相关论文: Modelling of nucleate pool boiling on coated subst…
Micro-structured surfaces influence nucleation characteristics and bubble dynamics besides increasing the heat transfer surface area, thus enabling efficient nucleate boiling heat transfer. Modeling the pool boiling heat transfer…
With recent advances in micro- and nanofabrication, superhydrophilic and superhydrophobic surfaces have been developed. The statics and dynamics of fluids on these surfaces have been well characterized. However, few investigations have been…
This study investigates the influence of heater material properties on nucleate pool boiling using a comprehensive simulation model. Copper and silicon oxide are selected as reference materials due to their properties as excellent and poor…
We study the role of surface topology, surface chemistry, and wall superheat temperature on the onset of boiling, bubble nucleation and growth, and the possible formation of an insulating vapour film by means of large-scale MD simulations.…
Boiling heat transfer occurs in many situations and can be used for thermal management in various engineered systems with high energy density, from power electronics to heat exchangers in power plants and nuclear reactors. Essentially,…
Insufficient overlap between the melt pools produced during Laser Powder Bed Fusion (L-PBF) can lead to lack-of-fusion defects and deteriorated mechanical and fatigue performance. In-situ monitoring of the melt pool subsurface morphology…
This study introduces a novel metric, the Index of Visual Similarity (IVS), to qualitatively characterize boiling heat transfer regimes using only visual data. The IVS is constructed by combining morphological similarity, through SIFT-based…
Nanoporous structures including single nanopores and nanoporous membranes have been utilized as a platform to study fundamental liquid-vapor phase change heat transfer (PCHT) processes as well as a promising candidate for high flux heat…
Accurate temperature estimation of pouch cells with indirect liquid cooling is essential for optimizing battery thermal management systems for transportation electrification. However, it is challenging due to the computational expense of…
New discoveries in chemistry and materials science, with increasingly expanding volume of requisite knowledge and experimental workload, provide unique opportunities for machine learning (ML) to take critical roles in accelerating research…
Machine learning offers promising tools to develop surrogate models for polymer structure-property relations. Surrogate models can be built upon existing polymer data and are useful for rapidly predicting the properties of unknown polymers.…
The transition from nucleate to film boiling on micro/nano textured surfaces is of crucial importance in a number of practical applications, where it needs to be avoided to enable safe and efficient heat transfer. Previous studies have…
We present a data-driven, differentiable neural network model designed to learn the temperature field, its gradient, and the cooling rate, while implicitly representing the melt pool boundary as a level set in laser powder bed fusion. The…
Accurate prediction of pure component physiochemical properties is crucial for process integration, multiscale modeling, and optimization. In this work, an enhanced framework for pure component property prediction by using explainable…
Two-phase boiling enables heat transfer rates an order of magnitude higher than single-phase cooling, but it remains difficult to model due to the strong coupling between phase change, turbulence, and transport, as well as extreme…
Accurate and efficient temperature prediction is critical for optimizing the preheating process of PET preforms in industrial microwave systems prior to blow molding. We propose a novel deep learning framework for generalized temperature…
Pool boiling is one of the efficient ways to remove heat from high-power electronics, heat exchangers, and nuclear reactors. Nowadays, the pool boiling method is tried to exercise frequently due to its ability to remove high heat flux…
A hybrid thermal lattice Boltzmann phase-change model was performed to simulate the pool boiling above a smooth horizontal heater. The effects of homogenous and heterogeneous wettability on entire boiling curves from the onset of nucleate…
In this paper, a phase-change model based on a geometric Volume-of-Fluid (VOF) framework is extended to simulate nucleate boiling with a resolved microlayer and conjugate heat transfer. Heat conduction in both the fluid and solid domains is…
The hydro-mechanical behavior of clay-sulfate rocks, especially their swelling properties, poses significant challenges in geotechnical engineering. This study presents a hybrid constrained machine learning (ML) model developed using the…