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The present work investigates higher order stress, strain and deformation analyses of a shear deformable doubly curved shell manufactures by a Copper (Cu) core reinforced with graphene origami auxetic metamaterial subjected to mechanical and thermal loads. The effective material properties of the graphene origami auxetic reinforced Cu matrix are developed using micromechanical models cooperate both material properties of graphene and Cu in terms of temperature, volume fraction and folding degree. The principle of virtual work is used to derive governing equations with accounting thermal loading. The numerical results are analytically obtained using Navier's technique to investigate impact of significant parameters such as thermal loading, graphene amount, folding degree and directional coordinate on the stress, strain and deformation responses of the structure. The graphene origami materials may be used in aerospace vehicles and structures and defence technology because of their low weight and high stiffness. A verification study is presented for approving the formulation, solution methodology and numerical results.

This study analyses the two-dimensional thermo-elastic response of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) cylindrical pressure vessels, by applying the third-order shear deformation theory (TSDT). The effective properties of FG-CNTRC cylindrical pressure vessels are computed for different patterns of reinforcement, according to the rule of mixture. The governing equations of the problem are derived from the principle of virtual works and are solved as a classical eigenproblem under the assumption of clamped supported boundary conditions. A large parametric investigation aims at showing the influence of some meaningful parameters on the thermo-elastic response, such as the type of pattern, the volume fraction of CNTs, and the Pasternak coefficients related to the elastic foundation.

This paper presents a free vibration analysis of functionally graded (FG) polymer composite curved nanobeams reinforced with graphene nanoplatelets resting on a Pasternak foundation. The size-dependent governing equations of motion are derived by applying the Hamilton’s principle and the differential law consequent (but not equivalent) to Eringen’s strain-driven nonlocal integral elasticity model equipped with the special bi-exponential averaging kernel. The displacement field of the problem is here described in polar coordinates, according to the first order shear deformation theory. A large parametric investigation is performed, which includes different FG patterns, different boundary conditions, but also different geometrical parameters, number of layers, weight fractions, and Pasternak parameters.

The purpose of this research is to present the wave propagation analysis of a functionally graded nano-rod made of magneto-electro-elastic material subjected to an electric and magnetic potential. The unified nonlocal elasticity theory and Love's rod model are used in this study. All mechanical, electrical and magnetic properties are assumed to be variable along the thickness direction based on a power law distribution. Two-dimensional electric and magnetic potential distributions due to an applied potential and a magnet at the top of the rod are considered. The governing equations of motion are obtained using equilibrium and nonlocal theory of elasticity in conjunction with the Hamilton principle. The effect of important parameters of the functionally graded magneto-electro-elastic nano-rod such as nonlocal parameters, power index, wave number, applied magnetic and electric potentials on the wave propagation characteristics is studied.

Here, an adaptive radial basis function (RBF) neural network (NN) backstepping controller is proposed for a class of input‐constrained flexible joint robotic manipulators represented by strict‐feedback form with unknown terms, external stochastic disturbance, and output disturbance. The proposed approach is robust against both deterministic and stochastic uncertainties and disturbances and copes with the control input amplitude saturation. Moreover, by deploying the minimal learning parameter method and command filter technique, the computational burden of derivative terms and adaptive terms greatly decreases. Considering the mean‐value theorem assists us to avoid the need for having the input saturation bounds in prior. The suggested tracking control scheme mandates the closed‐loop system states to be semi‐globally bounded‐in‐probability. Also, a quartic Barrier Lyapunov function is utilized to force the tracking error to be confined within a pre‐chosen small region around the origin. Eventually, a numerical simulation of a flexible joint robot manipulator with a single link is performed to show the effectiveness and performance of the developed control method. An adaptive neural network backstepping controller is proposed for input‐constrained flexible joint robotic manipulators with unknown terms, external stochastic disturbance, and output disturbance. Deploying the minimal learning parameter and command filter techniques decreases the computational burden. Considering the mean‐value theorem avoids the pre‐need for input saturation bounds. The quartic Barrier Lyapunov function confines the tracking error and mandates semi‐globally bounded‐in‐probability.

Background Both augmented inflammatory reaction and low vitamin D status are associated with depression but the magnitude of their relationships is unclear. This study was, therefore, conducted to evaluate the effects of vitamin D supplementation on serum 25(OH)D concentration, depression severity and some pro-inflammatory biomarkers in patients with mild to moderate depression. Methods An 8-week double-blind randomized clinical trial (RCT) was performed on 56 (18–60 yrs) patients with mild to moderate depression, randomly assigned to intervention (50,000 IU cholecalciferol 2wks −1 ) and control (placebo) groups. Serum 25(OH)D, intact parathyroid hormone (iPTH), interlukin (IL)-1β, IL-6, high-sensitivity C-reactive protein (hs-CRP) and depression severity (Beck Depression Inventory-II) (BDI-II)) were initially and finally assessed. Results At the end point, statistically significant changes were observed only in intervention group as compared with controls including increased 25(OH)D concentration (+ 40.83 ± 28.57 vs. + 5.14 ± 23.44 nmol L −1 , P  < 0.001) and decreased depression severity (-11.75 ± 6.40 vs. -3.61 ± 10.40, P  = 0.003). No significant within- or between group differences were observed in serum IL-1β, IL-6 and hs-CRP concentrations. Conclusion Increased circulating 25(OH)D concentrations following 8-week vitamin D supplementation (50,000 IU 2wks −1 ) resulted in a significant decrease in BDI-II scores in patients with mild to moderate depression. However, this effect was independent of the serum concentrations of the studied inflammatory biomarkers. Trial registration The clinical trial registration code was obtained from the Iranian Registry of Clinical Trials (date of registration: 17/09/2018, registration number: IRCT20170926036425N1) and ClinicalTrials.gov (date of registration: 04/12/2018, registration number: NCT03766074)

In this paper, dynamic characteristics of microconical sandwich shells are investigated. The microshell is considered to consist of a porous core made of a polymer and two face sheets made of that polymer which is reinforced by graphene nanoplatelets (GPLs). The face sheets effective mechanical characteristics are estimated utilizing the rule of mixture along with the Halpin–Tsai model, and size effects are incorporated based on the modified couple stress theory. Hamilton’s principle is applied for derivation of governing equations of motion as well as boundary condition in which differential quadrature method is employed for numerical solution. The accuracy of the presented solution is examined using the benchmark results reported in other papers. Influences of different parameters on the natural frequencies in the various vibrational modes of the microshells are examined, including the wave number, micro-length-scale parameter, the thickness of the porous core, dispersion patterns of the pores and the GPLs, porosity parameter, total mass fraction of the GPLs, and also the semi-vertex angle of the cone.

This research deals with the nonlinear vibration of the functionally graded nano-beams based on the nonlocal elasticity theory considering surface and flexoelectric effects. The flexoelectric functionally graded nano-beam is resting on nonlinear Pasternak foundation. Cubic nonlinearity is assumed for foundation. It is assumed that the material properties of the nano-beam change continuously along the thickness direction according to different patterns of material distribution. In order to include coupling of strain gradients and electrical polarizations in equation of motion, the nonlocal, nonclassical nano-beam model containing flexoelectric effect is employed. In addition, the effects of surface elasticity, di-electricity, and piezoelectricity as well as bulk flexoelectricity are accounted in constitutive relations. The governing equations of motion are derived using Hamilton principle based on first shear deformation beam theory and the nonlocal strain gradient elasticity theory considering residual surface stresses. The differential quadrature method is used to calculate nonlinear natural frequency of flexoelectric functionally graded nano-beam as well as nonlinear vibrational mode shape. After validation of the present numerical results with those results available in literature, full numerical results are presented to investigate the influence of important parameters such as flexoelectric coefficients of the surface and bulk, residual surface stresses, nonlocal parameter, length scale effects (strain gradient parameter), cubic nonlinear Winkler and shear coefficients, power gradient index of functionally graded material, and geometric dimensions on the nonlinear vibration behaviors of flexoelectric functionally graded nano-beam. The numerical results indicate that, considering the flexoelectricity leads to the decrease of the bending stiffness of the flexoelectric functionally graded nano-beams.

In this paper, a direct adaptive robust controller for a class of SISO nonaffine nonlinear systems is presented. The existence of an ideal controller is proved based on the Implicit Function Theorem. Since the Implicit Function Theorem only guarantees the existence of the controller and does not provide a way to construct it, a neural network is employed to approximate the unknown ideal controller. In addition, an observer is designed to estimate the system states because all the states may not be available for measurements. In this method, a priori knowledge about the sign of control gain is not required and, in order to cope with unknown control direction, the Nussbaum-type technique is used. Moreover, only one adaptive parameter is needed to be updated and also a robust term is used in the control signal to reduce the effect of external disturbances and approximation errors. Furthermore, the stability analysis for the closed-loop system is presented based on the Lyapunov stability method. Theoretical results are illustrated through a simulation example. These simulations show the effectiveness of the proposed method.

Battery management systems (BMSs) are critical to ensure the efficiency and safety of high-power battery energy storage systems (BESSs) in vehicular and stationary applications. Recently, the proliferation of battery big data and cloud computing advancements has led to the development of a new generation of BMSs, named Cloud BMS (CBMS), aiming to improve the performance and safety of BESSs. The CBMS is a cyber-physical system with connectivity between the physical BMS and a cloud-based virtual BMS, which is realized through a communication channel such as Internet of Things. Compared to the traditional BMS, the CBMS offers significantly higher computational resources, leveraging the implementation of advanced digital twin models and best-in-class algorithms in the BMS software, which will provide superior performances. However, as for any other CPS, the CBMS creates vulnerabilities against cyberattacks and if not properly secured, could end up damaging the BESS and/or causing dangerous, expensive, and life-threatening situations. Cybersecurity of the CBMSs has thus become a trending topic and several works have been published in this area in recent years. This paper conducts a scoping review to address different topics related to BMS cybersecurity. The CBMS architecture is presented, and the potential cyberattack surfaces are identified. Different possible attack scenarios, including attack points, attack types, and their impact at the component level (BMS and BESS) and system level (vehicle or grid), are discussed. In addition, the paper provides a review of potential countermeasures to protect the CBMS against cyberattacks. The paper also includes a review of the applicable standards and regulations that relate to this trending topic. Finally, based on the reviewed gaps, potential future research domains on BMS cybersecurity topics are identified and presented at the end of the paper.