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This paper aims to present a new approach to the fast determination of the effective, dynamic, mechanical properties of an adhesive for linear and nonlinear regions of the adhesive response, for both healthy and damaged states of the bond.

The proposed approach is based on the measurement of the linear and nonlinear frequency response function (FRF) of adhesive-bonded structure and using artificial neural network identification technique. For this purpose, linear and nonlinear FRFs are measured for several single-lap joint specimens that are fabricated in healthy and damaged configurations of the bond. The measured FRFs of healthy and damaged specimens are then used to identify the natural frequencies of the specimens. The experimental natural frequencies, in turn, would be used to train artificial neural network (ANN) which would be able to predict the effective Young’s and shear moduli and damping of adhesive in healthy and damaged specimens, for any given excitation level and frequency, within the training domain.

Simultaneous identification of the effective mechanical properties of adhesive for linear and nonlinear response regions, as well as healthy and damages states of the adhesive bond.

The introduced method is effective to model the assembled structures with the viscoelastic adhesive joints, for linear and nonlinear regions.

A fast methodology, using ANN, for identification the effective mechanical properties of adhesives, compared to other methods for both linear and nonlinear regions.

The purpose of this paper is to analyze the stability of aeroelastic systems using aeroelastic frequency response function (FRF).

The proposed technique determines the instability boundary of an aeroelastic system based on condition number (CN) of aeroelastic FRF matrix or directly from FRFs data.

Stability margins of typical section and hingeless helicopter rotor blade in the subsonic flow regimes (quasi‐steady and unsteady models) are determined using proposed techniques as two case studies.

The paper introduces a technique which is applicable not only when aerodynamic and structure analytical models are available but also when there are experimental models for structure and/or aerodynamics, such as impulse response functions data or FRFs data. In other words, the main advantage of the proposed method, besides its simplicity and low memory requirement, is its ability to utilize experimental data.

The purpose of this paper is to consider the dynamic characteristics identification of local structural nonlinearities.

Proposed identification method is based on minimum error linear frequency response function (MELF). Two different techniques are developed to extract nonlinear element's dynamic behavior from MELF. The first method, in which no pre‐assumed model is considered for the nonlinearity mechanism behavior, is called “direct identification method.” The second method is “model based identification method.”

Cubic stiffness dynamic characteristics are identified using the proposed techniques as a case study.

The paper shows that the proposed identification technique is simple and free of any sophisticated measurement hardwares and constraints, which is required by most of the methods proposed so far.

The objective of this article is to evaluate and compare the performance of two machine learning (ML) algorithms, i.e. support vector machines (SVMs) and random forests (RFs), when classifying seven states of operation of an electric motor using the Mel-frequency cepstral coefficients (MFCCs) as extracted representative features.

The extracted MFCCs are calculated using the motor’s vibration and audio signals separately.

After the training, the SVM model obtained a mean accuracy of 100% for the MFCCs obtained from database vibration signals and 69.6% for the database of audio signals.

The ML strategies and results reported are limited to the well-known data for industrial electric motors used in the evaluations, although it was performed tests and cross-validations with unseen data and the information from the confusion matrix.

The success of these methodologies in defect classification, where the RF presented a mean accuracy of 99.15% for the vibration signals and 63.82% for the audio signal, enables the use of this ML and extracted features as a predictive tool for failure and anomaly detection, lifetime predictions and online real-time monitoring.

It is the first time that the MFCCs are being used for anomaly detection in vibration and audio signals for electrical motors, as this extracted feature is usually used for human speech identification in the literature.

The purpose of this paper is to design an adaptive nonlinear controller for a nonlinear system of integrated guidance and control.

A nonlinear integrated guidance and control approach is applied to a homing, tail-controlled air vehicle. Adaptive backstepping controller technique is used to deal with the problem, and the Lyapanov theory is used in the stability analysis of the nonlinear system. A nonlinear model of normal force coefficient is obtained from an existing nonlinear model of lift coefficient which was validated by open loop response. The simulation was performed in the pitch plane to prove the benefits of the proposed scheme; however, it can be readily extended to all the three axes.

Monte Carlo simulations indicate that using nonlinear adaptive backstepping formulation meaningfully improves the performance of the system, while it ensures stability of a nonlinear system.

The proposed method could be used to obtain better performance of hit to kill accuracy without the expense of control effort.

A nonlinear adaptive backstepping controller for nonlinear aerodynamic air vehicle is designed and guaranteed to be stable which is a novel-based approach to the integrated guidance and control. This method makes noticeable performance improvement, and it can be used with hit to kill accuracy.

The purpose of this paper is to present a nonlinear model along with stability analysis of a flexible supersonic flight vehicle system.

The mathematical state space nonlinear model of the system is derived using Lagrangian approach such that the applied force, moment, and generalized force are all assumed to be nonlinear functions of the system states. The condition under which the system would be unstable is derived and when the system is stable, the region of attraction of the system equilibrium state is determined using the Lyapunov theory and sum of squares optimization method. The method is applied to a slender flexible body vehicle, which is referenced by the other researchers in the literature.

It is demonstrated that neglecting the nonlinearity in external force, moment and generalized force, as it was assumed by other researchers, can cause significant variations in stability conditions. Moreover, when the system is stable, it is shown analytically here that a reduction in dynamic pressure can make a larger region of attraction, and thus instability will occur in a larger angle of attack, greater angular velocity and elastic displacement.

In order to carefully study the behavior of aeroelastic flight vehicle, a nonlinear model and analysis is definitely necessary. Moreover, for the design of the airframe and/or control purposes, it is essential to investigate region of attraction of equilibrium state of the stable flight vehicle.

Current stability analysis methods for nonlinear elastic flight vehicles are unable to determine the state space region where the system is stable. Nonlinear modeling affects the determination of the stability region and instability condition. This paper presents a new approach to stability analysis of the nonlinear flexible flight vehicle. By determining the region of attraction when the system is stable, it is demonstrated analytically, in this research, that decreasing the dynamic pressure can produce larger region of attraction.

The purpose of this paper is to present a quick inspection method based on the post-flight data to examine static aeroelastic behavior for transport aircraft subjected to instantaneous high g-loads.

In the present study, the numerical approach of static aeroelasticity and two verified cases will be presented. The non-linear unsteady aerodynamic models are established through flight data mining and the fuzzy-logic modeling of artificial intelligence techniques based on post-flight data. The first and second derivatives of flight dynamic and static aeroelastic behaviors, respectively, are then estimated by using these aerodynamic models.

The flight dynamic and static aeroelastic behaviors with instantaneous high g-load for the two transports will be analyzed and make a comparison study. The circumstance of turbulence encounter of the new twin-jet is much serious than that of four-jet transport aircraft, but the characteristic of stability and controllability for the new twin-jet is better than those of the four-jet transport aircraft; the new twin-jet transport is also shown to have very small aeroelastic effects. The static aeroelastic behaviors for the two different types can be assessed by using this method.

As the present study uses the flight data stored in a quick access recorder, an intrusive structural inspection of the post-flight can be avoided. A tentative conclusion is to prove that this method can be adapted to examine the static aeroelastic effects for transport aircraft of different weights, different sizes and different service years in tracking static aeroelastic behavior of existing different types of aircraft. In future research, one can consider to have more issues of other types of aircraft with high composite structure weight.

This method can be used to assist airlines to monitor the variations of flight dynamic and static aeroelastic behaviors as a complementary tool for management to improve aviation safety, operation and operational efficiency.

The purpose of this paper is to investigate the relationship between the formability of cotton and cotton/polyester woven fabrics and their selected properties: weft density, weave and a way of finishing. It shows how the mentioned properties influence fabric formability and analyze a statistical significance of investigated relationships.

In paper two groups of cotton and cotton/polyester woven fabrics of different structure and a way of finishing have been measured in the range of their basic structural properties as well as bending rigidity and initial Young’s modulus. Formability of investigated fabrics has been calculated on the basis of bending rigidity and initial Young’s modulus. Next, ANOVA has been performed in order to analyze the relationships between the weft density, weave and a way of finishing of woven fabrics and their formability.

The paper shows that all selected properties of woven fabrics significantly influence their formability as well as that there is statistically significant interaction between mentioned independent factors. It provides empirical results confirming that the influence of raw material composition of investigated cotton and cotton/polyester woven fabrics on the formability of fabrics is statistically insignificant.

Results of investigations can be applied for cotton and cotton-like woven fabrics.

The paper includes implications for woven fabric engineering from the point of view of achieving the expected fabric formability.

The results enables the choice of appropriate fabric for the given clothing.

This paper fulfills an identified need to study how the formability of woven fabrics can be shaped by an appropriate selection of their structure and a way of finishing.

This study aims to present a diagnosis method to inspect the structure health for aging transport aircraft based on the postflight data in severe clear-air turbulence at transonic flight. The purpose of this method development is to assist certificate holder of aircraft maintenance factory as a complementary tool for the structural maintenance program to ensure that the transport aircraft fits airworthiness standards.

In this study, the numerical approach to analyze the characteristics of flight dynamic and static aeroelasticity for two four-jet transport aircraft will be presented. One of these two four-jet transport aircraft is an aging one. Another one is used to demonstrate the order of magnitude of the static aeroelastic behaviors. The nonlinear unsteady aerodynamic models are established through flight data mining and the fuzzy-logic modeling technique based on postflight data. The first and second derivatives of flight dynamic and static aeroelastic behaviors, respectively, are then estimated by using these aerodynamic models.

Although the highest dynamic pressure of aging aircraft is lower, the highest absolute value of static aeroelastic effects response to the wing of aging aircraft is about 3.05 times larger than normal one; the magnitude variations of angles of attack are similar for both aircrafts; the highest absolute value of the static aeroelastic effects response to the empennage of aging aircraft is about 29.67 times larger than normal one in severe clear-air turbulence. The stabilizer of aging aircraft has irregular deviations with obvious jackscrew assembly problems, as found in this study.

A lack of the measurement data of vertical wind speed sensor on board to verify the estimated values of damping term is one of the research limitations of this study. This research involved potential problem monitoring of structure health for transport aircraft in different weights, different sizes and different service years. In the future research, one can consider more structural integrity issues for other types of aircraft.

It can be realized from this study that the structure of aging transport aircraft may have potential safety threat. Therefore, when the airline managed aging transport aircraft, it ought to be conducted comprehensive and in-depth inspections to reduce such safety risks and establish a complete set of safety early warning measures to deal with the potential problem of aircraft aging.

It can be realized that the structure of aging transport aircraft has potential safety threat. The airline managed aging transport aircraft; it should conduct comprehensive and in-depth inspections to reduce safety risks and establish a complete set of safety early warning measures.

This method can be used to assist airlines to monitor aging transport aircraft as a complementary tool of structural maintenance program to improve aviation safety, operation and operational efficiency.

This paper aims to develop a new approach for aeroelastic analysis of hingeless rotor blades.

The aeroelastic approach developed here is based on the geometrically exact fully intrinsic beam equations and three-dimensional unsteady aerodynamics.

The developed approach is accurate, fast and very useful in rotorcraft aeroelastic analysis.

This beam formulation has been never combined with three-dimensional aerodynamic model to be used for aeroelastic analysis of blades. In addition, it is possible to handle the composite blades, as well as blades with initial curvatures and twist with this proposed formulation.