Directional Probabilistic Design of Three-Coupler-Point Four-Bar Mechanisms

1992 ◽  
Author(s):  
George R. Schade ◽  
Douglas R. Korbel ◽  
Deena D. Shanmugam
Keyword(s):  
Monte Carlo ◽  
Probabilistic Model ◽  
Probabilistic Design ◽  
Monte Carlo Test ◽  
Point Position ◽  
Synthesis Technique ◽  
Position Synthesis

Abstract A standard four-bar coupler-point position synthesis technique is augmented with a probabilistic model of randomness coupler-point position caused by production variations in link dimension. The synthesis is optimized to reduce the variations in a chosen direction. The probabilistic optimum is verified by Monte-Carlo test.

Crossover scaling in semidilute polymer solutions: a Monte Carlo test

1991 ◽  
Vol 1 (1) ◽  
pp. 37-60 ◽  
Author(s):  
Wolfgang Paul ◽  
Kurt Binder ◽  
Dieter W. Heermann ◽  
Kurt Kremer
Keyword(s):  
Monte Carlo ◽  
Polymer Solutions ◽  
Monte Carlo Test

Probabilistic Creep Modeling of 304 Stainless Steel Using a Modified Wilshire Creep-Damage Model

2020 ◽  
Author(s):  
Md. Abir Hossain ◽  
Jaime A. Cano ◽  
Calvin M. Stewart
Keyword(s):  
Stainless Steel ◽  
Monte Carlo ◽  
Temperature Stress ◽  
Creep Deformation ◽  
Material Properties ◽  
Probabilistic Model ◽  
Damage Model ◽  
Creep Damage ◽  
304 Stainless Steel ◽  
Creep Damage Model

Abstract Pressure vessel components subject to high temperature and pressure are susceptible to life-limiting creep and/or creep-induced failure. Traditional continuum damage mechanics (CDM) based creep-damage model are used extensively for the prediction and design against creep in these components. Conventional creep experiments show considerable uncertainty in the creep response of materials where scatter can span decades of creep life. The objective of this paper is to introduce the probabilistic methods into a deterministic creep-damage model in order to predict experimental uncertainty. In this study, a modified Wilshire model capable of creep deformation, damage, and rupture prediction is selected. Creep deformation data for 304 stainless steel is collected from the literature consisting of quintuplicate (five) tests at 600°C with varying stress levels. It is hypothesized that the scatter in creep data is due to: test condition (temperature fluctuations and eccentric loading), initial damage (pre-existing surface and sub-surface defects), and metallurgical (local variation in microstructure) uncertainties. Probability distribution functions (pdfs) and Monte Carlo simulations are applied to introduce the uncertainties into the modified Wilshire equations. The domain of each source of uncertainty must be defined. A systematic calibration approach is followed where the material constant for each creep curve (in the quintuple) are obtained and statistical analysis is performed on the material properties to assess the random distribution associated with each uncertain material parameter. The probabilistic calibration begins with the introduction of test condition randomness (±2°C and ±3.2% MPa of nominal temperature/stress) in accordance with the ASTM standards. Cross calibration of temperature-stress variability proceeds the approximation of initial damage uncertainty which captures the remaining scatter in the data. Deterministic calibration unveils the range of variabilities associated with the material properties. The best-fitted pdfs are assigned to each uncertain parameter and subsequently, the deterministic model is converted into a probabilistic model where reliability is a tunable factor. A large number of Monte Carlo simulation are conducted to generate probabilistic creep deformation, minimum-creep-strain-rate (MCSR), and stress-rupture (SR) predictions. It is demonstrated that the probabilistic model produces quantitatively and qualitatively good fits when compared with experimental data. Future work will be directed towards the inclusion of service condition related uncertainty (power plant, turbine blade, Gen IV nuclear reactor application) into the probabilistic framework where the uncertainties are more robust.

Template-Based Monte-Carlo Test Generation for Simulink Models

2019 ◽  
pp. 63-78 ◽  
Author(s):  
Takashi Tomita ◽  
Daisuke Ishii ◽  
Toru Murakami ◽  
Shigeki Takeuchi ◽  
Toshiaki Aoki
Keyword(s):  
Monte Carlo ◽  
Test Generation ◽  
Monte Carlo Test

scholarly journals THE EFFECTIVE STRING OF 3D Z2 GAUGE THEORY AS A c = 1 COMPACTIFIED CFT

1993 ◽  
Vol 08 (16) ◽  
pp. 2839-2858 ◽  
Author(s):  
M. CASELLE ◽  
F. GLIOZZI ◽  
S. VINTI ◽  
R. FIORE
Keyword(s):  
Field Theory ◽  
Monte Carlo ◽  
Conformal Field Theory ◽  
Central Charge ◽  
Three Dimensional ◽  
String Tension ◽  
Gauge Model ◽  
Expectation Values ◽  
Monte Carlo Test ◽  
Conformal Field

We report on a high precision Monte Carlo test of the three-dimensional Ising gauge model at finite temperature. The string tension σ is extracted from the expectation values of correlations of Polyakov lines. Agreement with the string tension extracted from Wilson loops is found only if the quantum fluctuations of the flux tube are properly taken into account. The central charge of the underlying conformal field theory is c = 1.

Monte Carlo Test of Theories for the Planar Model, theFModel, and Related Systems

1978 ◽  
Vol 41 (20) ◽  
pp. 1399-1402 ◽  
Author(s):  
William J. Shugard ◽  
John D. Weeks ◽  
George H. Gilmer
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Test ◽  
Planar Model

Synthesis of Four-Link Space Mechanisms Via Extension of Point-Position-Reduction Technique

1971 ◽  
Vol 93 (1) ◽  
pp. 85-89 ◽  
Author(s):  
A. H. Soni ◽  
Matthew Huang
Keyword(s):  
Reduction Technique ◽  
Planar Mechanisms ◽  
Point Position ◽  
Position Synthesis ◽  
Space Mechanisms

The principle of point-position-reduction technique, which is used for position-synthesis of planar mechanisms, is extended to synthesize spherical four-link and spatial four-link RCCC mechanisms for four precision positions.

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