A Deep Learning Based Approach for Response Prediction of Beam-like Structures

Beam-like structures arde a class of common but important structures in engineering.Over the past few centuries,extensive research has been carried out to obtain the static and dynamic response of beam-like structures.Although build-ing the finite element model to predict the response of these structures has proven to be effective,it is not always suitable in all the application cases because of high computational time or lack of accuracy.This paper proposes a novel approach to predict the deflection response of beam-like structures based on a deep neural net-work and the governing differential equation of Euler-Bernoulli beam.The Prandtl-Ishlinskii model is introduced as an element of prediction model to simu-late the plasticity of this beam structure.Finally the application of the proposed approach is demonstrated through four numerical examples including linear elastic/ideal plastic beam under concentrated/sinusoidal load and elastic/plastic continues beam under seismic load to demonstrate a proof of concept for the effectiveness of this AI-based approach.

Instability from Steady and Axisymmetric to Steady and Asymmetric Floating Half Zone Convection in a Fat Liquid Bridge of Larger Prandtl Number

The linear instability analysis of the present paper shows that the thermocapillary convection in a half floating zone of larger Prandtl number has a steady instability mode ωi = 0 and m = 1 for a fat liquid bridge V = 1.2 with small geometrical aspect ratio A = 0.6. This conclusion is different from the usual idea of hydrothermal instability, and implies that the instability of the system may excite a steady and axial asymmetric state before the onset of oscillation in the case of large Prandtl number.

Two‑Dimensional Black Phosphorus Nanomaterials:Emerging Advances in Electrochemical Energy Storage Science

Two-dimensional black phosphorus(2D BP),well known as phosphorene,has triggered tremendous attention since the first discovery in 2014.The unique puckered monolayer structure endows 2D BP intriguing properties,which facilitate its potential applications in various fields,such as catalyst,energy storage,sensor,etc.Owing to the large surface area,good electric conductivity,and high theoretical specific capacity,2D BP has been widely studied as electrode materials and significantly enhanced the performance of energy storage devices.With the rapid development of energy storage devices based on 2D BP,a timely review on this topic is in demand to further extend the application of 2D BP in energy storage.In this review,recent advances in experimental and theoretical development of 2D BP are presented along with its structures,properties,and synthetic methods.Particularly,their emerging applications in electrochemical energy storage,including Li−/K−/Mg−/Na-ion,Li–S batteries,and supercapacitors,are systematically summarized with milestones as well as the challenges.Benefited from the fast-growing dynamic investigation of 2D BP,some possible improvements and constructive perspectives are provided to guide the design of 2D BP-based energy storage devices with high performance.

Darcy-Forchheimer mangetized flow based on differential type nanoliquid capturing Ohmic dissipation effects

Hydromagnetic nanoliquid establish an extraordinary category of nanoliquids that unveil both liquid and magnetic attributes.The interest in the utilization of hydromagnetic nanoliquids as a heat transporting medium stem from a likelihood of regulating its flow along with heat transportation process subjected to an externally imposed magnetic field.This analysis reports the hydromagnetic nanoliquid impact on differential type(second-grade)liquid from a convectively heated extending surface.The well-known Darcy-Forchheimer aspect capturing porosity characteristics is introduced for nonlinear analysis.Robin conditions elaborating heat-mass transportation effect are considered.In addition,Ohmic dissipation and suction/injection aspects are also a part of this research.Mathematical analysis is done by implementing the basic relations of fluid mechanics.The modeled physical problem is simplified through order analysis.The resulting systems(partial differential expressions)are rendered to the ordinary ones by utilizing the apposite variables.Convergent solutions are constructed employing homotopy algorithm.Pictorial and numeric result are addressed comprehensively to elaborate the nature of sundry parameters against physical quantities.The velocity profile is suppressed with increasing Hartmann number(magnetic parameter)whereas it is enhanced with increment in material parameter(second-grade).With the elevation in thermophoresis parameter,temperature and concentration of nanoparticles are accelerated.