Development of an Optimized Loading Path for Material Parameters Identification

2013 ◽  
Vol 554-557 ◽  
pp. 2200-2211 ◽  
Author(s):  
Elisabete Ferreira ◽  
Joaquim Pinho-da-Cruz ◽  
António Andrade-Campos
Keyword(s):  
Thin Sheet ◽  
Testing Machine ◽  
Optimization Method ◽  
Mechanical Tests ◽  
Loading Path ◽  
Objective Criterion ◽  
Element Analysis ◽  
Material Parameters ◽  
Value Decomposition ◽  
Material Parameters Identification

Nowadays, the characterization of material is becoming increasingly important due to ma\-nu\-fac\-tu\-ring of new materials and development of computational analysis software intending to reproduce the real behaviour which depends on the quality of the models implemented and their material parameters. However, a large number of technological mechanical tests are carried out to characterize the mechanical properties of materials and similar materials may also have properties and parameters similar. Therefore, many researchers are often confronted with the dilemma of what should be the best set of numerical solution for all different results. Currently, such choice is made based on the empirical experience of each researcher, not representing a severe and objective criterion. Hence, via optimization it is possible to find and classify the most unique and distinguishable solution for pa\-ra\-me\-ters identification. The aim of this work is to propose a methodology that numerically designs the loading path of multiaxial testing machine to characterize metallic thin sheet behavior. This loading path has to be the most informative, exhibiting normal and shear strains as distinctly as possible. Thus, applying Finite Element Analysis (FEA) and Singular Value Decomposition (SVD), the loading path can be evaluated in terms of distinguishability and uniqueness. Consequently, the loading path that leads to the most distinguish and unique set of material parameters can be found using a standard optimization method and the approach proposed. This methodology has been validated to characterize the elastic moduli for an anisotropic material and extrapolated for an hyperelastic material.

An Optimized Loading Path for Material Parameters Identification in Elastoplasticity

2014 ◽  
Vol 611-612 ◽  
pp. 1734-1741
Author(s):  
Elisabete Ferreira ◽  
Joaquim Pinho-da-Cruz ◽  
António Andrade-Campos
Keyword(s):  
Mechanical Test ◽  
Mechanical Tests ◽  
Loading Path ◽  
Element Analysis ◽  
Material Parameters ◽  
Real Behavior ◽  
Value Decomposition ◽  
Constitutive Parameters ◽  
Material Parameters Identification

Presently, the need to characterize the constitutive parameters of materials has increased due to the manufacture of new materials and development of computational analysis software intending to reproduce the real behavior which depends on the quality of the models implemented and their material parameters. However, in order to identify all constitutive parameters of materials a large number of mechanical tests is required. Thus, only one mechanical test that could allow to characterize all the mechanical properties could be desired. Hence, the aim of this work is to propose a methodology that find the most informative loading path in the sense of display normal and shear strains as clear aspossible to warrantee that the solution is the most unique and distinguishable for the parameter identification process. To achieve this objective the proposed methodology uses Finite Element Analysis (FEA) and Singular Value Decomposition (SVD) coupled together with optimization strategies. Thismethodology is presented for elastoplasticity behavior.

Optimization-Based Inverse Finite Element Analysis for Material Parameter Identification of a Biphasic Viscoelastic Hydrogel

2008 ◽  
Author(s):  
Kaifeng Liu ◽  
Brian Thomas ◽  
J. Craig Fryman ◽  
Jeff Bischoff ◽  
Timothy Ovaert ◽  
...  
Keyword(s):  
Finite Element ◽  
Solid Phase ◽  
Polymer Network ◽  
Viscoelastic Model ◽  
Optimization Method ◽  
Creep Testing ◽  
Material Parameter Identification ◽  
Element Analysis ◽  
Biphasic Model ◽  
Material Parameters

Hydrogels are a cross-linked network of polymer swollen with a liquid, and are promising replacements for diseased or damaged load bearing tissues such as articular cartilage [1]. Recently, a linear biphasic model, developed originally for cartilage [2], has been applied to characterize the mechanical behavior of hydrogels [3, 4]. However, the linear elastic assumption for the solid phase ignores the intrinsic viscoelasticity of the polymer network [3, 4]. Some attempts have been made in the literature to simulate hydrogels with a biphasic viscoelastic model using a self-developed finite element code [5]. This study is aimed at simulating hydrogels with a biphasic viscoelastic model and investigating an inverse finite element (FE) technique to identify material parameters of hydrogels via combined creep testing and FE modeling. Creep testing of hydrogels is simulated in the commercial software ABAQUS, which makes this approach easy to adapt to other test geometries. Material parameters are identified by fitting the FE results to the experimental results using an optimization method.

Material Parameter Identification of Cazacu’s Model for Ti6Al4V Using the Simulated Annealing Algorithm

2010 ◽  
Vol 636-637 ◽  
pp. 1125-1130 ◽  
Author(s):  
Gaëtan Gilles ◽  
Anne Marie Habraken ◽  
Laurent Duchêne
Keyword(s):  
Simulated Annealing ◽  
Parameter Identification ◽  
Simulated Annealing Algorithm ◽  
Optimization Method ◽  
Mechanical Tests ◽  
Global Optimum ◽  
Material Parameter Identification ◽  
Local Optima ◽  
Material Parameters ◽  
The One

Phenomenological yield criteria are generally described by many material parameters. A technique to identify these parameters is required to find the best fit to the results of the mechanical tests. The parameter identification by the classical simulated annealing technique is presented in this paper. This algorithm, based on works by Metropolis et al, is a global optimization method that distinguishes between different local optima to reach the global optimum. The anisotropic model used in this study is the one proposed by Cazacu et al. To prove the efficiency of the proposed algorithm, the material parameters of Ti6Al4V titanium alloy are identified and compared with those obtained using different identification procedures and the same experimental data.

scholarly journals Material Identification Using a Bi-Axial Test Machine

2006 ◽  
Vol 3-4 ◽  
pp. 91-98 ◽  
Author(s):  
Paulo Flores ◽  
Pierre Moureaux ◽  
Anne Marie Habraken
Keyword(s):  
Plane Strain ◽  
Simple Shear ◽  
Rolling Direction ◽  
Mechanical Tests ◽  
Test Machine ◽  
Shear Tests ◽  
Sheet Rolling ◽  
Material Parameters ◽  
Optical Strain ◽  
Material Parameters Identification

This paper shows the identification of material parameters for a DC06 IF steel sheet of 0.8 mm by mechanical tests. The experimental equipment used consists of a tensile test machine, a bi-axial test machine able to perform plane-strain and simple shear tests separately or simultaneously and an optical strain gauge. Tensile, plane-strain and simple shear tests were performed at 0°, 45° and 90° from the sheet rolling direction in order to identify Hill 1948 and Hosford 1979 yield criteria. Two identification methods are used: one based on strain measurements (anistropy coefficients) and the other one based on stress measurements (plastic contours). The results confirm that mechanical tests applying other stress-states than tensile are required to obtain accurate material parameters identification.

Data-Driven Characterization of Composites Based on Virtual Deterministic and Noisy Multiaxial Data

2008 ◽  
Author(s):  
J. G. Michopoulos ◽  
T. Furukawa ◽  
S. G. Lambrakos
Keyword(s):  
Linear Equations ◽  
Testing Machine ◽  
Noisy Data ◽  
Loading Path ◽  
External Work ◽  
Design Variables ◽  
Characterization Of Materials ◽  
Value Decomposition ◽  
Loading Path Design

This paper presents an inverse methodology capable of identifying the elastic moduli of laminated composites from both deterministic and noisy data originating from virtual multiaxial tests. Unlike the conventional uniaxial characterization of materials, the methodology exploits the energy balance between the increment of external work and the corresponding increment of strain energy. It then formulates an overdetermined system of linear equations that are solved using Singular Value Decomposition (SVD) to compute the associated pseudoinverse array. The proposed methodology further controls the multiaxial testing machine by utilizing performance measures of the SVD process to construct objective functions that are maximized in order to compute loading path design variables. Numerical examples investigate the significance, robustness and efficiency of the proposed methodology. Deterministic and noisy data are synthesized in order to demonstrate the applicability of the technique with respect to realistic characterization problems. The effect of noisy data in the characterization process has been examined in a manner that leads to a demonstration of the practicality of the approach.

Effect of Loading Path and Specimen Shape on Inverse Identification of Elastic Properties of Composites

2006 ◽  
Author(s):  
J. G. Michopoulos ◽  
T. Furukawa
Keyword(s):  
Parameter Identification ◽  
Elastic Moduli ◽  
A Priori ◽  
Identification Problem ◽  
Loading Path ◽  
Material System ◽  
Inverse Identification ◽  
Element Analysis ◽  
Identification Process ◽  
Value Decomposition

This paper presents a methodology for using sensor-generated data from multi-degree-of-freedom mechatronic loading systems to identify the elastic moduli of a composite laminate material system. This is done not to demonstrate the method itself but rather to study how various features of the experimental and analytical procedure can affect the identification process. The analytical formulation of the identification problem is described first given the geometry of a test specimen and a loading path. The concept of singular value decomposition (associated with pseudo inversion factorization) is introduced for the purpose of parameter identification as it applies to the elastic moduli. Also, the concepts of distinguishability and uniqueness are introduced to evaluate the quality of parameter identification. The analysis is performed on a continuum model basis in order to evaluate if the proposed technique can work for specimens of arbitrary shape. Elastic coefficients were identified using pseudo-experimental (numerically synthesized) data created by finite element analysis (FEA) and the effect of the introduced distinguishability and uniqueness on the identification was investigated through several numerical examples. The effects of the form of the chosen multidimensional loading path(s) and the shape of the specimen on various features of the inverse identification process related to the elastic moduli parameter estimation are also determined. The results of the numerical studies demonstrate the efficacy of the proposed methodology and suggests subsequent avenues for optimizing the specification of the loading path both a priori and in real-time.

Improved nonlinear stress-strain relation for carbon-epoxy composites and identification of material parameters

2011 ◽  
Vol 45 (9) ◽  
pp. 1045-1057 ◽  
Author(s):  
Tomáš Kroupa ◽  
Vladislav Laš ◽  
Robert Zemčík
Keyword(s):  
Mathematical Optimization ◽  
Optimization Method ◽  
Tensile Tests ◽  
Epoxy Composites ◽  
Stress Strain ◽  
Element Analysis ◽  
Material Parameters ◽  
Stress Strain Relation ◽  
Nonlinear Stress ◽  
Comparison Of The Results

This study focuses on the comparison of selected nonlinear stress—strain relations for unidirectional continuous fiber carbon—epoxy composites and the identification of their parameters under tensile loading. Simple tensile tests of thin strips with various fiber orientations are performed. One linear relation, two types of nonlinear stress—strain relations taken from literature, and one improved relation are analyzed and used within the identification process. All the relationships are deduced from polynomial expansion of complementary energy density. The process, using a combination of the mathematical optimization method and finite element analysis, is described with the necessary details. Failure analysis for the determination of the first failure using Puck’s action plane concept is also performed. The tensile and shear strengths are investigated. The comparison of the results obtained from the identified material parameters with the results obtained using the material parameters given by manufacturer is included.

Lifetime Prediction of Tires with Regard to Oxidative Aging5

2008 ◽  
Vol 36 (1) ◽  
pp. 63-79 ◽  
Author(s):  
L. Nasdala ◽  
Y. Wei ◽  
H. Rothert ◽  
M. Kaliske
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Temperature Distribution ◽  
Superposition Principle ◽  
Accelerated Aging ◽  
Material Model ◽  
Aging Behavior ◽  
Element Analysis ◽  
Material Parameters ◽  
Reaction Processes

Abstract It is a challenging task in the design of automobile tires to predict lifetime and performance on the basis of numerical simulations. Several factors have to be taken into account to correctly estimate the aging behavior. This paper focuses on oxygen reaction processes which, apart from mechanical and thermal aspects, effect the tire durability. The material parameters needed to describe the temperature-dependent oxygen diffusion and reaction processes are derived by means of the time–temperature–superposition principle from modulus profiling tests. These experiments are designed to examine the diffusion-limited oxidation (DLO) effect which occurs when accelerated aging tests are performed. For the cord-reinforced rubber composites, homogenization techniques are adopted to obtain effective material parameters (diffusivities and reaction constants). The selection and arrangement of rubber components influence the temperature distribution and the oxygen penetration depth which impact tire durability. The goal of this paper is to establish a finite element analysis based criterion to predict lifetime with respect to oxidative aging. The finite element analysis is carried out in three stages. First the heat generation rate distribution is calculated using a viscoelastic material model. Then the temperature distribution can be determined. In the third step we evaluate the oxygen distribution or rather the oxygen consumption rate, which is a measure for the tire lifetime. Thus, the aging behavior of different kinds of tires can be compared. Numerical examples show how diffusivities, reaction coefficients, and temperature influence the durability of different tire parts. It is found that due to the DLO effect, some interior parts may age slower even if the temperature is increased.

Hybrid Elman Neural Network and an Invasive Weed Optimization Method for Bridge Defect Recognition

2020 ◽  
pp. 036119812096794
Author(s):  
Eslam Mohammed Abdelkader ◽  
Osama Moselhi ◽  
Mohamed Marzouk ◽  
Tarek Zayed
Keyword(s):  
Neural Network ◽  
Prediction Models ◽  
Statistical Significance ◽  
Optimization Method ◽  
Bridge Management ◽  
Invasive Weed Optimization ◽  
Invasive Weed ◽  
Elman Neural Network ◽  
Existing Bridges ◽  
Value Decomposition

Existing bridges are aging and deteriorating, raising concerns for public safety and the preservation of these valuable assets. Furthermore, the transportation networks that manage many bridges face budgetary constraints. This state of affairs necessitates the development of a computer vision-based method to alleviate shortcomings in visual inspection-based methods. In this context, the present study proposes a three-tier method for the automated detection and recognition of bridge defects. In the first tier, singular value decomposition ([Formula: see text]) is adopted to formulate the feature vector set through mapping the most dominant spatial domain features in images. The second tier encompasses a hybridization of the Elman neural network ([Formula: see text]) and the invasive weed optimization (I[Formula: see text]) algorithm to enhance the prediction performance of the ENN. This is accomplished by designing a variable optimization mechanism that aims at searching for the optimum exploration–exploitation trade-off in the neural network. The third tier involves validation through comparisons against a set of conventional machine-learning and deep-learning models capitalizing on performance prediction and statistical significance tests. A computerized platform was programmed in C#.net to facilitate implementation by the users. It was found that the method developed outperformed other prediction models achieving overall accuracy, F-measure, Kappa coefficient, balanced accuracy, Matthews’s correlation coefficient, and area under curve of 0.955, 0.955, 0.914, 0.965, 0.937, and 0.904, respectively as per cross validation. It is expected that the method developed can improve the decision-making process in bridge management systems.

Design Optimization Method for MR-Brake Actuators

2011 ◽  
Author(s):  
Ozan G. Erol ◽  
Hakan Gurocak ◽  
Berk Gonenc
Keyword(s):  
Optimal Solution ◽  
Volume Ratio ◽  
Optimization Methods ◽  
Search Space ◽  
Optimization Method ◽  
Friction Torque ◽  
Element Analysis ◽  
Taguchi Design Of Experiments ◽  
Variable Friction ◽  
Electronically Controllable

MR-brakes work by varying viscosity of a magnetorheological (MR) fluid inside the brake. This electronically controllable viscosity leads to variable friction torque generated by the actuator. A properly designed MR-brake can have a high torque-to-volume ratio which is quite desirable for an actuator. However, designing an MR-brake is a complex process as there are many parameters involved in the design which can affect the size and torque output significantly. The contribution of this study is a new design approach that combines the Taguchi design of experiments method with parameterized finite element analysis for optimization. Unlike the typical multivariate optimization methods, this approach can identify the dominant parameters of the design and allows the designer to only explore their interactions during the optimization process. This unique feature reduces the size of the search space and the time it takes to find an optimal solution. It normally takes about a week to design an MR-brake manually. Our interactive method allows the designer to finish the design in about two minutes. In this paper, we first present the details of the MR-brake design problem. This is followed by the details of our new approach. Next, we show how to design an MR-brake using this method. Prototype of a new brake was fabricated. Results of experiments with the prototype brake are very encouraging and are in close agreement with the theoretical performance predictions.

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