This study discusses a hypothetical method for tracking the propagation damage of Carbon Reinforced Fiber Plastic (CRFP) components underneath vibration fatigue. The High Cycle Fatigue (HCF) behavior of composite materials was generally not as severe as this of admixture alloys. Each fissure initiation in metal alloys may quickly lead to the opposite. The HCF behavior of composite materials is usually an extended state of continuous degradation between resin and fibers. The increase is that any layer-to-layer contact conditions during delamination opening will cause a dynamic complex response, which may be non-linear and dependent on temperature. Usually resulted from major deformations, it could be properly surveyed by a non-contact investigation system. Here, this article discusses the scanning laser application of that vibrometer to track the propagation damage of CRFP components underneath fatigue vibration loading. Thus, the study purpose is to demonstrate that the investigation method can implement systematically a series of hypothetical means and dynamic characteristics. The application of the relaxation method based on numerical simulation in the Artificial Intelligence (AI) Evolved Bat (EB) strategy to reduce the dynamic response is proved by numerical simulation. Thermal imaging cameras are also measurement parts of the chain and provide information in qualitative about the temperature location of the evolution and hot spots of damage.

Composite components damage tracking and dynamic structural behaviour with AI algorithm

Due to the feasibility of the gray model for predicting time series with small samples, the gray theory is well investigated since it is presented and is currently evolved in an important manner for forecasting small samples. This study proposes a new gray prediction criterion based on the Neural Ordinary Differential Equation (NODE), which is named the NODGM (Neural Based Ordinary Differential gray Mode). This mode permits the forecasting approximation to be learned by a training process which contains a new whitening equation. It is needed to prepare the structure and time series, compared with other models, according to the regularity of actual specimens in advance, therefore this model of NODGM can provide comprehensive applications as well as learning the properties of distinct data specimens. In order to acquire a better model which has highly predictive efficiency, afterwards, this study trains the model by NODGM meanwhile using the Runge-Kutta method to obtain the prediction sequence and solve the model. The controller establishes an advantageous theoretical foundation in adapting to novel wheels and comprehensive spreads the utilize extent of Mechanical Elastic Vehicle Wheel (MEVW). 

Neural ordinary differential gray algorithm to forecasting nonlinear systems

To ensure the asymptotic stability and improve the ride comfort of vehicles, this paper develops a fuzzy neural network (NN) based evolved bat algorithm (EBA) to design adaptive backstepping controllers with grey signal predictors. The Lyapunov theory and backstepping method were employed to evaluate the nonlinearity of controlled systems and derive the evolved control law for the signal tracking. The discrete grey model DGM (2,1) is utilized to obtain future movement of the nonlinear system, so that the command controller can prove the Lyapunov stability and feasibility of the entire scheme through the Lyapunov-like lemma. The controller design criterion is demonstrated in the range of mechanical elastic wheel (MEW) and lays a feasible mathematical framework for the matching of new wheels.

Grey signal predictor and FNN evolved control for practical nonlinear systems

Rotating MHD flow and heat transfer of generalized Maxwell fluid through an infinite plate with Hall effect


Purpose
To prove the effectiveness of the proposed design method, this study aims to propose the Fisher equation and temperature cooling fins that control high-speed aerospace vehicles.


Design/methodology/approach
A new approach whereby the control of aerospace vehicles can be achieved by fuzzy controller and appropriate Navier–Stokes equations in this article. The design of the controller based on models of Navier–Stokes equations simplified complex mathematical simulations and approximations.


Findings
If the fuzzy controller cannot stabilize the system, the Navier–Stokes fuzzy function is injected into the system as a controller tool, and the system is asymptotically stabilized by adjusting the fuzzy parameters.


Originality/value
The simulation results show that if the tuning frequency is high enough, the fuzzy controller and fuzzy observer can create chaotic movements by adjusting the dither amplitude appropriately. The demonstration of the Fisher equation and the temperature-cooled fin control problem for high-speed aerospace vehicles has displayed the benefits of combining fuzzy control with the Navier–Stokes equation.


Systematic fuzzy Navier–Stokes equations for aerospace vehicles

In recent years, with the maximization of control design and efficiency, and the improvement of economy and energy efficiency, building technology and control in the theory have attracted the attention of lots researchers. By trying various control theorems, many numerical methods have been investigated in the literature to achieve this target, but all these numerical methods are difficult to work out the problem correctly. This paper puts forward a potentially feasible evolutionary bat algorithm (EB) method for active control of earthquake-induced vibration in building structures. Based disturbance observer based control and S surface combined with the robust adaptive control scheme for solving optimization problems proposed, an important contribution in the control law is what the configuration control in the present study should not require known uncertainty limits and the disturbance is eliminated. A simulation case study was proposed to illustrate the possibility of implementing an apparent learning method in ANN to effectively control structural vibration under the influence of systematic motion under earthquake citations. The proposed learning numerical methods does not need to develop a mathematical model of structural dynamics or train another neural network to approximate the actual structural response to be performed.

Smart structural control and analysis for earthquake excited building with evolutionary design

Grey Signal Predictor and Evolved Control for Practical Nonlinear Mechanical Systems

The finite difference schemes for equations depicting the fluid flow, heat and mass transfer of viscoelastic fluid in porous media based on fractional constitutive model are analyzed, when Soret and Dufour effects are taken into account. Different from the conventional fractional partial differential equations, the governing momentum equation of this system not only contains convection terms, but also a term: D t β 0 ( ∂ 2 u / ∂ y 2 ) , which are great challenges when we do the stability analysis. In addition, the temperature equation and concentration equation are coupled with each other, which increases the difficulty of numerical analysis. By using the energy method, the stability and convergence of the finite difference schemes employed for the governing equations are obtained. The accuracy of the scheme for momentum equation is O ( τ + h x 2 + h y 2 ) , while the one for temperature and concentration equations is O ( τ 2 + h x 2 + h y ) . Finally, numerical examples are presented to verify methods and demonstrate the analysis effectiveness. 

Numerical analysis of fractional viscoelastic fluid problem solved by finite difference scheme

Solving generalized fractional problem on a funnel-shaped domain depicting viscoelastic fluid in porous medium

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