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This research makes a first attempt to investigate the dynamic characteristics of functionally graded carbon nanotube–reinforced composite plates and shell structures with surface-bonded piezoelectric layers. A variational formulation is derived based on the linear double director shell theory to ensure realistic parabolic variation of transverse shear strain along the thickness direction. The assumed natural strains method is adopted to enhance the accuracy of the four-node piezoelectric shell element developed in this study. Numerical studies are conducted to validate the efficiency and numerical stability of the proposed model to predict the behavior of piezolaminated composite shell structures. Furthermore, dynamic responses are extended to functionally graded carbon nanotube–reinforced composite shells covered by two active layers. The host structure is reinforced by single-walled carbon nanotubes, which are assumed to be graded through the thickness direction with different types of distributions and embedded in a polymer matrix. The effect of the volume fractions, distribution type, and geometrical parameters of the carbon nanotubes is examined.

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In this research work, design optimization and static analysis of a 3D printed based carbon PEEK (poly ether ether ketone, reinforced with carbon) polymer composite mono leaf spring was done using finite element analysis. Comparative study of leaf springs of a Dodge SUV car has been made by using 3D printed carbon PEEK. The main objective of this work is to optimize the design and material parameters, such as fiber diameter, fiber length, percentage volume of fibers and orientation angle of fibers in 3D printed based material with a mono polymer composite leaf spring. The effects of these parameters were studied to evaluate the deflection, bending stress, spring rate, stiffness and von Mises stress under different loading conditions. Furthermore investigation has been done to reduce the weight of leaf springs and claimed the 3D printed based leaf springs have better load carrying capacity. Thus an attempt has been made in this regard and we selected the 3D printed carbon PEEK in developing product design and material selection for minimum deflection and bending stress by means of response surface optimization methodology for an efficient leaf spring suspension system. The 3D printed carbon fiber polymer composite has three different percentage volume fractions such as 30%, 50%, and 60%. The selected carbon PEEK has 0°, 45°, and 90° fiber orientations. Finite element based analysis has been performed on 3D printed carbon PEEK material to conclude the optimized design parameters and best possible combination of factors affecting the leaf spring performance.

Compound nanoparticle drug delivery system plays an important role in the interaction with lymph nodes. There are three primary types of lymphocytes: B cells, T cells, and natural killer cells. When the cells of the immune system turn carcinogenic, they assault body cells. The lymph fluid plays an important role in attacking healthy cells of the body; hence, this paper aimed to design a drug delivery system, which can efficiently direct nanoparticles to target the infected cells, helping in high-speed elimination of such cells. The proposed design depends on the interaction between these molecules, and the intelligent nano-controller has the ability to guide the nanoparticles by anaerobic contact. The proposed design proved that the smaller the nanoparticle size and density, the less dynamic viscosity of the liquid would be, which would reflect its resistance to flow. In addition, it was concluded that hydrogen molecules play a significant role in reducing lymphatic fluid resistance due to their low density.

Abstract-The Scalable High Efficiency Video Coding (SHVC) has been proposed to improve the coding efficiency. However, this additional extension generally results an important coding complexity. Several studies were performed to overcome the complexity through algorithmic optimizations that led to an encoding time reduction. In fact, mode decision analysis is imperatively important in order to have an idea about the partitioning modes based on two parameters, such as prediction unit size and frame type. This paper presents statistical observations at two levels: coding units (CUs) and prediction units (PUs) selected by the encoder. Analysis was performed for several test sequences with different motion and texture characteristics. The experimental results show that the percentage of choosing coding or prediction unit size and type depends on sequence parameters, frame type, and temporal level.

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