Stochastic Model Calibration Based on Measurements from Different Experiments

2016 ◽  
Vol 825 ◽  
pp. 135-140
Author(s):  
Eliška Janouchová ◽  
Anna Kučerová ◽  
Jan Sýkora
Keyword(s):  
Stochastic Model ◽  
Model Calibration ◽  
Heterogeneous Material ◽  
Material Model ◽  
Identification Of Parameters ◽  
Model Response ◽  
Probabilistic Description ◽  
Different Types

The calibration of a heterogeneous material model can be formulated as a search for probabilistic description of its parameters providing the distribution of the model response corresponding to the distribution of the observed data. This contribution is focused on developing a method for identification of parameters along with their variations based on combining measurements from different types of destructive experiments.

scholarly journals BAYESIAN INFERENCE OF HETEROGENEOUS VISCOPLASTIC MATERIAL PARAMETERS

2018 ◽  
Vol 15 ◽  
pp. 41-45
Author(s):  
Eliška Janouchová ◽  
Anna Kučerová
Keyword(s):  
Experimental Data ◽  
Bayesian Inference ◽  
Material Model ◽  
Isotropic Hardening ◽  
Model Parameters ◽  
Viscoplastic Material ◽  
Loading Test ◽  
Model Response ◽  
Probabilistic Description ◽  
Probabilistic Setting

<p>Modelling of heterogeneous materials based on randomness of model input parameters involves parameter identification which is focused on solving a stochastic inversion problem. It can be formulated as a search for probabilistic description of model parameters providing the distribution of the model response corresponding to the distribution of the observed data</p><p>In this contribution, a numerical model of kinematic and isotropic hardening for viscoplastic material is calibrated on a basis of experimental data from a cyclic loading test at a high temperature. Five material model parameters are identified in probabilistic setting. The core of the identification method is the Bayesian inference of uncertain statistical moments of a prescribed joint lognormal distribution of the parameters. At first, synthetic experimental data are used to verify the identification procedure, then the real experimental data are processed to calibrate the material model of copper alloy.</p>

Pipe Ovalization Prediction for the Pipe-Laying Ocean System

2018 ◽  
Author(s):  
Matěj Bartecký ◽  
Radim Halama
Keyword(s):  
Plastic Deformation ◽  
Cross Section ◽  
Process Simulation ◽  
Model Calibration ◽  
Material Model ◽  
Pure Bending ◽  
Pipe Cross Section ◽  
Technical Practice ◽  
Chaboche Model ◽  
Insight Into

This contribution brings a new insight into pipe cross section ovalisation due to plastic deformation during pipe-lying process to the seabed. Firstly, the influence of material model calibration on ovalization prediction is presented on pure bending case including the Prager model, the Chaboche model and the modified Abdel-Karim–Ohno model. The mechanism responsible for cross section ovalisation was identified as the phenomenon of the accumulation of plastic deformation, the so-called ratcheting. The next part of this contribution presents main results of the pipe-laying process simulation. The pipe cross-section behavior during passing the considered pipe-laying system is studied in detail. A macro based solution makes possible to do a parametric study and to easily apply the offshore standard DNV-OS-F101 in technical practice.

scholarly journals Ancestral Graph with Bias in Gene Conversion

2013 ◽  
Vol 50 (1) ◽  
pp. 239-255 ◽  
Author(s):  
Shuhei Mano
Keyword(s):  
Stochastic Model ◽  
Gene Conversion ◽  
Importance Sampling ◽  
Diffusion Approximation ◽  
Multigene Family ◽  
Dual Process ◽  
Fixation Probability ◽  
Biased Gene Conversion ◽  
Different Types ◽  
Ancestral Graph

Gene conversion is a genetic mechanism by which one gene is ‘copied and pasted’ onto another gene, where the direction can be biased between the different types. In this paper, a stochastic model for biased gene conversion within a d-unlinked multigene family and its diffusion approximation are developed for a finite Moran population. A connection with a d-island model is made. A formula for the fixation probability in the absence of mutation is given. A two-timescale argument is applied in the case of the strong conversion limit. The dual process is generally shown to be a biased voter model, which generates an ancestral bias graph for a given sample. An importance sampling algorithm for computing the likelihood of the sample is deduced.

Plastic Response of Nested Systems under Static and Dynamic Loading Conditions Using FE and Experimental Techniques

2006 ◽  
Vol 3-4 ◽  
pp. 377-382
Author(s):  
Edmund Morris ◽  
Abdul Ghani Olabi ◽  
M.S.J. Hashmi
Keyword(s):  
Finite Element Method ◽  
Software Package ◽  
Material Model ◽  
Ring System ◽  
Plastic Response ◽  
Different Types ◽  
Out Of Plane ◽  
Dynamic Yield ◽  
Dynamic Loading Conditions ◽  
Static And Dynamic Loading

This paper presents the study of nested rings crushed laterally between rigid platens at 2 different velocities. In this investigation two different types of nested ring configurations are analysed: (A) In-Plane; where three rings of varying diameter are placed within each other and their axes are parallel. (B) Out of-Plane; where the rings have a 90 degree orientation. Material used was cold finished, drawn over mandrel (DIN 2393 ST 37-2) and is referred throughout the paper as mild steel. The Cowper-Symonds relation was used to predict the dynamic yield stress of the rings and this was included in the FE material model. The results obtained from experiments were compared to that of finite element method using the software package Ansys. Discussion is made on the post – collapse behaviour of these systems. It was found that the Out of-Plane ring system exhibited a more desirable force-deflection response due to its 90 degree orientation.

Fast Video Shot Boundary Detection Technique based on Stochastic Model

2016 ◽  
Vol 6 (2) ◽  
pp. 1-17
Author(s):  
Mohammad A. Al-Jarrah ◽  
Faruq A. Al-Omari
Keyword(s):  
Stochastic Model ◽  
Video Processing ◽  
High Performance ◽  
Boundary Detection ◽  
Video Stream ◽  
Detection Algorithm ◽  
Shot Boundary Detection ◽  
Different Types ◽  
Video Shot ◽  
Shot Boundary

A video is composed of set of shots, where shot is defined as a sequence of consecutive frames captured by one camera without interruption. In video shot transition could be a prompt (hard cut) or gradual (fade, dissolve, and wipe). Shot boundary detection is an essential component of video processing. These boundaries are utilized on many aspect of video processing such as video indexing, and video in demand. In this paper, the authors proposed a new shot boundary detection algorithm. The proposed algorithm detects all type of shot boundaries in a high accuracy. The algorithm is developed based on a global stochastic model for video stream. The proposed stochastic model utilizes the joined characteristic function and consequently the joined momentum to model the video stream. The proposed algorithm is implemented and tested against different types of categorized videos. The proposed algorithm detects cuts fades, dissolves, and wipes transitions. Experimental results show that the algorithm has high performance. The computed precision and recall rates validated its performance.

scholarly journals Ancestral Graph with Bias in Gene Conversion

2013 ◽  
Vol 50 (01) ◽  
pp. 239-255 ◽  
Author(s):  
Shuhei Mano
Keyword(s):  
Stochastic Model ◽  
Gene Conversion ◽  
Importance Sampling ◽  
Diffusion Approximation ◽  
Multigene Family ◽  
Dual Process ◽  
Fixation Probability ◽  
Biased Gene Conversion ◽  
Different Types ◽  
Ancestral Graph

Gene conversion is a genetic mechanism by which one gene is ‘copied and pasted’ onto another gene, where the direction can be biased between the different types. In this paper, a stochastic model for biased gene conversion within a d-unlinked multigene family and its diffusion approximation are developed for a finite Moran population. A connection with a d-island model is made. A formula for the fixation probability in the absence of mutation is given. A two-timescale argument is applied in the case of the strong conversion limit. The dual process is generally shown to be a biased voter model, which generates an ancestral bias graph for a given sample. An importance sampling algorithm for computing the likelihood of the sample is deduced.

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