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Träfflista för sökning "WFRF:(Singh Gupta V) ;hsvcat:2"

Sökning: WFRF:(Singh Gupta V) > Teknik

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1.
  • Gupta, R. K., et al. (författare)
  • Hot Deformation Studies on beta(0) Stabilized TiAl Alloy Made Through Ingot Metallurgy Route
  • 2021
  • Ingår i: Transactions of the Indian Institute of Metals. - : Springer Science and Business Media LLC. - 0972-2815 .- 0975-1645. ; 74:12, s. 2977-2989
  • Tidskriftsartikel (refereegranskat)abstract
    • Hot deformation studies of a newly designed gamma + alpha(2) based TiAl alloy of composition Ti-42Al-6Nb-3Cr-0.1B at.% (nominal) realized through ingot metallurgy route using double vacuum arc remelting were carried out. Hot isothermal compression testing was performed in Gleeble (TM) 3500 at different temperatures ranging from 1123 to 1373 K at 50 K intervals and strain rates of 0.001-1 s(-1). Processing maps were developed using an approach of dynamic material modeling of the flow curves to establish the safe hot working regime. Strain rate sensitivity and Zener-Holloman parameters were calculated and constitutive equation was derived. Microstructural investigation revealed dynamic recrystallization and activation of multiple twin systems as the main softening mechanisms operating at optimum hot working conditions. Safe hot working temperature and strain rate regime for the alloy was found to be in the temperature range of 1323-1373 K and strain rate range of 0.001-0.01 s(-1).
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2.
  • Gupta, Pooja, et al. (författare)
  • Oblique angle deposited FeCo multilayered nanocolumnar structure : Magnetic anisotropy and its thermal stability in polycrystalline thin films
  • 2022
  • Ingår i: Applied Surface Science. - : Elsevier BV. - 0169-4332 .- 1873-5584. ; 590, s. 153056-
  • Tidskriftsartikel (refereegranskat)abstract
    • Iron-Cobalt (FeCo) columnar, multilayered structure is prepared by depositing several thin FeCo layers by varying the angle between the surface normal and the evaporation direction as 0 (normal) and 60(oblique), alternatively. In situ X-ray scattering and magneto-optical Kerr effect (MOKE) measurements established the evolution of magnetic properties with that of the morphology and structure of the multilayer. The strong shape anisotropy and compressive stress of nanocolumns in alternative FeCo layers resulted in a well-defined uniaxial magnetic anisotropy (UMA) with the easy axis of magnetization along the projection of the tilted nanocolumns in the film plane. The stress in the film provides minimization of magnetoelastic energy along the in-plane column direction, which couples with the columnar shape anisotropy energies and results in the preferential orientation of the magnetic easy axis along the oblique angle deposition direction in the film plane. Drastic reduction in the in-plane UMA after annealing at 450 C is attributed to the merging of columns and removal of stresses after heat treatment. The present study opens a new pathway to produce magnetically anisotropic multilayer structures using single material and thus may have prominent implications for future technological devices.
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3.
  • Joshi, Bhupendra, et al. (författare)
  • A comparative survey between cascade correlation neural network (CCNN) and feedforward neural network (FFNN) machine learning models for forecasting suspended sediment concentration
  • 2024
  • Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14
  • Tidskriftsartikel (refereegranskat)abstract
    • Suspended sediment concentration prediction is critical for the design of reservoirs, dams, rivers ecosystems, various operations of aquatic resource structure, environmental safety, and water management. In this study, two different machine models, namely the cascade correlation neural network (CCNN) and feedforward neural network (FFNN) were applied to predict daily-suspended sediment concentration (SSC) at Simga and Jondhara stations in Sheonath basin, India. Daily-suspended sediment concentration and discharge data from 2010 to 2015 were collected and used to develop the model to predict suspended sediment concentration. The developed models were evaluated using statistical indices like Nash and Sutcliffe efficiency coefficient (NES), root mean square error (RMSE), Willmott’s index of agreement (WI), and Legates–McCabe’s index (LM), supplemented by a scatter plot, density plots, histograms and Taylor diagram for graphical representation. The developed model was evaluated and compared with CCNN and FFNN. Nine input combinations were explored using different lag-times for discharge (Qt-n) and suspended sediment concentration (St-n) as input variables, with the current suspended sediment concentration as the desired output, to develop CCNN and FFNN models. The CCNN4 model with 4 lagged inputs (St-1, St-2, St-3, St-4) outperformed the other developed models with the lowest RMSE = 95.02 mg/l and the highest NES = 0.0.662, WI = 0.890 and LM = 0.668 for the Jondhara Station while the same CCNN4 model secure as the best with the lowest RMSE = 53.71 mg/l and the highest NES = 0.785, WI = 0.936 and LM = 0.788 for the Simga Station. The result shows the CCNN model was better than the FFNN model for predicting daily-suspended sediment at both stations in the Sheonath basin, India. Overall, CCNN showed better forecasting potential for suspended sediment concentration compared to FFNN at both stations, demonstrating their applicability for hydrological forecasting with complex relationships.
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  • Resultat 1-3 av 3

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