Akira Todoroki

Measurement of orthotropic electric conductance of CFRP laminates and analysis of the effect on delamination monitoring with an electric resistance change method

Since delaminations of composite laminates are usually invisible or difficult to detect by visual inspections, delamination causes low reliability for primary structures. Automatic systems for delamination identifications in-service are desired in order to improve this low reliability. The present study employs an electric resistance change method for detection of delaminations. Since the method adopts reinforcement carbon fibre itself as sensors for delamination detections, this method does not cause reduction of static strength or fatigue strength; also, this method is applicable to existing structures. In the present study, a relationship between fibre volume fraction and orthotropic electric conductivities is confirmed by experimentation and the effect of measured orthotropic electric conductance on delamination monitoring is discussed analytically with FEM analyses. Two types of cross-ply laminates are prepared for delamination monitoring analyses: [0/90]s and [90/0]s. Electric resistance changes due to delamination creation are discussed for both specimen types with results of electric current density diagrams. As a result, it can be concluded that the fibre volume fraction has a large effect on electric conductance of the transverse and thickness directions, and electric conductance of the thickness direction has significant effects on delamination detection with the electric resistance change method.

Permutation genetic algorithm for stacking sequence design of composite laminates

Abstract Stacking sequence design of a composite laminate with a given set of plies is a combinatorial problem of seeking an optimal permutation. Permutation genetic algorithms optimizing the stacking sequence of a composite laminate for maximum buckling load are studied. A new permutation GA named gene–rank GA is developed and compared with an existing Partially Mapped Permutation GA, originally developed for solving the travelling salesman problem. The two permutation GAs are also compared with a standard non-permutation GA. It is demonstrated through examples that the permutation GAs are more efficient for stacking sequence optimization than a standard GA. Repair strategies for standard GA and the two permutation GAs for dealing with constraints are also developed. It is shown that using repair can significantly reduce computation cost for both standard GA and permutation GA.

Delamination identification of cross-ply graphite/epoxy composite beams using electric resistance change method

Detection of delaminations is a difficult task for visual inspections. Difficulty of detection underlines the importance of development of smart structures for monitoring delaminations of graphite/epoxy laminated composites. This study employs an electric resistance change method for identification of delamination location and size; applicability of the method is investigated experimentally using beam-type specimens fabricated from cross-ply laminates. On the specimen surface, multiple electrodes are mounted by co-curing copper foil to measure electric resistance changes. Interlamina shear tests are conducted to create a practical delamination crack in a beam-type specimen. Five beam specimen types were made and tested. A large number of tests were conducted to obtain a data set for solving inverse problems to estimate delamination location and size from measured electric resistance changes. Response surfaces are employed for a solver of inverse problems instead of well-known artificial neural networks. As a result, the method successfully identifies delamination location and size for these beam type specimens. To obtain practically efficient estimation performance, at least five electrodes are indispensable for these beam type specimens.

Stacking sequence optimization by a genetic algorithm with a new recessive gene like repair strategy

A genetic algorithm is used to obtain the stacking sequence of the laminate that has the set of lamination parameters that are the closest to a set of target lamination parameters. In addition, the laminate is required to be balanced and to have no more than 4 contiguous plies of the same orientation in order to satisfy practical considerations. This problem is a constrained combinatorial optimization problem which is usually difficult to solve. The difficulty of enforcing constraints in genetic optimization is handled by introducing a new repair strategy. The new repair strategy does not alter genes but only changes decoding rules, and is similar in this respect to the way recessive genes operate in biology. The relationship between the reliability of the genetic algorithm and the probability of repair was investigated, and it is shown that 100% probability of repair is optimal when the target laminates include 45° plies. Since practical composite laminates usually include 45° plies, it is concluded that the repair strategy discussed herein should always be used with the optimization.

Delamination monitoring of graphite/epoxy laminated composite plate of electric resistance change method

The present paper employs the electric resistance change method for monitoring of location and size of a delamination crack of graphite/epoxy composite laminates. The method is applied to a plate-type specimen with an embedded delamination of cross-ply and quasi-isotropic laminates. Ten electrodes made from copper foil are mounted on the specimen top surfaces. An embedded delamination crack is created by a static indentation test, and the electric resistance changes are measured using a conventional strain gage amplifier. Response surfaces are adopted as a tool for solving inverse problems to estimate location and size of delamination crack from the measured electric resistance changes of all segments between electrodes. As a result, the present method successfully provides estimations of location and size of the embedded delamination for graphite/epoxy laminated composites.

Three-dimensional printing of continuous-fiber composites by in-nozzle impregnation

We have developed a method for the three-dimensional (3D) printing of continuous fiber-reinforced thermoplastics based on fused-deposition modeling. The technique enables direct 3D fabrication without the use of molds and may become the standard next-generation composite fabrication methodology. A thermoplastic filament and continuous fibers were separately supplied to the 3D printer and the fibers were impregnated with the filament within the heated nozzle of the printer immediately before printing. Polylactic acid was used as the matrix while carbon fibers, or twisted yarns of natural jute fibers, were used as the reinforcements. The thermoplastics reinforced with unidirectional jute fibers were examples of plant-sourced composites; those reinforced with unidirectional carbon fiber showed mechanical properties superior to those of both the jute-reinforced and unreinforced thermoplastics. Continuous fiber reinforcement improved the tensile strength of the printed composites relative to the values shown by conventional 3D-printed polymer-based composites.

The effect of number of electrodes and diagnostic tool for monitoring the delamination of CFRP laminates by changes in electrical resistance

The present study employs an electric-resistance change method for the identification of delamination cracks. In this method, the appropriate number of electrodes for identifing delaminations is investigated, and the diagnostic tool for the inverse problems to identify the delamination crack location and size from the electric resistance changes is discussed. FEM analyses are conducted to obtain electric resistance changes due to delamination crack creation with three-, four- and five-electrode type specimens. By the use of artificial neural networks (ANNs), the required number of electrodes for the identification of delamination-crack location and size from the electric resistance changes is investigated. By comparison of the estimations with the ANNs and with the response surfaces (RS), a better diagnostic tool is discussed in detail. As a result, the five-electrode type specimen is shown to be better for identification, and use of the RS with quadratic polynomials is a better tool than ANNs for the identification of delamination-crack location and size using electric resistance change.

High performance estimations of delamination of graphite/epoxy laminates with electric resistance change method

Delamination of laminated composites is usually invisible or difficult to detect visually. Delamination causes low reliability for primary structures. Automatic systems for in-service delamination identifications are desired to improve low reliability. The present study employs an electric resistance change method for delamination detection. Since the method adopts reinforcement carbon fiber itself as sensors for delamination detection, this method does not reduce static or fatigue strength; also, the method is applicable to existing structures. Authors have found that the electric resistance change method with response surfaces is very effective experimentally and analytically. However, a large error of estimation remains for estimation of delamination location. In the present study, a new data processing procedure is proposed to improve performance of estimations of delamination location. The new method is applied to laminated composite beams. A delamination crack of a laminated composite beam is monitored with the new method using FEM analyses. As a result, the method reveals excellent performance of estimations of delamination location even for new data not used in regression equations.

Wireless Monitoring of Automobile Tires for Intelligent Tires

This review discusses key technologies of intelligent tires focusing on sensors and wireless data transmission. Intelligent automobile tires, which monitor their pressure, deformation, wheel loading, friction, or tread wear, are expected to improve the reliability of tires and tire control systems. However, in installing sensors in a tire, many problems have to be considered, such as compatibility of the sensors with tire rubber, wireless transmission, and battery installments. As regards sensing, this review discusses indirect methods using existing sensors, such as that for wheel speed, and direct methods, such as surface acoustic wave sensors and piezoelectric sensors. For wireless transmission, passive wireless methods and energy harvesting are also discussed.

Low-cost delamination monitoring of CFRP beams using electrical resistance changes with neural networks

Delamination is a significant defect of laminated composites. The present study employs an electrical resistance change method in an attempt to identify internal delaminations experimentally. The method adopts reinforcing carbon fibers as sensors. In our previous paper, an actual delamination crack in a carbon fiber reinforced plastic (CFRP) laminate was experimentally identified with artificial neural networks (ANNs) or response surfaces created from a large number of experiments. The experimental results were used for the learning of the ANN or for regressions of the response surfaces. For the actual application of the method, it is necessary to minimize the number of experiments in order to keep the cost of the experiments to a minimum. In the present study, therefore, finite-element method (FEM) analyses are employed to make sets of data for the learning of the ANN. First, the electrical conductivity of the CFRP laminate is identified by means of the least estimation error method. After that, the results of the FEM analyses are used for the learning of the ANN. The method is applied to the actual delamination monitoring of CFRP beams. As a result, the method successfully monitored the delamination location and size using only ten experiments.