input-parameter-variation results, the empirical model for predicting the joining force using the response-surface methodology (RSM) was obtained. By using RSM and a stochastic Monte Carlo simulation, the rejection rate was also determined. The predicted and the actual rejection rates for selected process parameters were 1.4 % and 1.5 %, respectively. Consequently, the press-fit process can also be optimized to reduce the rejection rate using the same Monte Carlo simulation. The results of the analysis show that the rejection rate can be reduced from 1.4 % to 0.2 %.

Estimating Weights of Evaluation Factors on Basis of Monte Carlo Simulation

2012 ◽  
Vol 268-270 ◽  
pp. 1735-1740
Author(s):  
Yan Fei Tian ◽  
Li Wen Huang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Random Process ◽  
Stochastic Simulation ◽  
Research Work ◽  
Simulation Method ◽  
Distribution Functions ◽  
Probability Process ◽  
Evaluation Work

Although the value of factor weight in an evaluation work is deterministic, the solving process is random, so connection between weight solution with digital characteristics or distribution functions of specific random variables or random process could be build. Using stochastic simulation method to get a lot of random solutions to the problem, expectation of the random solutions can be used as a estimation solution. On basis of idea of Monte Carlo simulation, this paper analyzed the probability process of calculating factor weight, and provided the procedures of estimating factor weight by means of Monte Carlo simulation. Through discussion and example in this paper, feasibility and validity of this method were proved, which may make foreshadowing for follow-up research work.

Magnetic Properties of the Cylindrical Ising Nanowire: A Monte Carlo Simulation Study

SPIN ◽  
2017 ◽  
Vol 07 (04) ◽  
pp. 1750011 ◽  
Author(s):  
A. Jabar ◽  
R. Masrour ◽  
M. Hamedoun ◽  
A. Benyoussef
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Magnetic Properties ◽  
Crystal Field ◽  
Remanent Magnetization ◽  
Hysteresis Loops ◽  
Core Shell ◽  
Monte Carlo Simulation Study ◽  
The Core ◽  
Magnetic Nanowire

A cylindrical ferrimagnetic magnetic nanowire system of core and shell layers has been investigated using Monte Carlo simulation. Critical temperature is obtained for different values of exchange couplings at the core–shell interface, at shell–shell and core–core. The total magnetization has been the determinate for different values of crystal field. Hysteresis loop, coercive field and remanent magnetization of a core and shell layers are obtained using the Monte Carlo simulation. A number of characteristic behaviors are found, such as the occurrence of single and triple hysteresis loops for appropriate values of crystal field, temperatures values and exchange interaction values.

Reliability Analysis of Uncertain Input Variables for Cracked Structures

2011 ◽  
Vol 52-54 ◽  
pp. 1358-1363 ◽  
Author(s):  
M.R.M. Akramin ◽  
A. Zulkifli ◽  
M. Mazwan Mahat
Keyword(s):  
Monte Carlo Simulation ◽  
Finite Element ◽  
Monte Carlo ◽  
Failure Probability ◽  
Probabilistic Analysis ◽  
Research Work ◽  
Adaptive Mesh ◽  
Element Analysis ◽  
Monte Carlo Simulation Technique ◽  
Cracked Structures

Probabilistic analysis aims at providing an assessment of cracked structures and taking relevant uncertainties into account in a rational quantitative manner. The main focus of this research work is on uncertainties aspect which relates with the nature of crack in materials. By using cracked structures modelling, finite element calculation, generation of adaptive mesh, sampling of cracked structure including uncertainties factors and probabilistic analysis using Monte Carlo method, the rigidity of cracked structures is estimated. Assessment of the accuracy in probabilistic structures is essential when limited amount of data is available. The hybrid finite element and probabilistic analysis represents the failure probability of the structures. The probability of failure caused by uncertainties relates to loads and material properties of the structure are estimated using Monte Carlo simulation technique. Numerical examples are presented to show probabilistic analysis based on Monte Carlo simulation provides accurate estimates of failure probability. The comparison shows that the combination between finite element analysis and probabilistic analysis provides a simple and realistic of quantify the failure probability.

scholarly journals A Flexible Bridge Rating Method Based on Analytical Evidential Reasoning and Monte Carlo Simulation

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Saleh Abu Dabous ◽  
Ghadeer Al-Khayyat
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Paired Comparison ◽  
Research Work ◽  
Condition Assessment ◽  
Evidential Reasoning ◽  
Future Research ◽  
Assessment Practices ◽  
Condition Rating ◽  
Rating Method

Several bridge inspection standards and condition assessment practices have been developed around the globe. Some practices employ four linguistic expressions to rate bridge elements while other practices use five or six, or adopt numerical ratings such as 1 to 9. This research introduces a condition rating method that can operate under different condition assessment practices and account for uncertainties in condition assessment by means of the Evidential Reasoning (ER) theory. The method offers flexibility in terms of using default elements and their weights or selecting alternative set of elements and condition rating schemes. The implemented ER approach accounts for uncertainties in condition rating by treating the condition assessments as probabilistic grades rather than numerical values. The ER approach requires the assignment of initial basic beliefs or probabilities, and typically these initial beliefs are assigned by an expert. Alternatively, this research integrates the Monte Carlo Simulation (MCS) technique with the ER theory to quantitatively estimate the basic probabilities and to produce robust overall bridge condition ratings. The proposed method is novel to the literature and has the following features: (1) flexible and can be used with any number of bridge elements and any standard of condition grades; (2) intuitive and simple paired comparison technique is implemented to evaluate weights of the bridge elements; (3) the MCS technique is integrated with the ER approach to quantify uncertainties associated with the stochastic nature of the bridge deterioration process; (4) the method can function with limited data and can incorporate new evidence to update the condition rating; (5) the final rating consists of multiple condition grades and is produced as a distributed probabilistic assessment reflecting the condition of the bridge elements collectively. The proposed method is illustrated with a real case study, and potential future research work is identified.

MONTE CARLO SIMULATION OF SELF-ASSEMBLED AMPHIPHILIC DIBLOCK COPOLYMER IN SOLUTION

2003 ◽  
Vol 17 (01n02) ◽  
pp. 241-244 ◽  
Author(s):  
PINGCHUAN SUN ◽  
YUHUA YIN ◽  
BAOHUI LI ◽  
QINGHUA JIN ◽  
DATONG DING
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Diblock Copolymer ◽  
Self Assembly ◽  
Diblock Copolymers ◽  
The Self ◽  
Amphiphilic Diblock Copolymer ◽  
The Core ◽  
Spherical Micelles ◽  
The Given

In this paper, Monte Carlo method is applied to simulate the process of the self-assembly of amphiphilic diblock copolymer with a series of block lengths of the insoluble and soluble blocks. Under the given simulation conditions, the diblock copolymers form spherical micelles in solution. The dependence of the core radii of spherical micelles on both block lengths is obtained and compared with experimental results of Eisenberg and coworkers.

Monte-Carlo Simulation of Pressure Propagation in Elastic Arteries: Proposing a New Algorithm for the Clinical Assessment of Carotid-Femoral PWV

2008 ◽  
Author(s):  
A. Mookerjee ◽  
A. M. Al-Jumaily ◽  
A. Lowe
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Pressure Wave ◽  
Human Population ◽  
Pulse Wave ◽  
Input Parameter ◽  
Propagation Characteristics ◽  
Random Input ◽  
Wave Characteristics ◽  
Pressure Propagation

A Monte-Carlo simulation is developed to study the pressure propagation characteristics in a representative healthy randomly selected human population. Normal distribution sets are defined for different anatomic and physiological parameters based on data available in literature. Random input parameter sets are then generated from these distributions. A mathematical model is then used to simulate the pressure propagation characteristics in large elastic arteries defined by these input parameters. The pressure wave characteristics are then analysed to estimate carotid-femoral pulse wave velocity. Predictions closely match clinically observed trends.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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