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This study is designed to analyze the fuzzy dynamical model of vibrating mass system by using neural networks (NNs). Stochastic numerical solvers are implemented with Levenberg–Marquardt backpropagation (LMB) algorithm. The proposed solvers handle the uncertainties of fuzzy differential system and minimize the error consistently. Validation, constancy and verification of NNs with LMB algorithm are endorsed by attaining reasonable accuracy through statistical measures in terms of error histograms, regression and mean squared errors for different values of fuzzy parameters. [ABSTRACT FROM AUTHOR]

In this research paper, an innovative bio-inspired algorithm based on evolutionary cubic splines method (CSM) has been utilized to estimate the numerical results of nonlinear ordinary differential equation Painlevé-I. The computational mechanism is used to support the proposed technique CSM and optimize the obtained results with global search technique genetic algorithms (GAs) hybridized with sequential quadratic programming (SQP) for quick refinement. Painlevé-I is solved by the proposed technique CSM-GASQP. In this process, variation of splines is implemented for various scenarios. The CSM-GASQP produces an interpolated function that is continuous upto its second derivative. Also, splines proved to be stable than a single polynomial fitted to all points, and reduce wiggles between the tabulated points. This method provides a reliable and excellent procedure for adaptation of unknown coefficients of splines by searching globally exploiting the performance of GA-SQP algorithms. The convergence, exactness and accuracy of the proposed scheme are examined through the statistical analysis for the several independent runs. [ABSTRACT FROM AUTHOR]

The growing interest in emerging nanotechnologies has led the scientists towards to investigate the interaction of nanoparticles with fluids. Current continuation endeavors the rheological analysis for the Oldroyd-B nanomaterial across periodically accelerated and heated surface. The interesting features of thermophoresis and Brownian motions are presented by following famous Buongiorno nanofluid model. Further, Cattaneo–Christov heat and mass flux expressions are exploited to determine the characteristics of thermal and mass diffusions. As a novelty, the variable thermal conductivity and heat absorption/generation consequences are also utilizing the energy equation. The flow model has been developed by using concerning boundary layer equations which are converted into dimensionless forms by using appropriate variables. The analytical solution of such transmuted equations is computed by using homotopy analytic method. Various physical parameters of interest are scrutinized through various graphs. The observations from analysis convey a declining change in nanofluid concentration and temperature with variation of thermal and solutal relaxation parameters, respectively. Moreover, thermophoresis parameter causes an enhancement of concentration profile while a retarded concentration profile results with increment of Schmidt number. The obtained theoretical results reflect significant applications in cooling and heating systems, thermal sciences, manufacturing processes, extrusion systems, enhancement of transport of energy and heat resources. [ABSTRACT FROM AUTHOR]

The main focus of this research is to explore the consequences of motile gyrotactic microorganisms for unsteady Williamson nanofluid induced by bidirectional periodically accelerated surface. The combined features of magnetic and buoyancy forces with association of nanoparticles and swimming microorganisms developed the nanofluid bioconvection. Thermal radiation and heat generation aspects are considered to analyze the heat transportation phenomenon. The consequences of activation energy and chemical reaction are further explored for physical relevance. Appropriate transformations have been employed to transmute the formulated nonlinear equations into dimensionless form, and then analytically elucidated by homotopic technique. The effect of diverse dominant parameters on velocities, concentration, temperature, motile microorganisms as well as skin friction coefficients are deliberated through various graphs while the deviation in local Sherwood, Nusselt and motile density numbers have been deliberated by numerical data in tabular form. It is noticed that both velocity components periodically drop for augmentation in Williamson parameter. Current investigation accentuated that higher reaction rate leads to decay in concentration distribution, but impact of activation energy parameter is rather conflicting. Furthermore, the profile of motile microorganism leads to be intensified for higher magnetic parameter, while opposite trend is perceived for bioconvected Peclet and Lewis numbers. [ABSTRACT FROM AUTHOR]

This paper portrays the exploitation/exploration of artificial intelligence (AI) inspired computing to study the behavior of the multi-delay differential systems that revealed the impact of latent period and the dynamics of the a susceptible, vaccinated, exposed, infectious and recovered (SVEIR) epidemic model involving vaccination by means of the neural networks backpropagation with Levenberg–Marquardt scheme (NNs-BLMS). The reference solutions of the five classes ordinary differential equations (ODEs) model of SVEIR dynamics are calculated by applying the Adams method for variation in delay due to the time spent in preventing the infection and delay due to the duration of recovery immunity in the cured population. The designed NNs-BLMS used the created dataset arbitrarily for training, validation, as well as, testing samples to determine the estimated results of the nonlinear SVEIR epidemic model involving vaccination impact. The achieved accuracy of the designed NNs-BLMS is authenticated/proven by analyzing the fitness function based on mean square error (MSE), regression analysis, and error histogram for sundry scenarios of SVEIR epidemic system with the impact of vaccination. [ABSTRACT FROM AUTHOR]

We studied the thermo-elastic properties of Ru2Fe Z ( Z=Si, Ge, Sn) Heusler alloys within the framework of density functional theory. Thermo-elastic properties corresponding to elastic modulus, anisotropy, phase stability, elastic wave velocities, thermal stability, Debye temperature, melting temperature, thermal conductivity and formation energy are calculated. The elastic constants C predict the structural and dynamical stabilities while the formation energies show thermal stability of the alloys at 0 K. Pugh's and Poisson's ratios display the ductile nature of alloys. All alloys are anisotropic and we also observed that Ru2FeSn is the hardest material than Ru2FeSi and Ru2FeGe. Moreover, longitudinal mode of vibrations are also observed and are maximum along [100], [110] and [111] directions than the transverse mode of vibrations. [ABSTRACT FROM AUTHOR]

In this paper, we communicate a new type of Auger-free luminescence (AFL) compounds, alkali tin fluorides ASnF3 (A = Na, K, Rb and Cs). The luminescence in these compounds originates due to the electron transition from the top valence band (VB) of tin- orbital to the outermost core levels of halogen, i.e., halogen- orbital (- transitions). The AFL of these compounds is expected to be of L-type. Furthermore, the electronic band structures and optical properties such as dielectric functions, refractive index and energy loss function are also investigated using ab initio calculations. [ABSTRACT FROM AUTHOR]

The nanoparticles convey noteworthy applications in many engineering and industrial systems like cooling and heat processes, thermal extrusion systems, heat exchangers, as an energy source, treatment of various diseases and chemotherapy. Owing to such importance of nanomaterials, various studies are presented for nanofluids with diverse flow features. This investigation discloses an unsteady flow of Cross nanofluid over periodically accelerated imbedded in porous space. The combined heat and mass transportation aspects of nanomaterials are entertained with applications of Buongiorno's model. Further, Cattaneo–Christov fluxes are mathematically implemented for investigating the diffusion aspect of heating and mass pattern. Additionally, the nonlinear on set of radiative distribution is followed. Referred to the suitable transformations, the independent variable in the governing system is reduced. The homotopy-based analytical expressions are obtained for set of flow parameters. The complete graphical exploration is visualized, for governing parameters, and scrutinized. The mass and heat transfer pattern has been inspected in the form of numerical data. It is perceived that velocity profile has decreasing tendency for enhancement in Weissenberg number and magneto-porous constant. The temperature and concentration profiles diminish with increase of thermal and solutal relaxation constants, respectively. [ABSTRACT FROM AUTHOR]

The objective of this work is to explore the flow features and thermal radiation properties of the 2-D Magnetohydrodynamic (MHD) Carreau nanofluid model over an impenetrable stretching surface by utilizing the supervised learning strength of Levenberg–Marquardt backpropagation neural networking technique (LMBNNT). The mathematical formulation for MHD Carreau nanofluid flow model (MHDCNFM) in terms of partial differential equations (PDEs) is transformed into equivalent nonlinear ordinary differential equations (ODEs) by utilizing the similarity transformation and dimensional parameters. A reference dataset of proposed LMBNNT is made for Carreau nanofluid flow model exploiting the strength of Lobatto IIIA technique through the variations of different parameters against the velocity, temperature profile and concentration. These reference datasets are placed for validation, training and testing by LMBNNT and obtained outcomes are compared with reference results to check the accuracy of the designed methodology. The validation of the proposed solution methodology is obtained through the mean square error (MSE), error histogram error profile, regression p lot and fitness plot. MSE values' accuracy is upto 1 0 − 1 0 which establish the reliability of the LMBNNT. Moreover, due to an increase in Weissenberg number, fluid velocity decays in case of shear thinning liquid and higher values of Biot number enhance the temperature profile and improves the rate of heat transfer. Moreover, the increment in Hartman number reduces the surface drag force and large values of Prandtl number reduce the heat transfer process. These results of all these parameters are expressed in well-organized numerical and graphical forms. [ABSTRACT FROM AUTHOR]

Structural, electronic, magnetic and mechanical properties of the perovskites BiFeO3 (BFO) and BaTiO3 (BTO) are investigated using density functional theory (DFT). Structural and mechanical parameters are calculated using generalized gradient approximation (GGA) and the results consistent with the available literature. The stable magnetic phases are achieved by optimizing total energies versus volumes of the cells in different magnetic configurations such as nonmagnetic (NM), ferromagnetic (FM) and antiferromagnetic (AFM). BTO is found to be NM while BFO favors G-type AFM (G-AFM) phase. The electronic properties are investigated using GGA, GGA with Hubbard potential (GGA + U) and modified Becke–Johnson (GGA-mBJ) exchange–correlation functionals. BFO is found to be a direct bandgap semiconductor having gap energy value 3.0 eV whereas BTO is an indirect semiconductor with bandgap energy 2.9 eV. Spin–orbit coupling effect is dominant in BFO due to the larger size of A-site cation. The electrical polarization shows that both the compounds are ferroelectric materials with significant spontaneous polarization of 144.1  μ C/cm2 and 27.9  μ C/cm2 for BFO and BTO respectively. [ABSTRACT FROM AUTHOR]

In this paper, structural, electronic and magnetic properties of the aluminum-rich intermetallic alloy Al13Fe4 are investigated using full potential linearized augmented plane waves (FPLAPW) approach in the frame work of density functional theory (DFT). The calculated structural parameters are consistent with the experimentally reported data. In this alloy, Fe atoms possess different coordination numbers with Al atoms, i.e., Fe(1) and Fe(2) have the same coordination number 5, whereas Fe(3), Fe(4) and Fe(5) have 4, 7 and 9 coordination numbers, respectively. The compound is found metallic and ferromagnetic in nature. Post-DFT (BoltzTraP code) calculations confirm the ferromagnetic and anisotropic behavior. The Fe(5) atom plays a central role in the electronic and magnetic properties of the alloy due to the large coordination with Al atom as compared to the rest Fe atoms. [ABSTRACT FROM AUTHOR]

In this paper, we explore the structural, electronic, thermoelectric and elastic properties of intermetallic compounds ScTM (TM = Cu, Ag, Au and Pd) using density functional theory. The produced results show high values of Seebeck coefficients and electrical conductivity for these materials. High power factor for these materials at room-temperature shows that these materials may be beneficial for low-temperature thermoelectric devices and alternative energy sources. Furthermore, elastic properties of these compounds are also calculated, which are used to evaluate their mechanical properties. The Cauchy's pressure and B/ G ratio figure out that these compounds are ductile in nature. The calculated results also predict that these compounds are stable against deforming force. [ABSTRACT FROM AUTHOR]

Spin-polarized density functional calculations are performed to study the correlation and spin-orbit coupling (SOC) effects in scandium intermetallic compounds viz. ScTM (TM=Co, Rh, Ir, Ni, Pd, Pt, Cu, Ag and Au) using FP-LAPW+lo method. The LDA, LDA+ U and LDA+ U+SOC exchange-correlation functionals are used to calculate the structural parameters and we found that the LDA+ U results are consistent with the experiments. The electronic properties reveal that these compounds are metallic in nature. Correlations effects are determined using the U/W ratio and we found that ScCo, ScIr, ScPd, ScPt, ScCu and ScAg are highly correlated compounds, whereas ScRh, ScNi and ScAu are intermediately correlated compounds. Furthermore, stable magnetic phase for each compound is optimized, which reveals that ScCo, ScRh, ScPd, ScPt and ScCu are stable in ferromagnetic phase, ScIr, ScNi and ScAu are anti-ferromagnetic, whereas ScAg is a nonmagnetic material. [ABSTRACT FROM AUTHOR]

This paper communicates the structural, electronic and optical properties of L-alanine, monofluoro and difluoro substituted alanines using density functional calculations. These compounds exist in orthorhombic crystal structure and the calculated structural parameters such as lattice constants, bond angles and bond lengths are in agreement with the experimental results. L-alanine is an indirect band gap insulator, while its fluorine substituted compounds (monofluoroalanine and difluoroalanine) are direct band gap insulators. The substitution causes reduction in the band gap and hence these optically tailored direct wide band gap materials have enhanced optical properties in the ultraviolet (UV) region of electromagnetic spectrum. Therefore, optical properties like dielectric function, refractive index, reflectivity and energy loss function are also investigated. These compounds have almost isotropic nature in the lower frequency range while at higher energies, they have a significant anisotropic nature. [ABSTRACT FROM AUTHOR]