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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Assessment of SCALE and MELCOR for a generic pebble bed fluoride high-temperature reactor

This paper presents the development and application of SCALE and MELCOR models for a fluoride salt-cooled high-temperature reactor (FHR) based on publicly available specifications. SCALE version 6.3beta15 was used to generate power distributions and decay heat curves, and MELCOR version 2.2.18019 was used to calculate the thermal hydraulic response of an assumed FHR primary system. Here, an approach was developed for determining the equilibrium state of the core using depletion of a core slice model and blending of fuel compositions at different burnups to provide three-dimensional fuel composition in the core. Results compared between a core with entirely fresh fuel and one with an equilibrium fuel composition revealed that the equilibrium core led to lower steady-state temperatures but slower cooldown during a loss of flow accident (LOFA). A sensitivity study was then conducted to explore the transient response of our FHR system to variations in thermal hydraulic parameters of the system using the equilibrium core. The inlet temperature, graphite thermal conductivity, and SCRAM time all provided significant control over peak fuel and coolant temperatures. Uncertainties in radionuclide decay data in SCALE were used to perform a decay heat sensitivity study, and we found that uncertainties in decay heat led to negligible impact on peak temperatures during the course of the transient. In all cases evaluated, the observed peak fuel temperatures remained approximately 700 K below anticipated failure limits for the LOFA.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Dynamic optimization and economic evaluation of flexible heat integration in a hybrid concentrated solar power plant

Hybridization of concentrated solar power (CSP) plants provides flexibility in operation that can drastically improve the solar-to-electric (STE) efficiency and levelized cost of electricity (LCOE) relative to standalone CSP plants. Flexible heat integration (FHI) is a novel concept where the collection and integration of CSP within a power plant is modified relative to the amount of solar energy available. FHI improves the thermal efficiency of a hybrid solar tower steam Rankine cycle power plant but leads to increased pumping needs due to continuously elevated molten salt flow rates through the collection system, which can negatively impact STE efficiency. The present work is carried out to maximize the STE efficiency of a hybrid CSP plant utilizing FHI by employing a dynamic optimization framework where a genetic algorithm optimizes the operation of the plant over a given solar irradiance profile. The study concerns a plant hypothetically located in Salt Lake City, Utah. Here, the optimization results confirm the accuracy of a predictive heuristic where the preferred operation of the plant can be estimated relative to local peaks in the incident power generated by the heliostat collection field. The optimized FHI operation demonstrates a yearly STE efficiency of 13.8%, whereas the equivalent base-level hybrid and solar-only plants exhibit solar efficiencies of 13.4% and 11.2%, respectively. Economic analysis shows that FHI reduces yearly natural gas costs, leading to a $\$0.5$/MWh reduction in LCOE relative to the base-level hybrid configuration. Overall, the results show that hybrid FHI schemes exhibit economic benefits along with observed thermodynamic improvements.

14 SOLAR ENERGY↗
DOE OSTI2021

A forecast-driven decision-making model for long-term operation of a hydro-wind-photovoltaic hybrid system

Hydro-wind-photovoltaic (PV) hybrid system has the potential to increase the integration of renewable energy sources into an existing grid. For the long-term operation of the system, due to the non-storable nature of wind and PV power, it is essentially to decide the optimal long-term carryover storage of cascade reservoirs. However, it remains a challenge due to high uncertainties of long-term forecasts and complicated hydraulic/electrical relationships between cascade reservoirs. Here in this study, a forecast-driven decision-making model is proposed for the hybrid system, which converts the multi-stage long-term operation process into a two-stage operation problem (including current stage and carryover stage) to avoid using longer-horizon forecast information with lower accuracy. First, the carryover stage energy surfaces (CESs) considering the forecast uncertainties of wind, solar and hydro resources are proposed to characterize carryover stage benefit quantitatively. Then a CESs-based forward decision-making optimization model is developed to guide the long-term operation of a hydro-wind-photovoltaic hybrid system. The applications in a hydro-wind-PV hybrid system of Yalong River basin results show that: compared with conventional operation, 1) power generation increases 9.03%; 2) in terms of the carryover storages control, the reservoir impounding and drawdown timing are delayed, and the drawdown depth is increased, which can be used to formulate better reservoir operation rules.

13 HYDRO ENERGY↗
DOE OSTI2025

Broad range material-to-system screening of metal–organic frameworks for hydrogen storage using machine learning

Hydrogen is pivotal in the transition to sustainable energy systems, playing major roles in power generation and industrial applications. Metal–organic frameworks (MOFs) have emerged as promising mediums for efficient hydrogen storage. However, identifying potential candidates for deployment is challenging due to the vast number of currently available synthesized MOFs. This study integrates molecular simulations, machine learning, and techno-economic analysis to evaluate the performance of MOFs across broad operation conditions for hydrogen storage applications. While previous screenings of MOF databases have predominantly emphasized high hydrogen capacities under cryogenic conditions, this study reveals that optimal temperatures and pressures for cost minimization depend on the raw price of the MOF. Specifically, when MOFs are priced at $15/kg, among the 9720 MOFs tested, 9692 MOFs achieve the lowest cost at temperatures between 170 K and 250 K and a pressure of 150 bar. Under these optimal conditions, 362 MOFs deliver a lower levelized cost of storage than 350 bar compressed gas hydrogen storage. Furthermore, this study reveals key material properties that result in low system cost, such as high surface areas (>3000 m2/g), large void fractions (>0.78), and large pore volumes (>1.1 cm3/g).

Hydrogen storage↗
DOE OSTI2025

Economic and environmental performance of biomass gasification for renewable natural gas production in the context of the U.S. natural gas supply

Bioenergy technologies offer potential for reducing greenhouse gas (GHG) emissions. One such promising technology is biomass gasification, which is the conversion of biomass into renewable natural gas (RNG) for use with a natural gas combined-cycle power generation system. However, the associated economic and emission effects need to be better understood to enable optimal decision-making and avoid missed opportunities for enhancing efficiency and increasing system circularity. This analysis explores opportunities to (1) decarbonize natural-gas-based systems and (2) leverage the extensive US natural gas infrastructure to mobilize biomass resources to achieve environmental and economic benefits. Here, in this analysis, the research team used a spatially explicit biomass logistics model (integrated with relevant biomass availability, technoeconomic analysis, and life cycle assessment information) to simulate economically optimal biomass allocation for RNG production and use for decarbonization in the United States. Results show that the United States has the potential to produce 9203 million GJ of RNG within the expected range of $\$$12–30/GJ. Further analyses tested the overall RNG production system's sensitivity to economic and emissions parameters of nine different processes. The sensitivity analysis results indicate that the median carbon abatement cost of RNG is most sensitive to changes in emissions associated with conversion processes and land use changes. These findings provide a deeper understanding of RNG's economic and emission potential for decision-making and guiding future research.

09 BIOMASS FUELS↗
DOE OSTI2020

Nexus of thermal resilience and energy efficiency in buildings: A case study of a nursing home

Extreme weather events become more frequent and severe due to climate change. Although energy efficiency technologies can influence thermal resilience of buildings, they are traditionally studied separately, and their interconnections are rarely quantified. This study developed a methodology of modeling and analysis to provide insights into the nexus of thermal resilience and energy efficiency of buildings. In this work, we conducted a case study of a real nursing home in Florida, where 12 patients died during Hurricane Irma in 2017 due to HVAC system power loss, to understand and quantify how passive and active energy efficiency measures (EEMs) can improve thermal resilience to reduce heat-exposure risk of patients. Results show that passive measures of opening windows and doors for natural ventilation, as well as miscellaneous load reduction, are very effective in eliminating the extreme dangerous occasions. However, to maintain safe conditions, active measures such as on-site power generators and thermal storage are also needed. The nursing home was further studied by changing its location to two other cities: San Francisco (mild climate) and Chicago (cold winter and hot summer). Results revealed that the EEMs' impacts on thermal resilience vary significantly by climate and building characteristics. The study also estimated the costs of EEMs to help stakeholders prioritize the measures. Passive measures that may not save energy may greatly improve thermal resilience, and thus should be considered in building design or retrofit. Findings from this study indicate energy efficiency technologies should be evaluated not only by their energy savings performance but also by their influence on a building's resilience to extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A data-driven linear formulation of the optimal demand response scheduling problem for an industrial air separation unit

Demand response (DR) has become a key element in balancing the power grid as the contribution of time-varying renewable power generation increases. Chemical plants are appealing candidates for DR programs as they offer large, concentrated and flexible loads. DR participation calls for frequent production rate changes over time scales that overlap with the dominant dynamics of the plant. Production scheduling should therefore consider the process dynamics explicitly. Here we present a data-driven approach for modelling the scheduling-relevant dynamics based on historical closed-loop operating data using autoregressive with extra inputs (ARX) models. We introduce a new, linear scheduling problem formulation based on the ARX representation, and demonstrate its implementation on an industrial air separation unit.

42 ENGINEERING↗
DOE OSTI2025

Plasma assisted NH 3 /H 2 /air ignition in nanosecond discharges with non-equilibrium energy transfer

Ammonia (NH 3 ), with its high energy density and easiness to store and transport as a hydrogen carrier, has become a promising alternative green fuel. However, its adoption in power generation is hindered by challenges such as low burning velocity, slow low-temperature oxidation, high NO x emissions, and ignition difficulty. Here, this work computationally investigates the effects of non-equilibrium energy transfer by nanosecond discharges on NH 3 ignition and flame propagation in an NH 3 /H 2 /air flow at 700 K and 1 atm. The simulation results demonstrate that NH 3 /air mixtures require a large ignition energy due to their large critical ignition radius. It is shown that adding 30 % hydrogen significantly reduces the critical ignition radius and minimum ignition energy. Two-dimensional modeling further shows a non-monotonic dependence of ignition kernel volume on the applied voltage and reduced electric field. The optimum ignition enhancement occurs at 200 Td where the generation of electronically excited species and radicals including N 2 (B), O( 1 D) and OH becomes most efficient. Higher voltages divert electron energy toward ionization, which makes it less effective for NH 3 ignition. The study also identifies an optimal electrode gap size for a given pulse energy. Smaller gap sizes increase deposited energy density, raising temperature and radical concentrations. However, excessive reduction of the gap distance reduces flame propagation speed due to the flame stretch effect in rich mixtures with the effective Lewis number greater than unity. A nonlinear relationship between pulse repetition frequency and ignition kernel volume is observed in a nanosecond pulsed high frequency discharge (NPHFD). An optimal frequency range of 200 kHz to 2 MHz is found when two pulses are used. In addition, an optimal number of pulses exists for each pulse repetition frequency, with higher frequencies requiring more pulses to maximize the overlap region. These findings provide critical insights on developing controlled plasma discharge techniques for efficient NH 3 ignition in reactive flows within internal combustion engines and gas turbines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Chemical timescale effects on detonation convergence

Numerical simulations of detonation-containing flows have emerged as crucial tools for designing next- generation power and propulsion devices. As these tools mature, it is important for the combustion community to properly understand and isolate grid resolution effects when simulating detonations. To this end, the objective of this work is to provide a comprehensive analysis of the numerical convergence of unsteady detonation simulations, with focus on isolating the impacts of chemical timescale modifications on convergence characteristics in the context of operator splitting. With the aid of an AMReX-based adaptive mesh refinement flow solver-which enables resolutions up to ($\mathcal{O}$ (1000) cells-per-induction length-the convergence analysis is conducted using two kinetics configurations: (1) the simplified three-step Arrhenius-based model mechanism of Short and Quirk (1997), where chemical timescales in the detonation are modified by adjusting activation energies in the initiation and branching reactions, and (2) a detailed hydrogen- air mechanism, where the chemical timescales are adjusted by varying the ambient pressure. The convergence of unsteady self-sustained detonations in one-dimensional channels is then analyzed with reference to steady-state theoretical baseline solutions using these mechanisms. The goal of the analysis is to provide a detailed comparison of the effects of grid resolution on both macroscopic (peak pressures and wave speeds) and microscopic (wave structure) quantities of interest, drawing connections between the deviations from steady-state baselines and minimum chemical timescales. In particular, chemical timescale reductions were found to have minimal impact on the convergence of macroscopic properties. Furthermore, analyses of microscopic convergence trends, particularly in the reaction front location, revealed a key insight: maintaining the induction time while eliminating prohibitive chemical timescales through mechanism simplifications and combustion modeling can significantly enhance detonation convergence properties. Ultimately, this work uncovers resolution-dependent unsteady detonation convergence regimes and highlights the important role played by not only the chemical timescales, but also the ratio between the chemical timescale and induction time on the numerical convergence of the detonation wave structure.

Adaptive mesh refinement↗
DOE OSTI2023

Photovoltaic device innovation for a solar future

Photovoltaics (PV), also known as solar cells, are now found everywhere - in utility plants; on roofs of homes and commercial buildings; on platforms at sea; in agricultural fields; on vehicles, buildings, drones, and backpacks; and, in their longest running application, providing power in space. Continuous device innovation has led to increased efficiency and improved reliability for multiple PV technologies. Confronted with an urgent need to deploy PV at multiterawatt (TW) scale over the next two decades to mitigate greenhouse gas emissions, PV device innovation takes on new urgency and impact. This perspective reviews recent progress in device design and performance for PV technologies that are currently in commercial production at greater than 1 GW/year or enabling significant space-based power generation - Si, CdTe, CIGS, and multijunction III-V - and looks ahead to the next 5 years. In conclusion, we also identify device-related topics requiring cross-cutting research and innovation.

14 SOLAR ENERGY↗
DOE OSTI2022

Integration of cryogenic energy storage with renewables and power plants: Optimal strategies and cost analysis

Energy storage is critical for overcoming challenges associated with the intermittency and the variable availability of renewable sources for decarbonizing the energy sector. Cryogenic energy storage (CES) is of interest due to its high technology readiness level, no geographical limitations, and moderate round-trip efficiency. The time-varying nature of demands and renewable availability needs to be considered at the design and integration stages of energy storage. We develop a mixed-integer nonlinear program (MINLP) model to obtain the energy storage costs on a daily basis for different scenarios that typically arise over an entire year. Using this optimization-based framework, we address key decision-making questions towards energy transition: What is the energy cost when CES is integrated with renewables and power plants? How does each scenario affect the overall energy cost? How much storage is needed for complete transition to renewables? What is the optimal integration towards 100% renewable energy? What are the optimal storage designs for both renewables and fossil-based power generation with current and future energy demands? Here, we discuss different scenarios and solutions to these questions.

25 ENERGY STORAGE↗
DOE OSTI2024

Coupled aero-hydro-geotech real-time hybrid simulation of offshore wind turbine monopile structures

Real-time hybrid simulation (RTHS) divides a structural system into an analytical and experimental substructure. The former is based on a well-established analytical model while the latter consists of a physical model in the laboratory, for which there is not a well-established analytical model. This paper extends real-time hybrid simulation to monopile-type Offshore Wind Turbines (OWTs) to enable the investigation of their behavior considering the response of pile foundations under operational and more severe conditions. The embedded foundation and surrounding soil of the OWT are modeled physically in a soil box in the laboratory while the remaining parts of the system and loading are modeled analytically. The program OpenFAST, developed by the National Renewable Energy Laboratory (NREL), is linked to the RTHS coordinator to determine the hydrodynamic and aerodynamic loads acting on the OWT, along with modeling the dynamics of the electric power generation equipment and associated controller for the OWT. The RTHS framework along with its initial implementation and validation are described in this paper. RTHSs of a 5 MW OWT subjected to operational and more severe conditions are performed to experimentally validate the framework. The framework offers a realistic approach to investigate the behavior of OWT structures supported on monopiles. Furthermore, this approach accounts for the coupled response of the OWT structure with its foundation, while experimentally capturing the nonlinearities of the soil-foundation interaction in real-time.

17 WIND ENERGY↗
DOE OSTI2025

A comprehensive review of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) techniques in protonic ceramic cells (PCCs): Current status and future perspective

Protonic ceramic cells (PCCs) have emerged as a promising technology for power generation, energy storage, and value-added chemical synthesis, offering benefits such as fuel flexibility, low emissions, and efficient operation at intermediate temperatures (300–600 ​°C). Recently, significant breakthroughs in materials and manufacturing methods have markedly enhanced the performance of PCCs. However, establishing a fundamental understanding of their electrocatalytic reactions has gained less attention. As a fast and cost-effective method for physicochemical fingerprinting, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) has proven to be a surface-sensitive analytical tool for structural and functional studies. This review critically examines the most up-to-date applications of DRIFTS for characterizing key components of PCCs, including oxygen electrodes, protonic electrolytes, and hydrogen electrodes for different applications, with a focus on revealing hydration properties and catalytic reactions, and guiding rational material design. The challenges for advancing DRIFTS, including quantitative capabilities and operando applications for PCC investigations, are highlighted and strategies to tackle these challenges are discussed. Ultimately, this review underscores the critical role of DRIFTS in accelerating the development of high-performance and durable PCCs for next-generation energy solutions, offering methodologies and insights broadly applicable to a wide range of electrochemical energy conversion and storage technologies.

Diffuse Reflectance Infrared Fourier Transform Spe↗
DOE OSTI2021

Investigating feasible light configurations for fish restoration: an ethological insight

Light environment significantly impacts the effectiveness of fish population restoration in developed watersheds, subserving fish passage reconstruction in hydraulic complex and habitat rehabilitation. To develop an interior connection between light-related fish response from the laboratory and field fish conservation practice, we employed a new indexing system, consisting of phototaxis rate, relative swimming speed (RSS), and optic evasion coefficient (OEC), to quantify the light-induced behaviors in Ptychobarbus kaznakovi, a representative rare cyprinid in Tibet, China, at four experimental illuminance levels (15 lx, 30 lx, 60 lx, 120 lx) and four wavelengths (red, yellow, green, blue). The fish showed negative phototaxis at all given illuminances and wavelengths. Under red light, the OEC increased significantly from 0.642 at 15 lx to 0.782 at 30 lx (P = 0.029), while the RSS decreased significantly from 3.752 to 2.383 (P < 0.001). Behaviorally, the fish shifted from sprint to wandering around, indicating the alteration of dominant physiological activity from behavioral stress response to negative phototaxis. Under the green treatment, P. kaznakovi swam around quickly and presented slight negative phototaxis, and OEC values were uniform among all illuminances, probably because of the similarity of green light to the ambient color of the habitat. Accordingly, ecologists and fisheries practitioners can utilize red light to exclude fish from dangerous waters and green light to guide them to ideal habitats, laying the necessary groundwork for the light-driven fish recovery effort. Furthermore, the appropriate light configuration can yield economic benefits through the tradeoff among fish protection, power generation, and investment costs.

Lin, Chenyu↗
DOE OSTI2021

The development of a Sustained High Power Density (SHPD) facility

A Sustained High Power Density (SHPD) facility is being planned within the U.S. as a non DT device which can be a bridge to a Compact Fusion Pilot Plant (CFPP) DT operated facility with the future capacity to produce a levelised cost of electricity at a rate competitive with current power generating systems. To accomplish this a review of ITER cost data and recent next step physics/engineering studies that promoted technology development, physics enhancements and innovated configuration improvements that increase operating availability have been injected into a proposed PPPL SHPD design. Much of the physics and engineering design basis for this effort centers on a series of ST studies carried out in recent years attempting to maximize the low aspect ratio (AR) ST performance within realistic engineering constraints of this compact fusion device. One issue found in the low AR design is the lack of volt-seconds generated by a small central solenoid that resides in the available space left after sizing the TF structure to support the high current density/HTS TF coil. Although not required in a larger pilot plant device, a solenoid wrapped around the plasma side of the SC TF coil was considered for the small low aspect ratio SHPD device. Adding a solenoid to the plasma side of the TF imposes a major change to the device configuration – a change which has been found to have cost and assembly issues when compared with an OH solenoid located at the machine center. Finally, the inclusion of a liquid metal first wall divertor system, the integration of local pairs of outboard DCLL blanket segments and a summary of physics performance conditions will be presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Fatigue-crack propagation behavior in a high-carbon chromium SUJ2 bearing steel: Role of microstructure

High-carbon chromium martensite steels are commonly selected for bearing components in the power generation, automotive and aerospace industries where fatigue failure is a major concern. Accordingly, it is of importance to elucidate the structure-property relationships governing the fatigue properties of such bearing steels. Here, the role of microstructure in influencing the fatigue-crack propagation behavior of a high-carbon chromium SUJ2 bearing steel is examined with emphasis on three martensitic structures: (i) a fine-grained (~10 μm) structure with intragranular (but no intergranular) carbides, (ii) a coarser-grained (~25 μm) structure with discontinuous grain-boundary carbides primarily near triple junctions, and (iii) a coarse-grained (~31 μm) structure with continuous grain-boundary carbides. Although growth rates were fairly similar above ~10 -8 m/cycle, significant differences in behavior were observed at lower, near-threshold growth rates; specifically at a load ratio of 0.1, the ΔKth fatigue threshold was increased from 3.8 MPa m ½ in the fine-grained structure to 5.9 to 6.3 MPa m ½ in the two coarser-grained structures. The dominant factor governing such near-threshold behavior was found to be crack-tip shielding from roughness-induced crack closure, which was most pronounced in the coarser-grained structures; additionally, shielding from crack deflection and branching was apparent in these structures as the crack propagated through the network of intersecting martensite lamellae within the coarse grains. Compared to high-strength stainless steels and low-strength carbon steels, the fine-grained SUJ2 steel displays an exceptional combination of high strength and fatigue-crack growth resistance and is considered to be a superior structural alloy for bearing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Numerical analysis of coalescence-induced bubble departure for enhanced boiling heat transfer

Boiling heat transfer plays a crucial role in a wide range of applications, such as power generation, refrigeration, electronics cooling, and pharmaceutics. Among the various factors that influence boiling heat transfer, the dynamics of vapor bubble nucleation, growth, and departure from the heated surface stand out as particularly important. An emerging phenomenon that can promote the departure of bubbles smaller than the Fritz diameter is coalescence-induced departure. If the dynamics of this process are fully understood, then surfaces can be engineered to promote faster bubble departure and substantially increase the performance of boiling heat transfer. Further, this work expands on published results by presenting a detailed numerical analysis of bubble coalescence and departure for a range of initial bubble diameters and size ratios between coalescing bubbles. Analysis of the results is focused on explaining how the release of surface energy and bubble surface dynamics lead to bubble departure, as well as fundamentally distinguishing capillary–inertial jumping and buoyant–inertial departure mechanisms across different bubble sizes and size ratios. The results show that both the initial sizes of the coalescing bubbles and the ratio between their sizes can determine whether the merged bubble will leave the surface through capillary–inertial jumping or buoyant departure. Below a certain bubble size, the release of surface energy by the merger is not sufficient to propel the merged bubble from the surface.

42 ENGINEERING↗