Sherif A. Sherif

This review covers issues not addressed in a review paper dealing with icing and frosting before. For example, in icing, we start from the role of nonuniform distribution of large droplets in clouds to the effect of droplet impaction, splashing, and mixing of the water layer. We highlight the important assumptions that have traditionally been made and identify those that weaken the validity of the analysis. We emphasize that the distribution of droplets in the cloud, their turbulent trajectory toward the airfoil, and the impingement and phase change processes on the airfoil are all stochastic processes. Many of the investigations focused on predicting the mean behavior. In this review, we focus on quantifying the stochastic fluctuations about the mean, both in terms of proper estimation of associated uncertainties and the effect of fluctuations on features such as ice surface roughness. Similarly, in frosting, the processes of ice crystal nucleation and deposition are also stochastic. We address supersaturated air that may exist both in the bulk airstream and within the pores of the porous frost layer. This aspect along with casting the problem in the context of psychrometric theory has never been addressed in a review paper before. Thus, while we review past icing and frosting-related research findings, we identify gaps in the current approach and suggest areas of future research that can clarify the physics and improve the fidelity of future modeling and simulation.

We conduct turbulence-informed Euler–Lagrange simulations of droplet-laden flow to examine the effects of atmospheric turbulence on droplet impingement characteristics on a NACA 0012 airfoil. We implement statistical overloading, whereby we inject millions of droplets, ranging in diameter from 1 to 160 microns, upstream of the airfoil at an average streamwise velocity of 120 m/s. Within a fraction of a second, these droplets would have either impinged on the airfoil or continued downstream. While the incoming air flow is maintained uniform, droplet injection is informed by ambient turbulence, affecting both the droplet velocity distribution as well as the size-dependent preferential concentration (inertial clustering) of the droplets over space. The droplet injection location and velocity components are obtained from a separate high-fidelity, droplet-laden simulation of isotropic turbulence. We extract the droplet collection efficiency, impingement velocity magnitude, and impingement orientation along the airfoil surface and compare the results against a nonturbulent inflow, where droplet injection is uniform. The collection efficiency remains largely unaffected by turbulence across all droplet sizes. In contrast, impingement velocity is observed to increase for the larger droplets in a turbulent flow. The effect of ambient turbulence is also observed in the impingement angle statistics, with increasing influence for the larger droplets.

This paper presents a unified modeling framework for quantifying power and energy consumption in motor-driven systems operating under variable frequency control and soft starter conditions. By formulating normalized expressions for voltage, current, and power factor as functions of motor speed, the model enables accurate estimation of instantaneous and cumulative energy use using only measurable electrical quantities. The effect of soft starter operation during startup is incorporated through ramp-based profiles, while variable frequency control is modeled through dynamic speed modulation. Analytical results show that variable speed control can achieve energy savings of up to 36.1% for sinusoidal speed profiles and up to 42.9% when combined with soft starter operation, with the soft starter alone contributing a consistent 8.6% reduction independent of the power factor. To support energy optimization under uncertain demand scenarios, a two-stage stochastic optimization framework is developed for motor sizing and control assignment, and four physics-guided machine learning models—MLP, LSTM, GRU, and XGBoost—are benchmarked to forecast normalized energy ratios from key electrical parameters, enabling rapid and interpretable predictions. The proposed framework provides a scalable, interpretable, and practical tool for monitoring, diagnostics, and smart energy management of industrial motor-driven systems.

We analyse the Messinger/Myers model by critically evaluating simplifying assumptions through a rigorous formulation of the rime ice accretion process. We explore the effects of both constant and variable ice density and thermal conductivity, along with the effects of sublimation from the ice surface. The effects of key factors such as droplet impact rate, ambient temperature relative to the freezing temperature and the temperature difference between the ambient air and the airfoil surface are examined. Under these varying conditions, the present rigorous formulation is used to assess the significance of unsteady effects, variable ice properties and sublimation. We observe that the Myers model performs remarkably well in certain icing situations and analyse the reasons for this strong performance. We also show that partially relaxing the model’s assumptions can lead to poorer performance. The Myers model can lead to overprediction of ice surface temperature and correspondingly underprediction of transition time under conditions of relatively weak sublimation and surface cooling. A modified Myers model is presented, which can be used to recover near-perfect results under widely varying icing conditions of relevance. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050 ≤ R e D , avg ≤ 4800 , with the characteristic length being the outer diameter of the tube and the velocity being the bulk fluid velocity between the plates (fins). Computational fluid dynamics simulations are employed to resolve the interactions between turbulent airflow and the frost layer. Our approach incorporates a modified immersed boundary method and a slow-time acceleration technique to address the complex dynamic interface between the continuously evolving frost layer and the flowing air stream. Our findings indicate that frost forms more on the sides of the finned surfaces (plates) and less on the tubes themselves. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.