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Exploring the Influence of Induced Magnetic Fields and Double-Diffusive Convection on Carreau Nanofluid Flow through Diverse Geometries: A Comparative Study Using Numerical and ANN Approaches
No full textThis current investigation aims to explore the significance of induced magnetic fields and double-diffusive convection in the radiative flow of Carreau nanofluid through three distinct geometries. To simplify the fluid transport equations, appropriate self-similarity variables were employed, converting them into ordinary differential equations. These equations were subsequently solved using the Runge-Kutta-Fehlberg (RKF) method. Through graphical representations like graphs and tables, the study demonstrates how various dynamic factors influence the fluid's transport characteristics. Additionally, the artificial neural network (ANN) approach is considered an alternative method to handle fluid flow issues, significantly reducing processing time. In this study, a novel intelligent numerical computing approach was adopted, implementing a Levenberg-Marquardt algorithm-based MLP feed-forward back-propagation ANN. Data collection was conducted to evaluate, validate, and guide the artificial neural network model. Throughout all the investigated geometries, both velocity and induced magnetic profiles exhibit a declining trend for higher values of the magnetic parameter. An increase in the Dufour number corresponds to a rise in the nanofluid temperature. The concentration of nanofluid increases with higher values of the Soret number. Similarly, the nanofluid velocity increases with higher velocity slip parameter values, while the fluid temperature exhibits opposite behavior, decreasing with increasing velocity slip parameter values
Bayesian inference of pit corrosion in prestressing strands using Markov Chain Monte Carlo method
No full textCorrosion monitoring has been widely studied to maintain the structural capacity of bridges through direct visual and nondestructive inspections or indirect inverse analysis-based methods. This study proposes a Bayesian inference method for inferring pit corrosion in the prestressing strands of prestressed concrete (PSC) bridges, which is an indirect method for corrosion monitoring. First, the probabilistic relationship between the mechanical properties of the strands and the amount of pit corrosion was defined using Bayes??? rule. Subsequently, a Markov chain Monte Carlo method was introduced to infer the posterior probability, which is a conditional probability distribution of the amount of corrosion given a certain mechanical property. Based on the inference results, probabilistic bounds for the amount of corrosion were derived. The proposed method was applied to two examples: (a) probabilistic corrosion inference of strands based on the tensile test results, and (b) probabilistic corrosion inference of embedded strands in PSC girders based on the bending test results. The inference results demonstrated the applicability of the proposed method
Spin Seebeck effect of the Yttrium Iron Garnet that Fabricated with Varying Sintering Step for Grain Variation
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Efficient X-ray luminescence imaging with ultrastable and eco-friendly copper(I)-iodide cluster microcubes
No full textThe advancement of contemporary X-ray imaging heavily depends on discovering scintillators that possess high sensitivity, robust stability, low toxicity, and a uniform size distribution. Despite significant progress in this field, the discovery of a material that satisfies all of these criteria remains a challenge. In this study, we report the synthesis of monodisperse copper(I)-iodide cluster microcubes as a new class of X-ray scintillators. The as-prepared microcubes exhibit remarkable sensitivity to X-rays and exceptional stability under moisture and X-ray exposure. The uniform size distribution and high scintillation performance of the copper(I)-iodide cluster microcubes make them suitable for the fabrication of large-area, flexible scintillating films for X-ray imaging applications in both static and dynamic settings
Prediction of Hardness and Phase Distributions in Laser Heat Treatment of AH36 Steel Using Deep Learning
No full textPhase-Bridged Hierarchical Catalysts for Efficient and Stable Water Electrolysis
No full textThe design and synthesis of low-cost electrocatalysts with high catalytic activity and long-term stability is a challenging task. This study utilizes a combination of electronic tuning and surface reconstruction to synthesize a ternary layered double hydroxide (LDH)/phosphide (P-NiCuFe-LDH) hierarchical-structure catalyst that improves the kinetics of the hydrogen/oxygen evolution reactions in water electrolysis by facilitating the thermodynamically limited reaction pathways. Spectroscopic analyses indicate synergistic electronic interactions among the metal atoms in the LDH and phosphide layers via the P-bridge effect. This cross-layer interaction optimizes the electron transport pathways and reaction kinetics, enabling the proposed hierarchical electrocatalyst to exhibit high intrinsic activity. Theoretical calculations confirm the configuration of the cross-phase bridges and elucidate the origin of the enhanced electrocatalytic effect of P-NiCuFe-LDH. For overall water splitting, the P-NiCuFe0.06-LDH || P-NiCuFe0.06-LDH system requires only 1.517 V to attain a current density of 10 mA cm-2. The P-O-containing surface (generated in situ during water electrolysis) prevents metal-ion leaching and endows P-NiCuFe-LDH with excellent operational stability; as demonstrated by the continuous long-term stability test over 1000 h with negligible performance degradation. This study provides important insights into the design of rational hierarchical structures for a wide range of applications beyond water splitting. A well-designed hierarchical catalyst, P-NiCuFe-LDH, is constructed by structural transformation and surface reconstruction, which enhance the electron transport efficacy and reaction kinetics due to the synergistic electronic interactions via the P-bridge effect. The excellent overall water splitting performance with a low cell voltage of 1.517 V at 10 mA cm-2 is shown by the proposed catalyst, along with remarkable operational stability over 1000 h.imag