SPECIALLY TAILORED TRANS FINITE-ELEMENT FORMULATIONS FOR HYPERBOLIC HEAT CONDUCTION INVOLVING NON-FOURIER EFFECTS

The phenomenon of hyperbolic heat conduction in contrast to the classical (parabolic) form of Fourier heat conduction involves thermal energy transport that propagates only at finite speeds as opposed to an infinite speed of thermal energy transport. To accommodate the finite speed of thermal wave propagation, a more precise form of heat flux law is involved, thereby modifying the heat flux originally postulated in the classical theory of heat conduction. As a consequence, for hyperbolic heat conduction problems, the thermal energy propagates with very sharp discontinuities at the wave front. The primary purpose of the present paper is to provide accurate solutions to a class of one-dimensional hyperbolic heat conduction problems involving non-Fourier effects that can precisely help understand the true response and furthermore can be used effectively for representative benchmark tests and for validating alternate schemes. As a consequence, the present paper purposely describes modeling/analysis formulations via specially tailored hybrid computations for accurately modeling the sharp discontinuities of the propagating thermal wave front. Comparative numerical test models are presented for various hyperbolic heat conduction models involving non-Fourier effects to demonstrate the present formulations.     

A Backdrop Case Study of AI-Drones in Indian Demographic Characteristics Emphasizing the Role of AI in Global Cities Digitalization

The automatic identification of the modulation format of a detected signal is a major task of an intelligent receiver in both military and civilian applications. It is well known that the maximum likelihood (ML) classifier requires a priori knowledge of the incoming signal and channel (including amplitude, timing information, noise power, and the roll-off factor of the pulse-shaping filter). To relax this requirement, we introduce a novel estimator to estimate the parameters required by the ML classifier which is blind to the modulation scheme of the received signal, and this gives rise to a new blind modulation classifier for digital amplitude-phase modulated signals. While the proposed classifier is completely blind, the simulation results show that the performance of this classifier is very close to the optimal non-blind classifier.

     

Stabilization of Sn Anode through Structural Reconstruction of a Cu–Sn Intermetallic Coating Layer

The metallic tin (Sn) anode is a promising candidate for next-generation lithium-ion batteries (LIBs) due to its high theoretical capacity and electrical conductivity. However, Sn suffers from severe mechanical degradation caused by large volume changes during lithiation/delithiation, which leads to a rapid capacity decay for LIBs application. Herein, a Cu–Sn (e.g., Cu₃Sn) intermetallic coating layer (ICL) is rationally designed to stabilize Sn through a structural reconstruction mechanism. The low activity of the Cu–Sn ICL against lithiation/delithiation enables the gradual separation of the metallic Cu phase from the Cu–Sn ICL, which provides a regulatable and appropriate distribution of Cu to buffer volume change of Sn anode. Concurrently, the homogeneous distribution of the separated Sn together with Cu promotes uniform lithiation/delithiation, mitigating the internal stress. In addition, the residual rigid Cu–Sn intermetallic shows terrific mechanical integrity that resists the plastic deformation during the lithiation/delithiation. As a result, the Sn anode enhanced by the Cu–Sn ICL shows a significant improvement in cycling stability with a dramatically reduced capacity decay rate of 0.03% per cycle for 1000 cycles. The structural reconstruction mechanism in this work shines a light on new materials and structural design that can stabilize high-performance and high-volume-change electrodes for rechargeable batteries and beyond.     

Teaching digital design to computing science students in a single academic term

How should digital design be taught to computing science students in a single one-semester course? This work advocates the use of state-of-the-art design tools and programmable devices and presents a series of laboratory exercises to help students learn digital logic. Each exercise introduces new concepts and produces the complete design of a stand-alone apparatus that is fun and interesting to use. These exercises lead to the most challenging capstone designs for a single-semester course of which the authors are aware. Fast progress is made possible by providing students with predesigned input/output modules. Student feedback demonstrates that the students approve of this methodology. An extensive set of slides, supporting teaching material, and laboratory exercises are freely available for downloading.