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DOE OSTI2025

Long-term thermal aging behavior and strength reduction in a laser powder bed fusion 316H stainless steel

The long-term thermal stability of structural alloys is essential for ensuring the safe and reliable operation of nuclear reactors and other power plants. While extensive research has explored the effects of thermal aging on conventional stainless steels, the behavior of additively manufactured (AM) alloys remains less understood. This study examines the thermal aging response of laser powder bed fusion (LPBF) 316H stainless steel (SS) at temperatures ranging from 550 °C to 750 °C over durations of up to 10,000 h (approximately 1.14 years). Advanced characterization techniques, including electron microscopy and synchrotron X-ray diffraction, were used to investigate dislocation recovery and phase evolution. Based on these findings, a time-temperature-precipitation (TTP) diagram was developed for LPBF 316H SS, revealing a 10- to100-fold acceleration in precipitation kinetics compared to wrought 316H SS. A physics-informed model was calibrated using the short-term experimental data, enabling predictions of average precipitate sizes, volume fractions of M 23 C 6 and Laves phases, and changes in molybdenum solute concentration for aging up to 1 × 10⁶ h (114 years). These microstructural insights were further utilized to estimate yield strength and extrapolate strength reduction factors over the extended aging period. Despite the accelerated aging kinetics, LPBF 316H SS demonstrated superior yield strength retention compared to its wrought counterpart. In conclusion, this study establishes a framework for evaluating long-term performance using short-term experimental data and supports the accelerated qualification of AM materials for high-temperature structural applications.

Laser powder bed fusion↗

DOE OSTI2026

Assessment of multi-stage telescopic control rods in a pebble bed reactor. Part II: corrosion and wear performance

To support High-Temperature Gas-Cooled Reactor designs, the effects of corrosion and wear on a SS316L telescopic control rod prototype were investigated in helium at 775 °C with up to 5 ppm oxygen for durations up to 500 h. Three deployment conditions were tested to assess their impact on wear and oxide formation: severe cycles, daily cycles, and gravity-driven deployments. Here, a chromium-rich oxide layer developed on regions exposed to the helium flow, reaching up to 2 µm in the most affected areas. No carburization or decarburization was observed. Oxide breakthrough occurred mainly at grooves and contact points during severe cycling of the telescopic rod, while in the other tests it was limited to contact points. Friction forces increased due to oxide growth and thermal expansion, the latter being the dominant factor, but never enough to hinder rod deployment significantly. Coaxial misalignment of stages was identified as the main potential risk to reliable operation under normal conditions.

Control rod↗

DOE OSTI2026

Scaling dynamics in low-salt-rejection reverse osmosis for high-salinity produced water desalination: Mechanistic modeling and membrane autopsy

Membrane scaling remains a critical barrier to the reliable operation of desalination systems, particularly for hypersaline produced water (PW) treatment. This study fills the knowledge gap of autopsy-based model validation for PW desalination by elucidating scaling mechanisms in a Low-Salt-Rejection Reverse Osmosis (LSRRO) system through the integration of pilot-scale experimentation and complementary modeling approaches. A semi-empirical modeling framework was developed and applied to a multistage pilot LSRRO system equipped with nanofiltration and RO membranes treating high-salinity PW from the Permian Basin. Water quality analysis showed that total dissolved solids decreased from ~130,000 mg/L to ~1900 mg/L in the permeate, then further reduced to ~300 mg/L by a second-pass RO. Two different thermodynamic modeling approaches were evaluated: the first extends the LSRRO framework by incorporating system complexity and scaling phenomena, whereas the second method explicitly captures concentration polarization in localized supersaturation. Both methods illustrate the tendency for carbonate and sulfate scaling throughout the stages. Membrane autopsies revealed a silica-dominated deposit matrix, localized CaSO 4 at Stage 2, and minor barite/celestite despite their prominence in model predictions. Quantum-chemical calculations indicated silica scaling can be rationalized by favorable adsorption of H 4 SiO 4 on Fe-oxide surfaces (ΔG ≈ −44 kJ/mol), providing a kinetic pathway for interfacial inorganic polymerization even when bulk equilibrium predictions are conservative. Overall, the thermodynamic scaling modeling and membrane autopsy revealed heterogeneous, localized deposits with limited impact on LSRRO performance, while quantum analysis rationalized the thermodynamically unfavorable precipitation formation under bulk equilibrium, reconciling model–autopsy discrepancies. These insights support targeted pretreatment and silica-specific antiscalants to extend membrane lifetime and increase recovery, providing a transferable framework for hypersaline water desalination systems. The combined experimental–computational approach provides new mechanistic insight into scaling in hypersaline membrane systems and establishes a transferable framework for predicting and mitigating scaling in next-generation desalination technologies.

Low-salt-rejection reverse osmosis↗

DOE OSTI2024

An Open-Source Parallel EMT Simulation Framework

As the integration level of inverter-based resources (IBRs) increases, ensuring the reliable operation of the bulk power systems requires the use of electromagnetic transient (EMT) simulation tools to identify and mitigate system-wide stability risks. Conducting EMT studies for large-scale, IBR-rich grids, however, is challenging due to the inherent computational bottleneck caused by the underlying high-fidelity models and required small time steps. This paper introduces ParaEMT: an open-source, generic EMT simulation framework designed to accelerate simulations by leveraging advanced parallel computational technologies, such as high-performance computers. This paper presents a comprehensive exposition of ParaEMT, covering its modeling library, simulation strategy, framework structure, operational procedures, and auxiliary features, alongside its extensible parallel computational architecture. Notably, ParaEMT is a publicly accessible and modularized framework written in Python, thereby facilitating future development and the integration of new models and algorithms. The accuracy and efficiency of ParaEMT are demonstrated by rigorous validations via multiple case studies.

electromagnetic transient simulation↗

DOE OSTI2025

Networked Microgrid Topology Reconfiguration to Promote Fairness in Proactive Load Shedding

Increasing occurrences of natural disasters and grid emergency events consistently challenge the safe and reliable operations of power systems. During such emergency situations, system operators may proactively shed load to mitigate risks. However, uncoordinated implementation of load shedding may disrupt electricity supply and even lead to cascading failures. Meanwhile, it is crucial to address potential biases affecting different customers when executing load shedding. This paper addresses the dynamic topology reconfiguration problem for networked microgrids with distributed energy resources under emergency conditions. Specifically, we propose a novel rolling-horizon optimization model that integrates fairness-aware constraints into the networked microgrid topology reconfiguration. Unlike existing approaches that focus solely on efficiency or apply fairness considerations in static settings, our method explicitly incorporates temporal fairness constraints to restrict repeated or excessive load curtailment for load blocks. Moreover, the fairness-aware constraints are specifically developed for the context of dynamic networked microgrid topology reconfiguration, and are designed to be convex or amenable to linear reformulations, which offers a more tractable alternative to traditional models with non-convex formulations. Numerical studies on a modified IEEE 13-bus system and a larger-sized SMART-DS networked microgrid system demonstrate the performance of the proposed algorithm towards more fairness-aware networked microgrid topology reconfiguration decision-making.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Computational analysis of flame initiation, quenching, and re-ignition in a prechamber natural gas engine under varying EGR-dilution levels

The on-road natural-gas (NG) fueled transportation relies on stoichiometric spark-ignition engines for the advantages of simple after-treatment system despite the efficiency penalty relative to lean-burn combustion strategies. Exhaust gas recirculation (EGR) has the potential to reduce this efficiency gap at low to moderate loads without the need for complex lean-exhaust aftertreatment systems. However, EGR dilution leads to reduced combustion stability and increased cycle-to-cycle variability. A promising technology that has the potential to achieve reliable operation under diluted conditions is the prechamber ignition (or turbulent jet ignition) which uses chemically active turbulent jets generated from combustion inside a prechamber to initiate, stabilize and accelerate combustion of the mixture inside the main chamber. The present work focusses on developing a RANS-based CFD approach to accurately reproduce in-cylinder phenomena in a stoichiometric NG prechamber-assisted heavy-duty engine without relying on complex combustion models that account for turbulence-chemistry interactions. This is necessary because reactive prechamber jets at high EGR dilution tend to extinguish while emerging into the main chamber, which is followed by a phase of re-ignition — a phenomenon that conventional G-equation or well-stirred reactor combustion models cannot reproduce. With addition of a damping multiplier to the well-stirred reactor model, the predictions are seen to show good agreement with experimental pressure evolution and combustion images acquired from a single cylinder Cummins N-14 optical diesel engine retrofitted with a prechamber ignition system. Model predictions of local heat release in the flame and temperature evolution inside the flame are used to investigate combustion dynamics in the prechamber and the main chamber. It is seen that the well-stirred reactor model with the inclusion of damping is able to reproduce the temporary reduction in heat release within the flame, which can be considered equivalent to quenching of jets, and the subsequent re-ignition of the flame inside the main chamber. The delay between quenching and re-ignition depends on the amount of dilution, as explained by an illustration of flame evolution in a Borghi diagram.

Prechamber ignition↗

DOE OSTI2026

Modeling and Experimental Validation of a Direct-Contact Counter-Flow Fluidized Bed Heat Exchanger for Thermal Energy Storage (TES) Applications

Particle-based thermal energy storage (TES) systems are an emerging energy storage technology. The technological advances have reduced costs, making TES more competitive and reliable in the marketplace but an efficient and reliable operation is heavily dependent on coherent heat transfer between air to particles or vice versa. The particle-based TES technologies provide an intermediate system that can store energy for short (0-10 h), long (10-200 h) and seasonal (> 200 h) timescales. The TES systems store energy by converting electricity to thermal energy; electricity can be directly sourced intermittent generation technologies and/or the grid, helping manage peak loads and other mismatches in supply and demand. The overall efficiency of the TES system depends on the performance of system components (particle storage silos and particle transfer mechanism etc.). The particle heat exchanger is one of the key system components that affects the system efficiency. The pressurized fluidized bed heat exchanger (PFB HX) performance is challenging to predict due to the chaotic behavior of particle and fluid interaction. This research presents a computational study of a novel direct-contact, counter-flow and air-to-particles PFB HX, that contributes in advancing the particle-based long-duration TES technologies. For the current analysis an unsteady Eulerian-Eulerian CFD model was developed and validated against experiments performed at the National Laboratory of the Rockies for two particle sizes (600 ..mu..m and 825 ..mu..m ). Following validation, parametric simulations were conducted to evaluate the effects of interphase drag models (Syamlal-O'Brien and Gidaspow), particle size, bed height and the influence of a frictional-viscosity term on hydrodynamics and heat transfer between the air & particles. The key findings from the analysis are: (1) for the studied operating window Syamlal-O'Brien provides superior agreement with measured gas temperatures (errors generally < 10%) while Gidaspow shows large deviations for the coarse particle case; (2) model predictions are most sensitive in the lower 0.2 m above the air distributor where bubble initiation and local mixing dominate interphase heat transfer; (3) representation of the distributor (number of inlet ports) materially affects predicted local mixing and temperature stratification; and (4) the Eulerian-Eulerian framework reproduces bulk thermal trends but shows regime dependent limitations for coarse particles, motivating mesoscale informed closures for scale-up analysis for future studies. These results provide validated guidance for drag selection and distributor design in particle-based thermal energy storage applications. Collectively, the validated model and parametric results quantify key drivers of PHB-HX performance and provide practical guidance for design and optimization. The results provide confidence in the model predictability and provide a step forward to improve on heat exchange performance. The demonstrated performance and modeling approach support the deployment and further development of this novel PHB-HX concept for robust, particle-based long-duration thermal energy storage systems.

25 ENERGY STORAGE↗

DOE OSTI2026

System-of-systems optimization of hydrogen infrastructure for heavy-duty freight corridors: The interstate 10 case study

Medium and heavy-duty freight transportation requires hydrogen energy infrastructure that is cost-effective, operationally reliable, spatially coherent, and resilient to demand variability along major corridors. This paper presents an integrated hydrogen corridor planning framework using Oak Ridge National Laboratory's OR-AGENT that couples freight-driven, route-resolved hydrogen demand modeling with optimized station siting, sizing, and station-level techno-economic analysis. The framework is demonstrated for the Interstate 10 freight corridor and the Houston-to-Los-Angeles region. Hydrogen demand is derived from high-resolution origin–destination freight data, duty-cycle characterization, and physics-based energy consumption modeling. Candidate refueling sites are selected from existing heavy-duty diesel fueling locations and optimized subject to onboard storage and station capacity constraints. Resulting station throughputs are evaluated using established techno-economic models for electrolytic hydrogen production and dispensing infrastructure. Results show that a regional, portfolio-level aggregation, average dispensed electrolytic hydrogen cost of $6.87–$7.26/kg is currently feasible, and is strongly influenced by demand density and utilization.

Sujan, Vivek [ORNL] (ORCID:0000000269882342)↗

DOE OSTI2024

Understanding the heat generation mechanisms and the interplay between joule heat and entropy effects as a function of state of charge in lithium-ion batteries

The thermal performance of lithium-ion battery cells is critical for ensuring their safe and reliable operation across various applications. In this study, we employed an isothermal calorimetry method to investigate the heat generation of commercial 18650 lithium-ion battery fresh cells during charge and discharge at different current rates, ranging from 0.05C to 0.5C, and across various temperatures: 20 °C, 30 °C, 40 °C, and 50 °C. Our findings revealed a direct correlation between heat generation and current rates, indicating that higher current rates lead to increased heat generation within the cells. Conversely, we observed that heat generation remained relatively stable as the temperature rose, suggesting that temperature changes within this range may not significantly impact the heat generation of fresh cells during typical operations. Furthermore, our study explored irreversible heat generation, which depends on the applied current and overpotential, using the galvanostatic intermittent titration technique at 0.05C–0.5C and 30 °C. Additionally, electrochemical impedance spectroscopy was performed on the same cells during charge and discharge at 20 °C, 30 °C, and 40 °C to analyze cell impedance. Finally, our results indicated a consistent dependence of impedance on the state of charge and depth of discharge, with a significant increase in impedance observed at the end of the discharge process.

25 ENERGY STORAGE↗

DOE OSTI2025

Horn Location Sensors for LBNF

The Horn Location Sensor (HLS) system—named for the magnetic focusing horns it monitors, along with other critical beamline elements – is a high-precision alignment system developed for the Long-Baseline Neutrino Facility (LBNF) to support the Deep Underground Neutrino Experiment (DUNE). With minimal maintenance, the HLS can operate reliably in environments with high radiation, and it ensures that key components such as the protective baffle, focusing horns, and beam position monitors are aligned correctly – each essential for maintaining one of the world’s most intense muon-neutrino beams. A high-precision hydrostatic level sensor, a linear variable differential transformer, and INVAR rods are all used in the system to monitor vertical motion and tilt with sub-millimeter accuracy. A novel Sweep Tracker interferometer enhances calibration fidelity by correcting for non-linearities in laser wavelength and scan rate in real time. A critical part of DUNE’s precision alignment and flux prediction requirements, the HLS system initially supports beam power of up to 1.2 MW and can be upgraded to 2.4 MW.

Frequency scanning interferometry↗

DOE OSTI2024

Rapid advances enabling high-performance inverted perovskite solar cells

Perovskite solar cells (PSCs) that have a positive–intrinsic–negative (p–i–n, or often referred to as inverted) structure are becoming increasingly attractive for commercialization owing to their rapid increase in power conversion efficiency, easily scalable fabrication, reliable operation and compatibility with various perovskite-based tandem device configurations. In this report we review key material and device considerations for making highly efficient and stable p–i–n PSCs. First, we summarize key advances in charge transport materials, which were critical to the rapid power conversion efficiency progress. Second, we discuss promising perovskite compositions and fabrication methods. We highlight various additive engineering approaches to improve the perovskite layer as well as interface engineering strategies that target either the buried or top perovskite surface layer. Third, we review progress in tandem devices, focusing on optimization of the interconnection layer. Next, we summarize the status and strategies for improving p–i–n PSC stability, especially considering the challenges of outdoor applications. We also provide prospects for future research directions and challenges.

14 SOLAR ENERGY↗

DOE OSTI2024

Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives

Abstract Diagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.

25 ENERGY STORAGE↗

DOE OSTI2024

Solid–liquid separation of lignocellulosic sugars from biomass by rotating ceramic disc filtration

In many biomass conversion processes, the separation of cellulosic sugars from residual, lignin-rich solids is a critical step, and achieving high recovery yields of sugars by conventional tangential crossflow and vacuum filtration is challenged by the presence of biomass solids, which rapidly foul filters, resulting in decreased throughput. Considering the performance limitations of traditional filtration methods, dynamic filtration, which generates high shear at the membrane surface to decrease fouling, is emerging as a viable alternative for demanding solid–liquid separations. For high solids separations, there is little available information regarding the performance, limitations, and energy consumption of dynamic filtration. To that end, here we characterized the performance of a dynamic filtration module, specifically a rotating ceramic disc (RCD) filter, for the aseptic recovery of cellulosic sugars from biomass solids following pretreatment and enzymatic hydrolysis. We show how RCD rotational velocity and percent biomass solids impact the filter throughput. Additionally, we used computational fluid dynamics (CFD) simulations to estimate the shear rate at the membrane surface and to visualize hydrodynamic profiles within the module. With the combined CFD simulations and experimental results, we estimated the energy demand and operating expenses for a viable dynamic filtration system operating with a lignocellulosic feed slurry. Our results indicate that an RCD filter can achieve ≥95% recovery of sugars and produce a retentate slurry containing 12 wt% insoluble solids with low energy consumption (a 2.2-fold improvement over cross-flow filtration) and low operating costs ($\$$0.06 per kg sugars). These results show a viable path towards operationally reliable, energy efficient, and cost-effective separations of sterilized cellulosic sugars from biomass solids and highlight the potential of dynamic filtration systems for challenging solid–liquid separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Decentralised Reinforcement Learning for Dynamic Cyberattack Response in Microgrid Networks

Microgrids rely on communication networks for reliable operation, which makes them inherently vulnerable to cyberattacks. Such attacks can destabilise system dynamics and drive states away from their nominal operating trajectories. Although several physics-informed and machine learning-based strategies have been developed to counter these threats, the rapidly evolving cyber landscape enables adversaries to bypass static defences or rules-based mitigation approaches. This paper proposes a dynamic, online-trained and fully decentralised reinforcement learning (RL)-based cyberattack response framework to protect microgrids from evolving cyberattacks. The proposed framework deploys multiple deep Q-networks (DQNs), each associated with a distributed energy resource (DER), to enable localised and adaptive attack mitigation. In this framework, each DQN processes local voltage and frequency measurements—combined with intrusion detection system (IDS) alerts—as observations and rewards to guide decision-making. Extensive simulation studies demonstrate the robustness of the proposed framework under diverse attack scenarios and varying IDS-induced detection delays. Comparative analysis highlights its superiority over existing static or preexisting rules-based mitigation approaches. Finally, we present an analysis that shows the framework's scalability to real-life microgrids with more interacting agents.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Thermally induced PtOx interfacial layer enhances stability of Pt/β-Ga2O3 vertical Schottky diodes

This study investigates the long-term stability of Pt/β-Ga2O3 field-plated Schottky barrier diodes at high temperatures, with extended thermal cycling and soaking stress. The device characteristics reveal a strong dependence on operating temperature, leading to an ON/OFF current ratio of ∼10× at ±3 V and 600 °C. Extensive thermal cycling (25 cycles over 100 h) between room temperature and 350 °C shows that leakage currents stabilize after the initial ten cycles. This stabilization is likely due to the formation of a thin PtOx layer at the Pt/β-Ga2O3 interface, as confirmed by high-resolution scanning transmission electron microscopy. Further exposure to a constant 350 °C environment for 10 h reveals a slight increase in the leakage current from 10−7 to 10−6 A at −5 V and degradation of the forward current, due to potential thermodynamic instability of the Ohmic contacts. This study provides insights into the changes in the Pt/β-Ga2O3 diode performance with thermal stress, offering a basis for predicting the device’s operational reliability at high temperatures for sensing and power applications.

08 HYDROGEN↗

DOE OSTI2025

Optimization and active stabilization of a far-infrared laser for NSTX-U high poloidal wavenumber scattering diagnostics

The far-infrared (FIR) laser output beam power and profile are important parameters in the laser-aided diagnostics, directly influencing the spatial resolution and signal-to-noise ratio of measurements. Here, this work focuses on developing a systematic control method to enhance FIR laser beam quality through optimized mirror alignment and real-time feedback-based precision cavity length tuning. A 150 W CO 2 laser, aligned with the waveguide axis using a HeNe reference laser, serves as the pump source. The sensitivity of FIR beam intensity to pump gas pressure and thermal expansion is investigated, revealing that even a 1 µm cavity expansion can significantly degrade output power stability to about two-thirds of its original value. To address this, a feedback control module has been designed and implemented for active cavity length adjustment, stabilizing the output power at ∼30 mW. In addition, maintaining a high formic acid gas pressure ($>$190 mTorr) within the cavity ensures reliable operation. The optimized FIR laser will be deployed on the National Spherical Torus eXperiment-U high poloidal wavenumber scattering system for studying electron-scale turbulence in tokamak plasmas.

Xu, Xinhang [Univ. of California, Davis, CA (Unite↗

DOE OSTI2026

Fluid-kinetic modeling of a high power density radio frequency inductively coupled positive hydrogen ion source

High power density radio-frequency (RF) inductively coupled positive ion sources are attractive candidates for next-generation neutral beam injection (NBI) systems, where higher injected power and longer pulse lengths are desired without sacrificing source reliability. Operating at absorbed power densities of order $\gt 1~\mathrm{W\,cm}^{-3}$ places these sources in a regime with stronger gas heating, higher dissociation, and non-Maxwellian electron energy distributions. The Large Uniform Plasma for Ionizing Neutrals (LUPIN) is an RF inductively coupled plasma source designed to explore this high power density regime and to provide guidance for a positive ion source upgrade for the DIII-D NBI system. LUPIN is designed to operate at up to 20 kW of RF power at 2 MHz, coupling energy through a cylindrical quartz vessel to achieve target ion current densities of $2100\,\mathrm{A\,m}^{-2}$ . This paper presents fluid-kinetic modeling of LUPIN using the hybrid plasma equipment model where electrons are treated kinetically, and the simulations reveal that electron energy distribution function transitions from nearly Maxwellian in the core to bi-Maxwellian towards the edge. Parametric simulations investigate the effects of RF power, gas pressure, and frequency on plasma density, ion flux, and uniformity. Parametric sweeps reveal that increasing power shifts the primary ionization channel from molecular to atomic with diminishing flux gains due to skin-depth contraction and gas rarefaction. Higher frequency localizes heating and increases $\mathrm{H}_2^+$ and $\mathrm{H}_3^+$ delivery to the grid, while elevated pressure boosts ionization yet hinders ion transport due to increase in collisionality.

inductively coupled plasma↗

DOE OSTI2025

Numerical simulation of frost formation and heat transfer on fin-and-tube heat exchangers in turbulent cross-flow

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’.

Science & Technology - Other Topics↗