Identification of Elasto-Plastic Constitutive Parameters by Self-Optimizing Inverse Method: Experimental Verifications

In this paper, the Self-Optimizing Inverse Method (Self-OPTIM) has been experimentally verified by identifying constitutive parameters solely based on prescribed boundary loadings without full-field displacements. Recently the Self-OPTIM methodology was developed as a computational inverse analysis tool that can identify parameters of nonlinear material constitutive models. However, the methodology was demonstrated only by numerically simulated testing with full-field displacement fields and prescribed boundary loadings. The Self-OPTIM is capable of identifying parameters of the chosen class of material constitutive models through minimization of an implicit objective function defined as a function of full-field stress and strain fields in the optimization process. The unique advantages of the Self-OPTIM includes: 1) model independency that is expected to open up a wide range of applications for various engineering simulations; 2) capabilities of parameter identification based solely on global measurements of boundary forces and displacements. In this paper, the Self-OPTIM inverse method is experimentally verified by using two different shapes of specimens made of AISI 1095 steel: 1) dog-bone and 2) notched specimens under a loading and unloading course. Parameters of a cyclic plasticity model with nonlinear kinematic hardening rule and associated flow theory are identified by the Self-OPTIM. Multiple tests and the inverse simulations are conducted to ensure consistent performance of the Self-OPTIM. The identified parameters are successively used to reconstruct the material response.     

Thermo-elastic material parameters identification using modified error in constitutive equation approach

This paper presents an identification procedure for anisotropic thermo-elastic heterogeneous material profile based on modified error in constitutive equation (MECE) approach. The inverse problem is posed as an optimization problem where the objective functional evaluates the difference in constitutive relation that associates kinematically admissible strain field to the statically admissible stress field. An additional term due to corruption in measurement data is included in the cost functional as a penalty form. While following standard MECE-based identification procedure, we have proposed a trace norm of the constitutive discrepancy functional that arises due to two dissimilar fields for material parameter update. In the process, we obtain explicit parameter update formula for general anisotropic thermo-elastic material. However, unlike elastic case, parameter update equations are nonlinear due to thermo-elastic constitutive relation. Finally, the potential of the proposed procedure in estimating anisotropic material parameters is illustrated through some large-scale parameter estimation problems.     

流体饱和孔隙介质参数反演的模拟退火算法

本文研究了模拟退火算法在流体饱和孔隙介质参数反演中的应用。通过计算响应数据与实测响应数据的拟合将参数反问题归结为最优化问题。由于流体饱和孔隙介质运动方程的复杂性，动力响应与材料参数之间呈复杂的非线性关系，优化目标函数是非凸多峰函数。传统的梯度类优化方法一方面受局部极值的困扰难以搜索到全局最优解； 另一方面确定搜索方向须进行复杂的参数敏度分析。为克服这些困难，本文应用模拟退火算法进行了多参数反演数值模拟，模拟结果表明了模拟退火算法的可行性和稳健性。     

A Computational Inverse Technique to Determine the Dynamic Constitutive Model Parameters of Concrete

In this paper, a computational inverse technique is presented to determine the constitutive parameters of concrete based on the penetration experiments. In this method, the parameter identification problem is formulated as an inverse problem, in which the parameters of the constitutive model can be characterized through minimizing error functions of the penetration depth measured in experiments and that computed by forward solver LS-DYNA. To reduce the time for forward calculation during the inverse procedure, radial basis function approximate model is used to replace the actual computational model. In order to improve the accuracy of approximation model, a local-densifying method combined with RBF approximation model is adopted. The intergeneration projection genetic algorithm is employed as the inverse solver. Through the application of this method, the parameters of HJC constitutive model are determined. Results show that the identified constitutive parameters' computational penetration depth and projectile deceleration-time curves are closely in accordance with experimental data. The proposed inverse approach is a potentially useful tool to effectively help identify material parameters.     

Metamodel-based inverse method for parameter identification: elastic–plastic damage model

This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic–plastic damage model parameter identification. An elastic–plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic–plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.     

Inverse analysis for heterogeneous materials and its application to viscoelastic curing polymers

This contribution aims at achieving two important goals: First, it outlines a numerical inverse homogenization strategy able to recover material parameters of the microstructure by using results of macroscopic tests. Second, it considers parameter identification for viscoelastic heterogeneous materials, which is a step providing the basis for the further extension toward the general treatment of dissipative processes. The approach proposed couples the Levenberg–Marquardt method with the multiscale finite element method. In this combination, the former is a gradient-based optimization strategy used to minimize a merit function while the latter is a numerical homogenization technique needed to solve the direct problem. The specific example studied in the paper deals with the investigation of a composite consisting of a viscoelastic curing polymer and a nonlinear elastic material. It proposes a three-step procedure for the evaluation of its material parameters and discusses the accuracy and the uniqueness of the solution.     

Identification of elastic orthotropic material parameters by the scaled boundary finite element method

This paper focuses on a parameter identification algorithm of two-dimensional orthotropic material bodies. The identification inverse problem is formulated as the minimization of an objective function representing differences between the measured displacements and those calculated by using the scaled boundary finite element method (SBFEM). In this novel semi-analytical method, only the boundary is discretized yielding a large reduction of solution unknowns, but no fundamental solution is required. As sufficiently accurate solutions of direct problems are obtained from the SBFEM, the sensitivity coefficients can be calculated conveniently by the finite difference method. The Levenberg–Marquardt method is employed to solve the nonlinear least squares problem attained from the parameter identification problem. Numerical examples are presented at the end to demonstrate the accuracy and efficiency of the proposed technique.     

双相介质二参数反演的同伦方法

研究了同伦方法在双相介质参数反演中的应用。从材料响应的理论合成应与实际测量数据相拟合这一出发点,将参数反演问题转化为非线性算子方程的零点求解问题,然后应用一种大范围收敛的同伦方法求出非线性算子等于零的根作为反问题的解。把这种方法用于Paul(1976)给出的具有解析解的二维双相介质模型的数值模拟,模拟结果表明了同伦反演方法的可行性和稳健性。     

Determination of constitutive parameters from a Taylor test using inverse analysis

Identification of material constitutive parameters is critical for accurate representation of the mechanical behavior of materials at high strain rates. However, customary characterization procedures based on curve fitting of stress‐strain curves, in some cases, are not accurate when the mechanical response exhibits strain rate dependency. In this paper, an inverse characterization technique based on the Taylor impact test is proposed. The technique uses a data reduction operator based on line moments and genetic algorithm optimization to determine the optimum constitutive parameters. Material parameters for a low carbon steel associated with the Plastic Kinematic model were determined using the proposed method.     

An inverse approach to determine the constitutive model parameters from axial crushing of thin-walled square tubes

Knowledge of the behaviour of structural components is essential for their design under crash consideration. Constitutive models describe their material behaviour in finite element (FE) codes. These constitutive models are in relation to the material parameters which have to be determined. The strain rates commonly observed in crash events are in the range of 0–500 s^-1. Classic experimental devices such as Hopkinson’s bars do not easily cover this range of strain rates. An inverse numerical approach based on the experimental quasi-static and dynamic axial crushing of thin-walled square tubes has therefore been developed to determine the constitutive model’s parameters. The inverse method is applied in this paper in two stages to determine the power type elastic–plastic constitutive model’s parameters and the Cowper–Symonds constitutive model’s parameters. The identified power law is compared with the results obtained by quasi-static tensile tests and shows that the identified parameters are intrinsic to the material behaviour. The Cowper– Symond’s parameters identified by this method are then used in FE simulation to predict the dynamic response of the same square tube subjected to bending loading. The results obtained show a good correlation between the experimental and numerical results.     

Inverse/genetic method and its application in identification of mechanical parameters of interface in composite

In this paper, an inverse/genetic method for interfacial parameter identification is developed. The interfacial parameter identification process can be converted into an inverse approximation problem using the method which includes finite element method and genetic algorithms for searching solution. Based on the interfacial failure information obtained from experiment, the inverse approximation procedure identifying interfacial parameters is constructed by taking the advantages of genetic algorithms over traditional gradient-based search methods. The study indicates that a good prediction with relatively high accuracy of the interfacial parameters of real composite can be achieved with the proposed method. It seems that the proposed method is promising in solving a wide range of parameter identification problems in robust way.     

结构影响线识别：反问题可识别性分析与降维贝叶斯不确定性量化

结构影响线识别是移动荷载下既有结构评估的理论基础,其本质上是基于系统输入-输出含噪数据反向对静力系统指定截面的响应函数进行识别。已有研究虽然取得了进展,但它们在以下两个方面存在局限性：缺乏反问题可识别性分析;缺乏不确定性量化。反问题可识别性分析是为了厘清系统识别的参数的解的情况。不确定性量化是基于测量输入-输出含噪数据估计影响线参数的后验概率密度函数。针对上述两个局限性,该文在贝叶斯概率框架的基础上开展关于影响线识别的反问题可识别性分析与贝叶斯不确定性量化。该文进行基于直接参数化的影响线识别,包括系统输入与输出、反问题可识别性分析、参数最优值。经分析得出：一方面,直接参数化无法保证全局模型可识别;另一方面,现有方法即使是全局模型可识别的情况下也无法进行不确定性量化。为保证反问题是全局模型可识别且同时获取参数后验概率密度函数,该文提出基于降维贝叶斯不确定性量化的影响线后验识别,包括系统输入与输出重构、反问题可识别性分析、后验概率密度函数。该文进行模拟数据下新光大桥吊杆拉力影响线识别,与实测及模拟数据下简支梁桥应变影响线识别,验证提出方法的有效性。     

系统非线性参数识别的松驰法

研究了非线性参数系统模型的识别问题,通过引入求解线性方程的松驰法思想,构造了一类新的迭代识别算法。算例表明此方法具有很好的参数识别精度,并且具有概念清楚,易于编程等特点,为非线性系统模型参数的识别问题提供了新的思路。     

A 3D domain decomposition approach for the identification of spatially varying elastic material parameters

The post‐treatment of (3D) displacement fields for the identification of spatially varying elastic material parameters is a large inverse problem that remains out of reach for massive 3D structures. We explore here the potential of the constitutive compatibility method for tackling such an inverse problem, provided an appropriate domain decomposition technique is introduced. In the method described here, the statically admissible stress field that can be related through the known constitutive symmetry to the kinematic observations is sought through minimization of an objective function, which measures the violation of constitutive compatibility. After this stress reconstruction, the local material parameters are identified with the given kinematic observations using the constitutive equation. Here, we first adapt this method to solve 3D identification problems and then implement it within a domain decomposition framework which allows for reduced computational load when handling larger problems. Copyright © 2015 John Wiley & Sons, Ltd.     

Characterisation by Inverse Techniques of Elastic,Viscoelastic and Piezoelectric Properties of Anisotropic Sandwich Adaptive Structures

In this article we present recent developments regarding parameter estimation in sandwich structures with viscoelastic frequency dependent core and elastic laminated skin layers, with piezoelectric patch sensors and actuators bonded to the exterior surfaces of the sandwich. The frequency dependent viscoelastic properties of the core material are modelled using fractional derivative models, with unknown parameters that are to be estimated by an inverse technique, using experimentally measured natural frequencies and associated modal loss factors. The inverse problem is formulated as a constrained minimisation problem, and gradient based optimization techniques are employed. Applications are presented and discussed, focused on the identification of viscoelastic frequency dependent core material properties.     

Probabilistic learning for modeling and quantifying model-form uncertainties in nonlinear computational mechanics

Recently, a novel nonparametric probabilistic method for modeling and quantifying model-form uncertainties in nonlinear computational mechanics was proposed. Its potential was demonstrated through several uncertainty quantification (UQ) applications in vibration analysis and nonlinear computational structural dynamics. This method, which relies on projection-based model order reduction to achieve computational feasibility, exhibits a vector-valued hyperparameter in the probability model of the random reduced-order basis and associated stochastic projection-based reduced-order model. It identifies this hyperparameter by formulating a statistical inverse problem, grounded in target quantities of interest, and solving the corresponding nonconvex optimization problem. For many practical applications, however, this identification approach is computationally intensive. For this reason, this paper presents a faster predictor-corrector approach for determining the appropriate value of the vector-valued hyperparameter that is based on a probabilistic learning on manifolds. It also demonstrates the computational advantages of this alternative identification approach through the UQ of two three-dimensional nonlinear structural dynamics problems associated with two different configurations of a microelectromechanical systems device.     

Indentation and imprint mapping for the identification of interface properties in film-substrate systems

Indentation tests are frequently employed at present for the identification of material parameters at different scales. An innovative inverse analysis technique, recently proposed by the Authors, combines the traditional indentation test with the mapping of the residual deformations (imprint), thus providing experimental data apt to be used to identify material parameters in film-substrate systems. In this paper, such methodology is enhanced to permit the identification of the fracture properties of the interface between a coating and its substrate once the bulk material parameters are known. In order to make the inverse problem well posed, a further set of experimental data, namely the horizontal displacement field measured on the film external surface, is considered as available experimental information. The sought material parameters are recovered through recursive calculations of the mechanical response of the film-substrate system, performed by a finite strain numerical simulation. The coating and a significant portion of the underlying bulk material are incorporated in the finite element models built up to this purpose, while delamination is accounted for through cohesive elements. The inverse analysis procedure rests on a batch, deterministic approach and conventional optimization algorithms are employed for the minimization of a suitably defined discrepancy norm. Extensive numerical computations have been performed in order to test the performance of the proposed methodology in terms of result accuracy and computational effort.     

幂强化弹塑性材料平面应变反问题

幂强化弹塑性材料在工程领域诸如金属管材制备、岩土工程分析中都具有广泛的应用。幂强化弹塑性材料的本构参数（例如弹性模量）和结构的边界条件（例如位移）往往不容易确定。在这种情况下,反问题为确定这些参数提供了一种新思路。将ABAQUS二次开发的子程序和复变量求导法结合,用于求解基于幂强化弹塑性材料的平面应变力学反问题:以传统的用户单元子程序为框架,将程序中实数变量转换为复数,建立了复数用户单元;采用复变量求导法确定测点位移对反演参数的灵敏度矩阵;结合最小二乘法和高斯消去法对反问题进行迭代求解。给出应用算例讨论了复变量求导法对正问题计算精度影响、算法在反问题求解过程中的精度,以及反演初值、测量误差对反演结果的影响。     

Bearing dynamic parameters identification of a flexible rotor-bearing system based on transfer matrix method

Bearing dynamic parameters are important factors governing the vibration characteristics of rotating machinery; however, they are difficult to determine due to limited experimentation, and inaccurate in modelling. In this paper, a parameter identification method is presented to identify the bearing dynamic parameters of a flexible rotor-bearing system. In this method, the parameter identification problem is formulated as an inverse problem. The bearing dynamic parameters have been characterized through minimizing the error squared of the rotor-bearing system unbalance response between the experiment results and the computational ones. The intergeneration projection genetic algorithm is used to minimize the error squared. As an efficient method for analysing the dynamic behaviour of a rotor-bearing system, an improved transfer matrix method has been employed to calculate the unbalance response. This approach has been applied to identify the bearing dynamic parameters of a test rig supported by two anisotropic bearings, according to the unbalance response experimental data. Results indicated that this method could identify the bearing dynamic parameters. It is also robust to the noise effects.     

The diagonalized contrast source inversion approach for elastic wave inversion

This study focuses on the inverse scattering of objects embedded in a homogeneous elastic background. The medium is probed by ultrasonic sources, and the scattered fields are observed along a receiver array. The goal is to retrieve the shape, location, and constitutive parameters of the objects through an inversion procedure. The problem is formulated using a vector integral equation. As is well-known, this inverse scattering problem is nonlinear and ill-posed. In a realistic configuration, this nonlinear inverse scattering problem involves a large number of unknowns, hence the application of full nonlinear inversion approaches such as Gauss-Newton or nonlinear gradient methods might not be feasible, even with present-day computer power. Hence, in this study we use the so-called diagonalized contrast source inversion (DCSI) method in which the nonlinear problem is approximately transformed into a number of linear problems. We will show that, by using a three-step procedure, the nonlinear inverse problem can be handled at the cost of solving three constrained linear inverse problems. The robustness and efficiency of this approach is illustrated using a number of synthetic examples.