scholarly journals Discrete-Direct Model Calibration and Propagation Approach Addressing Sparse Replicate Tests and Material, Geometric, and Measurement Uncertainties

2018 ◽  
Author(s):  
Vicente Romero
Keyword(s):  
Model Calibration ◽  
Direct Model ◽  
Measurement Uncertainties

Discrete-Direct Model Calibration and Uncertainty Propagation Method Confirmed on Multi-Parameter Plasticity Model Calibrated to Sparse Random Field Data

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Vicente J. Romero ◽  
Justin G. Winokur ◽  
George E. Orient ◽  
James F. Dempsey
Keyword(s):  
Strain Rate ◽  
Model Calibration ◽  
Structural Model ◽  
Uncertainty Propagation ◽  
Material Strength ◽  
Rate Dependent ◽  
Direct Model ◽  
Von Mises ◽  
Von Mises Stresses ◽  
Force Displacement

Abstract A discrete direct (DD) model calibration and uncertainty propagation approach is explained and demonstrated on a 4-parameter Johnson-Cook (J-C) strain-rate dependent material strength model for an aluminum alloy. The methodology's performance is characterized in many trials involving four random realizations of strain-rate dependent material-test data curves per trial, drawn from a large synthetic population. The J-C model is calibrated to particular combinations of the data curves to obtain calibration parameter sets which are then propagated to “Can Crush” structural model predictions to produce samples of predicted response variability. These are processed with appropriate sparse-sample uncertainty quantification (UQ) methods to estimate various statistics of response with an appropriate level of conservatism. This is tested on 16 output quantities (von Mises stresses and equivalent plastic strains) and it is shown that important statistics of the true variabilities of the 16 quantities are bounded with a high success rate that is reasonably predictable and controllable. The DD approach has several advantages over other calibration-UQ approaches like Bayesian inference for capturing and utilizing the information obtained from typically small numbers of replicate experiments in model calibration situations—especially when sparse replicate functional data are involved like force–displacement curves from material tests. The DD methodology is straightforward and efficient for calibration and propagation problems involving aleatory and epistemic uncertainties in calibration experiments, models, and procedures.

scholarly journals Dealing with Measurement Uncertainties as Nuisance Parameters in Bayesian Model Calibration

2020 ◽  
Vol 8 (4) ◽  
pp. 1287-1309 ◽  
Author(s):  
Kellin Rumsey ◽  
Gabriel Huerta ◽  
Justin Brown ◽  
Lauren Hund
Keyword(s):  
Bayesian Model ◽  
Model Calibration ◽  
Nuisance Parameters ◽  
Measurement Uncertainties

Relationships Between Bidirectional Work-Family Interactions and Psychological Well-Being

2014 ◽  
Vol 13 (2) ◽  
pp. 87-96 ◽  
Author(s):  
Xi-Chao Zhang ◽  
Oi Ling Siu ◽  
Jing Hu ◽  
Weiwei Zhang
Keyword(s):  
Family Conflict ◽  
Structural Equation ◽  
Time Lag ◽  
Well Being ◽  
Equation Modeling ◽  
Family Interactions ◽  
Work Family Conflict ◽  
Psychological Well Being ◽  
Direct Model ◽  
Work Family

This study investigated the direct, reversed, and reciprocal relationships between bidirectional work-family conflict/work-family facilitation and psychological well-being (PWB). We administered a three-wave questionnaire survey to 260 married Chinese employees using a time lag of one month. Cross-lagged structural equation modeling analysis was conducted and demonstrated that the direct model was better than the reversed causal or the reciprocal model. Specifically, work-to-family conflict at Time 1 negatively predicted PWB at Time 2, and work-to-family conflict at Time 2 negatively predicted PWB at Time 3; further, work-to-family facilitation at Time 1 positively predicted PWB at Time 2. In addition, family-to-work facilitation at Time 1 positively predicted PWB at Time 2, and family-to-work conflict at Time 2 negatively predicted PWB at Time 3.

Adaptive Control Scheme for Coupled Tank Process

2018 ◽  
pp. 89-95
Author(s):  
Vinodhini M.
Keyword(s):  
Adaptive Control ◽  
Nonlinear Behaviour ◽  
Simulation Studies ◽  
Input Output ◽  
Control Scheme ◽  
Direct Model ◽  
Multivariable Process ◽  
Model Reference Adaptive ◽  
Siso System ◽  
Adaptive Control Scheme

The objective of this paper is to develop a Direct Model Reference Adaptive Control (DMRAC) algorithm for a MIMO process by extending the MIT rule adopted for a SISO system. The controller thus developed is implemented on Laboratory interacting coupled tank process through simulation. This can be regarded as the relevant process control in petrol and chemical industries. These industries involve controlling the liquid level and the flow rate in the presence of nonlinearity and disturbance which justifies the use of adaptive techniques such as DMRAC control scheme. For this purpose, mathematical models are obtained for each of the input-output combinations using white box approach and the respective controllers are developed. A detailed analysis on the performance of the chosen process with these controllers is carried out. Simulation studies reveal the effectiveness of proposed controller for multivariable process that exhibits nonlinear behaviour.

Application of the Strip Yield Model to Crack Growth Predictions for Structural Steel

2010 ◽  
Vol 57 (1) ◽  
pp. 1-20
Author(s):  
Małgorzata Skorupa ◽  
Tomasz Machniewicz
Keyword(s):  
Structural Steel ◽  
Crack Growth ◽  
Model Calibration ◽  
Load History ◽  
Yield Model ◽  
Variable Amplitude Loading ◽  
Variable Amplitude ◽  
Constraint Factors ◽  
Strip Yield Model ◽  
Closure Mechanism

Application of the Strip Yield Model to Crack Growth Predictions for Structural SteelA strip yield model implementation by the present authors is applied to predict fatigue crack growth observed in structural steel specimens under various constant and variable amplitude loading conditions. Attention is paid to the model calibration using the constraint factors in view of the dependence of both the crack closure mechanism and the material stress-strain response on the load history. Prediction capabilities of the model are considered in the context of the incompatibility between the crack growth resistance for constant and variable amplitude loading.

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