Sharif Digital Repository

The purpose of this research study is to evaluate the solutions of Titanium and Aluminum alloy nanofluidic model with gyrotactic microorganisms (TAA-NFMGM) by applying stupendous knacks of Bayesian distributed adaptive neural structure (BDANS). The use of nanofluids containing gyrotactic microorganisms in combination with titanium and aluminum alloys have potential applications in diverse fields, including engineering, bioremediation, biomedical devices, biotechnology, and research depending on different factors like design of the system and use of certain microorganism. A dataset for BDANS is generated for the eight different events with Adam numerical technique for TAA-NFMGM by varying... 

This research work presents the numerical solution of the Darcy-Forchheimer flow of Casson nanofluidic model (DFFCNFM) on stretching sheets with Newtonian heating by utilizing a combination of nonlinear input-output neural networks with backpropagation of Levenberg-Marquardt computational approach. The presented study investigates the impact of electroosmosis forces on the boundary layer of the Casson nanofluid, focusing on viscous and Joule dissipations. A dataset for DFFCNFM is generated for the different events with backward differentiation formula (BDF) by varying Casson fluid parameter (β), permeability parameter (Da), electric parameter (E1), Reynolds number (Re) relative to stretching... 

The presented work examines the dynamics of convective Eyring–Powell magneto-nanofluid model (CEP-MNFM) with a stretching cylinder by using stupendous knacks of supervised stochastic Levenberg–Marquardt intelligent networks (SSLMINs). The partial differential equations governing the CEP-MNFM are reduced into coupled ODEs by incorporating the similarity transformations. The dataset of the proposed SSLMINs approach is generated with state-of-the-art Adam numerical method for seven different scenarios of CEP-MNFM including variation of radiation, Brownian diffusivity, and thermophoresis parameter, as well as, Biot, Schmidh, and Prandtl numbers. The reference dataset is further utilized for... 

Curcumin incorporated polyurethanes (CPU) are gaining much attention as a biomaterial. However, challenges are still remained due to hydrophobicity and low mechanical strength of CPU. Herein, we synthesized the CPU/ZnO nanocomposites with good mechanical and improved hydrophilic properties via in-situ polymerization. A series of curcumin incorporated polyurethane with different concentrations of ZnO nanoparticles (ZnCPU) are synthesized by using the curcumin, polyethylene glycol (PEG) as the soft segment, hexamethylene diisocyanate (HDI) as the hard segment, and 1,4-butanediol (BDO) as the chain extender. The addition of ZnO nanoparticles (NPs) facilitated the soft domain of PU which is... 

Porphyrin-POM hybrid materials with excellent NLO properties are supposed to be a worthy entrant for forthcoming telecommunication, optical fibers, optical data storage and optical limiting devices, but due to adverse solubility problems, they are replaced by polymeric materials. Herein, we assessed third order NLO and second hyperpolarizability of porphyrin-polyimide compounds (NH-PI and Zn-PI) synthesized from the reaction of 4,4ʹ-hexafluoroisopropylidene-diphthalic anhydride (6FDA) with C44H32N6 (NH-DATPP) and C44H30N4Zn (Zn-DATPP) porphyrins under ambient conditions. The Z-scan measurement of these compounds revealed reverse saturation absorption as well as self-defocusing performance.... 

The objective of this research is to establish the modelling and evaluation of a differential mathematical system for the radiated Carreau nanofluid model (RCNFM) by exploiting the skills of stochastic computing with Levenberg–Marquardt neural networks (SCLMNNs).The reference dataset is created using the Adams technique in the Mathematica software by variation of various physical quantities. The reference data results are trained using a split of seventy percent for training and thirty percent for validation and testing methods. This approach aims to enhance and compare the estimated outcomes with established solutions. The precision and efficacy of the developed stochastic computing with... 

Magnetic nanoliquids are pondered cutting-edge heat transference liquids, representing a modern generation because of their aptitude to function as smart liquids. The deployed magnetism externally exerts a readily manageable impact, escalating their adaptableness and practicality in various applications. In this analysis, electro magnetized Powell-Eyring rheological nanoliquid is modeled considering stretching cylinder based buoyancy-driven flow. Transport expressions include thermal radiation, Brownian diffusion, chemical reaction, thermophoresis, and thermal source effect. Prandtl theory of boundary-layer (BL) assists to develop the governing problems. Appropriate transformations are... 

Although flooding and its variants are widely deployed for broadcasting by different applications, there are limited results on a complete and comprehensive analytical framework describing their behavior in general cases. We have previously published results which provide an upper bound for the performance of flooding when flooded packets have the highest serving priority. In this paper, using a different and simpler approach, we develop an analytical framework for analysis of flooding in general cases where flooding packets do not receive any special priority treatment in the network. The analysis is performed for a static multi-hop ad hoc wireless network using CSMA as its MAC layer. The... 

There are applications where important and critical data should be sent to all nodes in a wireless Ad-hoc network. Flooding and its variants are typically used to achieve this target. Network coding can also be used for broadcasting in such an environment. Energy consumption in the network, coverage and total delay are all important parameters that should be considered when an algorithm is evaluated. In this article, a reliable and energy efficient single source broadcasting algorithm is proposed based on network coding. This algorithm guarantees the delivery of desired messages to all network nodes, consumes less energy compared and reduces the total delay compared to other algorithms. This... 

Al–5·6Zn, Al–5·6Zn–2·5Mg and Al–5·6Zn–2·5Mg–1·6Cu (wt-%) powder blends were compacted at 350 MPa and sintered in nitrogen at different temperatures to study microstructural evolution during sintering. Densification, dimensional changes and mechanical properties of the Al alloys were investigated. Microstructural analyses were performed by scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and simultaneous thermal analysis (STA) in order to determine the temperature and chemical composition of the phases formed during sintering. It was shown that various liquids and intermetallic phases including Al0·71Zn0·29 at 438°C,... 

Rare earth oxides with a trivalent nature play a pivotal role in reinforcing the magneto-optical attributes of spinel ferrite nanoparticles by replacing Fe3+ ions. In this study, rare earth Gd oxide doped with CoFe2O4 NPs with a composition of Co1+xGdxFe2-2xO4 (x = 0, 0.05, 0.10, and 0.15) were synthesized using sol-gel auto-combustion. The outcome of Gd cations on the physical, magneto-optical and electrical characteristics of the cobalt ferrite NPs were reported. X-ray diffraction (XRD), and Fourier transform infrared (FTIR) investigations confirmed the single-phase cubic crystalline nature and metal ion stretching in the cobalt ferrite synthesized samples. Decreasing drift in the average... 

Rare earth oxides with a trivalent nature play a pivotal role in reinforcing the magneto-optical attributes of spinel ferrite nanoparticles by replacing Fe3+ ions. In this study, rare earth Gd oxide doped with CoFe2O4 NPs with a composition of Co1+xGdxFe2-2xO4 (x = 0, 0.05, 0.10, and 0.15) were synthesized using sol-gel auto-combustion. The outcome of Gd cations on the physical, magneto-optical and electrical characteristics of the cobalt ferrite NPs were reported. X-ray diffraction (XRD), and Fourier transform infrared (FTIR) investigations confirmed the single-phase cubic crystalline nature and metal ion stretching in the cobalt ferrite synthesized samples. Decreasing drift in the average... 

Rate, energy and delay are three main parameters of interest in ad-hoc networks. In this paper, we discuss the problem of maximizing network utility and minimizing energy consumption while satisfying a given transmission delay constraint for each packet. We formulate this problem in the standard convex optimization form and subsequently discuss the tradeoff between utility, energy and delay in such framework. Also, in order to adapt for the distributed nature of the network, a distributed algorithm where nodes decide on choosing transmission rates and probabilities based on their local information is introduced. ©2009 IEEE