Estimation Of Material Properties Research Articles

Using regression models to determine the poroelastic properties of cartilage

The feasibility of determining biphasic material properties using regression models was investigated. A transversely isotropic poroelastic finite element model of stress relaxation was developed and validated against known results. This model was then used to simulate load intensity for a wide range of material properties. Linear regression equations for load intensity as a function of the five independent material properties were then developed for nine time points (131, 205, 304, 390, 500, 619, 700, 800, and 1000s) during relaxation. These equations illustrate the effect of individual material property on the stress in the time history. The equations at the first four time points, as well as one at a later time (five equations) could be solved for the five unknown material properties given computed values of the load intensity. Results showed that four of the five material properties could be estimated from the regression equations to within 9% of the values used in simulation if time points up to 1000s are included in the set of equations. However, reasonable estimates of the out of plane Poisson's ratio could not be found. Although all regression equations depended on permeability, suggesting that true equilibrium was not realized at 1000s of simulation, it was possible to estimate material properties to within 10% of the expected values using equations that included data up to 800s. This suggests that credible estimates of most material properties can be obtained from tests that are not run to equilibrium, which is typically several thousand seconds.

Estimation of material properties of nanocomposite structures

A method for the numerical modelling of mechanical behaviour of nanocomposite materials reinforced with the carbon nanotubes, based on computational homogenization as a multi-scale method, is presented. Since the carbon nanotube inside of the representative volume element (RVE) is modelled as a space frame structure, theoretical background and a proper way of modelling of carbon nanotubes is given. Novelty in this paper is an incorporation of interactions, based on the weak van der Waals forces and modelled by nonlinear rod elements, into a multiscale model as described below. An algorithm is developed for analysis of those interactions. Since the problem of modelling nanocomposite structures is a three-dimensional multi-scale problem, one part of this work is dedicated to multi-scale modelling methods, especially to the first order computational homogenization. Computational homogenization and representative volume element are the basis of the presented numerical model of the nanocomposites. Nano scale model is based on beam and non-linear rod finite elements. For the purpose of the software verification, examples, i.e. models of the nanocomposite material are presented. Obtained results are compared with the results given by the other authors.

Improved Assessment Methods for Static and Fatigue Resistance of Old Metallic Railway Bridges

A large number of railway structures in Europe are metallic bridges. The increasing volume of traffic and axle weight of trains mean that, for many structures, the loads today are much higher than those envisaged when they were designed. This paper presents a summary of the different recommendations and advice proposed in European guidelines for assessing load and resistance of railway bridges issued from a research project. The knowledge of the material properties of existing metallic bridges is essential for the resistance assessment and the determination of the remaining lifetime of old metallic bridges. Furthermore, old bridges require more exact and efficient assessment methods that call for a precise description of the material. Among the problems met in metallic structures and material properties estimation, fatigue is the most common cause of failure. To be able to make accurate assessments of existing bridges, it is important to know the behavior of bridges exposed to fatigue and how the old materials behave owing to cyclic exposure. The main question answered in this paper is how to make a safe estimation concerning the remaining life in service. The possible traffic load on steel rail bridges is usually limited by the fatigue resistance, but for certain situations the static resistance also has to be checked. Most design rules for steel structures are applicable also to riveted structures. However, some information is missing on how to deal with the special case when elements are intermittently connected in contrast to welded structures that are connected continuously. Because the traditional methods for assessing the resistance of steel bridges are based on elastic analysis, a method for utilizing a limited redistribution of bending moments based on beam theory is proposed.

Inverse-FEM Characterization of a Brain Tissue Phantom to Simulate Compression and Indentation

The realistic simulation of tool-tissue interactions is necessary for the development of surgical simulators and one of the key element for it realism is accurate bio-mechanical tissue models. In this paper, we determined the mechanical properties of soft tissue by minimizing the difference between experimental measurements and the analytical or simulated solution of the deformation. Then, we selected the best model parameters that fit the experimental data to simulate a bonded compression and a needle indentation with a flat-tip. We show that the inverse FEM allows accurate material property estimation. We also validated our results using multiple tool-tissue interactions over the same specimen.

Structural stability of rubble-pile asteroids

Granular aggregates, like fluids, do not admit all manners of shapes and rotation rates. It is hoped that an analysis of a suspected granular asteroid’s equilibrium shape and its structural stability will help confirm its rubble-pile nature, and, perhaps, even constrain the asteroid’s material parameters. Equilibrium shapes have been analyzed in the past by several investigators (Holsapple, K.A. [2001]. Icarus 154, 432–448; Harris, A.W., Fahnestock, E.G., Pravec, P. [2009]. Icarus 199, 310–318; Sharma, I., Jenkins, J.T., Burns, J.A. [2009]. Icarus 200, 304–322). Here, we extend the classical Lagrange–Dirichlet stability theorem to the case of self-gravitating granular aggregates. This stability test is then applied to probe the stability of several near-Earth asteroids, and explore the influence of material parameters such as internal friction angle and plastic bulk modulus. Finally, we consider their structural stability to close planetary encounters. We find that it is possible for asteroids to be stable to small perturbations, but unstable to strong and/or extended perturbations as experienced during close flybys. Conversely, assuming stability in certain situations, it is possible to estimate material properties of some asteroids like, for example, 1943 Anteros.

Minimum maximum temperature gradient coil design

Ohmic heating is a serious problem in gradient coil operation. A method is presented for redesigning cylindrical gradient coils to operate at minimum peak temperature, while maintaining field homogeneity and coil performance. To generate these minimaxT coil windings, an existing analytic method for simulating the spatial temperature distribution of single layer gradient coils is combined with a minimax optimization routine based on sequential quadratic programming. Simulations are provided for symmetric and asymmetric gradient coils that show considerable improvements in reducing maximum temperature over existing methods. The winding patterns of the minimaxT coils were found to be heavily dependent on the assumed thermal material properties and generally display an interesting "fish-eye" spreading of windings in the dense regions of the coil. Small prototype coils were constructed and tested for experimental validation and these demonstrate that with a reasonable estimate of material properties, thermal performance can be improved considerably with negligible change to the field error or standard figures of merit.

Use of tactile feedback to control exploratory movements to characterize object compliance

Humans have been shown to be good at using active touch to perceive subtle differences in compliance. They tend to use highly stereotypical exploratory strategies, such as applying normal force to a surface. We developed similar exploratory and perceptual algorithms for a mechatronic robotic system (Barrett arm/hand system) equipped with liquid-filled, biomimetic tactile sensors (BioTac® from SynTouch LLC). The distribution of force on the fingertip was measured by the electrical resistance of the conductive liquid trapped between the elastomeric skin and a cluster of four electrodes on the flat fingertip surface of the rigid core of the BioTac. These signals provided closed-loop control of exploratory movements, while the distribution of skin deformations, measured by more lateral electrodes and by the hydraulic pressure, were used to estimate material properties of objects. With this control algorithm, the robot plus tactile sensor was able to discriminate the relative compliance of various rubber samples.

Estimation of material properties in a MEMS based gyroscope using natural frequencies

This paper addresses the prediction of the distributed material properties of a microstructure. Predictions were made by measuring the dynamic response of fabricated materials used in the microstructures. When these distributed material properties are used to estimate the mechanical performance of microstructures, differences between computer simulations and the experimental results can be reduced, and reliable design can be developed. The distributed material properties of a micro-electromechanical system(MEMS)-based gyroscope were obtained numerically using the proposed method and experimentally using dynamic testing. The natural frequency of the numerical analysis was slightly higher (first mode: − 0.43 Hz, second mode: 0.33 Hz) than the result from the dynamic testing because some properties such as the microstructure porosity were neglected.

Comparison of spherical and cubical statistical volume elements with respect to convergence, anisotropy, and localization behavior

The statistical volume element (SVE) technique is commonly used for the estimation of the effective properties of a micro-structured material. Mostly, cubical SVEs with periodic boundary conditions are employed, which result in a better convergence, compared to the uniform boundary conditions. In this work, the possibility of using spherical SVEs is discussed, since their use promises a reduction of the influence of the boundary, and thus a more efficient estimation of the effective material properties. We discuss the applicability of boundary conditions which are similar to the periodic boundary conditions to spherical SVEs. Then we assess the convergence (subject 1) of spherical and cubical SVEs to the effective material behavior for the uniform and periodic boundary conditions, focusing on the elastic and plastic properties of a macroscopically isotropic matrix-inclusion material. It is shown that the spherical SVEs perform indeed better than the cubical SVEs. Also, unlike the spherical SVEs, the cubical SVEs with periodic boundary conditions induce a spurious anisotropy (subject 2), which is quantified for the effective elastic properties. Finally, we examine the effect of the periodicity frame on the localization behavior (subject 3) of cubical SVE, since cubical SVE with periodic boundary conditions are commonly used to estimate macroscale material failure. It is demonstrated that the orientation of the periodicity frame affects the overall SVE response significantly. The latter is not observed for spherical SVE.

Data fusion‐based assessment of raw materials in mammalian cell culture

In mammalian cell culture producing therapeutic proteins, one of the important challenges is the use of several complex raw materials whose compositional variability is relatively high and their influences on cell culture is poorly understood. Under these circumstances, application of spectroscopic techniques combined with chemometrics can provide fast, simple, and non-destructive ways to evaluate raw material quality, leading to more consistent cell culture performance. In this study, a comprehensive data fusion strategy of combining multiple spectroscopic techniques is investigated for the prediction of raw material quality in mammalian cell culture. To achieve this purpose, four different spectroscopic techniques of near-infrared, Raman, 2D fluorescence, and X-ray fluorescence spectra were employed for comprehensive characterization of soy hydrolysates which are commonly used as supplements in culture media. First, the different spectra were compared separately in terms of their prediction capability. Then, ensemble partial least squares (EPLS) was further employed by combining all of these spectral datasets in order to produce a more accurate estimation of raw material properties, and compared with other data fusion techniques. The results showed that data fusion models based on EPLS always exhibit best prediction accuracy among all the models including individual spectroscopic methods, demonstrating the synergetic effects of data fusion in characterizing the raw material quality.

Impact of particle size ratio and volume fraction on effective material parameters and performance in solid oxide fuel cell electrodes

Optimization of the microstructure of porous electrodes plays an important role in the enhancement of the performance of solid oxide fuel cells. For this, microstructural models based on percolation theory have proven useful for the estimation of the effective material properties of the electrode material, assumed to consist of a binary mixture of spherical electron and ion conducting particles. In this work, we propose an extension of prior approaches for calculating the effective size of the three-phase boundary, which we judge to be physically more sound and, in particular, well suited for characterizing mixtures of particles of different sizes. This approach is then employed in a one-dimensional cell level model encompassing the entire set of processes of gas transport, electronic and ionic conduction as well as the electrochemical reactions. The impact of the electron and ion conducting particle sizes, their volume fraction and their size ratio on the performance of the fuel cell are investigated in a parametric study. Under certain conditions, cathode microstructures having electronic conducting particles of size different from that of the ionic conducting particles become preferable and yield a higher maximum power density when compared to the best possible configuration of monodisperse particles.

Estimation of thermal properties of materials with application for inflatable spacecraft structure testing

The general method of iterative regularization is concerned with application to the estimation of material properties. The objective of this article is to estimate thermal and thermokinetic properties of advanced materials using the approach based on inverse methods. An experimental–computational system is presented for investigating the thermal and kinetics properties of composite materials by methods of inverse heat transfer problems and this is developed at the Thermal Laboratory of the Department of Space Systems Engineering, Moscow Aviation Institute. The system is aimed at investigating the materials in conditions of unsteady contact heating over a wide range of temperature changes and heating rates in vacuum, air and inert gas mediums.

A Bayesian approach to estimate material properties from global statistical data

This paper is devoted to presenting an updated approach based on the use of Bayesian networks. This methodology aims to update the statistical parameters related to a mechanical model thanks to experimental data. The proposed updating process has been applied to engineering problems. The results show that the proposed approach could be used to estimate the material parameters of a given structure and avoids carrying out destructive tests on site. Cet article vise à présenter une méthode d’actualisation basée sur l’utilisation des réseaux bayésiens. Cette approche a pour but d’actualiser les paramètres statistiques d’un modèle mécanique en intégrant de l’information expérimentalement disponible. L’approche proposée a été utilisée sur des cas pratiques auxquels l’ingénieur pourrait être confronté. En particulier, il ressort que la méthodologie proposée peut être utilisée pour déterminer les paramètres matériaux caractéristiques d’une structure donnée en évitant de réaliser des essais destructifs sur site.

Identification and removal of adverse effects of non-contact electromagnetic excitation in Oberst Beam Test Method

Although the Oberst Beam Test Method is widely used in practice, detailed information about how to perform a successful Oberst beam experiment is quite limited. In this paper, first, the effects of various parameters in an Oberst test rig, including the amplitude of the excitation, mounting conditions, input excitation type and the length of the test sample, are examined in an attempt to improve the accuracy of the estimated material properties. As it is observed that the electromagnetic effect created by a non-contact exciter can be the most significant source of error in estimated material properties, this paper then presents the results of extensive tests so as to quantify the level of the adverse effects of non-contact electromagnetic excitation. It is found that non-contact electromagnetic exciter creates a stiffness effect that can be modelled as a spring attached between the non-contact exciter location on the Oberst beam and the ground. In contrast to the common belief that the use of non-contact electromagnetic excitation has little drawbacks, it is shown that such excitation can introduce very significant level of errors in identified material properties. This paper also proposes a method for removing the adverse effects of the electromagnetic excitation in order to obtain more accurate material properties for uniform as well as composite beams.

Mechanical buckling of nanocomposite rectangular plate reinforced by aligned and straight single-walled carbon nanotubes

In this paper, the mechanical buckling of a functionally graded nanocomposite rectangular plate reinforced by aligned and straight single-walled carbon nanotubes (SWCNTs) subjected to uniaxial and biaxial in-plane loadings is investigated. The material properties of the nanocomposite plate are assumed to be graded in the thickness direction and vary continuously and smoothly according to two types of the symmetric carbon nanotubes volume fraction profiles. The material properties of SWCNT are determined according to molecular dynamics (MDs), and then the effective material properties at a point are estimated by either the Eshelby–Mori–Tanaka approach or the extended rule of mixture. The equilibrium and stability equations are derived using the Mindlin plate theory considering the first-order shear deformation (FSDT) effect and variational approach. The results for nanocomposite plate with uniformly distributed CNTs, which is a special case in the present study, are compared with those of the symmetric profiles of the CNTs volume fraction. A numerical study is performed to investigate the influences of the different types of compressive in-plane loadings, CNTs volume fractions, various types of CNTs volume fraction profiles, geometrical parameters and different types of estimation of effective material properties on the critical mechanical buckling load of functionally graded nanocomposite plates.

On the accurate analysis of linear elastic meta-material properties for use in design optimization problems

In the field of meta-materials engineering, asymptotic homogenization has proven to be a valuable tool to estimate material properties for many different design needs. Homogenization is used in the design of an object to tie the global material properties to the local material microstructure of the meta-material. The governing equations of the theory are derived from a small-parameter expansion that assumes the scaling length of the unit cell, the smallest repeatable structure found in the material, is much smaller than the entire material length scale. However, for those design problems that do not meet this scaling requirement, the meta-material properties given by homogenization may be inaccurate, leading to error in the material design process.To demonstrate some of these limitations, the more general set of macroscopic analyses derived from the average stress and average strain theorems are applied to several designs in which the assumptions of homogenization theory are no longer valid, those chiefly being materials made of a single or a few layers of unit cells. Then, by applying both materials analyses to simple design problems, the necessity of using a meta-material design method to link global and local properties in a manner consistent with global design methods is demonstrated. In particular, the use of homogenization in designing single layer materials is shown to incur a very large error in the design process, whereas the averaging method is much more accurate.

Estimation of macroscopic material properties using sintering simulation of porous microstructure affected by mechanical effects

Estimation of macroscopic material properties using sintering simulation of porous microstructure affected by mechanical effects

Energy Parameter Correlation of Failure Life Data between Cyclic Ball Indentation and Low Cycle Fatigue

Material properties provide important information about the fatigue life which makes life extension of critical components in various industries possible. The conventional methods of determining tensile strength and fatigue life through ASTM or equivalent standard specimen have their limitations due to size requirements of test specimen. Automated Ball Indentation (ABI) is a semi-invasive technique that is useful for determining the material properties. A tungsten carbide ball of diameter 1.57 mm is used to load the test specimen and the force vs. displacement response is used to estimate material properties. Methods have been formulated in the past to predict the fatigue life of the specimen by correlating Cyclic Indentation and Low Cycle fatigue data. In this work, investigation of the role of plastic dissipation energy in failure and its correlation for the two processes by Finite Element simulations in ABAQUS is attempted. Results such as force vs. displacement response, residual depth and plastic diameter with Haggag’s [1] formulation and experimental results are validated first. Then, the plastic dissipation energy density, which is a comparable parameter, is plotted for both Cyclic Indentation and Low Cycle Fatigue. A reasonably good correlation is obtained which also validates the failure life predicted from knee-point approach. Dependence of the pile-up profile of variables such as method of loading and the friction between the contacting bodies is also discussed.

Finite Element Methods for Maxwell's Transmission Eigenvalues

The transmission eigenvalue problem plays a critical role in the theory of qualitative methods for inhomogeneous media in inverse scattering theory. Efficient computational tools for transmission eigenvalues are needed to motivate improvements to theory, and, more importantly, are parts of inverse algorithms for estimating material properties. In this paper, we propose two finite element methods to compute a few lowest Maxwell's transmission eigenvalues which are of interest in applications. Since the discrete matrix eigenvalue problem is large, sparse, and, in particular, non-Hermitian due to the fact that the problem is neither elliptic nor self-adjoint, we devise an adaptive method which combines the Arnoldi iteration and estimation of transmission eigenvalues. Exact transmission eigenvalues for balls are derived and used as a benchmark. Numerical examples are provided to show the viability of the proposed methods and to test the accuracy of recently derived inequalities for transmission eigenvalues.

Causal fracture prediction: Curvature, stress, and geomechanics

We propose scaling volume curvature measurements with material property estimates to produce a superior prediction of natural fractures. Curvature is one of many, indirect, fracture-inferring attributes. It does not detect fractures, but is causally related to them through the assumption that increasing curvature relates to increasing strain. There are many other variables that are causally related to fractures. We propose that it would be advantageous to create combinations of these causal variables with curvature. Some of the most well known and important causes of variations in natural fracture density are material properties relating to brittleness. Material properties are critical geologically at all scales, from large-scale regional studies to prospect-level inquiries because the properties may vary significantly within individual formations and between formations. These vertical and lateral changes in material properties may be important and should be considered in fracture estimation, along with curvature. There is a lack of clarity regarding exactly which material property is best from the perspective of physics and rock mechanics; however, we have chosen a combination of parameters that we argue is a starting point. Fortunately, material properties are routinely estimated with amplitude variation with offset (AVO) techniques, and there is little practical reason not to use them together with curvature to produce a more complete attribute inferring fracture density. The combination of these variables is a step in the direction of creating quantitative causal fracture prediction estimates.