相关论文: TBL-induced energy transmission into a double wall…
Transition waves in mechanical metamaterials manifest themselves as propagating interfaces between different stable states in lattices composed of arrays of coupled, intrinsically bistable elements. Here, we show experimentally and…
We propose a protocol that transfers entanglement from an entangled atomic two-level-system (TLS) resource to a pair of free electrons in an energy-sideband ladder via local electron-TLS interactions. In a controlled rotating-wave regime,…
This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…
We present a machine learning (ML) method for efficient computation of vibrational thermal expectation values of physical properties from first principles. Our approach is based on the non-perturbative frozen phonon formulation in which…
Bluetooth Low Energy (BLE) is widely used in IoT systems because of its low power consumption, interoperability, and reliable bidirectional communication. However, its connection-oriented architecture introduces trade-offs among wake-up…
High Froude-number flows become self-aerated when the destabilizing effect of turbulence overcomes gravity and surface tension forces. Traditionally, the resulting air concentration profile has been explained using single-layer approaches…
In the present study, we conduct direct numerical simulations of two-way force-coupled particle-laden compressible turbulent boundary layers at the free-stream Mach number of 2.0 for the purpose of examining the effects of particles on the…
Physics Informed Machine Learning has emerged as a popular approach for modeling and simulation in digital twins, enabling the generation of accurate models of processes and behaviors in real-world systems. However, existing methods either…
Efficient heat dissipation to the substrate is crucial for optimal device performance in nanoelectronics. We develop a theory of electronic thermal boundary conductance (TBC) mediated by remote phonon scattering for the single-layer…
A churn prediction system guides telecom service providers to reduce revenue loss. However, the development of a churn prediction system for a telecom industry is a challenging task, mainly due to the large size of the data, high…
Next-generation communication networks will likely involve the energy-efficient transfer of information and energy over the same wireless channel, for which the physical layer will become more vulnerable to cyber attacks by potential…
The present study aims to optimize the structural design of a Z-type flow lithium-ion battery pack with a forced air-cooling system (FACS) known as BTMS (Battery Thermal Management System). The main goal is to minimize Tmax (maximum…
Mechanistic understanding and rational design of complex chemical systems depend on fast and accurate predictions of electronic structures beyond individual building blocks. However, if the system exceeds hundreds of atoms, first-principles…
This paper presents an online transfer learning framework for improving temperature predictions in residential buildings. In transfer learning, prediction models trained under a set of available data from a target domain (e.g., house with…
A suite of numerical model-derived turbulence assessment products has recently been developed by NESDIS/STAR and implemented on the World Wide Web. The existing product suite is intended to provide turbulence information to aircraft flying…
Comparison of echelle spectra to synthetic models has become a computational statistics challenge, with over ten thousand individual spectral lines affecting a typical cool star echelle spectrum. Telluric artifacts, imperfect line lists,…
The energy pathways from propagating internal waves to the scales of irreversible mixing in the ocean are not fully described. In the ocean interior, the triadic resonant instability is an intrinsic destabilization process that may enhance…
Exotic nondiffusive heat transfer regimes such as the second sound, where heat propagates as a damped wave at speeds comparable to those of mechanical disturbances, often occur at cryogenic temperatures (T) and nanosecond timescales in…
This study explores the potential for predicting turbulent kinetic energy (TKE) from more readily acquired temperature data using temperature profiles and turbulence data collected concurrently at 10 Hz during a small experimental…
Federated Learning (FL) is a distributed learning scheme that enables deep learning to be applied to sensitive data streams and applications in a privacy-preserving manner. This paper focuses on the use of FL for analyzing smart energy…