A method to estimate the thermally induced residual strain accumulation under varying temperature in a Bi2223/Ag/Ag alloy composite superconductor was presented, in which the mechanical property values measured from the stress-strain curves of the samples with different residual strain states, the residual strain value of Bi2223 filaments in the composite tape at room temperature measured by x-ray diffraction and the reported coefficients of thermal expansion of the constituents (Bi2223, Ag and Ag alloy) in the relevant temperature range were incorporated. This method was applied to estimate the change of the residual strain of all constituents of the high critical current type composite tape fabricated by American Superconductor Corporation as a function of temperature. The residual strain value at 77 K estimated by this method and the reported fracture strain of Bi2223 filaments accounted well for the measured strain tolerance of the critical current at 77 K.
We present a new modeling approach to describe the relation between the critical current and the applied bending strain of a multifilamentary Bi2223/Ag/Ag alloy superconducting composite tape. In the model, the shape of the superconducting core, in which the Bi2223 filaments that transport the superconducting current are embedded in Ag, and the damage strain parameter, defined as the difference between the intrinsic tensile fracture strain and the residual strain of the filaments in the sample length direction (= current transport direction), are combined with the exerted strain distribution in the bent sample. The extent of the damage to the core and the corresponding critical current are expressed as a function of bending strain. The present approach describes well the measured critical current–bending strain relation for the three different fabrication-route samples.
A modeling study was carried out to provide a description of the critical current distribution of bent multifilamentary Bi2223/Ag/Ag alloy superconducting composite tape samples. In the modeling, the difference between the tensile fracture strain of the Bi2223 filaments along the sample length under no residual strain and residual strain was used as a unifying parameter for the description of the damage evolution. The unifying parameter was treated to be different from sample to sample and also from position to position in each sample. The statistics of the unifying parameter were combined with the shape of the core and exerted tensile strain of the Bi2223 filaments, from which the relation of the heterogeneous damage evolution to the distribution of the critical current was formulated. The proposed model was applied to the reported data of 33 samples of the round robin test of VAMAS (Versailles project on advanced materials and standard)/TWA16 (Technical working area 16, superconducting materials) in 2000-2001. The reported distributions of the critical current of the bent-damaged samples were described well by the present model.
Mechanical and electromagnetic stresses are exerted on Bi2223∕Ag∕Ag alloy superconducting composite tapes during fabrication∕winding and operation, which cause reduction in critical current when the Bi2223 filaments are damaged. In the damage process, the thermally induced residual strain and fracture strain of the Bi2223 filaments play a dominant role. The aim of the present work was to propose a comprehensive method for estimation of these strain values and a quantitative description method of the relation of critical current to the applied bending∕tensile strain, and to examine the accuracy of the method in comparison with the experimental results. The residual strain of Bi2223 filaments in the composite tape was measured by the x-ray diffraction method. The measured residual strain value was used for analysis of the load-strain curve, from which the intrinsic fracture strain of filaments was estimated. The relation of critical current to applied bending∕tensile strain was predicted by the proposed calculation procedure, in which the estimated strain values were input. The predicted critical current-applied strain relation agreed well with the experimental results, suggesting that the present method is a useful tool for prediction∕description of tensile∕bending applied strain dependence of critical current of multifilamentary-type conductors.
Composite materials are heterogeneous in nature and suffer from complex non-linear modes of failure, such as delamination, matrix crack, fiber-breakage, and voids, among others. The early detection of damage in composite structures, such as airplanes, is imperative to avoid catastrophic failure and tragic consequences. This paper reports on the use of machine learning techniques for the damage assessment (i.e., detection, quantification, and localization) of smart composite structures. The success of the machine learning paradigm for damage assessment depends on the representational capability of the discriminative features for the problems of interest. However, from a practical standpoint, it is not possible to define a global or superset of discriminative features that could discriminate between damaged and undamaged states of the structures, and simultaneously make a distinction between various modes of failures. In addition, one machine learning algorithm may show optimum performance for the discriminative features of a particular problem but fails for others. This article focuses on a review of discriminative features and the corresponding machine learning algorithms (both supervised and unsupervised), for various types of damage in smart composite structures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.