Evaluation of Parametric Models Dedicated to a Magnetorheological Actuator Including Uncertainty and Sensitivity Analyses

2019 ◽  
Vol 5 (4) ◽  
Author(s):  
Philippe C. Fernandes Teixeira ◽  
Núbia dos Santos Saad ◽  
Fabian Andres Lara-Molina ◽  
Aldemir Ap Cavalini ◽  
Valder Steffen
Keyword(s):  
Experimental Data ◽  
Computational Cost ◽  
Parametric Models ◽  
Sensitivity Analyses ◽  
Engineering Systems ◽  
Hysteretic Model ◽  
Mr Dampers ◽  
Interval Approach ◽  
The Difference ◽  
Parametric And Nonparametric Approaches

Abstract Semi-active actuators have been used in engineering systems for vibration control purposes. For instance, magnetorheological (MR) dampers are applied in support of vehicle seats and smart suspensions of bridges and buildings. Parametric and nonparametric approaches were developed to model MR actuators, in which the former presents well-established and representative models. In this context, this work aims at comparing the so-called Bingham, modified Bouc-Wen (BW), and hysteretic models dedicated to MR actuators. Typical inverse problems were solved to minimize the difference between the forces determined by using these models and experimental data. The obtained results demonstrated that the hysteretic model is better adapted to represent the considered MR actuator, presenting lower computational cost and easy implementation. Additionally, uncertainty and sensitivity analyses based on the interval approach were applied on the updated MR models aiming to determine the working envelopes associated with the most important parameters of the models.

Data-driven seismic response prediction of structural components

2021 ◽  
pp. 875529302110533
Author(s):  
Huan Luo ◽  
Stephanie German Paal
Keyword(s):  
Experimental Data ◽  
Seismic Response ◽  
Computational Cost ◽  
Data Driven ◽  
Computational Time ◽  
Lateral Stiffness ◽  
Hysteretic Model ◽  
Structural Components ◽  
Rc Columns ◽  
Detailed Model

Lateral stiffness of structural components, such as reinforced concrete (RC) columns, plays an important role in resisting the lateral earthquake loads. The lateral stiffness relates the lateral force to the lateral deformation, having a critical effect on the accuracy of the lateral seismic response predictions. The classical methods (e.g. fiber beam–column model) to estimate the lateral stiffness require calculations from section, element, and structural levels, which is time-consuming. Moreover, the shear deformation and bond-slip effect may also need to be included to more accurately calculate the lateral stiffness, which further increases the modeling difficulties and the computational cost. To reduce the computational time and enhance the accuracy of the predictions, this article proposes a novel data-driven method to predict the laterally seismic response based on the estimated lateral stiffness. The proposed method integrates the machine learning (ML) approach with the hysteretic model, where ML is used to compute the parameters that govern the nonlinear properties of the lateral response of target structural components directly from a training set composed of experimental data (i.e. data-driven procedure) and the hysteretic model is used to directly output the lateral stiffness based on the computed parameters and then to perform the seismic analysis. We apply the proposed method to predict the lateral seismic response of various types of RC columns subjected to cyclic loading and ground motions. We present the detailed model formulation for the application, including the developments of a modified hysteretic model, a hybrid optimization algorithm, and two data-driven seismic response solvers. The results predicted by the proposed method are compared with those obtained by classical methods with the experimental data serving as the ground truth, showing that the proposed method significantly outperforms the classical methods in both generalized prediction capabilities and computational efficiency.

CFD Analysis of a Captive Bullet Entry in Calm Water With and Without Turbulence

2019 ◽  
Author(s):  
René Bettencourt Rauffus ◽  
António Maximiano ◽  
Luís Eça ◽  
Guilherme Vaz
Keyword(s):  
Experimental Data ◽  
Turbulent Flow ◽  
Turbulence Model ◽  
Computational Cost ◽  
Longitudinal Force ◽  
The Body ◽  
Test Case ◽  
Vertical Force ◽  
Pitch Moment ◽  
The Difference

Abstract Simulations are carried out for a simplified lifeboat drop test case, which consists of a captive axisymmetric generic lifeboat shape (bullet), that penetrates the water surface at a constant velocity and angle of attack. The quantities of interest are the body fixed longitudinal force FX, vertical force FZ, and pitch moment MYY.This case was previously used in a verification and validation exercise [1]. Here, a step forward in complexity is taken, as the previous numerical model is now supplemented with the eddy-viscosity based turbulence model k–ω SST. Both approaches are then used to simulate two different cases: Case 1 with minimal wake effects; and Case 3 with flow separation and significant wake. The results are compared with the experimental data. The numerical uncertainty is estimated for both models. It is seen that for Case 1 the difference between both models is mostly within the comparison uncertainty, except for the longitudinal force FX, where the turbulent flow predicts a larger force, improving the comparison with the experiments. The loads predicted with turbulent flow stayed mostly within 6 % of the laminar flow. For Case 3 small differences between both models are found during/after the wake collapse stage. However, this difference is often within the comparison uncertainty. A reasonable agreement is found with the experimental data, except for FZ after the bow wake collapse. The turbulent flow improves slightly on the laminar approach regarding the agreement with the experiments, however it can be argued if this difference justifies the increased computational cost of the turbulence model.

scholarly journals A Stochastic Model for Block Segmentation of Images Based on the Quadtree and the Bayes Code for It

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 991
Author(s):  
Yuta Nakahara ◽  
Toshiyasu Matsushima
Keyword(s):  
Computational Cost ◽  
Block Size ◽  
Input Image ◽  
Generative Model ◽  
Image Size ◽  
Variable Block ◽  
General Data ◽  
The Difference ◽  
Segmentation Of Images ◽  
Target Data

In information theory, lossless compression of general data is based on an explicit assumption of a stochastic generative model on target data. However, in lossless image compression, researchers have mainly focused on the coding procedure that outputs the coded sequence from the input image, and the assumption of the stochastic generative model is implicit. In these studies, there is a difficulty in discussing the difference between the expected code length and the entropy of the stochastic generative model. We solve this difficulty for a class of images, in which they have non-stationarity among segments. In this paper, we propose a novel stochastic generative model of images by redefining the implicit stochastic generative model in a previous coding procedure. Our model is based on the quadtree so that it effectively represents the variable block size segmentation of images. Then, we construct the Bayes code optimal for the proposed stochastic generative model. It requires the summation of all possible quadtrees weighted by their posterior. In general, its computational cost increases exponentially for the image size. However, we introduce an efficient algorithm to calculate it in the polynomial order of the image size without loss of optimality. As a result, the derived algorithm has a better average coding rate than that of JBIG.

Reliability and reliability-based sensitivity analysis of self-centering buckling restrained braces using meta-models

2021 ◽  
pp. 1045389X2110263
Author(s):  
Seyede Vahide Hashemi ◽  
Mahmoud Miri ◽  
Mohsen Rashki ◽  
Sadegh Etedali
Keyword(s):  
Failure Probability ◽  
Limit State ◽  
Computational Cost ◽  
Sensitivity Analyses ◽  
State Function ◽  
Reliability Indices ◽  
Buckling Restrained Brace ◽  
Polynomial Response Surface ◽  
Nonlinear Dynamic Analyses ◽  
High Computational Cost

This paper aims to carry out sensitivity analyses to study how the effect of each design variable on the performance of self-centering buckling restrained brace (SC-BRB) and the corresponding buckling restrained brace (BRB) without shape memory alloy (SMA) rods. Furthermore, the reliability analyses of BRB and SC-BRB are performed in this study. Considering the high computational cost of the simulation methods, three Meta-models including the Kriging, radial basis function (RBF), and polynomial response surface (PRSM) are utilized to construct the surrogate models. For this aim, the nonlinear dynamic analyses are conducted on both BRB and SC-BRB by using OpenSees software. The results showed that the SMA area, SMA length ratio, and BRB core area have the most effect on the failure probability of SC-BRB. It is concluded that Kriging-based Monte Carlo Simulation (MCS) gives the best performance to estimate the limit state function (LSF) of BRB and SC-BRB in the reliability analysis procedures. Considering the effects of changing the maximum cyclic loading on the failure probability computation and comparison of the failure probability for different LSFs, it is also found that the reliability indices of SC-BRB were always higher than the corresponding reliability indices determined for BRB which confirms the performance superiority of SC-BRB than BRB.

scholarly journals Epistemic values of quantity and variety of evidence in biological mechanism research

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Yin Chung Au
Keyword(s):  
Experimental Data ◽  
Causal Inference ◽  
Case Studies ◽  
Biological Mechanism ◽  
Data Generation ◽  
Extended Version ◽  
Epistemic Values ◽  
Difference Making ◽  
Mechanism Research ◽  
The Difference

AbstractThis paper proposes an extended version of the interventionist account for causal inference in the practical context of biological mechanism research. This paper studies the details of biological mechanism researchers’ practices of assessing the evidential legitimacy of experimental data, arguing why quantity and variety are two important criteria for this assessment. Because of the nature of biological mechanism research, the epistemic values of these two criteria result from the independence both between the causation of data generation and the causation in question and between different interventions, not techniques. The former independence ensures that the interventions in the causation in question are not affected by the causation that is responsible for data generation. The latter independence ensures the reliability of the final mechanisms not only in the empirical but also the formal aspects. This paper first explores how the researchers use quantity to check the effectiveness of interventions, where they at the same time determine the validity of the difference-making revealed by the results of interventions. Then, this paper draws a distinction between experimental interventions and experimental techniques, so that the reliability of mechanisms, as supported by the variety of evidence, can be safely ensured in the probabilistic sense. The latter process is where the researchers establish evidence of the mechanisms connecting the events of interest. By using case studies, this paper proposes to use ‘intervention’ as the fruitful connecting point of literature between evidence and mechanisms.

scholarly journals Couplings for determinantal point processes and their reduced Palm distributions with a view to quantifying repulsiveness

2021 ◽  
Vol 58 (2) ◽  
pp. 469-483
Author(s):  
Jesper Møller ◽  
Eliza O’Reilly
Keyword(s):  
Finite Number ◽  
Point Process ◽  
Point Processes ◽  
Parametric Models ◽  
Determinantal Point Processes ◽  
Determinantal Point Process ◽  
The Difference ◽  
Weaker Conditions ◽  
Palm Distributions

AbstractFor a determinantal point process (DPP) X with a kernel K whose spectrum is strictly less than one, André Goldman has established a coupling to its reduced Palm process $X^u$ at a point u with $K(u,u)>0$ so that, almost surely, $X^u$ is obtained by removing a finite number of points from X. We sharpen this result, assuming weaker conditions and establishing that $X^u$ can be obtained by removing at most one point from X, where we specify the distribution of the difference $\xi_u: = X\setminus X^u$. This is used to discuss the degree of repulsiveness in DPPs in terms of $\xi_u$, including Ginibre point processes and other specific parametric models for DPPs.

Dose-window dependence on Si crystal orientation in separation by implanted oxygen substrate formation

2004 ◽  
Vol 19 (12) ◽  
pp. 3607-3613 ◽  
Author(s):  
H. Iikawa ◽  
M. Nakao ◽  
K. Izumi
Keyword(s):  
Experimental Data ◽  
Numerical Analysis ◽  
Crystal Orientation ◽  
Oxygen Ion ◽  
The Difference ◽  
First Time ◽  
Good Agreement

Separation by implemented oxygen (SIMOX)(111) substrates have been formed by oxygen-ion (16O+) implantation into Si(111), showing that a so-called “dose-window” at 16O+-implantation into Si differs from Si(100) to Si(111). In SIMOX(100), an oxygen dose of 4 × 1017/cm2 into Si(100) is widely recognized as the dose-window when the acceleration energy is 180 keV. For the first time, our work shows that an oxygen dose of 5 × 1017/cm2 into Si(111) is the dose-window for the formation of SIMOX(111) substrates when the acceleration energy is 180 keV. The difference between dose-windows is caused by anisotropy of the crystal orientation during growth of the faceted buried SiO2. We also numerically analyzed the data at different oxidation velocities for each facet of the polyhedral SiO2 islands. Numerical analysis results show good agreement with the experimental data.

scholarly journals A study of computational methods for wake structure and base pressure prediction of a generic SUV model with fixed and rotating wheels

2017 ◽  
Vol 231 (9) ◽  
pp. 1222-1238 ◽  
Author(s):  
David Forbes ◽  
Gary Page ◽  
Martin Passmore ◽  
Adrian Gaylard
Keyword(s):  
Experimental Data ◽  
Computational Methods ◽  
Large Scale ◽  
Ground Plane ◽  
Computational Cost ◽  
Rear Wheel ◽  
Base Pressure ◽  
Detached Eddy Simulation ◽  
Wake Structure ◽  
Wake Interactions

This study is an evaluation of the computational methods in reproducing experimental data for a generic sports utility vehicle (SUV) geometry and an assessment on the influence of fixed and rotating wheels for this geometry. Initially, comparisons are made in the wake structure and base pressures between several CFD codes and experimental data. It was shown that steady-state RANS methods are unsuitable for this geometry due to a large scale unsteadiness in the wake caused by separation at the sharp trailing edge and rear wheel wake interactions. unsteady RANS (URANS) offered no improvements in wake prediction despite a significant increase in computational cost. The detached-eddy simulation (DES) and Lattice–Boltzmann methods showed the best agreement with the experimental results in both the wake structure and base pressure, with LBM running in approximately a fifth of the time for DES. The study then continues by analysing the influence of rotating wheels and a moving ground plane over a fixed wheel and ground plane arrangement. The introduction of wheel rotation and a moving ground was shown to increase the base pressure and reduce the drag acting on the vehicle when compared to the fixed case. However, when compared to the experimental standoff case, variations in drag and lift coefficients were minimal but misleading, as significant variations to the surface pressures were present.

The Tensile Property of the SPF/Cotton Blended Yarn

2011 ◽  
Vol 321 ◽  
pp. 192-195
Author(s):  
Qing Bin Yang ◽  
Xiao Yang
Keyword(s):  
Experimental Data ◽  
Simple Model ◽  
Tensile Property ◽  
Cotton Fibers ◽  
Blended Yarn ◽  
The Difference ◽  
The Relationship

In order to analysis the relationship between the strength and elongation and the blended ratio of SPF/Cotton blended yarn, the strength and elongation of SPF /cotton blended yarn with different blended ratio were measured and compared with the simple model. The results indicated that For the SPF/cotton blended yarn, the difference between the experimental data and the model value is remarkable because of the high cohesion of the cotton fibers.

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